JP6285147B2 - Severe large wheel load generation position identification device, Severe large wheel load generation position identification method - Google Patents

Description

  The present invention relates to a technique for specifying a position where a significant large wheel load is generated.

  In order to run a railway vehicle safely and comfortably, it is necessary to maintain the railroad track in a good condition at all times, and for this purpose, measurement of rail irregularities (track misalignment) is indispensable. Most of them measure vertical orbital irregularities (high and low deviations) and horizontal orbital irregularities (traffic deviations) based on a measurement principle called the “Seiya method”. This Masaya method is a kind of “difference method” that measures the trajectory error by the relative displacement of multiple points, and measures the distance between the midpoint and the rail by, for example, placing a water string between any two points. Is. In Japanese railways, track maintenance and management by the “10m string Masaya method”, which measures the distance between the center point of the rail and the rail by stretching a 10m long water string along the rail, is the most common. is there.

By the way, along with the speeding up of railway vehicles, the suppression of heavy wheel load is an important issue.
However, in the 10 m string Masaya method as described above, there is a problem that it is difficult to accurately grasp the location where a large wheel load is generated (see FIG. 7A).

Therefore, a management method using axle box acceleration has been proposed for management of a large wheel load (see, for example, Non-Patent Documents 1 to 3 and Patent Document 1).
In addition to the management method using the axle box acceleration, a management method using the wheel weight has been proposed (see Patent Document 2).

Management method of large wheel load and lateral pressure using axle box acceleration, Railway Research Institute report 2008-8 Detection Method of Short Wavelength Trajectory in High Speed Shinkansen, Railway Research Institute Report 1999-5 Management method of short-wavelength trajectory error utilizing axle box acceleration, Railway Research Institute report 1995-2

JP-A-8-184426 Japanese Patent No. 3537804

However, the management method using the axle box acceleration as described above has the following problems.
(1) In the method using the axle box acceleration described in Non-Patent Documents 1 to 3, since the response magnification between this and the wheel load changes depending on the frequency, the relationship between the two cannot be expressed easily. (For example, see the seventh line from the bottom of the left column of page 35 of Non-Patent Document 1).

  (2) Also, since the value of the axle box acceleration varies greatly depending on the traveling speed of the vehicle that measures the acceleration, there is a problem that it is difficult to use compared to a management method using a trajectory error that does not vary with the speed (for example, , See the sixth line from the bottom of the left column on page 40 of Non-Patent Document 1. Here, it is stated that the wheel load changes depending on the speed, but the axle box acceleration that has a certain correlation with this changes according to the speed. Means at the same time).

  (3) Non-Patent Document 3 describes the validity of using a 5 m string Masaya instead of the conventionally used 10 m string Masaya. There is a problem that the frequency characteristics of the detection have little correlation with the wheel load (see FIG. 2B), and this method has a poor effectiveness.

  (4) Further, in the technique of Patent Document 1, the axle box acceleration is integrated twice and converted into a displacement, which is regarded as a trajectory error, and is not affected by the traveling speed of the vehicle. There is a problem that it is impossible to specify the position of occurrence of a large wheel load from this information.

  (5) In the technique disclosed in Patent Document 2, a sensor such as a strain gauge is attached to a vehicle carriage to estimate wheel load, and this estimation is used as a method for track maintenance inspection. In this case, there is a problem that it is necessary to prepare and attach a special sensor and measurement means to the vehicle, and furthermore, this means cannot correctly estimate the wheel load of a relatively high frequency.

  This invention is made | formed in view of such a subject, The place made into the objective is to provide the technique which pinpoints the generation | occurrence | production position of a large wheel load accurately.

