JPH0345054A - Fault diagnostic method for terminal equipment - Google Patents

Abstract

PURPOSE:To easily diagnose normality or abnormity of a terminal equipment by providing a storage means, a count means, a comparison means and a diagnostic means, monitoring a call unit, a call pattern and a traffic or the like per unit time from the terminal equipment and comparing them with a predicted value so as to diagnose the normality of the terminal equipment. CONSTITUTION:A storage means 25 stores predicted call units in advance for plural time zones corresponding to each terminal equipment. A count means 24 counts a call unit of plural time zones for each terminal equipment 3 and a comparison means 23 compares a call number for each unit time in each terminal equipment 3 counted by the count means 24 with a prescribed call number for each unit time for each terminal equipment 3 stored in advance in the storage means 25 and gives the result of comparison to a diagnostic means 22. When both call numbers have a large difference as the result of comparison, the diagnostic means 22 discriminates it that the terminal equipment has an error and gives a result of discrimination to an output means 21 and output it to a display device. Thus, a fault of each terminal equipment is recognized by a central device.

Description

[Detailed Description of the Invention] [Industrial Application Field] The present invention relates to a method for diagnosing abnormalities in terminal devices, and is particularly applicable to distributed systems for building management systems, bank online systems, remote monitoring, control systems, etc. The present invention relates to an abnormality diagnosis method for a terminal device.

[Prior Art] As a conventional technology related to a distributed system for remote monitoring, control, etc., a method using polling from a central device is known. The method of diagnosing abnormalities in terminal devices in this system is to check for abnormalities in the terminal devices by calling each terminal device periodically and sequentially from the central device. If the communication time per terminal device is long, the time required for one round of polling for all terminal devices becomes longer, and the load on the central device due to this polling also increases.

Furthermore, as another conventional technique, a contention method (communication based on notifications from the terminal devices) is known in which communication between the central device and the terminal devices in the system is performed. In this method, when the terminal device does not issue an alarm, the central device cannot distinguish whether "the terminal device is normal and no alarm is issued" or "the terminal device is abnormal and cannot issue an alarm." In order to detect abnormalities in the terminal device, as in the previous case,
Wasteful operations such as periodically checking the terminal device by polling were performed.

Note that, as a conventional technique related to abnormality diagnosis of the terminal device as described above, for example, a technique described in Japanese Patent Application Laid-Open No. 60-91753 is known.

[Problems to be Solved by the Invention] The above-mentioned prior art, particularly the prior art in which the communication method is a contention method, is capable of determining whether a terminal device is normal or abnormal during normal operation without issuing a notification to the central device. Therefore, the polling method, in which the central device calls the terminal device and checks for abnormalities in the terminal device, is used only to check for abnormalities in the terminal device, which increases the load on the central device. Additionally, there is a problem in that if the terminal device is normal, it is performing unnecessary operations.

An object of the present invention is to provide a terminal device abnormality diagnosis method that solves the problems of the prior art described above and makes it possible to easily diagnose whether the terminal device is normal or abnormal without increasing the load on the central device. It is about providing.

[Means for Solving the Problem] According to the present invention, the above object includes a storage means, a counting means,
Equipped with comparison means and diagnostic means, it monitors the number of calls made from the terminal device per unit time, call pattern, traffic volume, etc., and diagnoses the normality of the terminal device by comparing these with predicted values. achieved.

[Operation] The storage means stores in advance the predicted number of calls in each unit time for each terminal device. The counting means measures and counts the actual number of calls made from the terminal device. The comparison means compares the number of calls (or its pattern) stored in the storage means described above with the number of calls (or its pattern) actually counted by the counting means. Further, the diagnostic means uses this comparison result to diagnose whether the terminal device is normal or abnormal.

The diagnostic results are outputted by the output device and displayed or printed, allowing maintenance personnel to quickly grasp the status of the terminal device and take prompt action when an abnormality occurs.

[Embodiment] Hereinafter, an embodiment of the terminal device abnormality diagnosis method according to the present invention will be described in detail with reference to the drawings.

FIG. 1 is a block diagram showing the system configuration of an embodiment of the present invention, FIG. 2 is a block diagram showing the configuration of the central device, and FIG.
6 to 6 are flowcharts for explaining the operation of an embodiment of the present invention, and FIGS. 7 to 11 are diagrams showing various tables necessary for the operation.

