JP2933797B2 - Equipment monitoring system - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method of mounting sensors on various devices such as power devices (substation devices) in a substation and predicting and diagnosing device abnormalities based on information collected from these sensors. Regarding equipment monitoring systems, in particular, abnormalities such as gas density, local overheating, partial discharge, etc. of gas insulated switchgear, abnormal leakage current of lightning arrester, abnormalities due to transformer oil temperature, oil level, partial discharge, overload The present invention relates to a device monitoring system suitable for monitoring an abnormality in a circuit breaker, disconnector, load regulator, and the like.

[0002]

2. Description of the Related Art In recent years, various types of equipment such as gas-insulated switchgear having a small size and a small number of exposed charging parts have become widespread due to the necessity of strengthening substation facilities accompanying an increase in power supply in urban areas. Many are operating.

[0003] By the way, devices with a small exposed charging section such as the above-mentioned gas insulated switchgear have various advantages, but on the other hand, it is difficult to detect and diagnose abnormalities, and maintenance and repair work when abnormalities occur inside the container is required. There was a problem that the work time was easy to increase because of the trouble.

Therefore, conventionally, in order to improve the reliability of the entire device including such a gas insulated switchgear, not only the appropriate design and manufacture of the individual devices but also the confirmation and monitoring of the reliability of the entire device. Various predictive maintenance systems have been considered as effective means.

Here, the latest predictive maintenance system includes a normal state support function for displaying the current state of a sensor attached to a device and performing various data compressions such as hourly time, date and time, and month time as history data. The sensor information is set to a predetermined abnormality detection level, and is compared with this value for determination.
In addition, when an abnormality is detected in combination with other monitoring items, and at the time of abnormality, a diagnosis support function is performed at regular intervals.In addition, the fault point is determined by combining various protection relay operation information such as a ground fault detection sensor. One that has a function to support accidents is already in the driving stage.

A device related to this type of device is disclosed in Japanese Patent Application Laid-Open No. 3-48997.

[0007]

As a predictive maintenance system to be applied to a device such as a gas insulated switchgear, particularly an ultra-high pressure gas insulated switchgear, an abnormal phenomenon support function is provided as an early detection of an abnormal phenomenon and a method for coping with the abnormal phenomenon. Need to help. At this time, it is desired that the abnormal phenomenon be stopped urgently and spontaneously before the accident occurs, and whether the abnormal phenomenon should be restored in a minimum time or the like be specified.

For this purpose, the detection sensitivity is increased to enable early detection of an abnormal phenomenon, the transition of data after detection is closely monitored, and diagnosis is sequentially performed in combination with other related sensor information. It is necessary to optimize the diagnosis interval in consideration of the processing capacity of the data processing device.

In this case, when calculating the change rate of data used as diagnostic information, there is a problem in which sample data is used to obtain highly reliable change rate data.

However, in the above-mentioned prior art, no special consideration is given to the setting of the diagnostic interval in consideration of the processing capability of the data processing device, and the processing is always performed at a constant diagnostic interval. In order to anticipate the appropriate diagnosis, it is necessary to set a quite frequent diagnosis interval, which requires a data processing device having a sufficient processing capacity, and there is a problem that the cost is likely to increase. .

An object of the present invention is to provide an equipment monitoring system for a predictive maintenance system which does not require a large capacity for data processing and can perform a sufficiently appropriate diagnosis.

[0012]

The object of the present invention is to provide an abnormality support process in a predictive maintenance system by constantly sampling and measuring a sensor signal to detect the presence or absence of an abnormality, and collecting related data after the abnormality is detected. The data processing unit that performs the diagnosis has a dual configuration, and the data collection and diagnosis processing in the data processing unit are not performed at regular intervals. Instead, the abnormal signal level value, the change rate, and the local processing unit This is achieved by fuzzy control adopting an integration method for calculation of the degree of conformity, in which the diagnostic intervals are sequentially set, with the elapsed time from the reception of the abnormality detection signal as a membership function.

[0013]

The data collection interval is controlled by the data level value and the rate of change. As a result, data fluctuation can be predicted, and data collection and abnormality diagnosis can be performed at the minimum required interval. Therefore, unnecessary data collection diagnosis time can be omitted.

The rate of change of data used for diagnosis is
The calculation can be performed from the data performed at the optimal interval, and the error can be suppressed as compared with the case where the data is performed at a constant interval. Therefore, more accurate diagnosis can be performed.

