Power transmission equipment health state real-time evaluation and operation and maintenance guidance system and method

Abstract

The invention discloses a power transmission equipment health state real-time evaluation and operation and maintenance guidance system and method. The method comprises the following steps: collecting inspection data of power transmission equipment according to a preset inspection route through an unmanned aerial vehicle; real-time operation data is acquired and equipment inspection data is received through an equipment data acquisition module, and preprocessing is carried out; real-time operation data and equipment inspection data sent by an equipment data acquisition module are received through an equipment state detection module, and the equipment operation state of the power transmission equipment is determined; through the operation and maintenance guidance module, the equipment operation state sent by the equipment state detection module is received, the alarm information is generated according to the equipment operation state and the early warning state threshold, the operation and maintenance guidance data is determined, and the operation and maintenance guidance data is recorded, so that the inspection efficiency and precision are improved, and the labor cost and risk are reduced; and potential faults can be quickly identified and early warning information can be generated, so that maintenance measures can be taken in time, and the efficiency and accuracy of power transmission equipment management are improved.

Description

Technical Field

[0001] The present invention relates to the field of electric power detection technology, and in particular to a system and method for real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance. Background Art

[0002] With the continuous development and expansion of power systems, the number of transmission equipment has increased dramatically.

[0003] In related technologies, the status detection of power transmission equipment mainly relies on regular manual inspections and limited online monitoring methods. This method is not only inefficient, but also difficult to cover all key points and easily misses hidden dangers. In addition, due to the lack of effective data analysis tools, even if a large amount of operating data is collected, it is difficult to convert it into valuable maintenance decision support in a timely manner. Summary of the invention

[0004] The present invention provides a real-time evaluation system and operation and maintenance guidance method for the health status of power transmission equipment, so as to solve the problems of untimely detection of power transmission equipment and delayed fault warning in the related art.

[0005] According to one aspect of the present invention, a real-time evaluation system for the health status of power transmission equipment and an operation and maintenance guidance system is provided, comprising: a drone, an equipment data acquisition module, an equipment status detection module and an operation and maintenance guidance module; wherein:

[0006] The drone is used to collect inspection data of the power transmission equipment according to a preset inspection route, and send the inspection data to the equipment data acquisition module;

[0007] The equipment data acquisition module is used to obtain the real-time operation data of the power transmission equipment and receive the equipment inspection data collected by the drone, and pre-process the real-time operation data and the equipment inspection data, and send the pre-processed real-time operation data and the equipment inspection data to the equipment status detection module;

[0008] The equipment status detection module is used to receive the real-time operation data and the equipment inspection data sent by the equipment data acquisition module, and determine the equipment operation status of the power transmission equipment according to the real-time operation data and the equipment inspection data, and send the equipment operation status to the operation and maintenance guidance module; wherein the equipment operation status is used to characterize the safety level of the power transmission equipment during operation;

[0009] The operation and maintenance guidance module is used to receive the equipment operating status sent by the equipment status detection module, generate alarm information according to the equipment operating status and the early warning status threshold, generate operation and maintenance guidance data corresponding to the power transmission equipment based on the equipment operating status and the alarm information, and record the operation and maintenance guidance data.

[0010] According to another aspect of the present invention, a method for real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance is provided, which is applied to the real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance system, wherein the real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance system comprises:

[0011] By using drones, the inspection data of the power transmission equipment is collected according to a preset inspection route, and the inspection data is sent to the equipment data collection module;

[0012] The equipment data acquisition module is used to obtain the real-time operation data of the power transmission equipment and receive the equipment inspection data collected by the drone, and pre-process the real-time operation data and the equipment inspection data, and send the pre-processed real-time operation data and the equipment inspection data to the equipment status detection module;

[0013] The device status detection module is used to receive the real-time operation data and the device inspection data sent by the device data acquisition module, and determine the device operation status of the power transmission device according to the real-time operation data and the device inspection data, and send the device operation status to the operation and maintenance guidance module; wherein the device operation status is used to characterize the safety level of the power transmission device during operation;

[0014] The operation and maintenance guidance module receives the equipment operation status sent by the equipment status detection module, generates alarm information according to the equipment operation status and the early warning status threshold, determines the operation and maintenance guidance data corresponding to the power transmission equipment based on the equipment operation status and the alarm information, and records the operation and maintenance guidance data.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance as described in any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance as described in any embodiment of the present invention when executed.

[0020] According to another aspect of the present invention, an embodiment of the present disclosure further provides a computer program product, including a computer program, which, when executed by a processor, implements the method for real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance as described in any of the embodiments of the present disclosure.

[0021] The technical solution of the embodiment of the present invention is as follows: first, the inspection data of the power transmission equipment is collected by the unmanned aerial vehicle according to the preset inspection route, and the inspection data is sent to the equipment data collection module, so that the power transmission equipment can be automatically inspected, the data can be efficiently collected and transmitted in real time; then, the real-time operation data of the power transmission equipment and the equipment inspection data collected by the unmanned aerial vehicle are obtained through the equipment data collection module, and the real-time operation data and the equipment inspection data are received, and the real-time operation data and the equipment inspection data are pre-processed, and the pre-processed real-time operation data and the equipment inspection data are sent to the equipment status detection module, which can ensure the comprehensiveness and accuracy of the data; then, the real-time operation data and the equipment inspection data sent by the equipment data collection module are received through the equipment status detection module, and the equipment operation status of the power transmission equipment is determined according to the real-time operation data and the equipment inspection data, and the equipment operation status is sent to the operation and maintenance guidance module. The equipment operation status is used to characterize the safety level of the power transmission equipment during operation. It can analyze real-time operation data and equipment inspection data, evaluate the equipment operation status and safety level of the power transmission equipment, and send them to the operation and maintenance guidance module to ensure rapid response to potential faults; finally, through the operation and maintenance guidance module, the equipment operation status sent by the equipment status detection module is received, and alarm information is generated according to the equipment operation status and the early warning status threshold. The operation and maintenance guidance data corresponding to the power transmission equipment is determined based on the equipment operation status and the alarm information, and the operation and maintenance guidance data is recorded. Potential faults or abnormal conditions can be discovered and located in time to ensure rapid response, which solves the problems of untimely detection of power transmission equipment and delayed fault warning in related technologies, improves inspection efficiency and accuracy, reduces labor costs and risks, and can quickly identify potential faults and generate early warning information to ensure timely maintenance measures, thereby improving the efficiency and accuracy of power transmission equipment management.

[0022] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 This is a structural diagram of a real-time health status evaluation and operation and maintenance guidance system for power transmission equipment provided according to Embodiment 1 of the present invention;

[0025] Figure 2 This is a flow chart of a method for real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance provided according to Embodiment 2 of the present invention;

[0026] Figure 3 It is a schematic diagram of application scenarios of the alarm information provided by the present invention;

[0027] Figure 4 It is a structural schematic diagram of an electronic device for implementing the real-time evaluation of the health status of power transmission equipment and the operation and maintenance guidance method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0031] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0032] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0033] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0034] As an optional but non-limiting implementation, in response to receiving an active request from the user, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0035] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet the relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0036] It is understandable that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and relevant provisions.

[0037] Embodiment 1

[0038] Figure 1 A structural schematic diagram of a system for real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance is provided for Embodiment 1 of the present invention. This embodiment is applicable to the situation of comprehensive and real-time health detection of power transmission equipment. The system can execute a method for real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance. The system for real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance can be implemented in the form of hardware and / or software, and optionally, can be implemented by an electronic device, which can be a mobile terminal, a PC or a server, etc.

[0039] like Figure 1As shown, the system may specifically include: a drone 110, an equipment data acquisition module 120, an equipment status detection module 130 and an operation and maintenance guidance module 140; wherein the drone 110 is used to collect inspection data of the power transmission equipment according to a preset inspection route, and send the inspection data to the equipment data acquisition module; the equipment data acquisition module 120 is used to obtain the real-time operation data of the power transmission equipment and receive the equipment inspection data collected by the drone, and pre-process the real-time operation data and the equipment inspection data, and send the pre-processed real-time operation data and the equipment inspection data to the equipment status detection module; the equipment status detection module 130, Used to receive the real-time operation data and the equipment inspection data sent by the equipment data acquisition module, and determine the equipment operation status of the power transmission equipment based on the real-time operation data and the equipment inspection data, and send the equipment operation status to the operation and maintenance guidance module; wherein the equipment operation status is used to characterize the safety level of the power transmission equipment during operation; the operation and maintenance guidance module 140 is used to receive the equipment operation status sent by the equipment status detection module, generate alarm information according to the equipment operation status and the early warning status threshold, generate operation and maintenance guidance data corresponding to the power transmission equipment based on the equipment operation status and the alarm information, and record the operation and maintenance guidance data.

