JP7845110B2 - Power equipment monitoring system and monitoring method - Google Patents

Description

This invention relates to a monitoring system and a monitoring method for power facilities.

Conventionally, systems have been proposed to monitor the status of power transmission lines, distribution lines, and surrounding power equipment such as transmission towers and utility poles, using optical fiber sensing mechanisms that utilize optical fiber cables laid along power transmission and distribution lines.

For example, Patent Document 1 describes a utility pole deterioration detection device configured for the purpose of detecting the deterioration state of utility poles with high accuracy. The utility pole deterioration detection device receives an optical signal containing a pattern corresponding to the deterioration state of the utility pole from a communication optical fiber contained in a cable including a communication optical fiber laid on the utility pole, and detects the deterioration state of the utility pole based on the pattern.

Furthermore, Patent Document 2 describes a utility pole breakage monitoring system configured for monitoring the breakage status of utility poles without causing a power outage. The utility pole breakage monitoring system comprises multiple utility poles connected such that buried optical fibers constitute a single optical signal path, a light source that emits test light from one end of the optical signal path, and optical signal detection means arranged at least one end of the optical signal path. The system detects broken utility poles by detecting the optical signal from the optical signal path based on the test light emitted from the light source.

For example, Patent Document 3 describes a nesting detection system configured to enable simple and reliable detection of nesting on utility poles. The nesting detection system emits light into an optical fiber, which is installed across multiple utility poles, from one end at predetermined intervals. It detects the reflected light from the optical fiber and identifies the utility pole where distortion has occurred based on a utility pole information table containing positional information indicating the location of each utility pole along the optical fiber path, the location of the distortion in the optical fiber determined by the time from when light is emitted to the end of the optical fiber until the reflected light is detected, and the intensity of the reflected light, along with the positional information of each utility pole recorded in the utility pole information table. If distortion is detected consecutively on the same utility pole a predetermined number of times or more, it is determined that nesting has occurred on the utility pole.

International Publication No. 2020/044655 Japanese Patent Publication No. 2008-67467 Japanese Patent Publication No. 2015-53832

"Study on the Dynamic Response Characteristics of Multi-Span Steel Tower-Transmission Line Systems," Shigehei Kozono (and 2 others), Institute of Applied Mechanics, Kyushu University, Journal of Structural Engineering, Architectural Institute of Japan, No. 353, July 1985.

"Study on Deterioration Diagnosis of Aging Power Transmission Towers Using High-Resolution Cameras," Tokuo Tsuji (et al.), Journal of Structural Engineering, Vol. 63A, March 2017, https://www.jstage.jst.go.jp/article/structcivil/63A/0/63A_570/_pdf/-char/ja, accessed July 20, 2022.

"A Study on the Vibration Characteristics of Power Transmission Lines During Strong Winds," Urban Disaster Management, Ken Inayoshi, Kyushu University, Master's Thesis List, URL: https://www.hues.kyushu-u.ac.jp/education/student/pdf/2003/2HE02019E.pdf, accessed July 20, 2022.

Power transmission lines, distribution lines, and surrounding power facilities such as transmission towers and utility poles are susceptible to the effects of natural phenomena such as strong winds, lightning, and snowfall. Therefore, regular monitoring for any abnormalities is necessary to prevent accidents such as power outages.

However, power transmission and distribution lines are often spread out over mountainous areas, making it extremely burdensome to monitor all of the vast number of power facilities in a region daily through manual inspections. Furthermore, while it's necessary to quickly identify the location of an accident, such as a lightning strike, even with technologies like LLS (Lightning Location System), pinpointing the location of an accident caused by physical stress like lightning is difficult. Additionally, access to the site is difficult during disasters like heavy snowfall, making it considerably time-consuming to identify the accident location.

The technologies described in Patent Documents 1 to 3 above all utilize optical fiber sensing mechanisms, but their detection targets are limited to specific items such as deterioration or breakage of utility poles, and the presence or absence of nesting. Furthermore, none of these documents are designed for the purpose of efficiently and accurately monitoring the status of power facilities for abnormalities during normal operation.