In order to solve the above-mentioned problem, the significant wheel load generation position specifying device of the present invention is a device for specifying a large wheel load generation position that is a position on the track where the large wheel load is generated. And a specifying means for specifying the position of occurrence of the large wheel load based on the orbit deviation data, which is data obtained by detecting the orbit deviation of the orbit , and the specifying means includes the orbit deviation data. Based on this, the curvature of the curve in the case where the change in the value of the trajectory deviation is shown in the coordinate system of “distance along the trajectory—the value of the trajectory deviation” is calculated as an evaluation value for evaluating the trajectory deviation of the trajectory. by calculated curvature is determined to be the Author Owa heavy generating position location is above a predetermined threshold value, it characterized that you identify the Author flowered heavy generation position.

  Further, the significant wheel load occurrence position identifying device of the present invention is a significant wheel load occurrence position identifying device for identifying a significantly large wheel load occurrence position that is a position on the track where the significant wheel load is generated, A specifying means for specifying the position of occurrence of the large wheel load based on the orbit deviation data, which is data obtained by detecting the orbit deviation, is provided, and the specifying means calculates the value of the orbit deviation based on the orbit deviation data. A location where the twice differential value, which is a value obtained by differentiating twice the distance along the trajectory, is calculated as an evaluation value for evaluating the trajectory error of the trajectory, and the calculated double differential value is a predetermined threshold value or more. Is determined to be the position where the excessively large wheel load is generated, so that the position where the significantly large wheel load is generated is specified.

  According to the large wheel load generation position specifying device of the present invention, for example, by utilizing the track error data obtained from the track inspection vehicle that has already been operated regularly, it is not affected by the speed of the vehicle to be measured. In addition, it is possible to accurately identify the position at which a large wheel load is generated by utilizing commonly used track error data without additionally preparing a special device or vehicle.

The markedly large wheel load occurrence position identifying method of the present invention made to solve the above-mentioned problem is a method of identifying a markedly large wheel load occurrence position that is a position on the track where the marked wheel load is generated, A curve when the change in the value of the orbital deviation is shown in the coordinate system of “distance along the orbit−the value of the orbital deviation” based on the orbital deviation data, which is data obtained by measuring the orbit deviation of Is calculated as an evaluation value for evaluating the trajectory deviation of the trajectory, and a position where the calculated curvature is equal to or greater than a predetermined threshold is determined to be the position of occurrence of the significant wheel load, The generation position is specified.

  Further, the markedly large wheel load occurrence position identifying method of the present invention is a markedly large wheel load occurrence position identifying method for identifying a markedly large wheel load occurring position that is a position on a track where the markedly large wheel load is generated, Based on the trajectory error data, which is the data obtained by measuring the trajectory error, the trajectory error of the trajectory is obtained as a twice-differential value obtained by differentiating the value of the trajectory error twice with the distance along the trajectory. Is determined as an evaluation value for evaluating the position, and the position at which the calculated double differential value is equal to or greater than a predetermined threshold is determined as the position at which the large wheel load is generated, thereby identifying the position at which the large wheel load is generated. It is characterized by.

  According to the method for identifying a position where a large wheel load is generated according to the present invention, for example, by utilizing track error data obtained from a track inspection vehicle that has already been operated regularly, it is not affected by the speed of the vehicle to be measured. In addition, it is possible to accurately identify the position at which a large wheel load is generated by utilizing commonly used track error data without additionally preparing a special device or vehicle.

It is a block diagram which shows schematic structure of the large wheel load generation | occurrence | production position specific | specification apparatus 1 of this embodiment. (A) is a graph showing the relationship between the wheel load response magnification and the frequency with respect to the trajectory deviation of the present embodiment, and (b) is the wheel load response magnification and frequency with respect to the curvature and the second derivative value of the present embodiment. It is a graph which shows the relationship. (A) is a graph showing the relationship between the position on the track and the wheel load, (b) is a graph showing the relationship between the position on the track and the trajectory error (original waveform), and (c) is on the track. (D) is a graph showing the relationship between the position on the orbit and the 5 m-string trajectory error, and (e) is the graph showing the relationship between the position on the orbit and the curvature. It is a graph which shows a relationship, (f) is a graph which shows the relationship between the position on a track | orbit, and a 2nd derivative value. It is a track maintenance work flow (1) of this embodiment. It is a track maintenance work flow (2) of this embodiment. It is a conventional track maintenance work flow. (A) is a graph which shows the relationship between 10m string height fluctuation and wheel load, (b) is a graph which shows the relationship between the curvature of a track | orbit, and wheel load.

