JP6462607B2 - Data complementing apparatus and data complementing method - Google Patents

Description

  The present invention relates to a data complementing apparatus and a data complementing method.

  Many infrastructures such as communication facilities and roads are constructed during a period of high growth, and there are concerns that there will be an increase in failures due to aging and an increase in maintenance costs. In addition, the total number and total length of these infrastructures are enormous, and technical progress related to maintenance is expected.

  For example, communication facilities are maintained and managed mainly by periodic inspections. By using the accumulated inspection data for reliability analysis and the like, it is possible to maintain and improve the reliability of the equipment and to improve the maintenance efficiency.

  When performing this reliability analysis, depending on the analysis method, information indicating failure / deterioration (hereinafter referred to as failure data) and information indicating failure / deterioration (hereinafter referred to as non-failure data) are also required. It becomes. For example, in a certain analysis method, the use years of each failure part and non-failure part are obtained from the failure data and non-failure data of the inspection data, and the average failure year (average life) of the management target is calculated.

  Here, depending on the inspection object, the inspection method, or the inspection recording method, unfailed data may not be recorded. For example, in the case of a method of recording a failed part or state, a part that has not failed may not be explicitly recorded. When reliability analysis (for example, cumulative hazard analysis or Weibull analysis) is performed using inspection data in which no failure data is recorded, the average lifespan is affected and the calculation result is true. It may deviate from the value.

  Therefore, in order to ensure the accuracy of maintenance and management of various facilities, it is important to supplement such a lack of unfailed data in the inspection data. Therefore, conventionally, as a technique for complementing missing data, a method for complementing dummy data prepared in advance or typical values to the missing part, an adjacent data value or an average value of adjacent data values, etc. is complemented to the missing part. And a method of complementing a missing value with a data value that minimizes the difference between a certain range of normal data and missing data have been proposed (see, for example, Patent Documents 1 and 2).

Japanese Patent No. 4488027 Japanese Patent No. 3654193

  However, in the conventional method, when the non-failed data itself is not included in the inspection data, the data cannot be complemented with high accuracy. For example, in the inspection data of a large facility such as an infrastructure, if the data is not missing and the non-failed data itself is not included in the inspection data, the data cannot be complemented with high accuracy. For this reason, the conventional method has a problem that data necessary for reliability analysis cannot be generated.

  The present invention has been made in view of the above, and even when the inspection data does not include the unfailed data itself, the unfailed data portion is complemented and is required for the reliability analysis. An object of the present invention is to provide a data complementing apparatus and a data complementing method capable of appropriately generating data.

  In order to solve the above-described problems and achieve the object, the data complementing apparatus according to the present invention is inspection data on inspections performed on the management target object, and includes inspection date, degree of deterioration, position A setting unit that sets a unit that is a measurement unit according to the management object with respect to inspection data associated with information, and a determination that determines that the unit that does not include at least the deterioration degree is in an unfailed state And a unit including the degree of deterioration, a characteristic value is estimated based on a construction date of the management object, an inspection date of the inspection data, and the degree of deterioration of the unit, and the degree of deterioration is calculated. For unit groups that are not included and that are not in failure, if the management target of the units adjacent to both ends of the unit group and the predetermined parameters related to inspection are the same, the both ends are respectively When the characteristic value of the unit group is estimated and complemented based on the characteristic value of the adjacent unit, and the predetermined parameters related to the management target and inspection of the unit adjacent to both ends of the unit group are different, An estimation unit that obtains a distribution of the number of deterioration points for each characteristic value recorded in the inspection data, and estimates and supplements the characteristic value based on an approximate curve for the obtained distribution. .

  According to the present invention, even when the inspection data does not include the unfailed data itself, the unfailed data portion is accurately supplemented and the data required for the reliability analysis is appropriately generated. Can do.

FIG. 1 is a diagram for explaining an example of the configuration of the analyzer according to the first embodiment. FIG. 2 is a diagram for explaining unit setting processing in the unit setting unit shown in FIG. FIG. 3 is a diagram for explaining the processing of the unit state determination unit shown in FIG. FIG. 4 is a diagram for explaining another process of the unit state determination unit shown in FIG. FIG. 5 is a diagram for explaining the processing of the unit state determination unit shown in FIG. FIG. 6 is a diagram for explaining the processing of the unit state determination unit shown in FIG. FIG. 7 is a diagram for explaining the processing of the characteristic value estimation unit shown in FIG. FIG. 8 is a flowchart showing the processing procedure of the analysis processing in the analyzer shown in FIG. FIG. 9 is a flowchart showing a processing procedure of the analysis data generation processing shown in FIG. FIG. 10 is a flowchart of a process procedure of the unit state determination process shown in FIG. FIG. 11 is a flowchart showing a processing procedure of the characteristic value estimation processing shown in FIG. FIG. 12 is a diagram illustrating an example of a computer in which an analysis apparatus is realized by executing a program.

  Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. In addition, this invention is not limited by this embodiment. Moreover, in description of drawing, the same code | symbol is attached | subjected and shown to the same part.

[Embodiment 1]
About the analyzer which concerns on Embodiment 1, the schematic structure of an analyzer, the flow of a process in an analyzer, and a specific example are demonstrated.

[Configuration of analyzer]
First, the configuration of the analyzer according to the first embodiment will be described with reference to FIG. FIG. 1 is a diagram for explaining an example of the configuration of the analyzer according to the first embodiment.

  The analysis apparatus 10 according to Embodiment 1 shown in FIG. 1 performs reliability analysis such as the average life of a management target object from inspection data for the management target object. Management objects are infrastructure equipment such as communication equipment and roads. In the first embodiment, a tunnel facility of a communication infrastructure facility is assumed as a management target. The inspection data used for the reliability analysis in the analysis device 10 is data in which unfailed data itself is missing, as will be described later. In the first embodiment, the analysis apparatus 10 divides the inspection data into predetermined measurement units (units), obtains the years of use of the units as characteristic values, and uses the characteristic values to calculate the average failure year ( An example of obtaining the average life) will be described.

