JPS594726B2 - Equipment monitoring method - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION 5. Field of Application of the Invention The present invention relates to a method for monitoring a large number of equipment such as power plants and chemical plants.

BACKGROUND OF THE INVENTION In order to operate a plant safely and efficiently, operators monitor the operating status of equipment that makes up the plant using an operation control panel.

In order to monitor the operating status, a conventional operation control panel is equipped with an indicator/recorder that displays analog data and an indicator light that displays digital data. Operators monitor the operating status of equipment by determining whether the 15 analog and digital data are normal or abnormal using indicators, recorders, and indicator lights. At this time, for digital data, depending on the blinking status of the indicator light, for example, ``If it is lit, it is normal; if it is off, it is 20 abnormalities.'' Can be judged.
Regarding analog data, depending on the current value displayed on the indicator/recorder, for example, ``The current value is below the limit value of that data, so it is normal'' or ``The current value is 2 times the limit value of that data.''
It is also possible to clearly determine whether it is "normal" or "abnormal", such as "It is abnormal because it exceeds the 5 limit value." In general, operators do not make a simple judgment of ``normal or abnormal,'' but rather judge ``how normal is it?'' or ``how abnormal is it?'' from the relationship between the current value and the limit value. , the so-called "normality" or "abnormality" of data is measured by an indicator.
The operating status of the equipment is monitored by reading from the recorder.
However, in large-scale plants such as nuclear power plants, there are more than 103 pieces of analog data representing different state quantities necessary for monitoring the operating states35 of the equipment that makes up the plant, so operators have to The amount of work required to read the meter is enormous.

In addition, in such a large-scale plant, a small abnormality that occurs in one piece of equipment can spread throughout the plant and cause a major accident, so with safety first in mind, it is necessary to prevent abnormalities from occurring in this type of equipment. In this case, an interlock automatically shuts down the entire plant. Therefore, in order to improve the operating efficiency of a plant, it is necessary to know in advance about abnormalities that are about to occur in equipment from changes in related analog data, and to take appropriate preventive measures. In other words, operators must constantly monitor indicators and recorders. As described above, the work of monitoring the operating states of the equipment constituting the plant using analog data indicating different state quantities displayed on indicators and recorders is a very burdensome work for operators.

OBJECTS OF THE INVENTION An object of the present invention is to provide an equipment monitoring method that can accurately determine the degree of abnormality in equipment and can improve the operating efficiency of a plant.

Summary of the Invention A feature of the present invention is that for each of a plurality of groups formed by collecting a plurality of related devices installed in a plant, the state quantity signal output from each device is determined to be a steady value and the above-mentioned alarm. A dimensionless abnormality signal is generated based on the difference between the state quantity signal and the steady value and the difference between the alarm value and the steady value when the input state quantity signal is between the alarm value and the alarm value. and the limit value, a non-dimensional abnormality signal is generated based on the difference between the alarm value and the state quantity signal and the difference between the limit value and the alarm value, and The purpose is to display the maximum abnormality signal.

Embodiment of the Invention A preferred embodiment of the present invention will be described below with reference to the drawings.

FIG. 1 shows the equipment monitoring device according to the present embodiment.
N and a display section 3.

The data conversion units 111 to 1Nn convert electric signals Dl, .about.DNO of different state quantities representing the current state from each device into abnormality degree signals Sll to SNO. Abnormality signal S
ll to SNO are grouped into N groups and input to the signal generators 21 to 2N. For example, taking a boiling water nuclear power plant as an example, as shown in Table 1, the plant can be divided into 14 groups.

Data included in a group includes different state quantities. The signal generators 21 to 2N generate abnormal signals Sll to SNn.
Display signals X1 to XN for each group are generated based on the values of . The display section 3 displays the display signals X1 to XN on a cathode ray tube, for example, as shown in FIG. As a result, in the case of a boiling water nuclear power plant, operators
By simply monitoring the 14 display signals X1 to Xl4 using the diagram as shown in the figure, virtually all 103 pieces of analog data are being monitored. In other words, it is possible to constantly monitor all the equipment that makes up the plant. Each section will be described in detail below. First, an embodiment of the data conversion section 111 is shown in FIG. 3 as a representative example of the data conversion sections 111 to 1Nn.