Embodiments of the present invention will be described below with reference to the drawings. In addition, this invention is not limited to the following embodiment, It is possible to implement in various aspects.
The remarkably large wheel load occurrence position specifying device 1 of the present embodiment is a position on the track where the large wheel load is generated based on the track misalignment data which is data obtained by detecting the track misalignment of the track. It has a function to specify the position of occurrence of large wheel load.

[1. Description of the configuration of the large wheel load generation position identification device 1]
As shown in FIG. 1, the large wheel load occurrence position specifying device 1 is mounted on a vehicle that travels on a track and is mounted on the same vehicle on which the measuring device 10 is mounted. And a management computer 20 installed in an external management center or the like. Hereinafter, it demonstrates in order.

[1.1. Description of Configuration of Measuring Device 10]
The measuring apparatus 10 includes a high / low error acquisition unit 11, a spot / km information acquisition unit 12, and a data recording / transfer unit 13.

The elevation deviation obtaining unit 11 obtains a displacement waveform corresponding to the elevation deviation of the rail, and supplies this to the data recording / transfer unit 13 as elevation deviation data (corresponding to orbit deviation data).
The point / km information acquisition unit 12 acquires point information for specifying the travel position of the vehicle and km information indicating the distance from the starting point, and supplies this to the data recording / transfer unit 13.

  The data recording / transfer unit 13 is a device for storing each data input from the ups and downs acquisition unit 11 and the point / km information acquisition unit 12 in a storage medium at a predetermined time interval or transferring it to an external device It is.

[1.2. Description of Configuration of Management Computer 20]
The management computer 20 is configured by a normal computer system (for example, a personal computer) having an appropriate processing capability, and includes an information processing unit 21 and an output unit 22.

  The information processing unit 21 performs information processing according to a program stored in a storage device (not shown). Specifically, the data of the high / low deviation (trajectory deviation) and the point / km distance stored in or transferred from the data recording / transfer unit 13 of the measuring apparatus 10 are acquired and analyzed. In this way, the position where the large wheel load is generated is specified. And the quality with respect to the generation | occurrence | production position of the specified heavy wheel load is determined, and the determination result is output to the output unit 22.

The information processing unit 21 corresponds to the specifying means (estimating means and determining means) in the claims.
The output unit 22 includes a display, a printer, a voice output device, and the like, and presents information output from the information processing unit 21 to the user by a method such as display, printing, and voice output.

[2. Explanation of the method to identify the position where a large wheel load is generated]
Next, a method for identifying a position where a large wheel load is generated will be described.
The large wheel load occurrence position identifying device 1 of the present embodiment requires a new device or vehicle without being influenced by the speed of the vehicle to which the inspection device is attached as a method for identifying the position where the large wheel load is generated. Instead, the data on the track error that has been generally used in railway track maintenance management will be used. Specifically, if the vehicle travels at a certain speed (if the vehicle travels at a certain speed, it can be converted into a relationship with a certain frequency. This corresponds to the track misalignment data). ) Can be estimated with a simple index (formula). In the present embodiment, the curvature ρ or the twice differential value is used as an index. This will be described in order below.

  First, the curvature ρ as an index is expressed as follows, where y is the value of the trajectory error and x is the distance along the trajectory.

In addition, you may replace the 1st differential part in Numerical formula (1), or a 2nd differential part with a primary difference and a secondary difference, respectively.

As illustrated in FIG. 2B, when the curvature ρ is multiplied by a predetermined coefficient, the relation of the wheel load response magnification with respect to the trajectory deviation is in good agreement between about 3 Hz and about 30 Hz.
That is, by using the value obtained by multiplying the curvature ρ by a predetermined coefficient as an index, it is generally not affected by the speed of the vehicle to be measured, and without preparing a special device or vehicle in general. It is possible to identify the location of the large wheel load by using the orbital deviation data that is used.