  As illustrated in FIG. 1, the analysis apparatus 10 includes an input unit 11, a storage unit 12, a control unit 13, and an output unit 14.

  The input unit 11 is an input interface that receives various operations from an operator of the analysis apparatus 10. For example, it is configured by an input device such as a keyboard and a mouse.

  The storage unit 12 is realized by a semiconductor memory device such as a RAM (Random Access Memory) and a flash memory, or a storage device such as a hard disk or an optical disk, and a processing program for operating the analyzer 10 Data used during execution is stored. The storage unit 12 includes an inspection data storage unit 121.

  The inspection data storage unit 121 stores inspection data of periodic inspections performed at a plurality of times in each tunnel-like facility in a large number of tunnel-like facilities constructed in various years. The inspection process is performed, for example, on a long wall surface inside the tunnel, and is stored in the inspection data storage unit 121 for each failure / deteriorated part in association with the management target information. The managed object information includes identification information of the managed object and the construction date of the managed object.

  In addition, the inspection data storage unit 121 stores, as inspection data, position information that can identify a failure / deterioration location, a failure / deterioration degree (degradation rank), and an inspection date associated with each other. Further, it is assumed that the inspection data is in a state where no failure / deterioration has occurred, that is, no failure data is recorded (missed). The inspection data storage unit 121 also stores the characteristic value obtained from the inspection data for the inspection data that has already undergone the characteristic value estimation processing in the control unit 13.

  The control unit 13 has an internal memory for storing a program that defines various processing procedures and the necessary data, and executes various processes using these programs. For example, the control unit 13 is an electronic circuit such as a CPU (Central Processing Unit) or an MPU (Micro Processing Unit).

  The control unit 13 includes an analysis data generation unit 131 (data complementing device) that generates analysis data for obtaining the average life of the management target from the inspection data of the management target, and an analysis data generation unit An analysis unit 132 that performs reliability analysis such as the average life of the management target using the analysis data generated from 131 is provided.

  The analysis data generation unit 131 includes a unit setting unit 131a, a unit state determination unit 131b, and a characteristic value estimation unit 131c.

  The unit setting unit 131a sets a unit according to the management object with respect to the inspection data of the management object to be analyzed.

  The unit state determination unit 131b determines whether the unit is a failed unit or a non-failed unit based on the presence / absence of the deterioration level in the unit and the deterioration level included in the unit.

  The characteristic value estimation unit 131c estimates the characteristic value of each unit based on the construction date of the management target, the inspection date of the inspection data, and the degree of deterioration of each unit. The characteristic value estimation unit 131 c generates data indicating the distribution information of the number of units for each characteristic value as data for reliability analysis of the management target object, and outputs the data to the analysis unit 132.

  Specifically, the characteristic value estimation unit 131c estimates a characteristic value based on the degree of deterioration of a unit including the degree of deterioration. Then, the characteristic value estimation unit 131c, for an unfailed unit group that does not include the degree of deterioration, has the same management target object and predetermined parameters for inspection of units adjacent to both ends of the unit group. When the characteristic values of the unit group are estimated and complemented based on the characteristic values of the units adjacent to both ends, and the management target of the units adjacent to both ends of the unit group and the predetermined parameters relating to inspection differ For this, the distribution of the number of deteriorated portions for each characteristic value recorded in the inspection data is obtained, and the characteristic value is estimated based on the approximate curve for the obtained distribution and complemented.

  The analysis unit 132 performs reliability analysis of the management target using the data generated by the characteristic value estimation unit 131c. For example, the analysis unit 132 uses the data generated by the characteristic value estimation unit 131c to calculate an average failure year (average life, hereinafter referred to as MTTF) of the management target object by cumulative hazard analysis or Weibull analysis. It is sufficient to use a known method for cumulative hazard analysis and Weibull analysis. Of course, the analysis unit 132 may be other analysis methods that use unfailed data, instead of cumulative hazard analysis, Weibull analysis, and the like. Further, the analysis unit 132 may calculate a value other than MTTF.

  The output unit 14 is, for example, a liquid crystal display or a printer, and outputs various information. The output unit 14 may be an interface that controls input / output of various data to / from an external device, and may output various information to the external device.

[Processing of unit setting part]
Hereinafter, processing of each unit of the analysis data generation unit 131 will be described. First, the processing of the unit setting unit 131a will be described.

  FIG. 2 is a diagram for explaining unit setting processing in the unit setting unit 131a. Assume that the management object is a tunnel facility, and in FIG. 2, the direction from the left direction to the right direction on the paper surface is the length direction of the tunnel facility. Then, a figure schematically showing the tunnel-like equipment extending along this direction is superimposed with an X mark indicating a failure / deterioration location included in the inspection data of the tunnel-like equipment. This will be described as inspection data D1.

  The unit setting unit 131a sets, for each unit, each portion divided at a certain distance from the end of the tunnel based on the facility characteristic that the management target is a long tunnel-like facility. Thereby, the total number of units to be managed is determined. For example, when the inspection data D1 shown in FIG. 2 corresponds to a tunnel-like facility with a total extension of 1 km, the data is divided every 1 m from the tunnel end. Thereby, in the example of the inspection data D1, the total number of units becomes 1000.

  In the example of FIG. 2, the units (0003) and (0999) indicated by a cross can be determined to be units having a failure / degradation data (failed unit) and are not indicated by a cross. Since no failure / degradation point is indicated, it can be determined that the unit is an unfailed unit. Therefore, the number of units where the failure / deterioration location is indicated is counted, and when the number of units is 150, 850 units obtained by subtracting the number of failed units from the total number of units 1000 are obtained as unfailed units. In other words, it is possible to obtain the total number of missing non-failed data in the inspection data D1.