[0040] The drone is used to fly according to a preset inspection route, collect images, videos or other data of the power transmission equipment, and transmit the inspection data to the equipment data acquisition module. The inspection route can be understood as a specific flight path set by the drone, which is used to ensure that the drone can cover all power transmission equipment that needs to be inspected to complete a comprehensive data collection task. The inspection data can be understood as information collected by the drone during the inspection process. The inspection data includes but is not limited to visual images and infrared thermal images, etc., which are used to evaluate the status of the power transmission equipment.

[0041] Among them, the equipment data acquisition module can be understood as a component for collecting and preliminarily processing data from different sources. Specifically, the equipment data acquisition module can obtain the real-time operation data of the power transmission equipment and the inspection data sent by the drone, and pass it to the equipment status detection module after preprocessing (such as cleaning, filtering or format conversion, etc.). The real-time operation data can be understood as various parameter information generated by the power transmission equipment during its operation. The real-time operation data can provide indicators about the current working conditions of the equipment, which are used to detect the performance of the power transmission equipment, including but not limited to temperature, pressure, current and voltage. The preprocessing can be understood as a series of preliminary processing steps performed on the real-time operation data and equipment inspection data, including but not limited to at least one of operations such as data cleaning, normalization and data compression.

[0042] The device status detection module can be understood as a component responsible for processing the pre-processed real-time operation data and equipment inspection data to determine the device operation status of the power transmission equipment. The device operation status can be understood as the working status of the power transmission equipment at a specific time point, which is used as an indicator to measure the safety level of the power transmission equipment and help determine whether the power transmission equipment is in good condition or needs maintenance.

[0043] Among them, the operation and maintenance guidance module can be understood as a component that provides maintenance and operation suggestions. Specifically, the operation and maintenance guidance module can generate alarm information based on the received equipment operation status information and the early warning threshold, provide corresponding operation and maintenance guidance, and record operation and maintenance guidance data. The early warning status threshold can be understood as a pre-set safety limit, and if the safety limit is exceeded, it is considered that there is a potential risk. The early warning status threshold can be used to trigger an alarm mechanism. The alarm information can be understood as a notification issued when the equipment operation status is lower than the early warning status threshold, which is used to remind the need to pay attention to the equipment operation status of the transmission equipment and respond. The operation and maintenance guidance data can be understood as the maintenance and operation suggestions and their records proposed for the equipment operation status.

[0044] On the basis of the above scheme, the drone can be equipped with an image acquisition component and an infrared acquisition component. The image acquisition component includes an image acquisition probe and a data storage device, the image acquisition probe acquires image data of the cable connected to the power transmission device and the power transmission device, and the data storage device stores the image data acquired by the image acquisition probe; the infrared acquisition component includes an infrared acquisition probe and a data buffer, the infrared acquisition probe acquires infrared image data of the power transmission line and the power transmission device, and the data buffer stores the infrared image data acquired by the infrared acquisition probe.

[0045] On the basis of the above scheme, optionally, the equipment data acquisition module includes a sensor unit, a data preprocessing unit and a data transmission unit; wherein the sensor unit includes a plurality of sensors distributedly arranged on the power transmission equipment, for collecting real-time operation data of the power transmission equipment; the data preprocessing unit is used to receive the equipment inspection data collected by the drone, and preprocess the real-time operation data and the equipment inspection data, and transmit the preprocessed real-time operation data and the equipment inspection data to the equipment status detection module through the data transmission unit.

[0046] Among them, the sensor unit can be understood as a collection of multiple sensors, which are distributedly installed on the power transmission equipment and are used to detect and collect various operating parameters of the power transmission equipment. The sensors include but are not limited to at least one of a temperature sensor, a pressure sensor, an odor sensor, an acceleration sensor, and a photoelectric sensor. The acceleration sensor can be understood as a sensor used to measure acceleration force (including gravity). Specifically, it can detect whether the power transmission equipment vibrates or displaces, which helps to evaluate the working status of the components of the power transmission equipment. The photoelectric sensor can be understood as a sensor that detects the existence, position or other characteristics of an object through a light beam, and can be used to detect switch status or obstacles, etc., to ensure the normal operation of the power transmission equipment.

[0047] By adopting this technical solution, through the distributed deployment of multiple sensors on the transmission equipment, real-time operation data can be collected efficiently and accurately, and comprehensive analysis can be carried out in combination with the inspection data collected by the drone; the data preprocessing unit preprocesses the real-time operation data and inspection data to ensure data quality and consistency; the data transmission unit transmits the preprocessed data to the equipment status detection module, supporting fast and accurate status assessment, which not only improves the reliability and availability of the data, but also enhances the timeliness and accuracy of fault warning.

[0048] On the basis of the above scheme, optionally, the device state detection module includes a feature extraction unit, a feature fusion unit, a health index determination unit and a state prediction unit; wherein the feature extraction unit is used to perform feature extraction on the real-time operation data and the equipment inspection data respectively to obtain multiple target device features of the power transmission equipment; wherein the target device features include voltage data, current data, infrared temperature anomaly data and cable sag data; the feature fusion unit is used to receive multiple target device features, determine the standardized deviation of multiple target device features relative to the standard device features, and transmit the standardized deviation to the health index determination unit; the health index determination unit is used to receive the standardized deviation of multiple target device features, determine the device health index of the power transmission equipment according to the standardized deviation of multiple target device features, and generate a prediction trigger signal when the device health index is less than a preset health index threshold, and send the prediction trigger signal to the state prediction unit; the state prediction unit is used to receive the prediction trigger signal, and in response to the prediction trigger signal, determine the device operation state of the power transmission equipment according to the historical device features of the power transmission equipment.

[0049] Among them, the feature extraction unit can be understood as a component for identifying and extracting features from real-time operation data and equipment inspection data. The feature extraction unit can analyze the real-time operation data and equipment inspection data to extract target device features that can characterize the performance of the power transmission equipment, and the target device features will serve as the basis for evaluating the health status of the power transmission equipment. The target device features can be understood as data that records the characteristics of the voltage, current, and temperature on the power transmission line or the power transmission equipment. The target device features include but are not limited to at least one of voltage data, current data, infrared temperature anomaly data, and cable sag data. The infrared temperature anomaly data can be understood as temperature data that exceeds the normal range detected using infrared technology. The cable sag data can be understood as data on the degree of natural sag of the power transmission cable in a suspended state. The feature fusion unit can be understood as a component for fusing features from different target devices. Specifically, the feature fusion unit can receive multiple target device features obtained by the feature extraction unit and determine the standardized deviation of the target device features relative to the standard device features. The standard device features can be understood as the standard value or range that the target device features should reach under ideal or normal working conditions of the power transmission equipment. The standardized deviation can be understood as the relative gap between the target device characteristics and the standard device characteristics. The standardized deviation can be normalized. The health index determination unit can be understood as a component for determining the health status of the power transmission device. Specifically, the health index determination unit can determine the device health index based on the standardized deviation. When the device health index is less than the preset health index threshold, it indicates that the device may have potential problems, generate a prediction trigger signal, and send the prediction trigger signal to the state prediction unit. The device health index can be understood as an indicator used to indicate the current health or working state of the device. The preset health index threshold can be understood as a pre-set reference value, which is used to generate a prediction trigger signal when the device health index is less than the preset health index threshold. The prediction trigger signal can be understood as a signal generated by the health index determination unit, which is used to start the work of the state prediction unit. The state prediction unit can be understood as a component that uses historical device characteristics and other relevant information to predict the future device operation state of the power transmission device. The historical device characteristics can be understood as the historical operation data and historical performance records accumulated by the power transmission device during its use, reflecting the actual working state of the power transmission device at different time points, including performance under normal operating conditions and abnormal conditions or fault events.