This invention was made in view of the above background, and aims to provide a power equipment monitoring system and monitoring method that can efficiently and accurately monitor for abnormalities in power transmission lines, distribution lines, or power transmission towers, utility poles, and other power equipment located around them.

One aspect of the present invention for solving the above problems is a power equipment monitoring system configured using an information processing device, which acquires vibration states from an optical analysis unit that acquires vibration states of power equipment present on or around power transmission lines or power distribution lines based on vibration states acquired by DAS (Distributed Acoustic Sensing) for each of a plurality of measurement points set along optical fibers attached along power transmission lines or power distribution lines, generates a model trained using training data created with the time change of vibration intensity of natural frequencies based on the acquired vibration states as explanatory variables and equipment state information, which is information indicating the state of the power equipment corresponding to the explanatory variables, as the objective variable, and inputs the time change of vibration intensity of natural frequencies based on the vibration states acquired in real time for each of the measurement points into the model , thereby acquiring equipment state information, which is information indicating the state of power equipment present on or around each of the measurement points , and outputs the acquired equipment state information.

Furthermore, the problems disclosed in this application and their solutions are clearly indicated in the section on embodiments for carrying out the invention and in the drawings.

According to this invention, it is possible to efficiently and accurately monitor for abnormalities in power transmission lines, distribution lines, or power equipment such as transmission towers and utility poles located around them.

This is a diagram showing the general configuration of the monitoring system. This is a diagram explaining the mechanism for measuring vibration conditions. This is an example of time-series data of the vibration intensity of the transverse wave component of the natural frequency of a power transmission line. This is an example of time-series data of the vibration intensity of the longitudinal wave component of the natural frequency of a power transmission line. This diagram shows the main components of an equipment monitoring system. This is a block diagram illustrating the main functions of the equipment monitoring device. This is a flowchart explaining the equipment monitoring process. This is an example of a screen displaying equipment status information.

The following matters will become clear from this specification and the accompanying drawings. The present invention will be described below with reference to the accompanying drawings, based on one embodiment thereof.

Figure 1 shows a schematic configuration of a system (hereinafter referred to as "monitoring system 1") that monitors the presence or absence of abnormalities in power equipment such as power transmission lines 3 and power transmission towers 2 located around them, as described as one embodiment of the present invention. Monitoring system 1 includes an equipment monitoring device 100 installed in power-related facilities such as substations 6, and an information provision and utilization device 200, which is an information processing device that provides various types of information to the equipment monitoring device 100 and utilizes the information provided by the equipment monitoring device 100. In this embodiment, the power equipment to be monitored is described as an example of power transmission lines 3 and power transmission towers 2, but the power equipment may also be, for example, distribution lines or utility poles (such as distribution concrete poles).

The equipment monitoring device 100 uses the optical fiber 4a of the OPGW4 (optical ground wire) (optical fiber composite overhead ground wire) installed on the power transmission line 3 as a vibration sensor. It acquires the vibration state at multiple points along the optical fiber 4a (hereinafter, each point will be referred to as a "measurement point") by measuring the vibration state (vibration intensity, vibration frequency) based on the expansion and contraction of the optical fiber 4a at each point using a technique (distributed multi-point vibration measurement method (hereinafter referred to as "DAS" (Distributed Acoustic Sensing))). DAS acquires the vibration state at the measurement points using, for example, the principle of C-OTDR (Coherent detection Optical Time Domain Reflectometer). By analyzing the acquired vibration state, the equipment monitoring device 100 acquires information regarding the state of power equipment present at the measurement points and in the surrounding areas (the span in which the measurement points are located and the area surrounding that span) (hereinafter referred to as "equipment state information").