  Here, the inspection data used by the analyzer 10 is recorded only when there is a failure / deterioration, and is not recorded for a portion where failure / deterioration is not recognized. In other words, it can be said that there is no failure except for the location recorded as failure data. In many reliability analyses, the number of failure data and non-failure data is important information, but in the case of such a recording method for a facility with a long distance and area, some measurement unit is newly set. Otherwise, the number of unfailed data cannot be obtained. In the first embodiment, the unit setting unit 131a can determine the total number of missing data that has been lost by setting a certain measurement unit (unit) as described above.

  In the first embodiment, since a long tunnel-like facility is taken as an example, the unit is described as having a width of 1 m, but of course, the size of this unit depends on the purpose of analysis, the state of the target facility, and the inspection. It is sufficient to set it in consideration of ease of handling.

  For example, if it is a tunnel wall surface, you may set the magnitude | size of a unit on the basis of the hardware etc. which are arrange | positioned at a certain space | interval. Further, not the length but the area or weight may be used as the unit. For example, when the area is defined, the inner wall surface of the tunnel may be divided by some rectangular grid, and each grid may be a unit. Furthermore, the size of the grid or the like can be set with reference to the magnitude of deterioration, for example, the average length of cracks.

[Processing of unit status determination unit]
Next, processing of the unit state determination unit 131b will be described. The unit state determination unit 131b determines whether each unit is a failed unit or a state A (first unfailed state) based on the presence / absence of the degree of deterioration (presence / absence of failure / deterioration data) and the value of the degree of deterioration. It is determined whether it is an unfailed unit, an unfailed unit in state B (second unfailed state), or an unfailed unit in state C (third unfailed state).

  First, a case where the unit state determination unit 131b determines a failed unit and an unfailed unit in the state A will be described with reference to FIG. FIG. 3 is a diagram for explaining the processing of the unit state determination unit 131b, and shows data D2 that is partial data of the inspection data D1 of FIG.

  For example, a case where determination of a deterioration state is divided into a plurality of deterioration ranks (deterioration degrees) according to a certain standard will be described as an example. Specifically, it is assumed that the rank is divided into 1 to 5 degradation ranks according to the degradation state. As the number increases, the degree of deterioration increases, with 1 being the least deteriorated and 5 being the most deteriorated. However, even the degradation rank 1 shows a state where there is some degradation, and is not a state where there is no degradation.

  Further, when it is desired to analyze based on the maximum deterioration of each measurement unit, a value having the highest deterioration rank is selected as a representative value among failure / deterioration data included in one unit. In this case, only the degradation rank 5 is regarded as a failure unit, and the degradation ranks 1 to 4 are regarded as unfailed units. Then, a unit for which failure / deterioration data is missing is regarded as an unfailed unit.

  For example, in the example of FIG. 3, failure / deterioration data is missing in the units (0001), (0002), and (0004). Therefore, the unit state determination unit 131b determines that the units (0001), (0002), and (0004) are unfailed units.

  The unit (0005) includes degradation of degradation rank 5. The unit state determination unit 131b determines that the unit (0005) is a failure unit (see arrow Y11) because the unit (0005) includes deterioration of the deterioration rank 5 (see arrow Y10). In other words, the unit (0005) including the predetermined deterioration degree among the units including the deterioration degree is determined as the failed unit.

  The unit (0003) includes three deteriorations of deterioration ranks 1, 3, and 4. The unit state determination unit 131b determines that the unit (0003) is an unfailed unit (see arrow Y13) because there is no deterioration of the deterioration rank 5 (see arrow Y12). Here, since the unit state determination unit 131b is a unit including the value of the deterioration rank, the state of the unit (0003) is determined to be an unfailed state (state A) having the value of the deterioration rank. In other words, among the units including the deterioration level, a unit whose predetermined deterioration level is not included in the deterioration level is determined as an unfailed unit in the state A.

  Therefore, in the example of FIG. 3, the unit state determination unit 131b determines that the unit (0005) is a failed unit, determines that the units (0001) to (0004) are unfailed units, and of these units (0003) ) Is determined as an unfailed unit in the state A.

  It should be noted that the degradation rank, which is a criterion for determining the failure state, may be changed for each unit according to the analysis purpose, the property of the facility to be managed, and the like. In addition to the above methods, a plurality of methods for determining a failure state and an unfailed state are conceivable depending on the purpose of analysis and the properties of the management target equipment. For example, when analyzing based on the average degree of deterioration, it is conceivable to select an average value of failure / deterioration data included in one unit. Other statistics (minimum value, median value, mode value, weighted average value, etc.) are also options. If the failure / degradation data is not a numerical value, the above average value can be calculated by converting the numerical value according to the degree of deterioration or permutation of the degree of deterioration. It becomes possible.

  Of course, all units including failure / deterioration data may be determined as failure units. In this case, as illustrated in FIG. 4, the unit state determination unit 131b determines that the units (0003) and (0005) including the failure / degradation part are the failed units regardless of the number. Of course, the unit state determination unit 131b determines that the units (0001), (0002), and (0004) that do not include any failure / deterioration part are unfailed units.

  Next, a case where the unit state determination unit 131b determines an unfailed unit in the state B will be described with reference to FIG. FIG. 5 is a diagram for explaining the processing of the unit state determination unit 131b, and shows data D3 that is partial data of the inspection data D1 of FIG.

  For example, a description will be given by taking continuous unit groups (0004) to (0121) as an example. These unit groups (0004) to (0121) are non-failed units because failure / degradation data is missing (see (1) in FIG. 5). For the unfailed unit group in which such failure / degradation data is missing, the unit state determination unit 131b determines the state of the unit group based on the failure / degradation data of the units adjacent to both ends of the unit group. judge.