[0015]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a device monitoring system according to the present invention will be described in detail with reference to the illustrated embodiments. FIG. 1 shows an example of a predictive maintenance system to which an embodiment of a device monitoring system according to the present invention is applied.
1 is a data processing device, 2 is a communication control device, 3 is a local processing device, 5 is a relay device, 6 is a thermocouple, 7 is a potentiometer, 8 is a contact device, and 9 is an optical cable.

The data processing device 1 includes a CPU (arithmetic processing circuit) 11 and a CCU (communication processing circuit) 12, and monitors the current state of the sensor, history display, diagnosis when an abnormality occurs, and changes in appearance thereafter. In addition, the function of displaying the result on a display device (not shown) is performed.

The communication processing device 2 includes a CPU 21, two CCUs 22 and 23, a display panel 24, and the like.
A process of collecting data from the plurality of local processing devices 3 via the optical cable 9 and transmitting the data to the data processing device 1 is performed.

Each of the local processing devices 3 has a CPU 3
1, CCU 32, O / E (optical-electrical converter) 33, A-
A device to be monitored, including a D (frequency-voltage converter) 34, an A / D (analog-digital converter) 35, a D / I (digital interface) 36, a display panel 37, etc. Are provided at a plurality of locations. And each relay device 5
, And transmits data to the communication processing device 2 via the optical cable 9. At this time, the optical cable 9 from each local processing device 3 is once taken into the star coupler 4 provided in one of the plurality of local processing devices 3, and here, the other local processing devices 3 It is adapted to be connected to the optical cable 9 of the communication processing device 2.

Although only one relay device 5 is shown in the figure, the relay device 5 is provided corresponding to each of the plurality of local processing devices 3 and includes a thermocouple 6, a potentiometer 7, a contact device 8, etc. And serves to transmit data from the various sensors composed of the various types of sensors and transmit them to the respective local processing devices 3. Therefore, various interfaces such as T / Ds 51 and 52 and HVDI 53 and V /
An F (voltage-frequency converter) 54 and an E / O (electric-optical converter) 55 are provided.

Here, the thermocouple 6 is a sensor for detecting the temperature of the device, and the potentiometer 7 is a sensor for detecting, for example, the pressure and liquid level of insulating oil or gas, or the position of a movable portion of the device. And the contact device 8 is constituted by, for example, a microswitch, and also functions as a sensor for detecting a position and the like.

Next, the operation of this embodiment will be described. As described above, in the predictive maintenance system, a function for confirming that the operating state is normal is required as a normal support function. Therefore, in this embodiment, each local processing device 3 creates sensor information at every hour, and based on an instruction from the communication control device 2, the data processing device 1
Transmit data to The data processing device 1 displays history data corresponding to each monitoring item and line in units of three days, three months, and three years based on the data. Further, the data processing device 1 can call each local processing device 3 at any time via the communication control device 2 and monitor the current value data of the sensor.

As described above, the local processing device 3
This embodiment mainly measures sensor signals and detects abnormalities. In this embodiment, as an auxiliary function, a display panel 37 is provided for facilitating maintenance for sensor adjustment. A variety of display processes, such as displaying the presence / absence of abnormalities in the automatic monitoring information and changing the setting of the set value for performing abnormality judgment, changing the display of the sensor initial setting information, setting the line operation status, alarm lock, and setting the test mode I can do it.

On the other hand, as an abnormal time support function, an abnormality sign of a device is detected immediately to prevent an accident, and
In the event of an accident, it is desired that abnormal locations, causes, and countermeasures can be dealt with.

Therefore, in this embodiment, as shown in FIG. 2, the abnormality detection processing by the local processing device 3 and the abnormality support processing by the data processing device 1 are executed.
The respective CPUs 31 and 11 are configured. First, in the abnormality detection processing by the local processing device 3, the measurement processing of the sensor signal is always performed, and the processing of constantly determining whether or not there is a sign of abnormality is repeated based on the result (S1, S2, here). And S stands for step).
Then, once an abnormality is detected, data representing the abnormality is transmitted to the higher-level data processing device 1 via the communication processing device 2 (S3, S4).

On the other hand, the data processing device 1 starts the abnormality support process triggered by the abnormality detection by the local processing device 2, and first executes a process (S5) of collecting data representing related sensor signals and fault information. Then, a level comparison and determination (S6) of the sensor signal and an abnormal pattern diagnosis (S7) based on the result are sequentially executed, and thereafter, it is determined whether or not a change has appeared in the state of the device (S6).
8) When it is determined that there is a change, the state of the device at that time, that is, various data at that time is registered (S9).

