JP2015197850A - Facility monitoring system and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a facility monitoring system capable of easily analyzing the state of a facility and operational problem by using a new index relevant to a singular point.SOLUTION: The facility monitoring system includes: a data acquisition section 11 that acquires a sensor data representing a state of a facility from a building monitoring server 2; a data analysis section 12 that analyzes the sensor data to extract singular points in a monitoring period to generate a piece of singular point information which includes a continuation period which represents a period when singular points are continuously extracted and a singular degree which represents the extent of singularity of a singular point in the continuation period; and a display processing section 13 that displays a maximum singular degree in a display unit time such as a month, a singular point continuation integrated time and a singular point detection frequency based on the singular point information as index data.

Description

  The present invention relates to an equipment monitoring apparatus and program, and more particularly to analysis of equipment status and operational problems.

  In a service that proposes energy saving and operational efficiency of building equipment, singularities that show behaviors that are different or abnormal from the normal state are extracted from the time series data of equipment setting values and sensor information, and the singularities are extracted. It is used to analyze whether there is a problem in equipment condition and operation. The extraction of the singular point can be performed by extracting a part that meets the condition of the singular point or does not meet the condition of the normal state using a program. As one method for extracting singular points, there is a method in which a threshold value is set in advance, and a singular point is extracted according to a comparison result between the threshold value and the sensor data value, the degree of fluctuation of the sensor data, or the like. Patent Documents 1 to 3 propose techniques for detecting and analyzing singular points.

JP-A-2005-296407 JP 2010-019830 A International Publication No. 2013/051101

  However, if the threshold for extracting singularities is set loosely, a huge amount of singularities will be extracted, and it will take a lot of time for analysis processing. On the other hand, if the threshold is set strictly, the singularities will be extracted. Therefore, there is a possibility that the singular point that is originally desired to be extracted cannot be extracted. Therefore, in order to avoid such a problem, it is common to operate so as to extract a large number of singular points without setting the threshold value to a very strict value.

  However, thousands of time-series data (signals) are collected from the building where the equipment to be monitored is installed, and there may be hundreds of singular points per day from one signal. Thousands may be extracted per day. Furthermore, when the analysis target period is several months, if analysis is performed with reference to each extracted singular point, it may take a long time to analyze a large number of singular points.

  An object of the present invention is to make it possible to easily analyze the state of equipment and operational problems using a new index related to a singularity.

  The equipment monitoring apparatus according to the present invention is an acquisition means for obtaining equipment data indicating the state of the equipment within the equipment monitoring target period, and the equipment data is analyzed so that the equipment is in a normal state within the monitoring target period. When the singular point is extracted as a singular point and when the singular point is continuously extracted, the date and time information for specifying the extracted period and the singularity degree of the singular point in the extracted period Analysis means for generating singularity information including at least the singularity indicating, and the monitoring target period is divided into predetermined display unit periods, and data generated based on the singularity information corresponding to each display unit period is Display processing means for displaying as indicator data indicating the state of the equipment in a display unit period.

  The display processing means further subdivides the selected display unit period to subdivide the display unit period, and displays data generated based on the singularity information corresponding to each subdivided display unit period. It is displayed as index data indicating the state of the equipment within a unit period.

  The display processing means displays the display form of the index data deviating from a predetermined threshold value indicating an abnormal state, different from the display form of the index data within the threshold value.

  The display processing means displays facility data and singularity information corresponding to the selected display unit period on the same graph.

  The program according to the present invention includes a computer, an acquisition unit that acquires equipment data indicating a state of the equipment within the monitoring target period of the equipment, and the equipment data is analyzed so that the equipment is in a normal state within the monitoring target period. When the singular point is extracted as a singular point and when the singular point is continuously extracted, the date and time information for specifying the extracted period and the singularity degree of the singular point in the extracted period Analysis means for generating singularity information including at least the singularity indicating the data, and the data generated based on the singularity information corresponding to each display unit period is displayed in such a manner that the monitoring target period is divided into predetermined display unit periods. It is for functioning as display processing means for displaying as index data indicating the state of the equipment within a unit period.