  Specifically, first, the unit state determination unit 131b indicates failure / deterioration data adjacent to both ends of the unit groups (0004) to (0121) for the unit groups (0004) to (0121). Find the unit that is. When the direction indicated by the arrow A1 is the assumed inspection execution direction, the unit (0003) is the unit adjacent to the left end where the failure / degradation data is shown with respect to the unit groups (0004) to (0121). And the unit (0122) is obtained as the unit adjacent to the right end where the failure / deterioration data is shown. Next, the unit state determination unit 131b determines whether the construction dates and the inspection dates of the units (0003) and (0122) are the same.

  Here, since it is considered that the tunnel equipment is generally inspected in order from the end, it is highly likely that the latest inspection date is the same in a certain range of unit groups. Therefore, in units where failure / deterioration data adjacent to both ends of a continuous unfailed unit group are shown, if the construction date and the inspection date are the same, the faulty units adjacent to both ends respectively. It is considered that the unfailed unit group sandwiched between the two is also equivalent to the construction date and the inspection date in the units adjacent to both ends. That is, the unfailed unit group sandwiched between the failed units adjacent to both ends can be considered to be in a deteriorated state equivalent to the unit adjacent to each end of the unit group.

  Therefore, the unit state determination unit 131b determines that the units (0003) and (0122) adjacent to both ends of the unit groups (0004) to (0121) have the same construction date and the same inspection date. Is a unit having a representative value (see (2) in FIG. 5), the unit groups (0004) to (0121) are equivalent to the units (0003) and (0122) adjacent to both ends, respectively. It can be regarded as a deteriorated state (see (3) in FIG. 5) and is determined as an unfailed unit in state B (see (4) in FIG. 5).

  That is, the unit state determination unit 131b is a predetermined parameter related to the management target and inspection of the units adjacent to both ends of the unit group in the unfailed unit group not including the degree of deterioration, that is, the construction date. And a unit group having the same inspection date are determined as unfailed units in the state B.

  Next, a case where the unit state determination unit 131b determines an unfailed unit in the state C will be described with reference to FIG. FIG. 6 is a diagram for explaining the processing of the unit state determination unit 131b, and shows data D4 that is partial data of the inspection data D1 of FIG.

  For example, a description will be given by taking continuous unit groups (0204) to (0321) as an example. The unit groups (0204) to (0321) are non-failed units because failure / deterioration data is missing (see (1) in FIG. 6).

  For the unfailed unit group in which such failure / degradation data is missing, the unit state determination unit 131b performs the same processing for the unit groups (0204) to (0321) as in the process described with reference to FIG. Then, a unit in which failure / deterioration data adjacent to both ends of the unit group is shown is obtained. In this case, units (0203) and (0322) are obtained as units adjacent to both ends of the unit groups (0204) to (0321). Next, the unit state determination unit 131b determines whether or not the construction date and the inspection date of the units (0203) and (0322) are the same.

  In the unit state determination unit 131b, the units (0203) and (0322) adjacent to both ends of the unit groups (0204) to (0321) are different in either the construction date or the inspection date, or both. When it is determined that the unit is the unit having the failure data as a representative value (see (2) in FIG. 5), the unit groups (0204) to (0321) are assigned to units (0203), ( 0322), it is determined that the unit is an unfailed unit in the state C (see (3) in FIG. 5).

  Then, the characteristic value estimation unit 131c estimates the characteristic value required for reliability analysis in correspondence with the state of each unit determined by the unit state determination unit 131b.

[Processing of characteristic value estimation unit]
Next, the process of the characteristic value estimation unit 131c will be described. Here, a case where the years of use are estimated as the characteristic values estimated by the characteristic value estimation unit 131c will be described as an example. The age of use is the usage time of the failure / deteriorated part adopted in each unit, and is used by the analysis unit 132 to calculate the MTTF.

  First, a case where the age of a failed unit is obtained will be described. Since this unit is already in a failure state, the characteristic value estimation unit 131c performs the construction date of the management target object including the unit, and the inspection date of the failure / deterioration point determined to be a failure in the unit. Obtain the years of use from the data. Specifically, the characteristic value estimation unit 131c obtains the time length between the construction date recorded in the inspection data and the inspection date as the years of use for the failed unit. In addition, when obtaining the representative value of the degradation rank using the average value, maximum value, etc. of a plurality of failure / deterioration states, the service life for the failure unit may be similarly set to the average value, maximum value, etc.

  Next, the case where the years of use of unfailed units in state A are estimated will be described. The unfailed unit has a degradation rank, and includes a degradation rank that is not determined to be a failure. Therefore, the characteristic value estimation unit 131c uses a function or the like indicating the deterioration progress state of the management target object based on the construction date and the inspection date of the management target object including the unit and the deterioration rank of the unit. In addition, the number of years of use until it is determined that there is a failure is estimated. In this case as well, when obtaining the representative value of the degradation rank using the average value and maximum value of a plurality of failure / degraded states, the service life for the unfailed unit in the state A is also set to the average value, maximum value, etc. That's fine.

  And the case where the years of use of the unfailed unit group in the state B are estimated will be described. The unfailed unit group in this state B can be regarded as equivalent to units adjacent to both ends of the unfailed unit group, in which both the construction date and the inspection date are the same. For this reason, the characteristic value estimation unit 131c employs the years of use of units adjacent to both ends of the state B unfailed unit group for the state B unfailed unit group, respectively. For example, for the unfailed unit groups (0004) to (0121) in the state B shown in FIG. 5, the characteristic value estimation unit 131c is adjacent to both ends of the unfailed unit groups (0004) to (0121). The years of use of (0003) and (0122) are adopted as the years of use of unfailed units (0004) to (0121).