  Further, the twice differential value as an index is expressed by the following equation (2), where y is the value of the trajectory error and x is the distance along the trajectory.

In addition, you may replace with the secondary difference about the twice differential part in Numerical formula (2).

As illustrated in FIG. 2B, when the differential value is multiplied by a predetermined coefficient twice, the relationship between the wheel load response magnification to the track error is well matched between about 3 Hz and about 30 Hz.
In other words, by using a value obtained by multiplying the twice-differentiated value by a predetermined coefficient as an index, it is not affected by the speed of the vehicle to be measured, and without preparing a special device or vehicle in general. It is possible to specify the position of the occurrence of a large wheel load by using the orbital deviation data that is used in general.

Incidentally, the 5 m string Masaya method does not agree very much with the relationship of the wheel load response magnification to the trajectory error (see FIG. 2B).
Further, a method for specifying the position where the large wheel load is generated will be described with reference to the graph of FIG.

  FIG. 3A is a graph in which the value of wheel load is the vertical axis and the distance along the track is the horizontal axis. For track maintenance, it is desirable to keep the wheel load below a certain value. For this reason, a position on the track where the wheel load value exceeds a certain value (threshold value) is determined as a position where a large wheel load has occurred. In the figure, the position at which the heavy wheel load has occurred is indicated by the arrow on the left side.

  FIG. 3B is a graph in which the value of the height of the rail surface of the track (original waveform of the track error) is the vertical axis, and the distance along the track is the horizontal axis. This graph is actually used in the current track maintenance field. According to this, it can be seen that the value indicated by the arrow on the left side is greatly sunk compared to others, but in addition to this, a sinking close to this occurs at the position indicated by the arrow on the right side. However, at the position of FIG. 3A corresponding to the arrow position on the right side of FIG. Therefore, it cannot be said that it is suitable to use the original waveform of the trajectory error as a method for accurately detecting the position where the large wheel load is generated.

  FIG. 3C is a graph in which the vertical axis indicates the value of the rail surface height of the track (track error) measured by the 10 m string Masaya method, and the horizontal axis indicates the distance along the track. According to this, the sinking of the right arrow is larger than the left arrow, and the state of occurrence of the wheel load in FIG. Therefore, it cannot be said that it is suitable to use the 10 m string Masaya method as a method for accurately detecting the position where the large wheel load is generated.

  FIG. 3D is a graph in which the vertical axis represents the height of the rail surface of the track (track misalignment) measured by the 5 m string Masaya method, and the horizontal axis represents the distance along the track. According to this, the sinking of the right arrow is larger than the left arrow, and the state of occurrence of the wheel load in FIG. Therefore, it cannot be said that it is suitable to use the 5 m string Masaya method as a method for accurately detecting the occurrence position of a large wheel load.

  FIG. 3E is a graph with the value of curvature ρ on the vertical axis and the distance along the trajectory on the horizontal axis. The curvature ρ is expressed by the above formula (1), where y is the value of the trajectory error and x is the distance along the trajectory. According to this, there is a relationship in which the values of the two arrows on the left and right in the figure coincide with the magnitude relation of the occurrence state of the wheel load in FIG. Further, the graph of FIG. 3E and the graph of FIG. 3A have a relationship that can be regarded as similar in general as waveforms. Therefore, it can be said that the use of the curvature is suitable as a method for accurately detecting the generation position of the large wheel load.

  FIG. 3F is a graph in which the twice-differentiated value is the vertical axis and the distance along the trajectory is the horizontal axis. The twice-differentiated value is expressed by the above formula (2), where y is the value of the trajectory error and x is the distance along the trajectory. According to this, there is a relationship in which the values of the two arrows on the left and right in the figure coincide with the magnitude relation of the occurrence state of the wheel load in FIG. Further, the graph of FIG. 3F and the graph of FIG. 3A have a relationship that can be regarded as similar in waveform. Therefore, it can be said that the use of the differential value twice is suitable as a method for accurately detecting the generation position of the large wheel load.

