KR20180035854A - Search system - Google Patents

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KR20180035854A
KR20180035854A KR1020187005750A KR20187005750A KR20180035854A KR 20180035854 A KR20180035854 A KR 20180035854A KR 1020187005750 A KR1020187005750 A KR 1020187005750A KR 20187005750 A KR20187005750 A KR 20187005750A KR 20180035854 A KR20180035854 A KR 20180035854A
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similarity
signal
degree
signal group
signals
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KR1020187005750A
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KR102045161B1 (en
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료타 다마야
유타카 마츠에다
히로시 후쿠나가
다카시 나카무라
아츠코 아오키
사토코 사카죠
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미쓰비시 덴키 빌딩 테크노 서비스 가부시키 가이샤
미쓰비시덴키 가부시키가이샤
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
    • B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
    • B66B5/0006—Monitoring devices or performance analysers
    • B66B5/0018—Devices monitoring the operating condition of the elevator system
    • B66B5/0025—Devices monitoring the operating condition of the elevator system for maintenance or repair
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G05B23/0275—Fault isolation and identification, e.g. classify fault; estimate cause or root of failure
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
    • B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0224—Process history based detection method, e.g. whereby history implies the availability of large amounts of data
    • G05B23/0227—Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions
    • G05B23/0229—Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions knowledge based, e.g. expert systems; genetic algorithms
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0224—Process history based detection method, e.g. whereby history implies the availability of large amounts of data
    • G05B23/0227—Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions
    • G05B23/0235—Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions based on a comparison with predetermined threshold or range, e.g. "classical methods", carried out during normal operation; threshold adaptation or choice; when or how to compare with the threshold
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30—

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Theoretical Computer Science (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Evolutionary Biology (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Data Mining & Analysis (AREA)
  • Databases & Information Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Maintenance And Inspection Apparatuses For Elevators (AREA)
  • Indicating And Signalling Devices For Elevators (AREA)

Abstract

The retrieval system includes a reading unit 10, a storage unit 9, a first similarity degree calculating unit 11, and a second similarity degree calculating unit 12. The reading unit 10 reads a first signal group including a plurality of signals. A second signal group including a plurality of signals is stored in the storage unit 9. [ The first degree-of-likeness calculating section 11 calculates the degree of similarity between the signal included in the first signal group and the signal included in the second signal group for a plurality of signals included in the first signal group. The second similarity degree calculating section 12 calculates the similarity degree between the first signal group and the second signal group on the basis of the plurality of similarities calculated by the first similarity degree calculating section 11. [

Figure P1020187005750

Description

Search system

The present invention relates to a search system that can be used to estimate the cause of a failure or the like.

Patent Document 1 describes a system for detecting an abnormality occurring in a plant. In the system described in Patent Document 1, an abnormality of the acquired data is detected on the basis of the distance relation with the partial space obtained by modeling the acquired data and the learning data by the subspace method.

Patent Document 1: Japanese Patent No. 5301310

For example, when a failure occurs in an elevator, a snapshot of signal values indicating the states of a plurality of sensors provided in the elevator is acquired for a certain period of time before and after occurrence of a failure. A snapshot of this signal value is referred to herein as trace data. Conventionally, when new trace data is acquired, past trace data similar to this trace data can not be retrieved. Such a search is useful for estimating the cause of the trouble from, for example, trace data.

SUMMARY OF THE INVENTION The present invention has been made to solve the above problems. It is an object of the present invention to provide a retrieval system capable of retrieving a signal group similar to a signal group including a plurality of signals by a simple configuration.

The search system according to the present invention is a search system comprising: reading means for reading a first signal group including a plurality of signals; storage means for storing a second signal group including a plurality of signals; 1 signal group and the signals included in the second signal group stored in the storage means are included in a plurality of signals included in the first signal group, And calculating a degree of similarity between the first signal group read by the reading unit and the second signal group stored in the storage unit based on the plurality of similarities calculated by the first similarity calculating unit And a second degree of similarity calculating means.

In the search system according to the present invention, a signal group similar to a signal group including a plurality of signals can be searched by a simple configuration.