  Furthermore, the case where the years of use of the unfailed unit group in the state C are estimated will be described. The unfailed unit group in this state C has at least one of the construction date and the inspection date of the units adjacent to both ends of this unfailed unit group. It cannot be regarded as equivalent to units adjacent to both ends. Therefore, for the unfailed unit group in state C, the number of years of use of the unfailed unit group in state C is obtained from the distribution of the number of failure / deterioration points recorded in the inspection data with respect to the characteristic value (( 4)).

  Therefore, a process for obtaining the service life of the unfailed unit group in the state C will be described in detail. The characteristic value estimation unit 131c obtains the distribution of the number of failure / deterioration points recorded in the inspection data with respect to the characteristic value for the unfailed unit group in the state C, and the state C based on the approximate curve for the obtained distribution. Estimate the service life of unfailed units. In other words, the characteristic value estimation unit 131c has characteristic values for units other than the unit group so as to coincide with the distribution shape corresponding to the characteristic value of the number of failure / deterioration points with respect to the years of use of the originally recorded inspection data. Using the distribution data of the number of units with respect to the failure state and the usage years of the unfailed units in the state C are determined.

  This will be specifically described with reference to FIG. FIG. 7 is a diagram for explaining processing of the characteristic value estimation unit 131c shown in FIG. (A) of FIG. 7 is a figure which shows distribution with respect to a characteristic value of the number of the failure and degradation locations currently recorded on inspection data. (B) of FIG. 7 is a figure which shows distribution of the ratio with respect to years of use of all the states mentioned above. First, the characteristic value estimation unit 131c obtains the number of years of use of each failure / deteriorated part recorded in the inspection data, and the distribution of the number of failures / deteriorated parts with respect to the years of use of the failure / degraded part ((a) of FIG. 7). (Refer to (1) in FIG. 7).

  Subsequently, the characteristic value estimation unit 131c obtains an approximated curve L1 that coincides in shape with respect to the bar graph indicating the distribution of the number of failure / deterioration points with respect to the years of use of the failure / deterioration points ((a) in FIG. 2)).

  Here, the distribution shape of the number of failure locations for each inspection date (the number of years used) recorded in the inspection data and the distribution shape of the number of units with respect to the number of years inspected for each inspection date are almost the same. It is considered that they match. This is because it is considered that the distance (that is, the number of units) where the inspection is performed on each inspection date and the number of failure / deterioration data recorded on the day are in a positive proportional relationship.

  For this reason, the characteristic value estimation unit 131c also estimates that the distribution shape of the number of units relative to the years of use is substantially the same as the distribution shape shown in FIG.

  Therefore, in order to obtain the distribution of the proportions of all the states shown in FIG. 7B with respect to the years of use, L1 ′ having the same shape as the approximate curve is obtained, and for the years of use of all units matching the approximate curve L1 ′. A distribution shape (a bar graph in FIG. 7B) is obtained (see (3) in FIG. 7).

  In the first embodiment, since the years of use of the failed unit and the unfailed units in the states A and B can be determined or estimated as described above, the failed unit and the unfailed units in the states A and B can be determined. Distribution data of the number of units with respect to the years of use can be obtained. For this reason, the characteristic value estimation unit 131c is a unit corresponding to each service life of the failed unit and the unfailed unit in the states A and B based on the determined or estimated service life of the failed unit and the unfailed unit in the states A and B. The distribution of the ratio of numbers (the bar graph white area in FIG. 7B) is obtained (see (4) in FIG. 7).

  For example, the characteristic value estimation unit 131c calculates a ratio with respect to the total number of units by using the number of units in each service life category of the unit as a variable. Then, the characteristic value estimation unit 131c performs the inspection by performing the least square method, the maximum likelihood method, or the like so that the calculated ratio is closest to the ratio in the respective years of use of the corresponding approximate curve (probability distribution) L1 ′. The distribution of the ratio of the number of units with respect to the years of use of all the units of the data is matched with the approximate curve L1 ′.

  Subsequently, the characteristic value estimation unit 131c distributes the ratio of the number of units with respect to the years of use of the failed units and the unfailed units in the states A and B (the bar graph white portions in FIG. 7B) and the approximate curve L1. By comparing the distribution of the ratio of the number of units with respect to the characteristic value that most closely matches ′ ((bar graph in FIG. 7B)), the entire unfailed unit group in the state C that is closest to the approximate curve L1 ′ The distribution of the ratio of the number of units to the characteristic value (the bar graph hatched portion in FIG. 7B) is obtained (see (5) in FIG. 7).

  In other words, the characteristic value estimation unit 131c uses the distribution data of the number of units with respect to the number of years of use for the failed unit for which the number of years of use and the unfailed unit in the states A and B are used, Use of a group of unfailed units in state C such that the distribution shape of all units including the unfailed units in states A and B and the unfailed units in state C matches the approximate curve L1 ′ as much as possible. Find the distribution data for years.

  The service life obtained in this way is the service life for the entire unfailed unit group in the state C. For example, there are 100 unfailed unit groups in the state C, and among these 100 units, as a result of performing the above processing, 55 units have been used for 30 years and 45 units have been used for 38 years. Suppose that it is calculated. This result is only a result for the entire group of 100 unfailed units in the state C, and does not indicate which years of use apply to which unit. However, even if there is no such combination information of years of use and units, if the years of use and the number of failed units and non-failed units in one tunnel-like facility to be analyzed are determined, the cumulative hazard Reliability analysis by analysis etc. can be performed.

  In this way, the characteristic value estimation unit 131c estimates characteristic values even for units for which the degree of deterioration is not indicated, and uses the data indicating the distribution information of the number of units for each characteristic value for reliability analysis of the management target object. Data is generated and output to the analysis unit 132.

  It should be noted that when obtaining the service life of the unfailed unit in the state C, the same process may be performed using the ratio of the number of each service life to the total service life.