[3. Explanation of work flow when maintaining track]
Next, the work flow for maintaining the track will be described.
[3.1. Regarding thresholds and maintenance standard values for judging track maintenance status]
First, the threshold value and the maintenance reference value for determining the track maintenance status used in the work flow for track maintenance will be described.

  Examples of the threshold used in this embodiment include (a) a method using a single value as a threshold, and (b) a method using a statistical value of a section as a threshold. As a method of setting the former (b) single value as a threshold, there are several types of thresholds for each single value for the entire line district (for example, between Tokyo and Shin-Osaka) for economics and safety. There is a method of determining, for example, the following (A-1) to (A-4) are set.

(A-1) As a threshold value based on economy, for example, a curvature that can minimize the maintenance input cost or a differential value is calculated by a theoretical calculation or the like, and this value is used as the threshold value.
(A-2) As a threshold based on safety, for example, a correlation analysis between a measured value of a wheel load and a curvature or a second derivative value to suppress the wheel load value to a certain value or a second derivative value is performed. Is a threshold value.

(A-3) A threshold value is set experimentally.
(A-4) Curvature that obtains wheel load by simulation analysis with trajectory error as input, performs curvature analysis based on input trajectory error or correlation analysis with differential value twice, and curbs the wheel load value below a certain value. Or the twice differential value as a threshold value.

Note that the method (a) is suitable for working with a portable small machine because the track maintenance extension per place is relatively short.
In addition, as a method of using the statistical value of the latter (b) section as a threshold value, a threshold value may be determined for a curvature calculated in a fixed section, for example, a 200 m section (lot) or a standard deviation of a twice-differentiated value. Can be mentioned. In this case, the track maintenance work is executed for the section exceeding the threshold. In this method, a standard deviation that can minimize the maintenance input cost is calculated by theoretical calculation or the like, and this is used as a threshold value. This method is suitable when working with large heavy machinery because the track maintenance extension per place is relatively long.

The maintenance reference value is also set in advance from the same viewpoint as the threshold value.
[3.2. Description of track maintenance work flow (1)]
Next, a work flow (1) for preparing a track using a method for identifying a position where a large wheel load of this embodiment is generated will be described with reference to FIG.

  In the first step S110, the curvature ρ or the differential value is input twice. The curvature ρ is expressed by the above formula (1), where y is the value of the trajectory error and x is the distance along the trajectory. Further, the twice differential value is expressed by the above formula (2), where y is the value of the trajectory error and x is the distance along the trajectory. The curvature ρ or the twice differential value is acquired from the measurement device 10 to the information processing unit 21 of the management computer 20. Thereafter, the process proceeds to S120.

  In S120, the information processing section 21 determines whether or not the input curvature ρ or the twice differential value is equal to or greater than a threshold value. If it is determined that there is a portion where the input curvature ρ or the second derivative value is equal to or greater than the threshold value (S120: YES), the process proceeds to S130. On the other hand, if it is determined that the input curvature ρ or the second-order differential value is not equal to or greater than the threshold value (S120: NO), the process proceeds to S170.

In S130, since the track needs to be maintained, the track maintenance is executed. Thereafter, the process proceeds to S140.
In S140, 10m string positive arrow value or 5m string positive arrow value is input. The 10 m string positive arrow value or the 5 m string positive arrow value is acquired by the information processing unit 21 from the measurement apparatus 10. Thereafter, the process proceeds to S150.

  In S150, the information processing section 21 determines whether or not the input 10m string positive arrow value or 5m string positive arrow value is equal to or less than the maintenance reference value. If it is determined that the 10 m string positive arrow value or the 5 m string positive arrow value is less than or equal to the maintenance reference value (S150: YES), the process proceeds to S160. On the other hand, when it is determined that there is a portion where the 10 m string positive arrow value or the 5 m string positive arrow value is larger than the maintenance reference value and it is not less than the maintenance reference value (S150: NO), the process proceeds to S130.