1 is a diagram showing a configuration example of a search system according to Embodiment 1 of the present invention.
2 is a diagram showing an example of trace data.
3 is a flowchart showing an example of the operation of the search system according to the first embodiment of the present invention.
4 is a diagram for explaining the function of the first similarity degree calculating section.
5 is a diagram for explaining the function of the first similarity degree calculating section.
6 is a diagram showing a display example of the display device.
7 is a diagram showing an example in which the maximum value of the degree of similarity between signals depends on the signal length.
8 is a diagram showing a configuration example of a search system according to Embodiment 2 of the present invention.
9 is a flowchart showing an example of the operation of the search system according to the second embodiment of the present invention.
10 is a flowchart showing an example of the operation of the search system according to the third embodiment of the present invention.
11 is a diagram showing a display example of a display device.
12 is a diagram showing the hardware configuration of the search device.

BRIEF DESCRIPTION OF THE DRAWINGS Fig. The redundant description is appropriately simplified or omitted. In the drawings, the same reference numerals denote the same or corresponding parts.

Embodiment 1

1 is a diagram showing a configuration example of a search system according to Embodiment 1 of the present invention. The search device 1 is capable of communicating with a plurality of remote elevator devices. Each elevator apparatus includes, for example, an elevator car 2 and a balance weight 3. The elevator car (2) and the balance weight (3) are suspended from the hoistway by the main rope (4). The hoisting machine of the elevator includes, for example, a drive sheave 5 and an electric motor 6. The main rope 4 is wound on the driving sheave 5. The drive sheave 5 is driven by the electric motor 6. The electric motor 6 is controlled by the control panel 7. A communication device 8 is connected to the control panel 7. The communication device 8 performs communication with an external device. Each elevator device communicates with the search device 1 by the communication device 8. [

When a failure occurs in the elevator apparatus, a snapshot (trace data) of signal values indicating the statuses of a plurality of sensors provided in the elevator is acquired by the communication device 8 for a certain period of time before and after occurrence of a failure. For example, the trace data includes a signal for specifying the elevator apparatus itself, a signal indicating time, a signal indicating the current value and voltage value of the control panel 7, a signal indicating the speed and torque of the electric motor 6, A signal indicating the position of the car 2, and a signal indicating the operating state of the safety device. The signal included in the trace data is not limited to the above example. Some of the illustrated signals need not be included in the trace data. Other signals may be included in the trace data.

2 is a diagram showing an example of trace data. Fig. 2 shows an example of four pieces of trace data. The representation of the signals included in the trace data is not limited to one type. For example, a signal expressed in binary, a signal expressed in hexadecimal, and a signal expressed in decimal may be mixed in trace data. Also, signals of various signal lengths may be mixed in the trace data. When the communication device 8 acquires the trace data, it transmits the acquired trace data to the search device 1. [

The search apparatus 1 includes a storage unit 9, a reading unit 10, a first similarity degree calculating unit 11, a second similarity degree calculating unit 12, a display control unit 13, Respectively. Hereinafter, functions and operations of the search apparatus 1 will be described with reference to Figs. 3 to 6. Fig. 3 is a flowchart showing an example of the operation of the search system according to the first embodiment of the present invention.

The reading unit 10 reads the trace data. When a failure occurs in an elevator connected to the search device 1, trace data at the time of occurrence of a failure is transmitted from the communication device 8 of the elevator device. The trace data transmitted from the communication device 8 is read by the reading unit 10 (S101). The trace data read by the reading unit 10 includes a plurality of signals. The order of the signals included in the trace data is predetermined.

A plurality of pieces of trace data previously read by the reading unit 10 are stored in the storage unit 9. That is, the trace data read by the reading unit 10 is stored in the storage unit 9. [ In the following description, the trace data newly read by the reading unit 10 is indicated as " trace data A ". The past trace data stored in the storage unit 9 is indicated as " trace data B ". In the storage unit 9, a plurality of trace data sets B are stored.

The first similarity degree calculating section 11 calculates the degree of similarity between the signal included in the trace data A and the signal included in the trace data B (S102). The type of the signal included in the trace data A is basically the same as the type of the signal included in the trace data B. The trace data A and the trace data B include corresponding signals. The first similarity degree calculating section 11 calculates the similarity between the corresponding signals in the trace data A and the trace data B. In other words, the first similarity degree calculating section 11 calculates the degree of similarity between a signal included in the trace data A and a signal included in the trace data B and corresponding to the signal included in the trace data A.