  ADVANTAGE OF THE INVENTION According to this invention, the state of an installation and the problem of operation can be simply analyzed using the new parameter | index relevant to a singular point.

  In addition, analysis can be performed while narrowing down the period.

  In addition, it is possible to easily find a period when the equipment is not in a normal state.

It is the figure which showed the structure of the system containing one Embodiment of the equipment monitoring apparatus which concerns on this invention, and the block structure of the equipment monitoring apparatus. It is a hardware block diagram of the computer which forms the equipment monitoring apparatus in this Embodiment. It is the flowchart which showed the equipment monitoring assistance process in this Embodiment. It is the figure which showed an example of the data structure of the singular point information in this Embodiment. It is the figure which showed an example of the display of the index data for the analysis of the state of an installation, or the problem of operation in this Embodiment. FIG. 6 is a diagram showing an example of display of index data when the display period is further narrowed down from FIG. 5. It is the figure which showed an example at the time of displaying the index data for the analysis of the state of an installation, or the problem of operation in a graph form in this Embodiment.

  Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.

  FIG. 1 is a diagram showing a system configuration including an embodiment of an equipment monitoring apparatus according to the present invention and a block configuration of the equipment monitoring apparatus. FIG. 1 shows a configuration in which a building monitoring server 2 and an equipment monitoring device 10 are connected to a network 4. The building monitoring server 2 is a server computer for monitoring equipment installed in the building. When the facility is an air conditioning facility, for example, the building monitoring server 2 is a controller in which the air conditioning facility is connected to sensor data indicating the state of the air conditioning facility such as the amount of power used measured by the watt hour meter and the room temperature measured by the thermometer. (Not shown) or collected directly from sensor means such as a watt hour meter. The configuration and processing related to the collection of sensor data may be the same as before.

  FIG. 2 is a hardware configuration diagram of a computer forming the equipment monitoring apparatus 10 in the present embodiment. The computer forming the equipment monitoring apparatus 10 in the present embodiment can be realized by a general-purpose hardware configuration that has existed in the past. That is, as shown in FIG. 2, the computer connects the CPU 21, ROM 22, RAM 23, hard disk drive (HDD) 24, mouse 25 and keyboard 26 provided as input means, and display 27 provided as a display device. An input / output controller 28 and a network controller 29 provided as communication means are connected to an internal bus 30.

  Returning to FIG. 1, the equipment monitoring apparatus 10 in the present embodiment includes a data acquisition unit 11, a data analysis unit 12, a display processing unit 13, a processing control unit 14, a sensor data storage unit 15, and a singular point information storage unit 16. doing. The data acquisition unit 11 is provided as an acquisition unit, and receives facility data (sensor data) from the building monitoring server 2 indicating the set values of the facilities and the state of the facilities collected by the building monitoring server 2 within the monitoring period of the facilities. The acquired sensor data is written and stored in the sensor data storage unit 15. Of course, you may comprise so that sensor data may be acquired directly from sensor means, such as an electric energy meter. The data analysis unit 12 is provided as an analysis unit, and by analyzing the facility data, the time when the facility performs a predetermined operation different from the normal state within the monitoring target period is extracted as a singular point, and the extracted singular point Is generated, singular point information indicating the characteristics in the period in which the singular point was extracted is generated, and is written and stored in the singular point information storage unit 16. The display processing unit 13 is provided as display processing means, and displays index data indicating the state of the equipment to be monitored with reference to the singularity information. The process control unit 14 performs process control in each of the constituent elements 11 to 13.

  Each component 11-14 in the equipment monitoring apparatus 10 is implement | achieved by cooperation operation | movement of the computer which forms the equipment monitoring apparatus 10, and the program which operate | moves by CPU21 mounted in the computer. The storage units 15 and 16 are realized by the HDD 24 mounted on the equipment monitoring apparatus 10. Alternatively, the RAM 23 or an external storage means may be used via a network.