[0050] In an optional implementation manner, the feature extraction unit performs feature extraction through the real-time operation data and the equipment inspection data to obtain the cable sag data of the power transmission equipment, which can be processed in the following manner:

[0051] S1. Image acquisition and calibration:

[0052] Capture Image: Take an image of the cable from a suitable angle, ideally perpendicular to the direction of the cable.

[0053] Calibration image: Calibrate reference objects of known length in the image (such as the distance between cable hanging points or calibration objects) to convert pixel distance to actual distance.

[0054] Among them, the actual width or length of the power transmission equipment corresponding to the inspection position is known, so:

[0055] Actual distance = pixel distance * scale;

[0056] The scale factor is calculated by knowing the actual distance and the corresponding pixel distance.

[0057] S2. Edge detection and cable contour extraction:

[0058] Edge Detection: Use edge detection algorithms (such as Canny edge detection) to extract the edges of the cables in the image.

[0059] Curve fitting: Perform curve fitting on the edge points of the cable to obtain the catenary shape of the cable.

[0060] The dotted line fitting is obtained by image processing technology, which is a well-known technical means for those skilled in the art, and thus will not be described in detail in this embodiment;

[0061] Specifically, edge point extraction: extract pixel coordinates of the cable contour to obtain a discrete point set along the edge of the cable, denoted as (x i ,y i ), where x i and i Respectively represent the horizontal and vertical coordinates of the edge points of the cable in the image, thus obtaining a series of edge point coordinate lists: (x1, y1), (x2, y2), ..., (x n ,y n ), the above edge points will be used to fit the catenary curve;

[0062] The shape of the cable connected to the power transmission equipment is usually approximately a catenary under the action of gravity. The standard equation of the catenary is:

[0063]

[0064] Among them, a is the catenary parameter, which represents the tension characteristics of the cable; b is the vertical displacement term, which translates the catenary curve along the y-axis to make it consistent with the actual cable position.

[0065] In order to make the fitted catenary curve closest to the actual shape of the cable, an error function is defined to minimize the distance between the edge point and the catenary:

[0066]

[0067] Where error represents the error function, and n is the total number of cable edge points;

[0068] The process of minimizing the error function will find the best values ​​of parameters a and b so that the catenary curve fits the collected edge points as closely as possible.

[0069] In the specific calculation, the curve fitting function is used to minimize the error function and automatically find the appropriate a and b values. In the process of curve fitting, the a and b values ​​are continuously adjusted until the error is minimized, thereby obtaining the most accurate a and b values;

[0070] In the standard catenary equation:

[0071] The horizontal coordinate of the lowest point is x=0:

[0072] At the catenary's axis of symmetry (usually at the center of the image), the curve reaches its lowest point.

[0073] So the x-coordinate of the lowest point of the catenary is 0.

[0074] The y coordinate of the lowest point min :

[0075] When x = 0, substituting into the catenary equation we get:

[0076] y min =acosh(0)+b=a+b;

[0077] where a and b are the parameters obtained by fitting. Therefore, the coordinate of the lowest point is y min =a+b.

[0078] S3. The coordinates of the two endpoints in the cable image are (x1, y1) and (x n ,y n ), then calculate the midpoint height of the suspension point:

[0079]

[0080] The sag is defined as the vertical distance from the midpoint of the suspension point line to the lowest point, then:

[0081]

[0082] Where, S is the sag;

[0083] Here min=a+b is the ordinate of the lowest point of the catenary, thereby obtaining the sag S of the cable.

[0084] The feature fusion unit obtains real-time operation data and real-time inspection data of the power transmission equipment, and establishes a real-time distribution P of each feature through the real-time operation data and inspection data;

[0085] The calculation formula of deviation is:

[0086] DVE Feature,i =D KL (P Feature,i ‖Q Feature,i );

[0087] Where DVE Feature,i The deviation of a feature (such as voltage, current, etc.) from the i-th standard device feature of the feature at the i-th observation is calculated by calculating two probability distributions P Feature,i and Q Feature,i The KL divergence (Kullback-Leibler Divergence, DKL) between them is obtained.

[0088] D KL (P Feature,i ‖Q Feature,i ) is the Kullback-Leibler divergence of a feature (such as voltage or current) at the i-th observation with the reference state of the feature. The calculation formula of KL divergence is:

[0089]

[0090] In the formula, P i (x) represents the probability distribution of the i-th feature under the actual observation state, Q i (x) represents the probability distribution of the i-th feature in the baseline or normal state.

[0091] P Feature,i It is the probability distribution of a certain feature (such as voltage, current, etc.) under the actual observation state at the i-th observation. Its value is the distribution calculated based on real-time or inspection data, and is used to describe the performance of the i-th feature in the current or real-time state of the device. Feature,i It is the baseline probability distribution of a certain feature (such as voltage and current) at the i-th observation, representing the ideal probability distribution of the feature under normal or healthy conditions. Its value is usually obtained based on historical data statistics.

[0092] In this embodiment, the reference probability distribution is determined according to the following steps:

[0093] S11. Collect historical data:

[0094] Define the health status: When the equipment is operating normally and without faults, collect long-term historical data and record the values ​​of target equipment characteristics (such as infrared temperature, current, voltage, etc.). The collection period can be weeks, months, or even years to ensure that the data is sufficiently stable and comprehensive.

[0095] S12. Determine the interval distribution of target device characteristics:

[0096] Each target device feature of the device is divided into multiple intervals (eg, infrared temperature intervals, current intervals, etc.) so as to calculate the occurrence frequency of each interval.

[0097] The interval division can be determined according to the value range of specific features, data distribution or application requirements:

[0098] Equal width interval: Divide the range of characteristic values ​​evenly into several intervals, for example, infrared temperature is divided into 50~55℃, 55~60℃, etc.

[0099] Equal frequency intervals: Make each interval contain a similar number of sample points, for example, divide more intervals in the range where the eigenvalues ​​are dense.

[0100] Custom intervals: Determine the range of each interval based on empirical knowledge (for example, infrared temperature is divided into "below 50°C", "50-60°C", "above 70°C", etc.).

[0101] S13. Calculate the probability of each interval:

[0102] Count the frequency of data in each interval and use the frequency value as the probability of the interval. Taking infrared temperature characteristics as an example, assume that the infrared temperature is divided into a intervals B1, B2,…, B i ,…,B a , the infrared temperature in each interval B in the statistical historical data i The frequency of occurrence is recorded as N(B i ), that is, the temperature falls within interval B i The number of data points.

[0103] Total number of samples: Count the total number of data points, recorded as N, which is the sum of the frequencies of all intervals:

[0104]

[0105] In the formula, a is the number of divided intervals;

[0106] Therefore, the reference distribution Q of infrared temperature in each interval IT (B i )for:

[0107]

[0108] For example, for the infrared temperature signature:

[0109] Assume that the system divides the infrared temperature into four intervals, namely 50-55°C, 55-60°C, 60-65°C, and 65-70°C.

[0110] In the historical data of the device, the infrared temperature of 50-55°C appeared 20 times, 55-60°C appeared 50 times, 60-65°C appeared 25 times, 65-70°C appeared 5 times, and the total data points were 100 times.

[0111] Therefore, the baseline distribution probability of infrared temperature characteristics is:

[0112] Probability of 50-55℃: Q IT (50~55℃)=20 / 100=0.2;

[0113] Probability of 55-60℃: Q IT (55~60℃)=50 / 100=0.5;

[0114] Probability of 60-65℃: Q IT (60~65℃)=25 / 100=0.25;

[0115] Probability of 65-70℃: Q IT (65~70℃)=5 / 100=0.05;

[0116] In this way, the reference probability distribution of infrared temperature features = {0.2, 0.5, 0.25, 0.05} is obtained.

[0117] Other features can be calculated in a similar way to the baseline probability distribution of infrared temperature features to obtain the baseline probability distribution Q of voltage. Voltage,i , the reference probability distribution of current Q Current,i , and the reference probability distribution Q of the sag of the cable connected to the transmission equipment Sag,i ;

[0118] Similarly, real-time operation data and inspection data are collected, and the probability distribution P of the voltage in the i-th interval in real time is obtained by using similar methods as above. Voltage,i , the probability distribution P of the current in the i-th interval in real time Current,i , the probability distribution P of the infrared temperature in the i-th interval in real time In,i , and the probability distribution P of the cable connected to the i-th interval power transmission equipment in real time Sag,i .