In FIGS. 1 and 2, l is a central device, 2 is a communication network,
3 is a terminal device, 4 is a central device side communication line, 5 is a terminal device side communication line, 21 is an output means, 22 is a diagnostic means, 23 is a comparison means, 24 is a counting means, and 25 is a storage means.

Distributed systems to which the present invention is applied include, for example, building management systems, bank online systems, remote monitoring systems, control systems, etc. As shown in FIG.
and a plurality of terminal devices 3, for example, a telephone line, LA
N. Communication via a dedicated line is connected via vfJ2 and line 4.5. The central device 1 takes in various information from the terminal device 3 and provides necessary information to the terminal device.

The various information sent and received between the central device 1 and the terminal device 3 differs depending on the system. For example, in a building management system, it is measurement data of building equipment, status change data, etc. If available, this information includes the amount of deposits and savings to be withdrawn, name, PIN number, etc.

In the system configured as described above, the central device 1
The functions provided in the central unit 1 according to the invention in order to diagnose abnormalities in the terminal device 3 are shown in FIG.

In general, when the central device l diagnoses the terminal device 3,
It works as follows.

The storage means 25 stores in advance the expected number of calls for each of a plurality of time periods for each terminal device.

The counting means 24 counts the number of calls for each of the plurality of time periods for each terminal device 3. The comparison means 23 calculates, for each terminal device 3 counted by the counting means 24,
The number of calls for each unit time is compared with the predicted number of calls for each unit time for each terminal device 3 stored in advance in the storage means 25, and the comparison result is provided to the diagnostic means 22. . As a result of this comparison, if there is a large difference between the numbers of calls made, the diagnostic means 22 determines that an abnormality has occurred in the terminal device, passes the determination result to the output means 21, and outputs the result to the display device or printing device. Output to .

The reason why it is possible to diagnose a terminal device using such a method will be explained below.

In general, if the system described above is operating normally and each terminal device is operating normally, the number of calls made from the terminal device to the central device will be statistically equal to the number of calls made for each time period during system operation. , is known to have a specific distribution. Therefore, the number of calls that can be predicted based on the statistically obtained characteristics of the terminal device for each time period for each terminal device is stored in the storage means as the predicted number of calls, and from the actual terminal device. If the number of calls is significantly different from the predicted number of calls, it can be determined that some abnormality has occurred in the terminal device.

The present invention is based on the above-mentioned principle, and its detailed operation will be explained below with reference to FIGS. 3 to 6.

FIG. 3 is a processing flow explaining the operation of the counting means 24, and the following processing is performed.

(1) First, check the timer and determine whether the time has changed. This time is the start time or end time of the time period for counting the number of calls made by each terminal device,
In this example, each hour is the hour (step 31).
6 (2) If the time has changed in step 31, it is determined whether it is the preset stop time of the counting means, and if it is the stop time, the process is ended (step 32).

(3) In step 32, if it is not the stop time, the number of calls made by each terminal device 3 that is being counted is calculated by (1)
It is stored in the actual call number table shown in FIG. 7 in the format shown in the formula (step 33).

K (n, t) = CONT (n, t) - (1) where, K: number of actual calls n: terminal device number (n = 1.2... + n) t:
Time (t = 0.l, 2, 3..., 2
3) CONT: Count number of measured calls As mentioned above, the number of calls made by each terminal device in each time period is registered in the actual number of calls table, but instead of this actual number of calls, (2 ) or (3), or may be a pattern thereof.

T (n, t) = CONT (n, t)
...43) However, A = traffic volume (4) C0NT (n, t) (n = 1, 2.-,
N, t=o, 1. =..., 23) is cleared to "0',
The counter is initialized (step 34).

(5) After step 34 or step 31
If the time has not changed, the line on the central equipment side [
It is determined whether or not there is a line that is on hold (used) for No. 1 to M. If there is no line, the process from step 31 is repeatedly executed (step 35).

(6) In step 35, if there is a line in use, the device numbers n1 and current time 1 of all terminal devices 3 communicating with the central device l.
．． In response to this, the counter is incremented by 1 as shown in equation (4), and then the process from step 31 is repeatedly executed (
Step 36).