The first similarity degree calculating section 11 calculates the degree of similarity between each signal included in the trace data A and the signal included in the trace data B. [ For example, the first similarity degree calculating section 11 calculates the similarity between the torque signal included in the trace data A and the torque signal included in the trace data B. As another example, the first similarity degree calculating section 11 calculates the degree of similarity between the door open / close signal included in the trace data A and the door open / close signal included in the trace data B.

Figs. 4 and 5 are diagrams for explaining the functions of the first similarity degree calculating section 11. Fig. The first degree-of-likeness calculating section 11 calculates the degree of similarity between signals using, for example, dynamic programming (DP matching). For example, a case is considered in which a signal (00001111) included in the trace data A is compared with a signal (00000111) included in the trace data B corresponding to the signal. The calculation of the degree of similarity by the dynamic programming method can be performed by calculating the degree of similarity using the dynamic programming method as shown in Figs. 4 and 5, by vertically arranging one signal and horizontally arranging the other signal, The lower right corner). Then, a path that minimizes the penalty is searched from the upper left square to the lower right square.

In the example shown in Fig. 4, the moving penalty in the right direction is set to +1, the moving penalty in the downward direction is set to +1, and the moving penalty in the diagonal direction to the lower right is set to 0. The penalty in the case of coincidence of values is set to 0, and the penalty in case of discrepancy of values is set to +1. In this case, the degree of similarity between the signals is calculated as 1. [ In the example shown in Fig. 5, the moving penalty in the right direction is set to +1, the moving penalty in the downward direction is set to +1, and the moving penalty in the diagonal direction to the right downward is set to 0. In addition, the penalty when the values are coincident is set to 0, and the penalty when the values are not coincident is set to +3. In this case, the degree of similarity between the signals is calculated as two. In the examples shown in Figs. 4 and 5, the closer the signals to be compared are, the smaller the value of the degree of similarity calculated by the first similarity degree calculating section 11 becomes. The method of setting the mobile penalty and the method of setting the inconsistency penalty are not limited to these examples. The method of calculating the degree of similarity by the first similarity degree calculating section 11 is not limited to the dynamic programming method.

The second similarity degree calculating section 12 calculates the degree of similarity between the trace data A and the trace data B (S103). The second similarity degree calculating section 12 performs the calculation based on the plurality of similarities calculated by the first similarity degree calculating section 11. [ For example, when 100 signals are included in each of the trace data A and the trace data B, the degree of similarity of each signal is calculated by the first similarity degree calculating section 11. That is, the first similarity degree calculating section 11 calculates 100 similarity degrees. The second similarity degree calculating section 12 performs the above calculation based on the 100 similarity degrees calculated by the first similarity degree calculating section 11.

For example, the second similarity degree calculating section 12 calculates the distance L between the trace data A and the trace data B by the following equation. L i is the similarity of the signal i, and N is the number of signals included in the trace data A (or trace data B).

[Equation 1]

Figure pct00001

The second similarity degree calculating section 12 calculates the similarity P match between the trace data A and the trace data B by using the following equation using the distance L obtained by the equation (1).

&Quot; (2) "

Figure pct00002

L max is the maximum value of the distance L between the trace data A and the trace data B. L max corresponds to the distance between the trace data A in which the value of all the signals is 1 and the trace data B in which the value of all the signals is 0, for example. The method for calculating the degree of similarity by the second similarity degree calculating section 12 is not limited to the above example.

A plurality of pieces of trace data B are stored in the storage unit 9. The search apparatus 1 calculates the similarity between the trace data A and each trace data B. To this end, when the similarity of trace data A and trace data B is calculated, search apparatus 1 determines whether or not similarity is calculated for all trace data B (S104). If there is trace data B for which the degree of similarity to trace data A is not calculated (No in S104), the process of S102 and the process of S103 are performed on the trace data B. That is, the first similarity degree calculating section 11 calculates the similarity between the signal included in the trace data A and the signal included in the trace data B. The second similarity degree calculating section 12 calculates the degree of similarity between the trace data A and the trace data B thereof.

The display control section 13 controls the display device 15. When the similarity between the trace data A and each trace data B is calculated (Yes in S104), the display control section 13 causes the display device 15 to display the calculation result of the second similarity degree calculating section 12. For example, the display control section 13 causes the display device 15 to display the information indicating the trace data B in the order of similarity calculated by the second similarity degree calculating section 12 (S105).