  In addition, since the probability distribution takes a continuous value, the numerical value derived as the service life of the unfailed unit in the state C does not match the service life value of the unit in another state where the service life is fixed. Can be considered. In this case, the numerical value derived as the service life of the unfailed unit in the state C may be replaced with the service life closest to the service life of the unit whose service life has been determined. Note that the replacement process is not particularly required when the number of years of use of the unfailed unit in the state C is estimated using the ratio of the number of years of use to the total number of years of use, instead of the probability distribution.

  In the above processing, the example has been described in which the years of use of the failed units and the unfailed units in the states A, B, and C are obtained and the obtained years of use are associated with the units. It can also be applied when required.

  If the unit of measurement is not a unit based on length but another unit such as a grid, analysis can be similarly performed by replacing the unit with a grid.

[Processing flow of the analyzer]
Next, the process flow of the analyzer 10 will be described. FIG. 8 is a flowchart showing the processing procedure of the analysis processing in the analyzer shown in FIG.

  As shown in FIG. 8, the analysis data generation unit 131 generates analysis data for determining the average life of the management object from the inspection data of the management object to be analyzed. (Step S1). Then, the analysis unit 132 uses the analysis data generated from the analysis data generation unit 131 to perform reliability analysis processing such as the average life of the management target (step S2).

[Flow of analysis data generation processing]
Next, the flow of the analysis data generation process shown in FIG. 8 will be described. FIG. 9 is a flowchart showing a processing procedure of the analysis data generation processing shown in FIG.

  As shown in FIG. 9, the analysis data generation unit 131 first performs an inspection data acquisition process for acquiring inspection data of an analysis target management object (step S <b> 11). Here, the inspection data acquired by the analysis data generation unit 131 indicates the degree of deterioration as failure data, and the non-failure data is missing.

  Subsequently, the unit setting unit 131a performs a unit setting process for setting a unit corresponding to the management target with respect to the inspection data acquired in step S11 (step S12). Subsequently, the unit state determination unit 131b performs unit state determination processing for determining whether the unit is a failed unit or a non-failed unit based on the presence / absence of the deterioration level in the unit and the deterioration level included in the unit. (Step S13). In this process, the unit state determination unit 131b determines that each unit is either a failed unit or an unfailed unit in states A to C.

  And the characteristic value estimation part 131c performs the characteristic value estimation process which estimates the characteristic value of each unit based on at least the deterioration degree shown by inspection data (step S14). Then, the characteristic value estimation unit 131c generates data indicating the distribution information of the number of units for each characteristic value based on the estimation result in step S14 as data for reliability analysis of the management target, and the analysis unit 132 The output process of outputting to (step S15) is performed.

[Unit status determination process flow]
Next, the flow of the unit state determination process shown in FIG. 9 will be described. FIG. 10 is a flowchart of a process procedure of the unit state determination process shown in FIG.

  As shown in FIG. 10, the unit state determination unit 131b first determines whether there is failure / deterioration data for the determination target unit (step S21).

  If the unit state determination unit 131b determines that this unit has failure / deterioration data (step S21: Yes), the deterioration rank included in the failure / deterioration data includes a deterioration rank that is treated as a failure. Whether or not (step S22).

  If the unit state determination unit 131b determines that the failure / deterioration data of this unit has a deterioration rank that is treated as a failure (step S22: Yes), the unit state determination unit 131b determines that this unit is a failed unit (step S23).

  On the other hand, if the unit state determination unit 131b determines that the failure / deterioration data of this unit does not have a deterioration rank that is treated as a failure (step S22: No), this unit is determined to be an unfailed unit in state A (step S22). S24).

  On the other hand, when the unit state determination unit 131b determines that this unit has no failure / deterioration data (step S21: No), the unit state determination unit 131b performs the following processing. When units without failure / degradation data are consecutive, the following processing is performed for the unit group without this failure / degradation data. First, the unit state determination unit 131b has, among other units having failure / degradation data, the previous unit and the subsequent unit closest to this unit group, that is, a unit group having no failure / degradation data. The construction date and the inspection date of the units adjacent to both ends of each are acquired (step S25). Subsequently, the unit state determination unit 131b determines whether the construction date and the inspection date of the units adjacent to the acquired both ends are the same (step S26).

  If the unit status determination unit 131b determines that the construction date and the inspection date of the units adjacent to both ends of the unit group are the same (Yes in step S26), the unit status determination unit 131b It is determined as a failed unit (step S27).

  On the other hand, when the unit state determination unit 131b determines that at least one of the construction date and the inspection date of the units adjacent to both ends of the unit group is different (step S26: No), this unit is in the state. It is determined as a C unfailed unit (step S28).

  Then, the unit state determination unit 131b determines whether there is a next determination target unit (step S29). If the unit state determination unit 131b determines that there is a next determination target unit (step S29: Yes), the unit state determination unit 131b returns to step S21 and performs state determination on the unit. When the unit state determination unit 131b determines that there is no next determination target unit (step S29: No), the unit for checking the data is associated with information for identifying the determined state in association with each unit of the inspection data. The unit state determination process is terminated.

[Flow of characteristic value estimation processing]
Next, the flow of the characteristic value estimation process shown in FIG. 9 will be described. FIG. 11 is a flowchart showing a processing procedure of the characteristic value estimation processing shown in FIG. FIG. 11 shows a case where the age of use is obtained as a characteristic value.

  First, the characteristic value estimation unit 131c determines whether or not the unit whose characteristic value is to be estimated is a faulty unit (step S31). When the characteristic value estimation unit 131c determines that this unit is a failure unit (step S31: Yes), the characteristic value estimation unit 131c determines whether the failure unit is between the construction date recorded in the inspection data and the inspection date. The time length is set as the number of years of use (step S32).

  On the other hand, when the characteristic value estimation unit 131c determines that the unit whose characteristic value is to be estimated is not a failure unit (step S31: No), the characteristic value estimation unit 131c determines that this unit is an unfailed unit, It is determined which of A to C (step S33).