Figure 2 illustrates the mechanism by which the equipment monitoring device 100 measures the vibration state at a measurement point. As shown in the figure, the equipment monitoring device 100 injects an optical pulse (laser pulse; hereinafter also referred to as "incident light") from the end face of the optical fiber 4a and measures the rate of change in the phase difference of the backscattered light of the optical pulse at the measurement point (≒stretching frequency). The equipment monitoring device 100 estimates the above phase difference from the intensity change due to interference between the backscattered light. Based on the measured rate of change, the equipment monitoring device 100 determines the longitudinal and transverse vibration frequencies of the optical fiber 4a at the measurement point (for example, vibration frequencies in the range of up to 10 kHz). Furthermore, the equipment monitoring device 100 determines the vibration intensity (spectral intensity, vibration amplitude) at the measurement point based on the phase difference for each vibration frequency. Finally, the equipment monitoring device 100 determines the position of the measurement point (distance from the end face) based on the elapsed time from the time the incident light is incident on the end face to the time the reflected light is received.

Measurement points are set, for example, at predetermined intervals d (m) shorter than the span of the transmission tower 2 along the optical fiber (0 (m), d (m), ..., N (m), N+d (m), N+2d (m)). For example, if the predetermined interval d is 5 (m) and measurement points are set within a range of up to 70 (km), approximately 14,000 measurement points will be set along the optical fiber.

The equipment monitoring device 100 acquires equipment status information for power equipment located in the span where the measurement point is situated and in the surrounding area by analyzing the vibration state of the measurement point. This equipment status information includes, for example, whether or not lightning has struck the power equipment, whether or not snow has accumulated on the power equipment, wind conditions (wind direction, wind speed) at the location of the power equipment, loosening, detachment, or damage to components or bolts in the power equipment, approach of moving objects such as heavy machinery or helicopters (detectable by noise), generation of corona noise (high vibration intensity in the 60Hz or 120Hz band in western Japan), occurrence of street jumps (detectable by vibration), and occurrence of electrical accidents (detectable by sound and vibration during ground faults or short circuits).

For example, see Non-Patent Literature 1 ("Study on the Dynamic Response Characteristics of Multi-Span Transmission Tower-Power Transmission Line Systems," Kyushu University Institute of Applied Mechanics, Shigehei Kozono (et al.), Journal of Structural Engineering, Architectural Institute of Japan, No. 353, July 1985), Non-Patent Literature 2 ("Study on Deterioration Diagnosis of Aging Power Transmission Towers Using High-Resolution Cameras," Tokuo Tsuji (et al.), Journal of Structural Engineering, Vol. 63A, March 2017, https://www.jstage.jst.go.jp/article/structcivil/63A/0/63A_570/_pdf/-char/ja, accessed July 20, 2022), Non-Patent Literature 3 ("Study on the Vibration Characteristics of Power Transmission Lines During Strong Winds," Urban Disaster Management, Inayoshi As described in Ken, Kyushu University, Master's Thesis List (URL: https://www.hues.kyushu-u.ac.jp/education/student/pdf/2003/2HE02019E.pdf, accessed July 20, 2022), the vibration state of the optical fiber 4a in the span has a certain correlation with the state of power equipment such as the power transmission line 3 located in the span and the power transmission tower 2 located around the power transmission line 3. For example, the vibration state of the power transmission line 3 changes due to the effects of wind, lightning strikes, snow accumulation, etc. Also, the vibration state of the power transmission tower 2 changes due to loosening, detachment, or damage to members and bolts.

Therefore, statistical models and AI (Artificial Intelligence) models (machine learning models) that represent the above correlation (hereinafter collectively referred to as "models") are pre-generated (trained) using data (hereinafter referred to as "training data") in which equipment status information is associated with explanatory variables based on vibration states acquired in the past for each measurement point. By inputting the vibration states acquired (newly) in real time for each measurement point into the generated model, it becomes possible to acquire equipment status information of power equipment surrounding the measurement point and each fixed point and detect abnormalities in the power equipment. Specifically, for example, the equipment monitoring device 100 analyzes the vibration state at the measurement point to determine the natural frequency (fundamental frequency) and its vibration intensity at the measurement point, inputs the time change (time-series data) of the vibration intensity of the determined natural frequency into the model to acquire equipment status information, and detects whether or not there is an abnormality in the power equipment based on the acquired equipment status information.