Fig. 6 is a diagram showing a display example of the display device 15. Fig. 6 shows an example in which the display control section 13 displays on the display device 15 information specifying the trace data B in descending order of the degree of similarity calculated by the second similarity degree calculating section 12. [ 6 shows an example in which the date and time when the failure occurred and information indicating the elevator device in which the failure occurred are displayed on the display device 15 as the information for specifying the trace data B. [ The information displayed on the display device 15 is not limited to the example shown in Fig.

With a search system having the above configuration, a signal group similar to a signal group including a plurality of signals can be searched by a simple configuration. The surveillance source and the maintenance person of the elevator can estimate the cause of the failure occurring in the elevator apparatus that has transmitted the trace data A by precisely investigating the contents of the trace data B displayed on the display 15. [

In the present embodiment, an example in which the search device 1 includes the display device 15 has been described. The display device 15 may be provided in an external device. In this case, the display control section 13 transmits information for displaying the calculation result of the second similarity degree calculating section 12 on the display device 15 to an external device.

In the present embodiment, an example in which the calculation result of the second similarity degree calculating section 12 is displayed on the display device 15 has been described. This is an example. The result of calculation by the second similarity degree calculating unit 12 may be stored in the search device 1 so that the surveillance person or the maintenance person of the elevator can use the calculation result of the second similarity degree calculating unit 12 later.

In the present embodiment, an example in which the first similarity degree calculating section 11 calculates the degree of similarity between signals using the dynamic programming method has been described. The trace data A includes, for example, a plurality of signals having different signal lengths. In this case, each trace data B also includes a plurality of signals having different signal lengths. In the calculation method of the degree of similarity disclosed in the present embodiment, the maximum value of the degree of similarity calculated by the first similarity degree calculating section 11 depends on the signal length.

7 is a diagram showing an example in which the maximum value of the degree of similarity between signals depends on the signal length. In the example shown in Fig. 7, the movement penalty in the right direction is set to +1, the movement penalty in the downward direction is set to +1, and the movement penalty in the diagonal direction to the lower right is set to 0, similarly to the example shown in Fig. The penalty in the case of coincidence of values is set to 0, and the penalty in case of discrepancy of values is set to +1. As shown in FIG. 7, the maximum value of the degree of similarity between signals having a signal length of 2 is 2. On the other hand, the maximum value of the degree of similarity between signals having a signal length of 8 is 8.

The first degree-of-likeness calculating section 11 may calculate the degree of similarity between the signals so that the maximum value of the degree of similarity is the same regardless of the signal length. For example, the first similarity degree calculating section 11 calculates the similarity degree by the following equation.

&Quot; (3) "

Figure pct00003

The first degree of similarity calculating section 11 may calculate the degree of similarity between the signals so that the maximum value of the degree of similarity may be the same regardless of the signal length. In this case, the trace data A includes, for example, a plurality of signals of different importance and signal length. Each trace data B also includes a plurality of signals having different importance levels and signal lengths. The first similarity degree calculating section 11 calculates the degree of similarity by, for example, the following equation.

&Quot; (4) "

Figure pct00004

Embodiment 2 Fig.

8 is a diagram showing a configuration example of a search system according to Embodiment 2 of the present invention. The search system shown in Fig. 8 is different from the configuration shown in Fig. 1 in that the search device 1 further includes the specifying unit 14. [ Other configurations and functions of the retrieval system are the same as those of the configuration and function disclosed in the first embodiment.

The specifying unit (14) specifies the exclusion signal among the signals included in the trace data (B). The exclusion signal is a signal that does not require calculation of the degree of similarity between signals. That is, the first degree-of-likeness calculating section 11 does not calculate the degree of similarity between signals for the exclusion signal specified by the specifying section 14. [

Among the signals included in the trace data B, there is a signal having a very low correlation with the failure. Such a signal is specified by the specific portion 14 as an exclusion signal. For example, the signal for specifying the elevator apparatus itself is specified by the specifying section 14 as an exclusion signal. The specifying unit 14 specifies an exclusion signal based on information input from an input terminal such as a keyboard, for example.

The specifying unit 14 may specify the exclusion signal based on the information stored in the storage unit 9. [ In this case, for example, each trace data B is stored in the storage unit 9 in association with the failure information indicating the failure point of the elevator. 9 is a flowchart showing an example of the operation of the search system according to the second embodiment of the present invention. Fig. 9 shows a processing flow for specifying the exclusion signal by the specifying unit 14. Fig.