  When the characteristic value estimation unit 131c determines that this unit is an unfailed unit in the state A (step S33: A), the construction date recorded in the inspection data for the unfailed unit in the state A, The service life is estimated based on the inspection date and the degree of deterioration (step S34).

  When the characteristic value estimation unit 131c determines that this unit is an unfailed unit in the state B (step S33: B), the unit in the state B has the same construction date and inspection date. It is regarded as being equivalent to units adjacent to both ends of the unfailed unit group (step S35), and the same service life as the units adjacent to both ends is adopted (step S36).

  When the characteristic value estimation unit 131c determines that this unit is an unfailed unit in the state C (step S33: C), the same years of use as the units adjacent to both ends of the unfailed unit group cannot be adopted. The failure / deteriorated location recorded in the inspection data and the years of use of each location are acquired from the inspection data storage unit 121 (step S37). Then, the characteristic value estimating unit 131c obtains the distribution of the number of failure / deterioration points with respect to the failure / deterioration locations recorded in the inspection data and the years of use of each location from the acquired data (step S38). Subsequently, the characteristic value estimation unit 131c obtains an approximate curve for the obtained distribution (step S39).

  Then, the characteristic value estimating unit 131c acquires the years of use of the failed unit and the unfailed units in the states A and B (step S40). Therefore, the characteristic value estimation unit 131c executes the estimation process of the years of use for the unfailed unit group in the state C after estimating the years of use for all other failed units and the unfailed units in the states A and B. .

  Subsequently, the characteristic value estimation unit 131c compares the distribution data of the number of units with respect to the number of years of use that most closely matches the approximate curve with the distribution data of the number of units with respect to the number of years of use of the failed unit and the unfailed units in the states A and B. A comparison process with the approximate curve to be performed (step S41) is performed. The characteristic value estimation unit 131c obtains a distribution with respect to the characteristic value of the unfailed unit group in the state C so as to be closest to the approximate curve, and thereby estimates the years of use of the unfailed unit group in the state C (step S42). .

[Effect of Embodiment 1]
The inspection data exemplified above does not record non-failure data (non-failure location) itself, so the service data of the faulty unit (characteristic value) is calculated using the inspection data including failure data (failure location) and non-failure data. ) Is difficult to determine the years of use in the same way as In particular, as in the case of the first embodiment, in the case of a long facility, the progress of the inspection is greatly affected by the degree of deterioration, etc., and if the record such as “to which position has been inspected” is not clear, where is the same This is because it is difficult to determine whether the inspection date is.

  Therefore, in the first embodiment, first, the number of missing unfailed data to be complemented can be accurately determined by setting inspection data units corresponding to the purpose of analysis, the properties of the target equipment, and the like. it can.

  In the first embodiment, by dividing the inspection data into units, a method for determining the degree of failure / degradation (degradation rank) can be set on a unit basis, depending on the purpose of analysis and the properties of the target equipment. You can get years of service.

  Further, in the first embodiment, with respect to an unfailed unit group in which failure / deterioration data is missing, the management target of the units adjacent to both ends of the unit group and the predetermined parameters related to inspection are the same. In this case, the characteristic values of the unit group are estimated and complemented based on the characteristic values of the units adjacent to both ends, and predetermined management parameters and inspection parameters of the units adjacent to both ends of the unit group are determined. If they are different, the distribution of the number of deterioration points for each characteristic value recorded in the inspection data is obtained, and the characteristic value is estimated and complemented based on the approximate curve for the obtained distribution.

  Therefore, in the analysis apparatus 10 according to the first embodiment, even when the inspection data does not include the unfailed data itself, the unfailed data portion is complemented with high accuracy and is required for the reliability analysis. Data can be appropriately generated. Then, by using data in which the non-failed data part is appropriately supplemented, the analysis accuracy in the analysis unit 132 can be improved, and this contributes to maintenance of social functions and reduction of infrastructure maintenance costs. be able to.

[Other embodiments]
[System configuration, etc.]
Each component of each illustrated device is functionally conceptual and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to that shown in the figure, and all or a part thereof may be functionally or physically distributed or arbitrarily distributed in arbitrary units according to various loads or usage conditions. Can be integrated and configured. Further, all or a part of each processing function performed in each device may be realized by a CPU and a program analyzed and executed by the CPU, or may be realized as hardware by wired logic.

  Also, among the processes described in this embodiment, all or part of the processes described as being performed automatically can be performed manually, or the processes described as being performed manually can be performed. All or a part can be automatically performed by a known method. In addition, the processing procedure, control procedure, specific name, and information including various data and parameters shown in the above-described document and drawings can be arbitrarily changed unless otherwise specified.

[program]
FIG. 12 is a diagram illustrating an example of a computer in which the analysis apparatus 10 is realized by executing a program. The computer 1000 includes a memory 1010 and a CPU 1020, for example. The computer 1000 also includes a hard disk drive interface 1030, a disk drive interface 1040, a serial port interface 1050, a video adapter 1060, and a network interface 1070. These units are connected by a bus 1080.

  The memory 1010 includes a ROM (Read Only Memory) 1011 and a RAM 1012. The ROM 1011 stores a boot program such as BIOS (Basic Input Output System). The hard disk drive interface 1030 is connected to the hard disk drive 1090. The disk drive interface 1040 is connected to the disk drive 1100. For example, a removable storage medium such as a magnetic disk or an optical disk is inserted into the disk drive 1100. The serial port interface 1050 is connected to a mouse 1110 and a keyboard 1120, for example. The video adapter 1060 is connected to the display 1130, for example.

  The hard disk drive 1090 stores, for example, an OS 1091, an application program 1092, a program module 1093, and program data 1094. That is, a program that defines each process of the analysis apparatus 10 is implemented as a program module 1093 in which a code executable by the computer 1000 is described. The program module 1093 is stored in the hard disk drive 1090, for example. For example, a program module 1093 for executing processing similar to the functional configuration in the analysis apparatus 10 is stored in the hard disk drive 1090. The hard disk drive 1090 may be replaced by an SSD (Solid State Drive).