  Further, the program used in this embodiment can be provided not only by communication means but also by storing it in a computer-readable recording medium such as a CD-ROM or DVD-ROM. The program provided from the communication means or the recording medium is installed in the computer, and various processes are realized by the CPU of the computer sequentially executing the program.

  Next, facility monitoring support processing performed by the facility monitoring apparatus 10 for facility monitoring in the present embodiment will be described using the flowchart shown in FIG. In the equipment monitoring support process in the present embodiment, index data indicating the state of the equipment to be monitored is generated and displayed based on the sensor data acquired by the equipment monitoring device 10 so that the state of the equipment can be visually recognized. In particular, in the present embodiment, the continuity time in which the singular point is detected and the singularity indicating the singular (or abnormal) degree of the singular point detected within the continuation time are analyzed for the problem of the equipment state and the operation. One of the features is that it is provided as index data. Furthermore, it is one of the features that display is possible while narrowing down the display period of the index data.

  When the data acquisition unit 11 acquires the sensor data to be analyzed collected within the monitoring target period from the building monitoring server 2, the data acquisition unit 11 stores the acquired sensor data in the sensor data storage unit 15 (step 110). The monitoring target period may be a predetermined period or a period specified by a monitor or the like, but a relatively long period such as one year is preferable in consideration of display processing for narrowing down the subsequent display period. The sensor data to be analyzed may be determined in advance, or may be designated by a supervisor or the like at the start of processing. Further, although it may be limited to sensor data related to a specific facility, in the present embodiment, all collected sensor data is an analysis target. However, since it is only necessary to perform the same processing for each sensor data, here, it is assumed that the processing is performed on one sensor data for convenience.

  The data analysis unit 12 reads out the sensor data to be analyzed from the sensor data storage unit 15, and in the monitoring target period (for example, 2013), the normal state is determined from the sensor data (time series data) such as the set values of the equipment and sensor information. Are extracted singular points exhibiting different or abnormal behavior (step 120). In the present embodiment, when an amplitude (sensor value) greater than a specified amplitude is detected, the detected time point is extracted as a singular point. For example, a point in time when the amplitude (sensor value) is 2.0 or more is extracted as a singular point. The threshold value of 2.0 may be set as appropriate depending on the type of sensor data (signal). Then, the data analysis unit 12 generates singular point information by analyzing the extraction status of the extracted singular points (step 130) and stores it in the singular point information storage unit 16 (step 140). An example of the data structure of the generated singularity information is shown in FIG.

  When the singular point is extracted, the data analysis unit 12 generates singular point information in accordance with the extraction state of the singular point as described above. In the present embodiment, when the sensor data is waveform data, the singular point information is generated on the condition that a specified number of amplitudes (sensor values) are generated within a specified period. As a specific example, if sensor data in a monitoring target period is divided into a predetermined unit time of 10 minutes and analyzed, a wave indicating a singular point having an amplitude of 2.0 or more in 10 minutes (sensor When the generation condition that two or more (values) are detected is satisfied, the data analysis unit 12 associates the generation condition with the sensor data name that is information for identifying the sensor data that satisfies the generation condition. Singularity information including the start date and time indicating the beginning of the period, the end date and time indicating the end, the duration indicating the length of time when the singularity was detected, and the specificity as date and time information for identifying the period in which the satisfied singularity was extracted Is generated. At this time, a record number is added to the singularity information. As described above, the “specificity” is an index indicating the degree of singularity (or abnormality) detected in the duration, but in this embodiment, the singularity included in the duration The maximum value of (sensor value) is used as “specificity”.