By performing the above-mentioned processing, the counting means 24
The actual number of calls made for each terminal device 3 is counted.

The comparison means 23 compares the actual number of calls made by each terminal device 3,
A comparison is made with the predicted number of calls for each time period for each terminal device 3 stored in advance in the storage means 25, and the result is output to the diagnosis means 22. The predicted number of calls for each time period for each terminal device 3 stored in the storage means 25 is obtained by collecting the actual number of calls for a long time when the terminal device 3 is normal and performing statistical processing. This is the obtained value and is stored in a predicted number of calls storage table as shown in FIG. The processing flow of the comparing means 23 which compares the predicted number of calls made by each terminal device with the actual number of calls is shown in FIG. 4, and will be explained below.

(1) First, set the initial value of the device number n of the terminal device 3 to “1”
The number of calls K(n, t) (t=1.2..., 23) actually measured by the counting means 24 is set to 7th.
The predicted number of calls M (n, t) (t' = 1.2.
. . , 23) from the predicted number of calls table shown in FIG. 8 (steps 401 to 403).

(2) Next, using the data imported in steps 402 and 403, calculate the sum of squares of deviations in multiple time periods (5), (
Calculate using equations 6) and (7).

t=8 Equations (5) to (7) above are the sum of squares of deviations for 24 hours, the sum of squares of deviations between 8:00 and 19:00, that is, the sum of squares of deviations during working hours, and the sum of squares of deviations during nighttime. , the sum of squares of early morning deviations is determined, but the range of these sums is arbitrary, and may be set to include, for example, daytime and nighttime, working hours and other time periods, etc. (step 404).

(3) Upper limit value εL9a of ε1 stored in advance. , and the lower limit value εLMTLI, and the ε obtained above
3 using equation (8).

εLMTtl+<ε4. ε１くεLMあL1...
...(8) As a result of this comparison, if equation (8) is satisfied, D(n, 1
) is '1', and if it is not satisfied, D(n, l)
is set to "o" (steps 405 to 407).

(4) Next, the upper limit value ε of ε2 stored in advance
LMTUZ and the lower limit value εLMTL2 are compared with ε2 obtained above using equation (9).

εt, Mtuz<ε2. ε2kuεLMTL2...
...(9) As a result of this comparison, if equation (9) is satisfied, D(n, 2
) is set to “1”, and if it is not satisfied, D(n,
2) is set to O'' (steps 408 to 410).

(5) Also, the upper limit value ε of ε stored in advance
LMTLI3 and lower limit value εLM? and ε obtained above are compared using equation (9).

εLM ding υ3ku ε 3+E3< εt, M'rL3
......(10) As a result of this comparison, (10)
If the formula is satisfied, D(n, 3) in the comparison result table shown in FIG. 9 is set to "1"; if not, D(n, 3) is set to "o" (step 411～
413).

(6) Terminal device number n processed above and total number of terminal devices N
It is determined whether the processing for all terminal devices has been completed or not. If the processing has been completed, the processing is completed, and if it has not been completed, the terminal device number is updated by +1, and from step 402. The process of step 414 is repeatedly executed.
415).

Through the above-described processing, the comparison results between the actual number of calls and the predicted number of calls for each terminal device are stored in the comparison result table shown in FIG.

The diagnostic means 22 determines, based on the contents of this comparison result table,
Diagnose abnormalities in each terminal device. The processing flow of this diagnostic means 22 is shown in FIG. 5, and will be explained below.

(]) First, the device number n of the terminal device 3 is set to "1", and from the comparison result table shown in FIG. 9, the comparison result of the terminal device with the device number n is D(n.

1), D(n, 2), and D(n, 3) (steps 51 and 52).

(2) Using the diagnostic table shown in Figure 10, D(n, l
)l D(n, 2)j The content corresponding to the value of D(n, 3) is stored in the output table shown in FIG. 11 as the diagnosis result (step 53).

(3) Terminal device number n processed above and total number of terminal devices N
It is determined whether the processing for all terminal devices has been completed or not. If the processing has been completed, the processing is completed. If not, the terminal device number is updated by +1, and from step 52. Repeat the process (steps 54 and 55).
).