[0119] The data fusion unit obtains the reference probability distribution of voltage

[0120] Q Voltage,i = {q Voltage,1 ,q Voltage,2 ,…,q Voltage,n}, where q Voltage,n is the reference probability distribution of the last interval of voltage; the reference probability distribution of current is Q Current,i = {q Current,1 ,q Current,2 ,…,q Current,m}, where q Current,m is the benchmark probability distribution of the last interval of the current; the benchmark probability distribution of the infrared temperature feature

[0121] Q Voltag = = {q InfraredTemperature,1 ,q InfraredTemperature,2 ,…,q InfraredTemperature,k}, where q InfraredTemperature,k is the benchmark probability distribution of the last interval of the infrared temperature feature; the benchmark probability distribution Q of the sag of the cable connected to the power transmission equipment CableSag = {q Sag,1 ,q Sag,2 ,…,q Sag,l}, where q Sag,l is the reference probability distribution of the last interval of the sag; and the probability distribution P of the voltage in real time state Voltage ={p Voltage,1 ,p Voltage,2 ,…,p Voltage,n}, where p Voltage,n is the probability distribution of the last interval of voltage; the probability distribution of current in real time state P Current ={p Current,1 ,p Current,2 ,…,p Current,m}, where p Current,m is the probability distribution of the last interval of the current; the probability distribution of the infrared temperature in real time state P IT ={p IT,1 ,p IT,2 ,…,p IT,k}, where p IT,k is the probability distribution of the last interval of infrared temperature; and the probability distribution of the sag of the cable connected to the power transmission equipment in real time

[0122] P Sag ={p Sag,1 ,p Sag,2 ,…,p Sag,l}, where p Sag,l is the probability distribution of the last interval of the cable sag connected to the power transmission equipment; and the deviation of each key feature is calculated according to the following formula;

[0123] Specifically, for the voltage deviation DVE Voltage is the actual observed distribution of voltage P Voltage Relative to the benchmark distribution Q Voltage The KL divergence of is calculated according to the following formula:

[0124]

[0125] Where, p Vo l tage,i is the probability distribution P of the voltage in real time Voltage The probability value in the i-th interval, q Voltage,i The reference probability distribution of voltage Q Voltage The probability value in the i-th interval.

[0126] Similarly, the current deviation DVE Voltage , infrared temperature deviation DVE In , sag deviation DVE CableSag The calculation form of the above formula can be used for reference, so it will not be repeated here.

[0127] The data fusion unit obtains the current deviation DVE Current , infrared temperature deviation DVE In , sag deviation DVE CableSag , and calculate the voltage standard deviation NormDev according to the following formula Voltage , NormDev, the standardized deviation of current Current 、NormDev, the standardized deviation of infrared temperature IT , Standardized deviation of sag value NormDev Sag :

[0128] Specific:

[0129]

[0130] Where DVE Voltage is the voltage deviation, DVE Current is the current deviation, DVE IT is the infrared temperature deviation, DVE Sag is the sag deviation, μ Voltage is the average value of voltage deviation under normal conditions, μ Current is the average value of the current deviation under normal conditions, μ IT is the average value of infrared temperature deviation under normal conditions, μ Sag is the average value of the sag deviation under normal conditions, σ Vo l tage is the standard deviation of voltage deviation under normal conditions, σCurrent is the standard deviation of the current deviation under normal conditions, σ IT is the standard deviation of infrared temperature deviation under normal conditions, σ Sag is the standard deviation of the sag deviation under normal conditions;

[0131] Among them, the average value of voltage deviation on the normal state line μ Vo l tage and the standard deviation of voltage deviation under normal conditions σ Voltage Follow these steps:

[0132] 1) Under normal conditions, N voltage data points are collected, each of which represents the voltage deviation (DVE Voltage,j represents the voltage deviation of the jth observation).

[0133] In this embodiment, the voltage deviation sample {DVE Voltage,1 ,DVE Voltage,2 ,…,DVE Voltage,N}, then the average value of the voltage deviation from the normal state line μ Voltage Calculate according to the following formula:

[0134]

[0135] Where N is the number of samples of normal state deviation, DVE Voltage,j represents the voltage deviation of the jth observation;

[0136] 2) Standard deviation of voltage deviation under normal conditions σ Voltage Calculate according to the following formula:

[0137]

[0138] Where N is the number of samples of normal state deviation, DVE Voltage,j represents the voltage deviation of the jth observation; μ Voltage is the average value of voltage deviation under normal conditions;

[0139] Similarly, for the average value μ of the current deviation under normal conditions Current , the average value of infrared temperature deviation under normal conditions μ IT , the average value of the sag deviation under normal conditions μ Sag , the standard deviation of the current deviation under normal conditions σ Current , the standard deviation of infrared temperature deviation under normal conditions σ IT , the standard deviation of the sag deviation under normal conditions σ Sag The average value μ of the voltage deviation in the normal state line can be used as a reference. Vol tage , and the standard deviation of voltage deviation under normal conditions σ Vo l tage The calculation formula is used for calculation, so in this embodiment, no further description is given;

[0140] On the basis of the above solution, specifically, the health index determination unit is specifically used to determine the device health index of the power transmission device according to the standardized deviation of the plurality of target device characteristics by the following formula:

[0141]

[0142] Among them, OHS represents the equipment health index of the transmission equipment, NormDev Voltage Indicates the standardized deviation of the voltage data of the power transmission equipment, NormDev Current Indicates the standardized deviation of the current data of the power transmission device, NormDev IT Indicates the standardized deviation of the infrared temperature abnormal data of the power transmission equipment, NormDev Sag represents the standardized deviation of the cable sag data of the power transmission equipment, and K represents the scaling factor.

[0143] An optional implementation has a set of standardized deviation data

[0144] {NormDev i,1 ,NormDev i,2 ,…,NormDev i,t}, perform moving average smoothing on the above standardized deviation data to obtain the smoothed data sequence:

[0145] Among them, the window size is used, that is, a moving average is calculated for every w data points, and the moving average at the tth time is calculated according to the following formula:

[0146]

[0147] Where t is the current time, NormDev i,j is the standardized deviation at the jth moment, indicating the standardized deviation value of feature i at the jth time point.

[0148] In the above formula, the window size w is the time span used to calculate the moving average, which means looking back at the data of w time points at the current time t. t-w+1 is the starting position of the window, ensuring that w data points are looked back from the current time t.

[0149] The summation range t-w+1 to t just includes the latest w data points, which is the core mechanism of moving average.

[0150] Assume t = 10, window size w = 3, then:

[0151] The time points covered by the window are: t-ω+1=10-3+1=8 to 10;

[0152] That is, the data points at time points 8, 9, and 10 are used to calculate the moving average at the 10th moment.

[0153] Next, the moving average smoothed sequence is used as data input and fitted using a linear regression model. The linear regression model formula is:

[0154] NormDev i (t) = β0 + β1@t;

[0155] Where, NormDev i (t) is the standardized deviation of feature i at time t, β0 is the intercept, indicating the initial deviation level; β1 is the slope, indicating the rate of change of deviation over time.

[0156] The smoothed standardized deviation data is matched with time t one by one, and the optimal regression coefficients β0 and β1 are calculated using the linear regression method. Specifically, the fitting process will find the optimal β0 and β1 by minimizing the residual sum of squares, and the formula is:

[0157]

[0158] Where T is the total number of time points used for linear regression fitting, that is, the length of the normalized deviation data sequence after smoothing. When moving average smoothing is performed, due to the existence of the window size w, the data of the initial w-1 time points cannot generate smooth values, so the length of the smoothed data sequence will be w-1 less than the original data.

[0159] Assuming that the length of the original data is N, the length of the smoothed sequence is: T = N-w+1.

[0160] The fitting optimization process can be implemented by standard regression tools or algorithms (such as the least squares method).

[0161] In addition, according to the fitting slope β1:

[0162] If β1>0, it means that the deviation tends to increase over time, which may indicate that the equipment status is deteriorating.

[0163] If β1<0, it means that the deviation tends to decrease over time, indicating that the equipment status tends to stabilize or improve.