  According to the example shown in FIG. 4, as for the singularity information of the first record, two or more amplitudes of 2.0 or more were extracted from 13:15 on April 5, 2013 to 10:13 at 13:35. The singular point information is generated at, and the wave (sensor value) indicating the maximum value among the two or more extracted singular points is 3.0. In addition, the singularity information of the second record is generated by extracting two or more amplitudes of 2.0 or more in 10 minutes from 13:35 on April 5, 2013. Is continuously extracted from 13:35 on April 5, 2013 to 15:15:13, and the wave (sensor value) indicating the maximum value among the extracted singular points is 8.0. Show. Note that even if the analysis is performed with the monitoring target period divided into 10-minute intervals, if the singularity occurs continuously for more than 10 minutes across multiple periods, integration is performed as in the second record. To generate singularity information. As described above, when the data analysis unit 12 generates the singular point information described above, the data analysis unit 12 stores it in the singular point information storage unit 16.

  As described above, when the data analysis unit 12 generates the singularity information, the display processing unit 13 reads the singularity information from the singularity information storage unit 16 and performs a tabulation process or the like to be described later and the state and operation of the equipment. Index data for analyzing the problem is displayed on the display 27 (step 150). An example of the display contents is shown in FIG.

  FIG. 5 is a diagram illustrating a display example when singularity information is tabulated for each month as a display unit period when the monitoring target period is one year. As illustrated in FIG. 5, the index data is aggregated and displayed for each sensor data. Each month's display area (hereinafter referred to as “cell”) displays the index data in three levels, of which the upper level shows the maximum specificity, the middle level shows the singularity duration cumulative time, and the lower level shows. The number of singularity detections is displayed respectively. The maximum specificity is the maximum value among the specificities set in the singularity information included in the current month. The singular point duration cumulative time is the cumulative value of the duration set in the singular point information included in the current month. The number of singularity detections corresponds to the number of records of singularity information included in the current month.

  In this way, the display processing unit 13 divides the monitoring target period of one year into display unit periods every month, and based on the singularity information corresponding to each month, the maximum singularity, the singularity duration cumulative time, Index data called the number of singularity detections is calculated and displayed.

  In addition, for each index data, in the present embodiment, threshold values (for example, 50, 350, and 30 for the maximum singularity, the singular point continuous accumulated time, and the number of singular point detection times, respectively) indicating that the equipment is not in a normal state are set. The index data set in advance and deviating from the threshold is displayed in a different form. Although shown in bold in FIG. 5, the monitor can easily recognize that the equipment corresponding to the sensor data is in an abnormal state by changing the display color such as red or blinking. It may be.

  Further, depending on the degree of abnormality, for example, the display form in the cell may be varied depending on the number of index data exceeding the threshold. FIG. 5 shows an example in which the display form is changed by the fill effect in the cell.

  Here, FIG. 6 shows an example of a screen displayed on the display 27 when the monitor clicks to select the April cell 51 of the sensor data A.

  FIG. 6 is a diagram illustrating a display example in which the month of April is further divided into each day, and singularity information corresponding to each day is tabulated every day. Even when tabulated on a daily basis, the display format is basically the same as when tabulated on a monthly basis. Therefore, in each cell, the maximum value (maximum specificity) of the singularity information included in the singularity information included on the current day is displayed in the upper row, and the duration of the singularity information included in the singularity information included in the current day is displayed in the middle row. The cumulative value (single point continuous cumulative time) is displayed, and the number of records of singular point information included in the day (the number of singular point detections after continuous singular point aggregation) is displayed in the lower part. Similarly to FIG. 5, a threshold value (for example, 40, 50, 5 for each of the maximum singularity, the singular point duration cumulative time, and the number of singular point detection times) is set for each index data, and the index exceeds the threshold value. The data may be displayed in a different form.

  In this embodiment, the facility status can be analyzed while narrowing down the display period by month and by day. However, the period to narrow down can be arbitrarily set such as quarter or time. May be.

  Here, FIG. 7 shows an example of a screen displayed on the display 27 when the monitor clicks to select the cell 61 on the 5th day of the sensor data A.