Then, the data processing device 1
After the processing of step 8 or S9, an interval until the next diagnosis processing is started, that is, a predetermined interval is set,
After the elapse of the predetermined interval, the process returns to the process of S5, and thereafter, the abnormality support process including the processes of S5 to S10 is repeated again until the abnormality is recovered.

Next, the predetermined interval setting process in S10 will be described. First, as shown in FIG. 3, the level of data taken from various sensors, ie, the sensor level, the rate of change of this sensor level, and the time when the local processing device 2 detects an abnormal symptom, ie, the progress from the aspect change Three types of tables (a), (b), and (c) using time as a variable are prepared, and the diagnostic interval suitability is calculated from these tables. Then, using the diagnostic interval fitness as a membership function, an integration method is adopted for the fitness calculation, and a predetermined interval is calculated by fuzzy control.

That is, as the sensor level increases,
Alternatively, the fuzzy control is performed by setting the membership function so that the interval becomes shorter as the rate of change in the sensor level becomes larger, the interval becomes shorter immediately after abnormal symptom detection, and immediately after the appearance change, and then becomes longer as time elapses. You do it. It goes without saying that these processes are executed by the CPU 11 in the data processing device 1.

As a result, according to this embodiment, after the sign of abnormality appears, when the sensor level further rises, the rate of change in sensor level becomes large, and immediately after the detection of abnormal sign or immediately after the appearance change, When it becomes necessary to enhance the abnormality monitoring, the frequency of the abnormality diagnosis is made sufficiently high, and otherwise, the frequency of the abnormality diagnosis is reduced, so that the accurate abnormality diagnosis is always performed without increasing the load on the CPU 11. Can be obtained.

Here, in the case of the above embodiment, the load on the CPU required to obtain an accurate abnormality diagnosis is about 1 / compared to the case where the abnormality diagnosis is performed at regular intervals as in the prior art. It is reduced to 2.

[0031]

According to the present invention, abnormal signs appear,
When it becomes necessary to increase the frequency of abnormality diagnosis, it is possible to always set an accurate diagnosis interval accordingly.As a result, in the steady state, the reliability of abnormality diagnosis can be improved even if the frequency of abnormality diagnosis is reduced. Because there is no risk of damage,
The increase in the load on the arithmetic unit is suppressed, and the cost can be sufficiently reduced.

Further, according to the present invention, by setting the detection sensitivity of the sensor abnormality sign in the local processing device to a high level, it is possible to extract the abnormality at an early stage and then make a timely inference by the data processing device. As a result, the aspect of the device can be accurately grasped, so that the performance of the abnormality support function can be further improved.

[Brief description of the drawings]

FIG. 1 is a block diagram showing an example of a predictive maintenance system to which an embodiment of a device abnormality monitoring system according to the present invention is applied.

FIG. 2 is a flowchart illustrating the operation of one embodiment of the present invention.

FIG. 3 is an explanatory diagram showing a membership function in one embodiment of the present invention.

[Explanation of symbols]

 Reference Signs List 1 data processing device 2 communication control device 3 local processing device 4 star coupler (SC) 5 relay device 6 thermocouple (sensor) 7 potentiometer (sensor) 8 contact device (sensor) 9 optical cable

────────────────────────────────────────────────── ─── Continuation of the front page (56) References JP-A-59-108192 (JP, A) JP-A-2-293624 (JP, A) JP-A-4-323518 (JP, A) (58) Survey Field (Int.Cl. ⁶ , DB name) G01R 31/00 G01R 31/02 G01R 31/12 G01D 21/00 G08B 23/00-31/00 H02B 13/065

Claims (2)

(57) [Claims] An apparatus monitoring system for diagnosing an abnormality of a device based on a signal from a sensor attached to the device.
A local processing means for constantly measuring the sensor signal to detect a level indicating an abnormality; and starting an abnormality diagnosis of the apparatus at predetermined intervals triggered by the fact that the level indicating the detected abnormality has reached a predetermined level. Data processing means, wherein the data processing means is configured such that the predetermined interval is sequentially set by fuzzy control using a membership function of a signal level from the sensor and an elapsed time since being triggered. A device monitoring system characterized by being performed. 2. The apparatus according to claim 1, wherein the abnormality diagnosis processing of the device by the data processing means is a processing for determining the appearance of the equipment based on the time-series data collected from the sensor, and according to a result of the appearance determination processing. A device monitoring system configured to perform an abnormal display.