[0164] If β1 = 0, there is no obvious change trend in the deviation, and the equipment state is relatively stable.

[0165] Using the fitted regression model, the standardized deviation value at future time points can be predicted. For example, the predicted value at time T+1 is:

[0166] NormDev i (T+1)=β0+β1·(T+1);

[0167] Substituting the optimal β0 and β1 found by the previous fitting into the above formula, we can get the prediction regression model at time T+1. The predicted value calculated by the prediction regression model can determine the future state change trend of the equipment.

[0168] By adopting this technical solution, the target equipment features, such as voltage, current, infrared temperature anomalies and cable sag data, are extracted from the real-time operation data and inspection data through the feature extraction unit. The feature fusion unit determines the standardized deviation of the target equipment features relative to the standard equipment features and transmits it to the health index determination unit. The health index determination unit calculates the equipment health index of the transmission equipment according to the standardized deviation. When the equipment health index is lower than the preset health index threshold, a prediction trigger signal is generated, and the activation status prediction unit determines the equipment operation status based on the historical equipment features, thereby realizing accurate assessment and early warning of the health status of the transmission equipment, ensuring that potential faults can be discovered and handled in a timely manner, and significantly improving the safety and reliability of the power system.

[0169] On the basis of the above scheme, optionally, the operation and maintenance guidance module includes an early warning mechanism unit; the early warning mechanism unit includes a data receiver, a threshold memory, a comparator and an alarm; wherein the data receiver is used to receive the equipment operation status sent by the equipment status detection module; the threshold memory is used to store the early warning status threshold; the comparator is used to compare the equipment operation status with the early warning status threshold, and when the equipment operation status is lower than the early warning status threshold, generate an early warning control signal corresponding to the equipment operation status; the alarm is used to generate alarm information according to the early warning control signal, and issue an early warning based on the alarm information.

[0170] Among them, the early warning mechanism unit can be understood as a component used to monitor the operating status of the equipment and issue an early warning when a potential problem is detected. The early warning status threshold can be understood as a pre-set critical value, which is used as a standard for judging whether the power transmission equipment is in a safe working condition. The early warning control signal can be understood as an indication signal generated by a comparator, which is used to indicate that the operating status of the equipment has reached a level that requires an early warning. The alarm information can include a description of the operating status of the equipment, such as at least one of an alarm type or an alarm level.

[0171] In an optional implementation manner, the content of the alarm information includes information type, abnormality level, difference between evaluation result and warning threshold, and corresponding alarm code.

[0172] The specific work flow of the early warning mechanism unit includes:

[0173] S21. Data reception: The data receiver receives the equipment operating status from the health status assessment module as input data for the early warning mechanism. The assessment result is usually a quantitative value such as the health index of the equipment or the deviation of key features, which is used to determine the current health status of the equipment.

[0174] S22. Threshold acquisition: The threshold memory stores the system preset warning threshold. The threshold can be set based on the historical data and expected performance standards of the device, indicating the range in which the evaluation result of the device should be under normal operation. After receiving the data, the threshold memory provides the threshold to the comparator for comparison with the evaluation result.

[0175] S23, state comparison: the comparator compares the operating state of the device with the preset warning threshold value provided by the threshold memory to determine whether the device is in a normal state.

[0176] Comparison logic:

[0177] When the equipment operating status is lower than the preset warning threshold, it is judged as abnormal health status.

[0178] When the equipment operating status is higher than or equal to the preset warning threshold, the equipment status is normal and no alarm is triggered.

[0179] S24, alarm trigger:

[0180] When the comparator determines that the health status of the device is abnormal, the alarm will generate and send an alarm message.

[0181] The alarm information includes the following parts:

[0182] Message type: Such as "Warning" or "Critical", indicating the urgency of the message.

[0183] Abnormality level: Abnormal conditions are graded (such as "low", "medium", "high") according to the degree of deviation from the threshold.

[0184] The difference between the evaluation result and the warning threshold: that is, the specific numerical value of the deviation, which is used to intuitively display the severity of the anomaly.

[0185] Alarm code: Set a unique code for each abnormal situation to facilitate system recording and subsequent tracking and processing.

[0186] S25, alarm notification:

[0187] Depending on the system configuration, the alarm can send alarm information to the management terminal, operator or related maintenance system to ensure that abnormal conditions receive timely attention and processing.

[0188] In this embodiment, in the content of the alarm information, the information type includes:

[0189] 1) “Warning”: Indicates that the device has a minor abnormality and requires attention.

[0190] 2) “Warning”: Indicates that the device has a moderate abnormality and needs to be checked as soon as possible.

[0191] 3) “Serious”: Indicates that there is a serious abnormality in the equipment, which may affect operation and requires immediate attention.

[0192] Exception levels include:

[0193] 1) “Low”: The assessment result deviates slightly from the threshold and the risk is low.

[0194] 2) “Medium”: There is a significant deviation in the assessment results and the risk is increased.

[0195] 3) “High”: The assessment results are seriously deviated from the threshold, the risk is high, and immediate repair may be required.

[0196] The alarm codes include:

[0197] 1) "AL01": Minor equipment abnormality (warning).

[0198] 2) "AL02": Moderate equipment abnormality (warning).

[0199] 3) "AL03": serious equipment abnormality (serious).

[0200] Each code represents a different exception level, which is convenient for subsequent query and recording.

[0201] Among them, Figure 3 The alarm information shown indicates that the current evaluation result of the device is lower than the set threshold of 0.15, which is a medium abnormality and needs to be checked and processed as soon as possible.

[0202] By adopting this technical solution, the equipment operating status is obtained through the data receiver, and the comparator compares it with the warning status threshold in the threshold memory. When the equipment operating status is lower than the warning status threshold, a warning control signal is generated to trigger the alarm to send out an alarm message, thereby ensuring early detection and rapid response to potential faults, improving the safety and reliability of the equipment, reducing downtime and maintenance costs caused by equipment failures, and optimizing operation and maintenance efficiency.

[0203] On the basis of the above scheme, optionally, the operation and maintenance guidance module includes a decision support unit; the decision support unit includes a rule engine, a data caller and a priority trigger; wherein the rule engine is used to store operation and maintenance guidance data corresponding to multiple fault types; the data caller is used to obtain the equipment operation status and the alarm information of the power transmission equipment; wherein the alarm information at least includes an alarm level; the priority trigger is used to determine the fault type of the power transmission equipment according to the equipment operation status of the power transmission equipment, determine the operation and maintenance guidance data corresponding to the power transmission equipment according to the fault type and the alarm information, and send the operation and maintenance guidance data to the target terminal.

[0204] The fault types may be understood as different types of problems or abnormal conditions occurring in the power transmission equipment.

[0205] Based on the above solution, optionally, the priority trigger includes a data query subunit and a data sorting subunit; wherein,

[0206] The data query subunit is used to determine the fault type of the power transmission equipment according to the equipment operation state of the power transmission equipment, and obtain operation and maintenance guidance data corresponding to the fault type from the rule engine;

[0207] The data sorting subunit is used to sort the sub-data in the multiple operation and maintenance guidance data according to the alarm level and the standardized deviation of multiple target device characteristics relative to the standard device characteristics, and send the sorted operation and maintenance guidance data to the target terminal.

[0208] The sub-data may be understood as a part of the operation and maintenance guidance data, and may be a detailed content of the specific maintenance suggestions and operation guides for a specific fault type. The target terminal may be understood as a user interface or device that receives and displays the operation and maintenance guidance data.

[0209] In an optional implementation, if the standardized deviation is small, the mild abnormality rule is called; if the alarm level is "serious", the emergency processing rule is called.

[0210] The guiding rules in the rule engine are set by the system or the administrator according to the actual situation, which is well known to those skilled in the art, and thus will not be described in detail in this embodiment;

[0211] Assume that the real-time evaluation results and alarm information of the current equipment are:

[0212] Evaluation results:

[0213] Current normalization deviation: 0.5;

[0214] Infrared temperature normalized deviation: 1.2 (higher);

[0215] Sag standard deviation: 0.7;

[0216] Alarm information:

[0217] Message type: severe;

[0218] Abnormality level: high;

[0219] Difference: infrared temperature deviates from the threshold value by 1.2;

[0220] Alarm code: AL03;

[0221] The specific workflow triggered is as follows:

[0222] The data caller obtains the standardized deviation data of each feature from the health status assessment module and obtains the alarm information from the early warning mechanism unit.