Through the above-described processing, the diagnostic means 22 diagnoses all terminal devices and stores the results in an output table. This diagnostic result is outputted by the output means 21, displayed on a display device, or printed out by a printing device. The operation flow of this output means is shown in FIG. 6, and will be explained below.

(1) First, set the device number n of the terminal device 3 to “l” and read the device number n from the diagnosis result table shown in FIG.
The content of the diagnosis result of the terminal device is output to the output device (steps 61 and 62).

(2) Terminal device number n processed above and total number of terminal devices N
It is determined whether the processing for all terminal devices has been completed or not. If the processing has been completed, the processing is completed. If not, the terminal device number is updated by +1, and the process is performed in step 62. The process is repeated (steps 63 and 64).

According to the above-described embodiment of the present invention, by constantly monitoring the number of calls made from each terminal device, the central device can detect abnormalities in each terminal device without calling the terminal device by means such as polling. I can do it.

The embodiment of the present invention described above only monitors whether the number of calls from the terminal device is between the upper and lower limits of the expected number of calls; , "The lower limit has not been reached", "j between the upper limit and the lower limit" can also be monitored to distinguish between them. In this case, more accurate diagnosis of the terminal device can be performed.

Further, in the embodiment of the present invention described above, the number of calls made by each terminal device is monitored, but the present invention monitors the pattern of the number of calls made by each terminal device, the amount of traffic, the amount of calls, or the number of calls made by each terminal device. A similar effect can also be achieved by monitoring the pattern etc. Furthermore, in the embodiment of the present invention described above, abnormalities in each terminal device are diagnosed using the sum of the number of calls made by each terminal device in one day. It is also possible to diagnose abnormalities in the terminal device using the number of calls made individually.

Next, other embodiments of the present invention will be described with reference to the drawings.

FIG. 12 is a block diagram showing the system configuration of another embodiment of the present invention, FIG. 13 is a block diagram showing the configuration of the central device, FIG. 14 is a flowchart explaining communication control processing of the central device, and FIG. 15 16 is a block diagram showing the configuration of the processor, and FIG. 17 is a flowchart illustrating communication control processing of the processor.

In FIG. 12, FIG. 13, and FIG. 16, 6 is a processor, 7 is a communication line, 26.27 is a communication control means,
Other symbols are the same as in FIGS. 1 and 2.

In another embodiment of the present invention, the central device 1 counts the number of calls made by each terminal device 3, transmits this counted number to the processor 6 via the communication line 1ti7, and the processor 6 detects the abnormality of each terminal device. It is used for diagnosis. Therefore, as shown in FIG. 13, the central device 1 is configured to include only the counting means 24 and the communication control means 26 as means for diagnosing the terminal device 3. The processor 6 provided for this embodiment also serves as a means for diagnosing the terminal device 3, as shown in FIG.
In addition to the communication control means 27 for communication with The apparatus includes means 21, diagnostic means 22, comparison means 23, and storage means 25.

This other embodiment of the present invention is as described above, except that the number of calls made by each terminal device 3 is transferred between the communication control means 26 of the central device and the communication control means 27 of the processor 6. Since it is possible to diagnose each terminal device in the same manner as in the embodiment, only the operation of the communication control means will be described in detail.

First, the processing of the communication control means 26 in the central device 1 is
This will be explained using the flow shown in the figure.

(1) Initialize the device number n of the terminal device 3 to “1”,
As in the case of the previous embodiment, the number of calls K(n, t) (t = 1.2.----., 23) actually measured by the terminal device is taken from the actual number of calls table shown in FIG. (Steps 141, 142).

(2) Transfer the terminal device number n and the captured number of calls from that terminal device K(n, t) (t-1, 2, -, 23) to the sending buffer in the format shown in Figure 15, for example. (step 143).

(3) After instructing the processor 6 to receive data and confirming that the processor 6 is ready for reception, the data stored in the transmission buffer is transmitted to the processor 6 (steps 144 and 145).

(4) Terminal device number n processed above and total number of terminal devices N
It is determined whether the processing for all terminal devices has been completed or not. If the processing has been completed, the processing is completed. If not, the terminal device number is updated by +1, and from step 142. The process of step 146 is repeatedly executed.
147).

Corresponding to the processing of the communication control means 26 in the central device 1, the communication control means 27 in the processor 6
It operates according to the processing flow shown in the figure.