In this practical example, the abnormality degree signal Sll is set in advance to the steady value D? It is calculated and determined for each width ΔDll using 1 as a reference and stored in the memory 1111. Divider 1
112 determines to what address in the memory the current data value Dll corresponds, and the reader 1113 reads the abnormality degree S from a predetermined address in the memory 1111 based on the result of the determination.
Read and output ll. Here, in order for the plant equipment monitoring device of this embodiment to be useful for monitoring the operating states of equipment constituting a plant, the method of calculating the degree of abnormality Sll stored in the memory 1111 is important.

Conventionally, an operator determines the degree of abnormality of data by comparing the current value of the data with a steady value. This is formulated as is by the formula (c) for data D
This is a method of obtaining the abnormality degree signal Sll of ll. here,
D? , is the steady-state value of the day.

However, if we use the formula (c), for example, in a boiling water nuclear power plant, if the recirculation system fluid joint oil temperature rises to 88°C from a steady state value of 80°C, and if the recirculation pump bearing temperature at a steady state value of 50°C rises to 55°C, The degree of abnormality is 0.
It becomes 1.

However, in reality, in the former case, the recirculation pump trips when the temperature reaches 88°C, while in the latter case, even if the temperature reaches 55°C, there is no problem in operating the recirculation pump, just as if the temperature were 50°C. . Therefore, data cannot be compared with each other using the abnormality degree Sll in equation (1). Therefore, it is more appropriate to calculate the degree of abnormality Sll using equation (2). Here, D'1 is a data alarm value and DJi'1 is a data limit value.

Expression (2) can be expressed graphically as shown in FIG. 4.

When the abnormality degree Sll is calculated using equation (2) for the recirculation system fluid joint oil temperature and recirculation pump bearing temperature described above,
The recirculation system fluid joint temperature of 88°C matches the limit value, so the abnormality level is 1.0, and the recirculation pump bearing temperature of 55°C is below the alarm value of 100°C, so the abnormality level is 0.09, which clearly shows the difference. comes out. Therefore, since the abnormality degree signal is made dimensionless based on the alarm value and limit value as shown in Equation 2, the degree of abnormality of the equipment can be determined with high precision in accordance with the current value of the data. Therefore, it is possible to accurately know the degree of the abnormality, that is, the degree to which urgent action is required to implement driving operations to avoid the abnormality.

This makes it possible to reliably prevent the abnormality from expanding. In addition, if the limit value D, is not clearly defined for the data D,, equation (2) can be used by transforming it into the following equation (2). If expressed in a graph, it would look like Figure 5.

Furthermore, like the reactor water level in a boiling water nuclear power plant,
There is also data D, which has two alarm values and two limit values.

In other words, the steady value D of the reactor water level? , is 100, but the alarm value is set to 112cnL and 43CIrL, and the limit value D is set to 122 (V7I and 18 (V7l). In such a case, the abnormality degree Sll is (2'') (Q) Here, d↑1 is the alarm value on the lower side of the data, and Dtl is the limit value on the lower side of the data.

Equation (2″) can be expressed as a graph as shown in Figure 6. Equation (2), (2, and (2) is an example of the functional form for determining the degree of abnormality Sll, and the current value of the data is Dll is steady value D?, alarm value D↑pi d+1, limit value D 1,000,・dya,
Any functional form may be used as long as it changes between ``0'' and 6r'' as the value changes.

For example, in FIG. 4, a straight line may connect the steady value D+1 and the alarm value D+1, and the alarm value D+1 and the limit value. In addition, the value of the abnormality signal Sll is not necessarily limited to the limit value D, and the alarm value D+1 is set to 0.5-steady value Dll.
There is no need to set it to 60゛. In this way, the data conversion section converts different state quantities such as recirculation pump bearing temperature and reactor water level into dimensionless degrees of abnormality, so it is easy to calculate the degree of abnormality of various different state quantities obtained from groups. I can understand it.

The obtained abnormality degree signal is input to a predetermined signal generating section for each group. Next, as an example of the signal generating sections 21 to 2N, an embodiment of the signal generating section 21 is shown in FIG.