In S160, maintenance is completed because the 10 m string positive arrow value or the 5 m string positive arrow value is less than or equal to the maintenance reference value. Thereafter, this work flow is terminated.
In S170, since it is determined that there is no portion where the curvature ρ or the twice differential value is equal to or greater than the threshold value and the threshold value is not equal to or greater than the threshold value, it is determined that maintenance of the track is unnecessary. Thereafter, this work flow is terminated.

[3.3. Description of track maintenance work flow (2)]
Next, a work flow (2) for preparing a track using the method for specifying the position where the large wheel load of this embodiment is generated will be described with reference to FIG.

  In the first step S210, a 10 m string positive arrow value or a 5 m string positive arrow value is input. The 10 m string positive arrow value or the 5 m string positive arrow value is acquired by the information processing unit 21 from the measurement apparatus 10. Thereafter, the process proceeds to S220.

  In S220, the information processing section 21 determines whether or not the input 10m string positive arrow value or 5m string positive arrow value is equal to or greater than a threshold value. If it is determined that the 10 m string positive arrow value or the 5 m string positive arrow value is equal to or greater than the threshold value and is determined to be equal to or greater than the threshold value (S220: YES), the process proceeds to S230. On the other hand, if it is determined that the 10 m string positive arrow value or the 5 m string positive arrow value is not equal to or higher than the threshold value (S220: NO), the process proceeds to S290.

  In S230, the curvature ρ or the twice differential value is input. The curvature ρ is expressed by the above formula (1), where y is the value of the trajectory error and x is the distance along the trajectory. Further, the twice differential value is expressed by the above formula (2), where y is the value of the trajectory error and x is the distance along the trajectory. The curvature ρ or the twice differential value is acquired from the measurement device 10 to the information processing unit 21 of the management computer 20. Thereafter, the process proceeds to S240.

  In S240, the information processing section 21 determines whether or not the input curvature ρ or the twice differential value is equal to or greater than a threshold value. If it is determined that there is a portion where the input curvature ρ or the twice differential value is equal to or greater than the threshold value (S240: YES), the process proceeds to S250. On the other hand, if it is determined that there is no place where the input curvature ρ or the twice differential value is equal to or greater than the threshold and the threshold is not equal to or greater than the threshold (S240: NO), the process proceeds to S300.

In S250, since the track needs to be maintained, the track maintenance is executed. Thereafter, the process proceeds to S260.
In S260, a 10 m string positive arrow value or a 5 m string positive arrow value is input. The 10 m string positive arrow value or the 5 m string positive arrow value is acquired by the information processing unit 21 from the measurement apparatus 10. Thereafter, the process proceeds to S270.

  In S270, the information processing section 21 determines whether or not the input 10m string positive arrow value or 5m string positive arrow value is equal to or less than the maintenance reference value. If it is determined that the 10 m string positive arrow value or the 5 m string positive arrow value is equal to or less than the maintenance reference value (S270: YES), the process proceeds to S280. On the other hand, when it is determined that there is a portion where the 10 m string positive arrow value or the 5 m string positive arrow value is larger than the maintenance reference value and it is not less than the maintenance reference value (S270: NO), the process proceeds to S250.

In S280, since the 10 m string positive arrow value or the 5 m string positive arrow value is equal to or less than the maintenance reference value, the maintenance is completed. Thereafter, this work flow is terminated.
In S290, it is determined in S220 that the 10m string positive arrow value or the 5m string positive arrow value is not equal to or greater than the threshold value and it is determined that the track maintenance is unnecessary. Thereafter, this work flow is terminated.

  In S300, since it is determined in S240 that there is no portion where the curvature ρ or the twice differential value is equal to or greater than the threshold value and the threshold value is not equal to or greater than the threshold value, it is determined that maintenance of the track is unnecessary. Thereafter, this work flow is terminated.