Figure 3A shows an example of the time-series data (time-dependent analysis) of the vibration intensity of the transverse wave component (component perpendicular to the extension direction of the optical fiber 4a) at each span of the power transmission line 3, obtained by the equipment monitoring device 100 analyzing the vibration state. In the graph shown in the figure, the horizontal axis represents time, and the vertical axis represents the change in vibration intensity of the transverse wave component for each natural frequency.

Figure 3B shows an example of the time evolution (time-series data) of the vibration intensity of the longitudinal wave component (component in the direction of extension of the optical fiber 4a) of the natural frequencies (fundamental frequencies) of each span of the power transmission line 3, obtained by the equipment monitoring device 100 analyzing the vibration state. In the graph shown in this figure, the horizontal axis represents time, and the vertical axis represents the change in vibration intensity of the longitudinal wave component for each natural frequency.

The equipment monitoring device 100 acquires equipment status information of power equipment by inputting, for example, the time change in vibration intensity of natural frequencies based on the vibration state of measurement points acquired in real time (hereinafter also referred to as "natural frequency waveform") into a model. Furthermore, the equipment monitoring device 100 uses, for example, an anomaly detection model in time-series analysis as the model to capture abnormal changes in equipment status information (for example, waveform changes as shown by reference numeral 31 in Figure 3A and reference numeral 32 in Figure 3B), thereby detecting abnormalities occurring in the power equipment or precursors to potential abnormalities in the power equipment.

Figure 4A shows the main components of the equipment monitoring device 100. As shown in the figure, the equipment monitoring device 100 comprises a processor 101, main memory 102 (memory), auxiliary storage device 103 (external storage device), input device 104, output device 105, communication device 106, and optical analysis unit 107. These are connected via a bus or communication cable for communication. Furthermore, the equipment monitoring device 100 may be implemented entirely or partially using virtual information processing resources, such as a virtual server provided by a cloud system.

The processor 101 is composed of, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a GPU (Graphics Processing Unit), an FPGA (Field Programmable Gate Array), an ASIC (Application Specific Integrated Circuit), and an AI (Artificial Intelligence) chip.

The main memory 102 is a memory device used by the processor 101 when executing a program, and is, for example, ROM (Read Only Memory), RAM (Random Access Memory), or non-volatile memory (NVRAM (Non-Volatile RAM)).

The auxiliary storage device 103 is a device for storing programs and data, and can be composed of, for example, an SSD (Solid State Drive), a hard disk drive, or an optical storage device (CD (Compact Disc), DVD (Digital Versatile Disc), etc.). The auxiliary storage device 103 can read programs and data from recording media or other information processing devices equipped with storage devices via a recording media reader or communication device 106. Programs and data stored in the auxiliary storage device 103 are read into the main memory 102 as needed.

The input device 104 is an interface that accepts information input from an external source, such as a keyboard, mouse, touch panel, or voice input device.

The output device 105 is an interface for outputting various information, such as processing progress and processing results, to an external source. The output device 105 may include, for example, a display device that visualizes the above-mentioned information (such as a liquid crystal monitor or LCD), a device that converts the above-mentioned information into audio (such as an audio output device or speaker), or a device that converts the above-mentioned information into text (such as a printing device). Alternatively, for example, the equipment monitoring device 100 may be configured to input and output information to and from other devices via the communication device 106.

The input device 104 and output device 105 constitute a user interface that enables interactive processing with the user (receiving information, providing information, etc.).

The communication device 106 is a device that enables communication with other devices via a communication network (LAN (Local Area Network), WAN (Wide Area Network), the Internet, a public communication network, a dedicated line, etc.). The communication device 106 is a wired or wireless communication interface that enables communication with other devices via a communication medium, such as a NIC (Network Interface Card), a wireless communication module, or a USB module.