[0223] The rule engine recognizes that the current alarm code is "AL03", which corresponds to a severe alarm of overtemperature, and calls the emergency processing rules for abnormal temperature.

[0224] The priority trigger places the temperature check strategy at the highest priority based on the alarm level being "high" and the infrared temperature deviation being 1.2 (high).

[0225] The output guidance strategy is as follows:

[0226] First priority: infrared temperature check, focusing on abnormal temperature areas to ensure there is no overheating.

[0227] Second priority: sag detection to eliminate abnormal sag caused by high temperature of the cable.

[0228] Third priority: Current load monitoring to ensure that the load level is within the normal range.

[0229] On the basis of the above scheme, optionally, the data sorting sub-unit is specifically used to determine the sub-data corresponding to each of the target device characteristics from the operation and maintenance guidance data corresponding to the fault type according to the alarm level, sort the sub-data corresponding to the multiple target device characteristics in order from high to low according to the standardized deviation of the multiple target device characteristics relative to the standard device characteristics, and send the sorted operation and maintenance guidance data to the target terminal.

[0230] With this technical solution, the rule engine is used to store operation and maintenance guidance data corresponding to various fault types. The data caller obtains the equipment operating status and alarm information in real time. The data query subunit in the priority trigger determines the fault type according to the equipment operating status and obtains the corresponding operation and maintenance guidance data from the rule engine. The data sorting subunit sorts the sub-data in the operation and maintenance guidance data according to the alarm level and the standardized deviation of the target equipment characteristics to ensure that high-priority tasks are processed first. Finally, the sorted operation and maintenance guidance data is sent to the target terminal, providing the target object with accurate and orderly operation guidelines, significantly improving the response speed and maintenance efficiency, reducing the fault handling time, and enhancing the safety and reliability of the power system.

[0231] On the basis of the above scheme, optionally, the real-time evaluation and operation and maintenance guidance system for the health status of power transmission equipment further includes: an interaction module; wherein the operation and maintenance guidance module is also used to send the operation and maintenance guidance data to the interaction module; the interaction module is used to generate target interaction information according to the operation and maintenance guidance data, and send the target interaction information to the target terminal so that the target terminal displays the target interaction information.

[0232] The target interaction information can be understood as specific information content generated by the interaction module based on the operation and maintenance guidance data. The target interaction information can be in the form of a graphical interface, table or flowchart to intuitively display at least one of the fault type, alarm level and recommended operation steps.

[0233] On the basis of the above scheme, the operation and maintenance guidance module further includes: an intelligent scheduling unit, a task evaluation unit and a rescue unit, wherein the intelligent scheduling unit schedules the target object according to the alarm information, the task evaluation unit collects maintenance time-consuming data of the target object, and evaluates the task according to the time-consuming data and the early warning information of the operation and maintenance guidance module to form an evaluation result, and the rescue unit sends a rescue instruction to the control center according to the evaluation result to trigger the control center to control the intelligent scheduling unit to schedule the target object according to the rescue instruction; wherein the target object includes maintenance personnel; wherein the control center is set to the transmission line monitoring main control room;

[0234] The intelligent scheduling unit obtains the alarm information and calculates the number of scheduled maintenance personnel PER according to the following formula:

[0235]

[0236] Where S is the severity of the task, which is set based on the abnormality level and ranges from 1 to 3 (corresponding to "low", "medium" and "high"); I is the information type coefficient, which is set according to the information type in the alarm information, and its value is 1 (warning), 1.5 (warning), 2 (severe); A is the alarm code coefficient, which is set according to the alarm code type, and its value is 1.0 (AL01 warning), 1.2 (AL02 warning), 1.5 (AL03 severe); E is the empirical coefficient, [] is the rounding down symbol, and ensures that at least one worker is dispatched;

[0237] Among them, the empirical coefficient E is calculated according to the following formula:

[0238]

[0239] In the formula, Y is the number of years the worker has worked in the field, Skill is the skill level, and C is the task completion rate, which is equal to the ratio of the number of successfully completed tasks to the total number of tasks;

[0240] Skill level is calculated according to the following formula:

[0241]

[0242] In the formula, C is the task completion rate, and YC is the working years score;

[0243] Among them, YC is the specific setting of the working years score:

[0244] 0-1 years: 1 point;

[0245] 2-3 years: 2 points;

[0246] 4-6 years: 3 points;

[0247] 7-10 years: 4 points;

[0248] More than 10 years: Score 5 points.

[0249] The task evaluation unit includes a time consumption timer and a data evaluator, wherein the time consumption timer is used to record the maintenance time consumption data of the dispatched maintenance worker, and the data evaluator evaluates the maintenance task of the maintenance worker according to the time consumption data and the warning information to form an evaluation result;

[0250] The time-consuming timer records the task start time when the task starts, and records the task end time when the task is completed.

[0251] The data evaluator obtains the time-consuming data and warning information and calculates the evaluation index Score according to the following formula:

[0252]

[0253] Where S is the severity of the task, which is set based on the abnormality level and ranges from 1 to 3 (corresponding to "low", "medium" and "high"); I is the information type coefficient, which is set according to the information type in the alarm information and takes values ​​of 1 (warning), 1.5 (warning) and 2 (severe); A is the alarm code coefficient, which is set according to the alarm code type and takes values ​​of 1.0 (AL01 warning), 1.2 (AL02 warning) and 1.5 (AL03 severe); T actual is the actual time consumed, which indicates the actual time consumed by the maintenance worker to complete the task, T standard The standard time consumption indicates the reasonable completion time set according to the task type and complexity. The value is set by the system. For example, inspection tasks (such as basic inspection of equipment status or data recording): the standard time consumption is set to 20 to 30 minutes.

[0254] Medium maintenance tasks (such as replacing parts or performing routine maintenance): The standard time is set at 60 to 90 minutes.

[0255] Complex maintenance tasks (such as disassembly and assembly of multiple components or repair of major faults): The standard time is set at 120 to 180 minutes.

[0256] If the evaluation index Score is lower than the evaluation threshold Monitor set by the system, the assistance unit is triggered to send an assistance command to the control center.

[0257] If the evaluation index Score exceeds the evaluation threshold Monitor set by the system, it means that the dispatched maintenance worker is competent for the maintenance task;

[0258] Among them, the evaluation threshold Monitor set by the system is set by the system or administrator according to actual conditions and input from the human-computer interaction interface. This is a technical means well known to technicians in this field. Technicians in this field can refer to relevant technical manuals to learn about the technology, so it will not be described one by one in this embodiment.

[0259] The rescue unit includes a flat key monitor, a rescue determiner, an instruction generator and a communication interface. The evaluation monitor is used to continuously monitor the evaluation index Score of the task and compare it with the evaluation threshold Monitor set by the system to determine whether it is necessary to trigger rescue; the rescue determiner determines whether the rescue conditions are met based on the real-time evaluation results provided by the evaluation monitor. If the conditions are met, a rescue instruction is generated and passed to the instruction generator; the instruction generator generates a specific rescue instruction based on the judgment of the rescue determiner; the communication interface transmits the generated rescue instruction to the control center to ensure that the control center can receive the rescue information in real time and start the scheduling process.

[0260] The request for assistance includes key information such as the task information, the number of workers required, and the required skill level;

[0261] In addition, after the control center responds to the rescue instruction, it triggers the intelligent scheduling unit to dispatch a corresponding number of maintenance workers. In this embodiment, the number of people dispatched is the same as the number of people dispatched last time.

[0262] By adopting this technical solution, the interactive module receives the operation and maintenance guidance data sent by the operation and maintenance guidance module, generates intuitive target interaction information, and sends it to the target terminal for display, so that the target object can understand the equipment status and maintenance suggestions, improving the convenience of operation and response speed.