[3.4. Description of conventional track maintenance work flow]
Next, for reference, a work flow in preparing a track using a conventional method for specifying a position where a large wheel load is generated will be described with reference to FIG.

  In the first step S1010, a 10 m string positive arrow value or a 5 m string positive arrow value is input. The 10 m string positive arrow value or the 5 m string positive arrow value is acquired by the information processing unit 21 from the measurement apparatus 10. Thereafter, the process proceeds to S1020.

  In S1020, the information processing unit 21 determines whether or not the input 10m string positive arrow value or 5m string positive arrow value is equal to or greater than a threshold value. If it is determined that the 10 m string positive arrow value or the 5 m string positive arrow value is equal to or greater than the threshold value (S1020: YES), the process proceeds to S1030. On the other hand, if it is determined that the 10 m string positive arrow value or the 5 m string positive arrow value is not equal to or greater than the threshold value (S1020: NO), the process proceeds to S1070.

In S1030, since the track needs to be maintained, track maintenance is executed. Thereafter, the process proceeds to S1040.
In S1040, a 10 m string positive arrow value or a 5 m string positive arrow value is input. The 10 m string positive arrow value or the 5 m string positive arrow value is acquired by the information processing unit 21 from the measurement apparatus 10. Thereafter, the process proceeds to S1050.

  In S1050, the information processing section 21 determines whether or not the input 10m string positive arrow value or 5m string positive arrow value is equal to or less than the maintenance reference value. If it is determined that the 10 m string positive arrow value or the 5 m string positive arrow value is less than or equal to the maintenance reference value (S1050: YES), the process proceeds to S1060. On the other hand, if it is determined that there is a portion where the 10 m string positive arrow value or the 5 m string positive arrow value is larger than the maintenance reference value and it is not less than the maintenance reference value (S1050: NO), the process proceeds to S1030.

In S1060, since the 10 m string positive arrow value or the 5 m string positive arrow value is equal to or less than the maintenance reference value, the maintenance is completed. Thereafter, this work flow is terminated.
In S1070, it is determined in S1020 that the 10m string positive arrow value or the 5m string positive arrow value is not equal to or greater than the threshold value and it is determined that maintenance of the track is unnecessary. Thereafter, this work flow is terminated.

[3.5. Explanation of the advantage of the method for identifying the position where the large wheel load of this embodiment is generated over the conventional method]
Next, it will be described that the method of specifying the position where the large wheel load of this embodiment is generated is more advantageous than the conventional method.

  In the work flow when preparing a track using the conventional method for identifying the position where the large wheel load is generated as shown in FIG. 6, the 10m string positive arrow value and the 5m string positive arrow value are equal to or greater than a predetermined threshold value. Then, track maintenance is executed, and the quality of the execution result is confirmed by the 10 m string Masaya value and the 5 m string Masaya value.

However, with the 10 m string positive arrow value and the 5 m string positive arrow value, the accuracy of detecting a large wheel load is insufficient, and an irrational situation in which originally unnecessary track maintenance is performed occurs.
Therefore, the above-described “curvature ρ” or “double differential value” may be used as a means for estimating the location of occurrence of a large wheel load on the track as a single index instead of the conventional Masaya method.

  However, for those who are actually engaged in track maintenance management, the curvature ρ and the twice differential value will not be familiar, and it is not easy to measure these values locally. In addition, it is appropriate to confirm the finished accuracy after the maintenance work by using a positive arrow value that can be easily measured on site.

  For example, at the location where the curvature of FIG. 3 (e) or the double differential value of FIG. 3 (f) is large, the 10m chord trajectory error (sinking side) of FIG. 3 (c) or the location of FIG. It is reasonable to use the positive arrow value for the confirmation of the finishing accuracy because the condition that the 5 m-string trajectory deviation (sinking side) becomes large is satisfied. On the other hand, since the reverse relationship does not hold, the 10 m chord trajectory error (sinking side) in FIG. 3C or the 5 m chord trajectory error (sinking side) in FIG. There is a rational issue in the maintenance.