  The setting data used in the processing of the above-described embodiment is stored as program data 1094 in, for example, the memory 1010 or the hard disk drive 1090. Then, the CPU 1020 reads the program module 1093 and the program data 1094 stored in the memory 1010 and the hard disk drive 1090 to the RAM 1012 and executes them as necessary.

  The program module 1093 and the program data 1094 are not limited to being stored in the hard disk drive 1090, but may be stored in, for example, a removable storage medium and read out by the CPU 1020 via the disk drive 1100 or the like. Alternatively, the program module 1093 and the program data 1094 may be stored in another computer connected via a network (LAN, WAN, etc.). Then, the program module 1093 and the program data 1094 may be read by the CPU 1020 from another computer via the network interface 1070.

  As mentioned above, although embodiment which applied the invention made | formed by this inventor was described, this invention is not limited with the description and drawing which make a part of indication of this invention by this embodiment. That is, other embodiments, examples, operation techniques, and the like made by those skilled in the art based on this embodiment are all included in the scope of the present invention.

DESCRIPTION OF SYMBOLS 10 Analysis apparatus 11 Input part 12 Storage part 13 Control part 14 Output part 121 Inspection data storage part 131 Analysis data generation part 131a Unit setting part 131b Unit state determination part 131c Characteristic value estimation part

Claims (6)

Inspection data for an inspection performed on a management object, which is a unit of measurement according to the management object with respect to inspection data in which the inspection date, deterioration degree, and position information are associated with each other A setting section for setting the unit;
A determination unit that determines that the unit that does not include at least the deterioration degree is in an unfailed state;
For the unit including the degree of deterioration, a characteristic value is estimated based on the construction date of the management target object, the inspection date of the inspection data, and the degree of deterioration of the unit, and the unit does not include the degree of deterioration. In the case of a unit group in a fault state, if the management target of the unit adjacent to both ends of the unit group and the predetermined parameters related to inspection are the same, the characteristic values of the units adjacent to the both ends are used as the basis. The characteristic value of the unit group is estimated and complemented, and when the management object of the unit adjacent to both ends of the unit group and the predetermined parameters regarding the inspection are different, they are recorded in the inspection data. An estimation unit that obtains a distribution of the number of deterioration points for each characteristic value, and estimates and supplements the characteristic value based on an approximate curve for the obtained distribution;
A data complementing device characterized by comprising:   The estimation unit includes a unit group that is different from a unit group that is not included in the failure level and that has different predetermined parameters related to the management target and inspection of the unit adjacent to both ends of the unit group. By comparing the distribution data of the number of units with respect to the characteristic value for units other than the group and the distribution data of the number of units with respect to the characteristic value that most closely matches the approximate curve, the unit for the characteristic value with respect to the unit group 2. The data complementing apparatus according to claim 1, wherein number distribution data is obtained. The determination unit determines the unit group including a predetermined deterioration level among the units including the deterioration level as a unit group in a failure state, and the predetermined deterioration level among the units including the deterioration level is the The unit group that is not included in the degree of deterioration is determined as the first unfailed unit group, and the unit group that is not included in the deterioration level is adjacent to both ends of the unit group. A unit group having the same predetermined parameters related to the management object and inspection of the unit is determined as a second unfailed unit, and among the unfailed unit group not including the degree of deterioration, the unit group A unit group having different predetermined parameters regarding the management object and inspection of the unit adjacent to both ends is determined as a third unfailed unit,
The estimation unit acquires the characteristic value based on a construction date of the management target object and an inspection date of the inspection data for the unit group in the failure state, and the first unfailed state For the unit group, the characteristic value is estimated based on the construction date of the management object, the inspection date of the inspection data, and the degree of deterioration of the unit, and the unit group in the second unfailed state Estimates the characteristic values of the units adjacent to both ends of the unit group as the characteristic values of the unit group, and for the third unfailed unit group, the failed state and the first unfailed state Using the distribution data of the number of units for the characteristic values for the units of the state and the second unfailed state, the distribution for the characteristic values of all the units of the third unfailed state that is closest to the approximate curve is obtained. Data interpolation apparatus of claim 2, wherein.   The said estimation part produces | generates the data which show the distribution information of the said unit number with respect to each characteristic value as data for the reliability analysis of the said management target object, The Claim 1 characterized by the above-mentioned. The data complementing device described.   The data complementing device according to any one of claims 1 to 4, wherein the characteristic value is an age of use. A data supplementing method executed by a data complementing device that supplements inspection data on inspections performed on managed objects,
The data complementing apparatus has a storage unit for storing inspection data in which inspection date, deterioration degree, and position information are associated with each other as inspection data executed for each period with respect to the management object,
The step of setting a unit which is a measurement unit according to the management object with respect to the inspection data, the data complementing device;
A step of determining that the data complementing apparatus is in an unfailed state with respect to the unit not including at least the degree of deterioration;
For the unit including the degree of deterioration, the data complementing apparatus estimates a characteristic value based on the construction date of the management object, the inspection date of the inspection data, and the degree of deterioration of the unit, For a unit group in an unfailed state that does not include a degree of deterioration, the unit adjacent to both ends of the unit group when the management target of the unit adjacent to both ends of the unit group and the predetermined parameters relating to inspection are the same. If the characteristic value of the unit group is estimated and complemented, and the management object of the unit adjacent to both ends of the unit group and the predetermined parameters relating to the inspection are different, the inspection data Obtaining a distribution of the number of deterioration points for each characteristic value recorded in the method, and estimating and supplementing the characteristic value based on an approximate curve for the obtained distribution;
A data complementing method characterized by including.

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