The optical analysis unit 107 is a device that measures the vibration state of a measurement point using DAS, and includes a vibration measurement device and signal processing circuit using C-OTDR. The optical analysis unit 107 includes a CW (continuous wave) laser light source that generates optical pulses (laser light) to be input to the end face of the optical fiber 4a, an optical pulse generator, an optical amplifier, optical instruments (optical detector, optical interferometer), and a signal processing circuit (phase calculation circuit, etc.). The connection between the optical analysis unit 107 and the optical fiber 4a is made, for example, by optically connecting the output section of the laser light source of the optical analysis unit 107 to the connection port (socket) of the core wire (optical fiber 4a) of the OPGW 4 installed in the substation. Therefore, the connection does not cause any impact on the power system, such as power outages.

The equipment monitoring device 100 may have, for example, an operating system, a file system, a DBMS (Database Management System) (relational database, NoSQL, etc.), a KVS (Key-Value Store), etc. installed on it.

The various functions of the equipment monitoring device 100 are realized either by the processor 101 reading and executing programs stored in the main memory 102, or by the hardware (FPGA, ASIC, AI chip, etc.) that constitutes the equipment monitoring device 100 itself. The equipment monitoring device 100 stores various types of information (data) as, for example, database tables or files managed by a file system.

Figure 4B is a block diagram illustrating the main functions of the equipment monitoring device 100. As shown in the figure, the equipment monitoring device 100 comprises the following functions: a storage unit 110, a vibration state measurement unit 120, a vibration state analysis unit 130, an equipment state monitoring unit 140, an equipment state information output unit 155, and an information acquisition and management unit 180.

Of the above functions, the memory unit 110 stores vibration status 111 for each measurement point, natural vibration information 112 for each measurement point, a model 113 (statistical model or AI model), equipment status information 114, and various other information 118. Furthermore, as shown in the figure, the equipment status information 114 includes lightning strike information 1141, snow accumulation information 1142, wind condition information 1143, galloping information 1144, and equipment malfunction information 1145.

The vibration state measurement unit 120 measures the vibration state of the measurement points in real time using DAS, and manages the real-time vibration state (time-series data of vibration intensity and vibration frequency) measured for each measurement point as the vibration state 111 for each measurement point.

The vibration state analysis unit 130 determines the natural frequency of each measurement point based on the vibration state of the measurement point, which is managed as vibration state 111 for each measurement point, and manages the waveform of the determined natural frequency as natural vibration information 112 for each measurement point.

The equipment status monitoring unit 140 acquires equipment status information about the power equipment at a measurement point by inputting the waveform of the natural frequency of the measurement point (for example, the waveform in the most recent predetermined time range) obtained from the natural vibration information 112 for each measurement point into the model 113. As shown in the figure, the equipment status monitoring unit 140 includes a lightning strike monitoring unit 1401, a snow accumulation monitoring unit 1402, a wind condition monitoring unit 1403, a galloping monitoring unit 1404, and an equipment abnormality monitoring unit 1405.

Of these, the lightning strike monitoring unit 1401 uses the waveform of the natural frequency acquired during a lightning strike on power equipment over a predetermined time interval as an explanatory variable, and the equipment status information corresponding to that natural frequency as an objective variable. This model 113 has been trained using training data, and the waveform of the natural frequency newly acquired at each measurement point is input to acquire equipment status information (presence or absence of lightning strikes (or the probability of lightning strikes), number of lightning strikes, etc.). The acquired equipment status information is then managed as lightning strike information 1141.

The snow accumulation monitoring unit 1402 uses the waveform of the natural frequency acquired when snow accumulates on power equipment over a predetermined time interval as an explanatory variable, and the equipment status information corresponding to that natural frequency as the target variable. This model 113 was trained using this model as training data. By inputting the waveform of the natural frequency newly acquired at each measurement point, the unit acquires equipment status information (presence or absence of snow accumulation (or probability of snow accumulation), amount of snow accumulation, etc.), and manages the acquired equipment status information as snow accumulation information 1142.