[0263] The technical solution of the embodiment of the present invention is as follows: first, the inspection data of the power transmission equipment is collected by the unmanned aerial vehicle according to the preset inspection route, and the inspection data is sent to the equipment data collection module, so that the power transmission equipment can be automatically inspected, the data can be efficiently collected and transmitted in real time; then, the real-time operation data of the power transmission equipment and the equipment inspection data collected by the unmanned aerial vehicle are obtained through the equipment data collection module, and the real-time operation data and the equipment inspection data are received, and the real-time operation data and the equipment inspection data are pre-processed, and the pre-processed real-time operation data and the equipment inspection data are sent to the equipment status detection module, which can ensure the comprehensiveness and accuracy of the data; then, the real-time operation data and the equipment inspection data sent by the equipment data collection module are received through the equipment status detection module, and the equipment operation status of the power transmission equipment is determined according to the real-time operation data and the equipment inspection data, and the equipment operation status is sent to the operation and maintenance guidance module. The equipment operation status is used to characterize the safety level of the power transmission equipment during operation. It can analyze real-time operation data and equipment inspection data, evaluate the equipment operation status and safety level of the power transmission equipment, and send them to the operation and maintenance guidance module to ensure rapid response to potential faults; finally, through the operation and maintenance guidance module, the equipment operation status sent by the equipment status detection module is received, and alarm information is generated according to the equipment operation status and the early warning status threshold. The operation and maintenance guidance data corresponding to the power transmission equipment is determined based on the equipment operation status and the alarm information, and the operation and maintenance guidance data is recorded. Potential faults or abnormal conditions can be discovered and located in time to ensure rapid response, which solves the problems of untimely detection of power transmission equipment and delayed fault warning in related technologies, improves inspection efficiency and accuracy, reduces labor costs and risks, and can quickly identify potential faults and generate early warning information to ensure timely maintenance measures, thereby improving the efficiency and accuracy of power transmission equipment management.

[0264] Embodiment 2

[0265] Figure 2This is a flowchart of a method for real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance provided in the second embodiment of the present invention. The method can be applied to a real-time evaluation of the health status of power transmission equipment and an operation and maintenance guidance system. The method can be implemented by an electronic device, which can be a mobile terminal, a PC, or a server, etc.

[0266] like Figure 2 As shown, the method may specifically include:

[0267] S210, collecting inspection data of power transmission equipment according to a preset inspection route through a drone, and sending the inspection data to an equipment data collection module;

[0268] S220, obtaining the real-time operation data of the power transmission equipment and receiving the equipment inspection data collected by the drone through the equipment data acquisition module, preprocessing the real-time operation data and the equipment inspection data, and sending the preprocessed real-time operation data and the equipment inspection data to the equipment status detection module;

[0269] S230, receiving the real-time operation data and the equipment inspection data sent by the equipment data acquisition module through the equipment status detection module, and determining the equipment operation status of the power transmission equipment according to the real-time operation data and the equipment inspection data, and sending the equipment operation status to the operation and maintenance guidance module; wherein the equipment operation status is used to characterize the safety level of the power transmission equipment during operation;

[0270] S240. Receive, through the operation and maintenance guidance module, the device operating status sent by the device status detection module, generate alarm information according to the device operating status and the early warning status threshold, determine the operation and maintenance guidance data corresponding to the power transmission equipment based on the device operating status and the alarm information, and record the operation and maintenance guidance data.

[0271] On the basis of the above scheme, optionally, in step S220, real-time operation data of the power transmission equipment is collected through a sensor unit; wherein the sensor unit includes a plurality of sensors distributedly arranged on the power transmission equipment, and the sensors include at least one of a temperature sensor, a pressure sensor, an odor sensor, an acceleration sensor and a photoelectric sensor; through a data preprocessing unit, the equipment inspection data collected by the drone is received, and the real-time operation data and the equipment inspection data are preprocessed, and the preprocessed real-time operation data and the equipment inspection data are transmitted to the equipment status detection module through the data transmission unit.

[0272] On the basis of the above scheme, optionally, in step S230, a feature extraction unit is used to extract features of the real-time operation data and the equipment inspection data respectively to obtain multiple target equipment features of the power transmission equipment; wherein the target equipment features include voltage data, current data, infrared temperature anomaly data and cable sag data; a feature fusion unit is used to receive multiple target equipment features, determine the standardized deviations of the multiple target equipment features relative to the standard equipment features, and transmit the standardized deviations to the health index determination unit; a health index determination unit is used to receive the standardized deviations of the multiple target equipment features, determine the equipment health index of the power transmission equipment according to the standardized deviations of the multiple target equipment features, and generate a prediction trigger signal when the equipment health index is less than a preset health index threshold, and send the prediction trigger signal to the state prediction unit; a state prediction unit is used to receive the prediction trigger signal, and in response to the prediction trigger signal, determine the equipment operation state of the power transmission equipment according to the historical equipment features of the power transmission equipment.

[0273] On the basis of the above solution, optionally, the device health index of the power transmission device is determined according to the standardized deviation of the plurality of target device characteristics by the following formula:

[0274]

[0275] Among them, OHS represents the equipment health index of the transmission equipment, NormDev Voltage Indicates the standardized deviation of the voltage data of the power transmission equipment, NormDev Current Indicates the standardized deviation of the current data of the power transmission device, NormDev IT Indicates the standardized deviation of the infrared temperature abnormal data of the power transmission equipment, NormDev Sag represents the standardized deviation of the cable sag data of the power transmission equipment, and K represents the scaling factor.

[0276] On the basis of the above scheme, optionally, the operation and maintenance guidance module receives the equipment operating status sent by the equipment status detection module, and generates alarm information according to the equipment operating status and the early warning status threshold. The specific steps include: receiving the equipment operating status sent by the equipment status detection module through a data receiver; storing the early warning status threshold through a threshold memory; comparing the equipment operating status with the early warning status threshold through a comparator, and generating an early warning control signal corresponding to the equipment operating status when the equipment operating status is lower than the early warning status threshold; generating alarm information according to the early warning control signal through an alarm, and issuing an early warning based on the alarm information.

[0277] On the basis of the above scheme, optionally, operation and maintenance guidance data corresponding to the power transmission equipment is determined based on the equipment operating status and the alarm information, and the operation and maintenance guidance data is recorded. The specific steps include: storing operation and maintenance guidance data corresponding to multiple fault types through the rule engine; obtaining the equipment operating status and the alarm information of the power transmission equipment through the data caller; wherein the alarm information at least includes an alarm level; determining the fault type of the power transmission equipment according to the equipment operating status of the power transmission equipment through the priority trigger, determining the operation and maintenance guidance data corresponding to the power transmission equipment according to the fault type and the alarm information, and sending the operation and maintenance guidance data to the target terminal.

[0278] On the basis of the above scheme, optionally, through the priority trigger, the fault type of the power transmission equipment is determined according to the equipment operating status of the power transmission equipment, the operation and maintenance guidance data corresponding to the power transmission equipment is determined according to the fault type and the alarm information, and the operation and maintenance guidance data is sent to the target terminal. The specific steps include: through the data query subunit, the fault type of the power transmission equipment is determined according to the equipment operating status of the power transmission equipment, and the operation and maintenance guidance data corresponding to the fault type is obtained from the rule engine; through the data sorting subunit, the sub-data in the multiple operation and maintenance guidance data are sorted according to the alarm level and the standardized deviation of multiple target equipment characteristics relative to the standard equipment characteristics, and the sorted operation and maintenance guidance data are sent to the target terminal.

[0279] On the basis of the above scheme, optionally, through the data sorting sub-unit, the sub-data in the multiple operation and maintenance guidance data are sorted according to the alarm level and the standardized deviation of the multiple target device characteristics relative to the standard device characteristics, and the sorted operation and maintenance guidance data are sent to the target terminal. The specific steps include: through the data sorting sub-unit, according to the alarm level, the sub-data corresponding to each of the target device characteristics are determined from the operation and maintenance guidance data corresponding to the fault type, and the sub-data corresponding to the multiple target device characteristics are sorted in order from high to low according to the standardized deviation of the multiple target device characteristics relative to the standard device characteristics, and the sorted operation and maintenance guidance data are sent to the target terminal.

[0280] On the basis of the above scheme, optionally, the method for real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance further includes: sending the operation and maintenance guidance data to the interaction module through the operation and maintenance guidance module; generating target interaction information according to the operation and maintenance guidance data through the interaction module, and sending the target interaction information to the target terminal so that the target terminal displays the target interaction information.

[0281] The method for real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance provided by the embodiment of the present invention can be executed by the system for real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution system.