The specific unit 14 acquires the trace data B associated with the same failure information from the storage unit 9 (S201). For example, the specifying unit 14 acquires a plurality of pieces of trace data B associated with the failure information indicating the power supply circuit from the storage unit 9.

The specific unit 14 calculates the degree of similarity between the signals with respect to the trace data B to which the same trouble information is associated (S202). That is, the specifying unit 14 calculates the degree of similarity between signals for all combinations of the trace data B obtained in S201. The method by which the specific portion 14 calculates the degree of similarity between signals is the same as the method by which the first similarity degree calculating section 11 calculates the degree of similarity between signals.

Next, the specifying unit 14 specifies the excluded candidate signal (S203). The excluded signal is selected from the excluded candidate signals. For example, the specifying unit 14 specifies a signal having a large deviation of similarity calculated in S202 as a excluding candidate signal. For example, the elevator car position is low in relation to the failure of the power supply circuit. Therefore, if the degree of similarity between the signals is calculated for the trace data B correlated with the failure information indicating the power supply circuit, the degree of similarity between the signals indicating the positions of the elevator car takes various values. When the deviation of the degree of similarity between the signals indicating the car position of the car exceeds the threshold value, the specifying unit (14) specifies the signal indicating the car position as the excluded candidate signal in the power supply circuit.

The specifying unit (14) specifies the exclusion candidate signal in all the failure information. For this purpose, when the specifying unit 14 specifies the exclusion candidate signal in one piece of failure information, it is judged whether or not the exclusion candidate signal is specified for all pieces of failure information (S204). If there is any failure information for which the exclusion candidate signal is not specified (No in S204), trace data B associated with the failure information is acquired, and the process of S202 and the process of S203 are performed on the obtained trace data B. Thus, the excluded candidate signal is specified for all the fault information.

If the excluded candidate signal is specified for all the fault information (Yes in S204), the specifying unit 14 specifies the excluded signal (S205). The specifying unit 14 specifies, for example, a signal in which the deviation of the degree of similarity exceeds the threshold for all fault information as an exclusion signal. That is, if the same signal is included in the excluded candidate signal in all the fault information, the specifying unit 14 specifies the signal as an exclusion signal. As a result, the signal that takes various values regardless of the failure point is excluded from the object of calculation of the degree of similarity by the first similarity degree calculating section 11. [

In the search system having the above configuration, a signal included in the trace data and having a very low correlation with the failure can be excluded from the calculation object of similarity. The degree of similarity calculated by the second degree of similarity calculating unit 12 more strongly indicates the similarity with the content of the failure, so that it is possible to more easily estimate the cause of the failure.

Embodiment 3:

The configuration of the search system in the present embodiment is the same as the configuration disclosed in the first embodiment or the second embodiment. In the present embodiment, an example in which the display control section 13 displays a failure point on the display device 15 will be described. In the present embodiment, each trace data B is stored in the storage unit 9 in association with the failure information indicating the failure point of the elevator. Other functions of the search system in this embodiment are the same as those in the first embodiment or the second embodiment.

10 is a flowchart showing an example of the operation of the search system according to the third embodiment of the present invention. The processing of S301 to S304 shown in Fig. 10 is the same as the processing of S101 to S104 shown in Fig.

When the similarity between the trace data A and each trace data B is calculated (Yes in S304), the display control unit 13 calculates the similarity based on the similarity calculated by the second similarity calculating unit 12 and the failure information associated with the trace data B , And causes the display device 15 to display a fault point that is likely to have occurred (S305).

For example, the display control section 13 extracts a plurality of pieces of trace data B having a high degree of similarity by arranging the trace data B in descending order of degree of similarity calculated by the second similarity degree calculating section 12. The display control unit 13 extracts, for example, trace data B having a high degree of similarity. For example, the display control section 13 extracts the trace data B up to the upper 100th position with a high degree of similarity. As another example, the display control unit 13 may extract the trace data B whose similarity exceeds the reference value.

Next, the display control section 13 specifies a failure point of the extracted trace data B. This specification is made on the basis of, for example, failure information associated with the extracted trace data B, for example. For example, when 100 pieces of trace data B are extracted, the display control section 13 specifies a failure point for the 100 pieces of trace data B. The display control unit 13 causes the display unit 15 to display a fault point in the descending order of the number of faulty traces for all extracted trace data B. [

11 is a diagram showing a display example of the display device 15. In Fig. For example, of the extracted trace data B, 50 pieces of data in which the fault point is the control panel, 30 pieces of data in which the fault point is the power circuit, 15 pieces of data in which the fault point is the traction unit, and data in which the fault point is the communication card In the case of five cases, display as shown in Fig. 11 is performed.