The wind condition monitoring unit 1403 uses the waveform of the natural frequency due to wind at the location where the power equipment is located as an explanatory variable, and the equipment status information corresponding to that natural frequency as an objective variable. The unit learns from this model 113 using training data, and inputs the waveform of the natural frequency newly acquired at each measurement point to acquire equipment status information (wind conditions (average wind speed, average wind direction), etc.). The acquired equipment status information is then managed as wind condition information 1143.

The galloping monitoring unit 1404 uses the waveform of the natural frequency over a predetermined time range due to the phenomenon of galloping (vibration of the power transmission line 3 when ice or snow adheres to it and strong winds blow) as an explanatory variable, and the equipment state information corresponding to that natural frequency as an objective variable. By inputting the waveform of the natural frequency newly acquired at each measurement point into the model 113, the unit acquires equipment state information (stress and torsional force acting on the power equipment, etc.) and manages the acquired equipment state information as galloping information 1144.

The equipment abnormality monitoring unit 1405 uses the waveform of the natural frequency over a predetermined time interval when abnormalities such as deterioration or damage occur in the power equipment as an explanatory variable, and the equipment status information corresponding to that natural frequency as an objective variable. By inputting the waveform of the natural frequency newly acquired at each measurement point into the model 113, the unit acquires equipment status information (such as the degree of deterioration of the power equipment, or loose or improperly tightened bolts and nuts on clamps, connecting fittings, dampers, etc., of the transmission tower 2), and manages the acquired equipment status information as equipment abnormality information 1145.

The equipment status information output unit 155 outputs the contents of the equipment status information 114 via the user interface and provides it to the user. Furthermore, the equipment status information output unit 155 provides the contents of the equipment status information 114 to the information provision and utilization device 200 via the communication device 106.

The information acquisition and management unit 180 acquires the information necessary to operate the vibration state measurement unit 120, the vibration state analysis unit 130, the equipment state monitoring unit 140, and the equipment state information output unit 155 from the information provision and utilization device 200. The information provision and utilization device 200, for example, acquires the above information from the management system of the power transmission and distribution equipment and provides it to the information acquisition and management unit 180.

Figure 5 is a flowchart illustrating an example of a process performed by the equipment monitoring device 100 (hereinafter referred to as "equipment monitoring process S500"). The equipment monitoring process S500 will be explained below in conjunction with this figure.

In S510, the vibration state measurement unit 120 acquires the vibration state for the most recent predetermined time interval at each measurement point and manages the acquired vibration state as the vibration state 111 for each measurement point.

The process from S511s to S511e is a loop process that repeatedly selects each measurement point sequentially.

First, in S512, the vibration state analysis unit 130 determines the waveform of the natural frequency based on the vibration state of the selected measurement point over the predetermined time width, and manages the determined waveform as natural vibration information 112 for each measurement point.

Next, the lightning strike monitoring unit 1401 acquires equipment status information by inputting the waveform of the natural frequency obtained in S512 into the model 113, and manages the acquired equipment status information as lightning strike information 1141 (S513).

Next, the snow accumulation monitoring unit 1402 acquires equipment status information by inputting the waveform of the natural frequency obtained in S512 into the model 113, and manages the acquired equipment status information as snow accumulation information 1142 (S514).

Next, the wind condition monitoring unit 1403 acquires equipment status information by inputting the waveform of the natural frequency obtained in S512 into the model 113, and manages the acquired equipment status information as wind condition information 1143 (S515).

Next, the galloping monitoring unit 1404 acquires equipment status information by inputting the waveform of the natural frequency obtained in S512 into the model 113, and manages the acquired equipment status information as galloping information 1144 (S516).

Next, the equipment abnormality monitoring unit 1405 acquires equipment status information by inputting the waveform of the natural frequency obtained in S512 into the model 113, and manages the acquired equipment status information as equipment abnormality information 1145 (S517).

Once the loop processing from S511s to S511e is completed, the equipment status information output unit 155 then outputs the contents of the equipment status information 114 (presented to the user or transmitted to the information provision and utilization device 200) (S521).