  Therefore, in the method of identifying the position where the large wheel load is generated according to the present embodiment, as one of more practical examples, either one of the curvature ρ or the twice differential value and the 10 m string positive arrow value or the 5 m string positive arrow method is used. It is used as a means to specify the position of the occurrence of a large wheel load in combination with the orbital deviation caused by. Since the Masaya method has been used in the past, it is easy to get used to those who are actually engaged in track maintenance, and it is also easy to measure the Masaya value on site. On the basis of this, further narrowing down can be performed using the curvature or the twice differential value as an index.

[4. Effects of the embodiment]
As described above, according to the large wheel load occurrence position specifying device 1 of the present embodiment, for example, the speed of the vehicle to be measured is measured by utilizing the track error data obtained from the track inspection and measurement vehicle that has already been operated regularly. It is possible to estimate the occurrence point of a large wheel load by using commonly used track error data without being influenced by the above and without additionally preparing a special device or vehicle. Note that trajectory error data obtained from a trajectory inspection device other than the trajectory inspection vehicle may be used. Therefore, it is possible to accurately specify the position where the large wheel load is generated.

  DESCRIPTION OF SYMBOLS 1 ... Authorized large wheel load generation | occurrence | production position identification apparatus, 10 ... Measuring apparatus, 11 ... High / low deviation acquisition part, 12 ... Point / km information acquisition part, 13 ... Data recording / transfer part, 20 ... Management computer, 21 ... Information processing Part, 22 ... output part.

Claims (4)

A device for identifying a position where a large wheel load is generated, which is a position on a track where the large wheel load is generated,
Comprising a specifying means for specifying the position of occurrence of the large wheel load based on the trajectory error data which is data obtained by measuring the trajectory error of the trajectory ;
The specifying means, based on the trajectory error data, indicates the curvature of the curve when the change of the trajectory error value is indicated in the coordinate system of “distance along the trajectory−value of the trajectory error”. The position where the calculated curvature is greater than or equal to a predetermined threshold is determined as the position where the significant wheel load is generated, thereby identifying the position where the significant wheel load is generated <br / > A large wheel load generation position identification device characterized by   A device for identifying a position where a large wheel load is generated, which is a position on a track where the large wheel load is generated,
  Comprising a specifying means for specifying the position of occurrence of the large wheel load based on the trajectory error data which is data obtained by measuring the trajectory error of the trajectory;
The specifying means uses, as an evaluation value for evaluating the trajectory error of the trajectory, a twice-differentiated value that is a value obtained by differentiating the trajectory error value twice by the distance along the trajectory based on the trajectory error data. Calculating and determining the position where the excessively large wheel load is generated by determining that the position where the calculated double differential value is equal to or greater than a predetermined threshold is the position where the significantly large wheel load is generated.
  A device for identifying the location of large wheel load, characterized by   A method for specifying a position where a large wheel load is generated, which is a position on the orbit where the large wheel load is generated,
  When the change in the value of the trajectory error is indicated in the coordinate system of “distance along the trajectory—the value of the trajectory error” based on the trajectory error data, which is data obtained by measuring the trajectory error of the trajectory. The curvature of the curve is calculated as an evaluation value for evaluating the trajectory deviation of the trajectory, and a position where the calculated curvature is equal to or greater than a predetermined threshold is determined to be the position where the significant wheel load is generated. Identify the location of large wheel load
  A method for identifying the position of occurrence of heavy wheel load, characterized by   A method for specifying a position where a large wheel load is generated, which is a position on the orbit where the large wheel load is generated,
  Based on the trajectory error data, which is data obtained by detecting the trajectory error of the trajectory, a twice differential value that is a value obtained by differentiating the trajectory error value twice with respect to the distance along the trajectory is obtained. Is calculated as an evaluation value for evaluating the trajectory deviation, and the position where the calculated double differential value is equal to or greater than a predetermined threshold is determined as the position where the significant wheel load is generated. To identify
  A method for identifying the position of occurrence of heavy wheel load, characterized by