The one with the maximum abnormality degree signal S, i from the abnormality degree signals Sll to SLL is set as the signal X1 representing the group.
In other words, the least normal data among the data in the group is always selected. The embodiment of the signal generator 21 shown in FIG. 7 has (11) high value gates (H
Ighvaluegate) 211 to 21 (1-1).

Each high value gate 211-21(1-1) compares two inputs and outputs the larger one. Therefore, the maximum value of the abnormality degree signals Sll to Sl is selected as the signal X1.
If the maximum abnormality degree is displayed as the representative value of the group, if even one data in the group exceeds the limit value for that data, the entire group will be affected even if the rest of the data in the group is normal. In the event of an abnormality, the group status will be accurately displayed. According to this embodiment,
When the state quantity signal is between the steady value and the alarm value, a dimensionless abnormality degree signal is generated based on the difference between the state quantity signal and the steady value and the difference between the alarm value and the steady value, and is also input. When the detected state quantity signal is between the alarm value and the limit value, a dimensionless abnormality degree signal is generated based on the difference between the alarm value and the state quantity signal and the difference between the limit value and the alarm value. There is.

In other words, since the abnormality degree signal is made dimensionless by considering the alarm value and limit value, especially the alarm value, the degree of abnormality for the current state quantity signal that exceeds the steady value can be calculated based on the characteristics of each state quantity signal. It can be calculated with high accuracy by taking into consideration.
Therefore, when the state quantity signal exceeds a steady value, the operator can be accurately informed of the degree of urgency with which to perform plant operation to resolve the situation. Therefore, the plant can be operated safely and efficiently. In addition, since the maximum abnormality signal for each group is displayed from various different state quantity signals for each group, all equipment that emits different state quantities in the plant can be constantly monitored just by monitoring the maximum abnormality signal for each group. be able to. FIG. 8 is a flowchart showing an example of the processing procedure when the device monitoring method is implemented using a computer in another embodiment of the present invention.

In this embodiment, processing is performed for each group. That is, for all data within a group, after taking in signals from each device and converting them into abnormality degree signals, the maximum abnormality degree signal within the group is output. As an embodiment of the display section 3, a device which has already been applied for (Japanese Patent Application No. 48-133416) that displays a graphical display as shown in FIG. 2 can be used as it is, so its explanation will be omitted here. In addition, in FIG. 2, the display signal X1 for each device or group
-XN are standardized so that they line up on the same circumference when everything is normal, and are displayed in polar coordinates. Therefore, the operator who monitors this can determine whether or not an abnormality has occurred in terms of pattern recognition based on the degree of distortion of the displayed figure from the circle. Effects of the Invention As explained above, according to the present invention, even in a large-scale plant, all equipment constituting the plant can be constantly monitored based on a large number of different state quantities obtained from the plant.

Moreover, since the alarm value is taken into consideration, the degree of abnormality can be determined with high accuracy, and the degree of urgency of operations to avoid abnormality can be accurately known. Therefore, the plant can be operated safely and efficiently.

[Brief explanation of the drawing]

FIG. 1 is a diagram showing the configuration of an equipment monitoring device embodying the method according to the present invention, FIG. 2 is a diagram showing an example of a graphical display on the display unit 3 in FIG. 1, and FIG. 3 is a diagram similar to the one shown in FIG. 4, 5, and 6 are diagrams showing examples of the data conversion unit 111 in FIG. FIG. 7 is a diagram showing an example of the signal generating section 21 in FIG. 1, and FIG. 8 is a flowchart. 111~1Nn...Data conversion section, 21~2N
......Signal generation section, 3...Display section.

Claims (1)

[Claims] 1. Sequentially input a plurality of different state quantity signals representing the current state of each of a plurality of groups formed by collecting a plurality of related devices installed in a plant, and When a steady value, an alarm value, and a limit value are determined, when the input state quantity signal is between the steady value and the alarm value, the difference between the state quantity signal and the steady value and the alarm value A dimensionless abnormality degree signal is generated based on the difference between the alarm value and the steady value, and when the input state quantity signal is between the alarm value and the limit value, the alarm value and the state generating a dimensionless abnormality degree signal based on the difference with the quantity signal and the difference between the limit value and the alarm value, and outputting the maximum abnormality degree signal in each group for each of the groups; A device monitoring method that displays the maximum abnormality degree signal for each group.