  FIG. 7 shows an example in which the selected five-day sensor data 71 and the singular point information 72 to 74 are superimposed and displayed with time on the horizontal axis and sensor data values on the vertical axis. In the present embodiment, the singular point information 72 to 74 is indicated by the product (hatched portion) of the singularity and the duration. The supervisor can know the degree of abnormality of the facility sensuously by referring to the area of the hatched portion. Thereby, the state of the equipment on the 5th can be grasped, and it can be used for a maintenance plan and operation of the equipment in the future.

  In addition, when a plurality of days are specified in FIG. 6, a plurality of days may be displayed together in one graph. In addition, when a plurality of days are selected, the selected days may be displayed on the screen so as to be easily compared in the vertical and horizontal directions. In FIGS. 5 and 6, the cell display form is made different depending on the number of index data exceeding the threshold, but the cell display form is made different according to the sum of the integrated values of the specificity and the duration. It may be.

  According to the present embodiment, since the singular points included in a certain period (10 minutes in the above example) are collectively handled by a new index called singularity, it is compared with the case where singular points are individually analyzed. As a result, it becomes possible to easily analyze the state of equipment and operational problems. This period of 10 minutes is an example, and when the number of singular points is enormous, the period to be monitored may be divided into periods longer than 10 minutes for analysis.

  In the present embodiment, the maximum value of the amplitude (sensor value) representing the singular point included in the duration is used as the “singularity”, but for example, the number of amplitudes within a predetermined period or the maximum amplitude A combination of value and number of amplitudes may be used as specificity.

  In the present embodiment, the equipment monitoring apparatus 10 is separately connected to the network 4. However, the building monitoring server 2 is installed by incorporating the functions provided by the equipment monitoring apparatus 10 into the building monitoring server 2. You may comprise so that it may function as an apparatus.

  2 building monitoring server, 4 network, 10 facility monitoring device, 11 data acquisition unit, 12 data analysis unit, 13 display processing unit, 14 processing control unit, 15 sensor data storage unit, 16 singularity information storage unit, 21 CPU, 22 ROM, 23 RAM, 24 hard disk drive (HDD), 25 mouse, 26 keyboard, 27 display, 28 I / O controller, 29 network controller, 30 internal bus.

Claims (5)

An acquisition means for acquiring equipment data indicating the state of the equipment within the equipment monitoring period;
By analyzing the equipment data, when the equipment has performed a predetermined operation different from the normal state within the monitoring target period, it is extracted as a singular point, and when the singular point is continuously extracted, the extracted period Analyzing means for generating singularity information including at least the date and time information for identifying the singularity indicating the singularity of the singularity in the extracted period;
Display processing means for dividing a monitoring target period into predetermined display unit periods and displaying data generated based on singularity information corresponding to each display unit period as index data indicating the state of the equipment in the display unit period When,
A facility monitoring apparatus comprising:   The display processing unit further subdivides the selected display unit period to subdivide the display unit period, and generates data generated based on the singular point information corresponding to each subdivided display unit period. The equipment monitoring apparatus according to claim 1, wherein the equipment monitoring apparatus is displayed as index data indicating a state of the equipment in the inside.   The facility according to claim 1, wherein the display processing unit displays a display form of index data deviating from a predetermined threshold value indicating an abnormal state different from a display form of index data within the threshold value. Monitoring device.   The equipment monitoring apparatus according to claim 1, wherein the display processing means displays equipment data and singularity information corresponding to the selected display unit period on the same graph. Computer
An acquisition means for acquiring equipment data indicating the state of the equipment within the equipment monitoring period,
By analyzing the equipment data, when the equipment has performed a predetermined operation different from the normal state within the monitoring target period, it is extracted as a singular point, and when the singular point is continuously extracted, the extracted period Analyzing means for generating singularity information including at least date and time information for identifying the singularity and the specificity indicating the singularity of the singularity in the extracted period;
Display processing means for dividing a monitoring target period into predetermined display unit periods and displaying data generated based on singularity information corresponding to each display unit period as index data indicating the state of the equipment in the display unit period ,
Program to function as.

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