(1) Upon receiving a request for a reception instruction from the communication control means 25 of the central device 1, it prepares for reception and sends a notification that the reception preparation has been completed to the communication control means 26 of the central device 1 (step 70
1).

(2) Receive data sent from the communication control means of the central device 1, and store the received data in a reception buffer configured similarly to the transmission buffer shown in FIG. 15 described above (step 702).

(3) Receive data stored in the receive buffer,
The lines to be stored in the same actual call number table as explained with reference to FIG. 7 provided in the processor 6 (step 7
03).

Thereafter, various means within the processor 6 diagnose each terminal device using the data of the actual call number table, as in the above-described embodiment.

In such other embodiments of the present invention, it is possible to diagnose terminal devices using the traffic volume, call volume, etc. of each terminal device, as in the case of the above-mentioned embodiments. The burden on the central device for device diagnosis can be reduced.

Furthermore, in other embodiments of the present invention, how various means for diagnosing a terminal device are distributed between the central unit and the processor is arbitrary, and the processing load on the central unit and the processing load on the processor are arbitrary. The decision should be made by taking these into consideration.

[Effects of the Invention] As explained above, according to the present invention, the operating status of a terminal device can be reliably determined without issuing a notification from the central device to each terminal device in order to check and diagnose the status of the terminal device. This enables early detection of terminal device abnormalities and countermeasures.Furthermore, since the central device issues notifications for terminal device diagnosis, communication lines are not put on hold, making communication lines more effective. becomes possible to use.

[Brief explanation of drawings]

FIG. 1 is a block diagram showing the system configuration of an embodiment of the present invention, FIG. 2 is a block diagram showing the configuration of the central device, and FIG.
6 to 6 are flowcharts explaining the operation of one embodiment of the present invention, FIGS. 7 to 11 are diagrams showing various tables necessary for the operation, and FIG. 12 is a system of another embodiment of the present invention. FIG. 13 is a block diagram showing the configuration of the central device, FIG. 14 is a flowchart explaining the communication control process of the central device, and FIG. 15 is a block diagram showing the data sent and received between the central device and the processor. Figure 16 is a block diagram showing the configuration of the processor,
FIG. 17 is a flowchart illustrating communication control processing by the processor. 1...Central device, 2...Communication network, 3.
...Terminal device, 4...Central device side communication line, 5...Terminal device side communication line, 6...
・Processor, 7...Communication line, 21...
...Output means, 22...Diagnosis means, 23...
... Comparison means, 24 ... Counting means, 25
. . . Storage means, 26.27 . . . Communication control means. Fig. 1...Seo 5 2...Communication network 3...Terminal device 4...Line (medium size UL work J) 5...Times ML (Hot bed equipment side) Figure 3 Figure 4 Figure 5 Figure 6 Figure 9 Figure 10 Figure 11 Figure 12 Figure 14 Figure 15 Figure 17

Claims (1)

[Claims] 1. In a distributed system configured by connecting a central device and a plurality of distributed terminal devices via communication lines, each terminal device for each time period a storage means for storing the number of calls or its pattern that can be predicted in advance depending on the characteristics of the device; a counting means for counting the actual number of calls or its pattern for each terminal device; It is characterized by comprising a comparison means for comparing the number of calls or its pattern corresponding to each time period of the counting means, and a diagnosis means for diagnosing whether each terminal device is normal or abnormal based on the comparison result of the comparison means. A method for diagnosing abnormalities in terminal devices. 2. The abnormality diagnosis method for a terminal device according to claim 1, further comprising output means for outputting the diagnosis result of the diagnosis means to an output device such as a display device or a printing device. 3. A processor connected to the central device, wherein at least the counting means is provided in the central device and the other means are provided in the processor, according to claim 1 or 2. A method for diagnosing abnormalities in terminal devices. 4. Claim 1, characterized in that the traffic volume or its pattern, or the traffic volume or its pattern is used instead of the number of calls or its pattern.
3. A method for diagnosing an abnormality in a terminal device according to item 2 or 3. 5. Claims 1 to 4, characterized in that the distributed system is a building management system, a bank online system, or a remote monitoring and control system.
A method for diagnosing an abnormality in a terminal device according to item 1 of the items.