[0282] Embodiment 3

[0283] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0284] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0285] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0286] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a real-time evaluation and operation and maintenance guidance method for the health status of a power transmission device.

[0287] In some embodiments, a method for real-time evaluation of the health status of a power transmission device and operation and maintenance guidance may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for real-time evaluation of the health status of a power transmission device and operation and maintenance guidance described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute a method for real-time evaluation of the health status of a power transmission device and operation and maintenance guidance by any other appropriate means (e.g., by means of firmware).

[0288] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0289] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0290] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0291] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0292] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0293] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0294] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0295] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A real-time evaluation and operation and maintenance guidance system for the health status of power transmission equipment, characterized in that: include: UAV, equipment data collection module, equipment status detection module and operation and maintenance guidance module; among them, The drone is used to collect inspection data of the power transmission equipment according to a preset inspection route, and send the inspection data to the equipment data acquisition module; The equipment data acquisition module is used to obtain the real-time operation data of the power transmission equipment and receive the equipment inspection data collected by the drone, and pre-process the real-time operation data and the equipment inspection data, and send the pre-processed real-time operation data and the equipment inspection data to the equipment status detection module; The equipment status detection module is used to receive the real-time operation data and the equipment inspection data sent by the equipment data acquisition module, and determine the equipment operation status of the power transmission equipment according to the real-time operation data and the equipment inspection data, and send the equipment operation status to the operation and maintenance guidance module; wherein the equipment operation status is used to characterize the safety level of the power transmission equipment during operation; The operation and maintenance guidance module is used to receive the equipment operating status sent by the equipment status detection module, generate alarm information according to the equipment operating status and the early warning status threshold, generate operation and maintenance guidance data corresponding to the power transmission equipment based on the equipment operating status and the alarm information, and record the operation and maintenance guidance data.

2. The real-time evaluation and operation and maintenance guidance system for the health status of power transmission equipment according to claim 1 is characterized in that: The equipment data acquisition module includes a sensor unit, a data preprocessing unit and a data transmission unit; wherein, The sensor unit includes a plurality of sensors distributed on the power transmission device, and is used to collect real-time operation data of the power transmission device; wherein the sensor includes at least one of a temperature sensor, a pressure sensor, an odor sensor, an acceleration sensor, and a photoelectric sensor; The data preprocessing unit is used to receive the equipment inspection data collected by the drone, preprocess the real-time operation data and the equipment inspection data, and transmit the preprocessed real-time operation data and the equipment inspection data to the equipment status detection module through the data transmission unit.

3. The real-time evaluation and operation and maintenance guidance system for the health status of power transmission equipment according to claim 1 is characterized in that: The device status detection module includes a feature extraction unit, a feature fusion unit, a health index determination unit and a status prediction unit; wherein, The feature extraction unit is used to extract features from the real-time operation data and the equipment inspection data respectively to obtain multiple target equipment features of the power transmission equipment; wherein the target equipment features include voltage data, current data, infrared temperature anomaly data and cable sag data; The feature fusion unit is used to receive the plurality of target device features, determine the standardized deviations of the plurality of target device features relative to the standard device features, and transmit the standardized deviations to the health index determination unit; The health index determination unit is used to receive the standardized deviations of the plurality of target device features, determine the device health index of the power transmission device according to the standardized deviations of the plurality of target device features, generate a prediction trigger signal when the device health index is less than a preset health index threshold, and send the prediction trigger signal to the state prediction unit; The state prediction unit is used to receive the prediction trigger signal, and in response to the prediction trigger signal, determine the device operating state of the power transmission device according to the historical device characteristics of the power transmission device.

4. The real-time evaluation and operation and maintenance guidance system for the health status of power transmission equipment according to claim 3 is characterized in that: The health index determination unit is specifically configured to determine the device health index of the power transmission device according to the standardized deviations of the plurality of target device characteristics by using the following formula: Among them, OHS represents the equipment health index of the transmission equipment, NormDev Voltage Indicates the standardized deviation of the voltage data of the power transmission equipment, NormDev Current Indicates the standardized deviation of the current data of the power transmission device, NormDev IT Indicates the standardized deviation of the infrared temperature abnormal data of the power transmission equipment, NormDev Sag represents the standardized deviation of the cable sag data of the power transmission equipment, and K represents the scaling factor.

5. The real-time evaluation and operation and maintenance guidance system for the health status of power transmission equipment according to claim 1 is characterized in that: The operation and maintenance guidance module includes an early warning mechanism unit; the early warning mechanism unit includes a data receiver, a threshold memory, a comparator and an alarm; wherein, The data receiver is used to receive the device operation status sent by the device status detection module; The threshold memory is used to store the warning state threshold; The comparator is used to compare the device operation state with the warning state threshold, and generate a warning control signal corresponding to the device operation state when the device operation state is lower than the warning state threshold; The alarm is used to generate alarm information according to the early warning control signal and to issue an early warning based on the alarm information.

6. The real-time evaluation and operation and maintenance guidance system for the health status of power transmission equipment according to claim 1 is characterized in that: The operation and maintenance guidance module includes a decision support unit; the decision support unit includes a rule engine, a data caller and a priority trigger; wherein, The rule engine is used to store operation and maintenance guidance data corresponding to various fault types; The data caller is used to obtain the device operating status and the alarm information of the power transmission device; wherein the alarm information at least includes an alarm level; The priority trigger is used to determine the fault type of the power transmission equipment according to the equipment operating status of the power transmission equipment, determine the operation and maintenance guidance data corresponding to the power transmission equipment according to the fault type and the alarm information, and send the operation and maintenance guidance data to the target terminal.

7. The real-time evaluation and operation and maintenance guidance system for the health status of power transmission equipment according to claim 6 is characterized in that: The priority trigger includes a data query subunit and a data sorting subunit; wherein, The data query subunit is used to determine the fault type of the power transmission equipment according to the equipment operation state of the power transmission equipment, and obtain operation and maintenance guidance data corresponding to the fault type from the rule engine; The data sorting subunit is used to sort the sub-data in the multiple operation and maintenance guidance data according to the alarm level and the standardized deviation of multiple target device characteristics relative to the standard device characteristics, and send the sorted operation and maintenance guidance data to the target terminal.

8. The real-time evaluation and operation and maintenance guidance system for the health status of power transmission equipment according to claim 7 is characterized in that: The data sorting subunit is specifically used to determine the sub-data corresponding to each target device feature from the operation and maintenance guidance data corresponding to the fault type according to the alarm level, sort the sub-data corresponding to the multiple target device features in order from high to low according to the standardized deviation of the multiple target device features relative to the standard device features, and send the sorted operation and maintenance guidance data to the target terminal.

9. The real-time evaluation and operation and maintenance guidance system for the health status of power transmission equipment according to claim 1 is characterized in that: Also includes: Interaction module; The operation and maintenance guidance module is further used to send the operation and maintenance guidance data to the interaction module; The interaction module is used to generate target interaction information according to the operation and maintenance guidance data, and send the target interaction information to the target terminal so that the target terminal displays the target interaction information.

10. A method for real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance, applied to the real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance system as claimed in claims 1-9, wherein: The method for real-time evaluation of the health status of power transmission equipment and operation and maintenance guidance includes: By using drones, the inspection data of the power transmission equipment is collected according to a preset inspection route, and the inspection data is sent to the equipment data collection module; The real-time operation data of the power transmission equipment and the equipment inspection data collected by the UAV are obtained through the equipment data acquisition module, and the real-time operation data and the equipment inspection data are preprocessed, and the preprocessed real-time operation data and the equipment inspection data are sent to the equipment status detection module; The real-time operation data and the equipment inspection data sent by the equipment data acquisition module are received through the equipment status detection module, and the equipment operation status of the power transmission equipment is determined according to the real-time operation data and the equipment inspection data, and the equipment operation status is sent to the operation and maintenance guidance module; wherein the equipment operation status is used to characterize the safety level of the power transmission equipment during operation; The operation and maintenance guidance module receives the equipment operation status sent by the equipment status detection module, generates alarm information according to the equipment operation status and the early warning status threshold, determines the operation and maintenance guidance data corresponding to the power transmission equipment based on the equipment operation status and the alarm information, and records the operation and maintenance guidance data.

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