In the search system having the above configuration, it is possible to display, on the display device 15, a point having a high probability of occurrence of a failure as a failure point candidate. The surveillance source and the maintenance person of the elevator can take appropriate measures such as preferentially investigating the failure point candidate displayed on the display device 15. [

In the first to third embodiments, an example in which the search apparatus 1 is connected to the elevator apparatus has been described. The place where the search apparatus 1 acquires the signal group is not limited to the elevator apparatus. The search device 1 may acquire an information group from another facility or a plant or the like.

The parts denoted by reference numerals 9 to 14 denote the functions of the search device 1. 12 is a diagram showing a hardware configuration of the search device 1. As shown in Fig. The search apparatus 1 has hardware resources such as a circuit including an input / output interface 16, a processor 17, and a memory 18. [ The function of the storage unit 9 is realized by the memory 18. [ The search device 1 executes the programs stored in the memory 18 by the processor 17 to realize the respective functions of the units 10 to 14. [ Some or all of the functions of each of the units 10 to 14 may be realized by hardware.

[Industrial Availability]

The search system according to the present invention can be used to estimate the cause of a failure occurring in a facility or a plant.

1: Search device
2: Elevator car
3: Balance weight
4: Main rope
5: Driving sheave
6: Electric motor
7: Control panel
8: Communication device
9:
10:
11: First degree of similarity calculating section
12: second similarity calculating section
13:
14:
15: Indicator
16: I / O interface
17: Processor
18: Memory

Claims (9)

Reading means for reading a first signal group including a plurality of signals;
A storage means for storing a second signal group including a plurality of signals;
The similarity degree between the signal included in the first signal group read by the reading means and the signal corresponding to the signal included in the first signal group among the signals included in the second signal group stored in the storage means, First similarity degree calculating means for calculating a plurality of signals included in the signal group,
Second similarity calculating means for calculating a similarity between the first signal group read by the reading means and the second signal group stored by the storing means based on the plurality of similarities calculated by the first similarity calculating means Equipped search system. The method according to claim 1,
A plurality of second signal groups are stored in the storage means,
The first degree of similarity calculation means calculates the degree of similarity between signals for the first signal group read by the reading means and for each second signal group stored in the storage means,
And the second degree of similarity calculation means calculates the degree of similarity between the first signal group read by the reading means and each second signal group stored in the storage means. The method of claim 2,
And a display control unit for controlling the display unit,
Wherein the display control unit causes the display unit to display information indicating the second signal group in order of similarity calculated by the second similarity calculating unit. The method according to claim 2 or 3,
The first signal group and each second signal group include a plurality of signals having different signal lengths,
Wherein the first similarity degree calculating means calculates the degree of similarity between the signals so that the maximum value of the similarity degree is the same regardless of the signal length. The method according to claim 2 or 3,
The first signal group and each second signal group include a plurality of signals having different importance and signal length,
The first degree of similarity calculating means calculates the degree of similarity between the signals so that the maximum value of the degree of similarity is the same regardless of the signal length. The method according to any one of claims 2 to 5,
Further comprising specifying means for specifying an exclusion signal among the signals included in the second signal group stored in the storage means,
The first similarity degree calculating means does not calculate the degree of similarity between signals for the exclusion signal specified by the specifying means. The method of claim 6,
The first signal group and each second signal group include signals from a plurality of sensors provided in the elevator,
Each of the second signal groups is stored in the storage means in association with the failure information indicating a failure point of the elevator,
The specifying means calculates the similarity between the corresponding signals for the second signal group to which the same failure information is associated, specifies a signal whose deviation of the degree of similarity exceeds the threshold for the failure information, And a signal whose deviation exceeds a threshold value as an exclusion signal. The method according to any one of claims 2 to 6,
The first signal group and each second signal group include signals from a plurality of sensors provided in the elevator,
Each of the second signal groups being stored in the storage means in association with failure information indicating a failure point of the elevator. The method of claim 8,
And a display control unit for controlling the display unit,
Wherein the display control unit causes the display device to display a failure point likely to have occurred on the basis of the similarity calculated by the second similarity degree calculation means and the failure information associated with the second signal group.
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