Next, the equipment monitoring device 100 shifts a predetermined time interval (advancing the start and end times of the predetermined time interval) (S522), and then the process returns to S510.

Figure 6 shows an example of the screen displayed by the equipment status information output unit 155 via the user interface in S521 of Figure 5 (hereinafter referred to as the "equipment status information display screen 600"). As shown in the figure, the equipment status information display screen 600 has a field for specifying the line ID 610, a field for specifying the span number 611, a field for specifying the display period 612, a field for displaying lightning strike information 613, a field for displaying snow accumulation information 614, a field for displaying wind condition information 615, a field for displaying galloping information 616, and a field for displaying equipment abnormality information 617.

In the track ID specification field 610, the user enters the identifier of the track to be displayed on the screen (hereinafter referred to as "track ID"). The user can either directly enter the track ID or select it using the pull-down menu.

In the span number specification field 611, the user enters the identifier of the span to be displayed on the screen (hereinafter referred to as "span ID"). The user can either directly enter the span ID or select it using the pull-down menu.

In the display period specification field 612, the user enters the period for which they want the equipment status information to be displayed on the screen (hereinafter referred to as the "display period"). The user can either directly enter the display period or select it using the pull-down menu.

The display field 613 for lightning strike information shows the contents of the lightning strike information 1141 for the span number specified in the span number specification field 611 and for the display period specified in the display period specification field 612.

The snow accumulation information display field 614 displays the snow accumulation information 1142 for the span specified in the span number specification field 611 and for the display period specified in the display period specification field 612.

The wind condition information display field 615 displays the contents of the wind condition information 1143 for the span specified in the span number specification field 611 and for the display period specified in the display period specification field 612.

The galloping information display field 616 displays the contents of the galloping information 1144 for the span specified in the span number specification field 611 and the display period specified in the display period specification field 612.

The equipment malfunction information display field 617 displays the contents of the equipment malfunction information 1145 for the span specified in the span number specification field 611 and for the display period specified in the display period specification field 612.

<Summary>
As described above, the monitoring system 1 of this embodiment inputs information based on vibration states acquired in real time from the optical analysis unit into a model (statistical model or AI model) to acquire and output the status of power equipment (equipment status information), thereby enabling efficient monitoring of whether or not there are abnormalities in power equipment such as transmission lines, distribution lines, or transmission towers and utility poles located around them.

Furthermore, by using time-series data of vibration intensity at the natural frequencies of the vibration state (waveforms of the natural frequencies) as information based on the vibration state, it is possible to generate models tailored to the characteristics of each power facility, for example, enabling highly accurate monitoring of the power facility's condition. Additionally, in the event of an accident caused by lightning strikes or other incidents, the accident point can be identified accurately and quickly.

Furthermore, information regarding the status of power equipment can be obtained in real time from remote locations such as substations and monitoring stations. This includes information on lightning strikes on power equipment in each span, snow accumulation on power equipment, wind conditions at the locations where power equipment is installed, galloping on power equipment, and deterioration or damage to power equipment. This allows for the early detection of potential accidents and the prevention of power outages and other accidents.

Furthermore, the above embodiments are provided to facilitate understanding of the present invention and are not intended to limit its interpretation. The present invention may be modified and improved without departing from its spirit, and equivalents thereof are also included.

1. Monitoring system, 2. Transmission tower, 3. Transmission line, 4. OPGW, 4a. Optical fiber, 6. Substation, 100. Equipment monitoring device, 107. Optical analysis unit, 110. Memory unit, 111. Vibration state per measurement point, 112. Natural vibration information per measurement point, 113. Model, 114. Equipment status information, 1141. Lightning strike information, 1142. Snow accumulation information, 1143. Wind condition information, 1144. Galloping information, 1145. Equipment abnormality information, 118. Various information, 120. Vibration state measurement unit, 130. Vibration state analysis unit, 140. Equipment status monitoring unit, 1401. Lightning strike monitoring unit, 1402. Snow accumulation monitoring unit, 1403. Wind condition monitoring unit, 1404. Galloping monitoring unit, 1405. Equipment abnormality monitoring unit, 155. Equipment status information output unit, 180. Information Acquisition and Management Department, S500 Equipment Monitoring Processing

Claims (10)

It is configured using an information processing device,
Based on the vibration state acquired by DAS (Distributed Acoustic Sensing) for each of the multiple measurement points set along the optical fiber attached to the power transmission line or distribution line, the vibration state of the power transmission line or distribution line or the power equipment surrounding them is acquired from an optical analysis unit that acquires the vibration state of the power transmission line or distribution line or the power equipment surrounding them.
A model is generated using training data created with the time variation of vibration intensity of natural frequencies based on the acquired vibration state as the explanatory variable, and equipment state information, which is information indicating the state of the power equipment corresponding to the explanatory variable , as the objective variable.
By inputting the time change of the vibration intensity of the natural frequency based on the vibration state acquired in real time for each of the measurement points into the model , equipment status information, which is information indicating the state of power equipment present at each of the measurement points or in the vicinity of each of the measurement points ,
Output the acquired equipment status information.
A monitoring system for power facilities. A power equipment monitoring system according to claim 1 ,
The aforementioned equipment status information is information indicating at least one of the following: the status of lightning strikes on the power equipment, the status of snow accumulation on the power equipment, the wind conditions at the location where the power equipment is installed, and the status of galloping occurring on the power equipment.
A monitoring system for power facilities. A power equipment monitoring system according to claim 1 ,
The aforementioned equipment status information is information indicating the state of deterioration or damage to the power equipment.
A monitoring system for power facilities. A power equipment monitoring system according to claim 1 ,
The information based on the vibration state acquired in real time is time-series data of the information based on the vibration state over the most recent predetermined time period.
A monitoring system for power facilities. A power equipment monitoring system according to claim 1 ,
The system includes a user interface that presents the aforementioned equipment status information to the user.
A monitoring system for power facilities. A power equipment monitoring system according to claim 5,
The aforementioned equipment status information is information indicating an abnormality in the power equipment,
The system receives information specifying the span of the transmission line or distribution line corresponding to the measurement point, and information specifying the period for which the equipment status information is to be displayed.
The system outputs a list of the equipment status information for the power equipment in the spans that was received during the period for which the information was received.
A monitoring system for power facilities. A power equipment monitoring system according to claim 1 ,
The system includes a communication device that transmits the aforementioned equipment status information to another information processing device.
A monitoring system for power facilities. Information processing device,
A step of acquiring vibration states from an optical analysis unit that acquires vibration states of power transmission lines or distribution lines or power equipment present around them, based on vibration states acquired by DAS (Distributed Acoustic Sensing) for each of a plurality of measurement points set along optical fibers attached along power transmission lines or distribution lines,
A step of generating a model trained using training data created with the time change of vibration intensity of the natural frequency based on the acquired vibration state as the explanatory variable , and equipment state information, which is information indicating the state of the power equipment corresponding to the explanatory variable, as the objective variable,
The steps include: inputting the time change of the vibration intensity of the natural frequency based on the vibration state acquired in real time for each of the measurement points into the model to acquire equipment status information , which is information indicating the state of power equipment present at each of the measurement points or in the vicinity of each of the measurement points ; and
Steps include outputting the acquired equipment status information,
A method for monitoring power equipment, which involves performing the following actions. A method for monitoring power equipment according to claim 8 ,
The aforementioned equipment status information is information indicating at least one of the following: the status of lightning strikes on the power equipment, the status of snow accumulation on the power equipment, the wind conditions at the location where the power equipment is installed, and the status of galloping occurring on the power equipment.
Methods for monitoring power equipment. A method for monitoring power equipment according to claim 8 ,
The aforementioned equipment status information is information indicating the state of deterioration or damage to the power equipment.
Methods for monitoring power equipment.