Safety management and control method and system for electric power operation and maintenance operation

Abstract

The invention provides a safety management and control method and system for electric power operation inspection operation, and relates to the technical field of electric power and safety. According to the specific implementation scheme, on the basis of fusion data obtained by fusing sensing data collected under the power operation and maintenance operation and risk scores of the fusion data, the safety state of the power operation and maintenance operation is determined; determining an adjustment strategy set for performing safety control on the electric power operation and maintenance operation based on the safety state of the electric power operation and maintenance operation; determining the decision cost of each adjustment strategy based on the decision execution time of each adjustment strategy in the adjustment strategy set, the risk score of the fusion data and the environmental dynamic influence factor; and based on the decision cost of each adjustment strategy, determining a target adjustment strategy for the power operation inspection operation in the adjustment strategy set. According to the invention, a corresponding adjustment strategy can be accurately provided for the electric power operation and maintenance operation, and the safety of the electric power operation and maintenance operation is improved.

Description

Technical Field

[0001] The present invention relates to the field of power and safety technology, and in particular to a safety management and control method and system for power operation and inspection. Background Art

[0002] Power operation and inspection is an important part of ensuring the stable operation of the power system. With the rapid development of the power industry, the scale and complexity of power operation and inspection operations are increasing, and ensuring safe and efficient operation has become a vital task. Traditional power operation and inspection safety management methods mainly rely on manual inspections, experience judgments, and simple monitoring tools, and face many severe challenges.

[0003] Therefore, it is necessary to rely on efficient safety management systems and supervision and guarantee mechanisms to conduct comprehensive risk analysis and reduce the probability of potential safety hazards. Especially in the operation of power grids, effective control of the operation and inspection system and equipment is particularly critical. It is necessary to strictly restrain the irregular behavior of operators, comprehensively protect the life safety of engineering personnel, and ensure the continuous and stable operation of the power grid. Summary of the invention

[0004] The present invention provides a safety management and control method, device, system and storage medium for power operation and inspection operations, which can solve at least one of the above technical problems.

[0005] According to one aspect of the present invention, a safety control method for electric power operation and inspection is provided, comprising: Determine the safety status of the power operation and inspection operation based on the fusion data obtained by fusing various sensor data collected during the power operation and inspection operation and the risk score of the fusion data; Based on the safety status of the power operation and inspection operation, determining an adjustment strategy set for safety management and control of the power operation and inspection operation; Determining the decision cost of each adjustment strategy based on the decision execution time of each adjustment strategy in the adjustment strategy set, the risk score of the fused data, and the environmental dynamic impact factor; Based on the decision costs of the respective adjustment strategies, a target adjustment strategy for the power operation and inspection task is determined in the adjustment strategy set.

[0006] According to another aspect of the present invention, there is provided a safety control device for electric power operation and inspection, comprising: A safety status assessment module, used to determine the safety status of the power operation and inspection operation based on fusion data obtained by fusing various sensor data collected during the power operation and inspection operation and a risk score of the fusion data; A strategy set determination module, used to determine an adjustment strategy set for safety management and control of the power operation and inspection operation based on the safety status of the power operation and inspection operation; A decision cost determination module, used to determine the decision cost of each adjustment strategy based on the decision execution time of each adjustment strategy in the adjustment strategy set, the risk score of the fusion data, and the environmental dynamic impact factor; The target strategy determination module is used to determine the target adjustment strategy for the power operation and inspection operation in the adjustment strategy set based on the decision costs of each of the adjustment strategies.

[0007] According to another aspect of the present invention, there is provided an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute any safety management and control method for power operation and inspection operations in the embodiments of the present invention.

[0008] According to another aspect of the present invention, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute any safety management and control method for power operation and inspection operations according to any embodiment of the present invention.

[0009] By adopting the technical solution of the present invention, the safety status of the power operation and inspection operation is determined based on the fusion data obtained by fusing various sensor data collected under the power operation and inspection operation, as well as the risk score of the fusion data. In this way, the safety status of the power operation and inspection operation can be accurately evaluated. Based on the safety status of the power operation and inspection operation, a set of adjustment strategies for safe management and control of the power operation and inspection operation is determined; based on the decision execution time of each adjustment strategy in the adjustment strategy set, the risk score of the fusion data, and the environmental dynamic influencing factor, the decision cost of each adjustment strategy is determined respectively; based on the decision cost of each adjustment strategy, the target adjustment strategy for the power operation and inspection operation is determined in the adjustment strategy set. In this way, corresponding adjustment strategies can be accurately proposed for the power operation and inspection operation to improve the safety of the power operation and inspection operation.

[0010] 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

[0011] The accompanying drawings are used to better understand the present invention and do not constitute a limitation of the present invention. Figure 1It is a flow chart of a safety control method for electric power operation and inspection operation according to an embodiment of the present invention; Figure 2 This is a structural block diagram of a safety control device for electric power operation and inspection according to an embodiment of the present invention; Figure 3 The block diagram is a block diagram of an electronic device for implementing the method according to the embodiment of the present invention. DETAILED DESCRIPTION

[0012] The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be appreciated by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present invention. Similarly, for clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0013] Figure 1 It is a flow chart of a safety control method for electric power operation and inspection operations according to an embodiment of the present invention.

[0014] like Figure 1 As shown, the safety control method for power operation and inspection may include: S110, determining the safety status of the power operation and inspection operation based on fused data obtained by fusing various sensor data collected during the power operation and inspection operation and risk scoring of the fused data; S120, determining an adjustment strategy set for safety management and control of the power operation and inspection operation based on the safety status of the power operation and inspection operation; S130, determining the decision cost of each adjustment strategy based on the decision execution time of each adjustment strategy in the adjustment strategy set, the risk score of the fusion data, and the environmental dynamic impact factor; S140, based on the decision costs of the various adjustment strategies, determining a target adjustment strategy for the power operation and inspection task in the adjustment strategy set.

[0015] For example, during power operation and inspection, different types of transmitters may be used for data collection, such as heart rate sensors, accelerometers, and gas detection transmitters, to detect information such as the health status and work behavior of operators.

[0016] For example, the vital signs monitoring module: including heart rate sensors and blood oxygen monitoring modules, used to collect vital signs data of workers. Behavior recognition module: integrated with accelerometers and gyroscopes, used to capture behavioral feature data. Environmental perception module: including gas detection sensors and electromagnetic field strength monitoring sensors, used to perceive risk factors in the working environment. Communication module: IoT gateway module based on NBIoT or LoRa technology, used for remote data transmission.

[0017] Exemplarily, the sensor data may include vital sign data (such as heart rate, blood oxygen saturation), behavioral acceleration characteristic data, ambient gas concentration, electromagnetic field strength, and other data collected at the current moment.

[0018] Exemplarily, each sensor data may be weighted averaged to obtain fused data.

[0019] For example, a risk assessment model may be used to perform risk assessment on the fused data to obtain a corresponding risk score.

[0020] Exemplarily, a predetermined comprehensive status assessment function may be used to calculate the fused data and the risk score of the fused data to obtain the safety status of the power operation and inspection work at the current moment.

[0021] For example, a pre-trained adjustment strategy generation model can be used to calculate the safety status of the power operation and inspection work at the current moment and the change trend of the safety status at the current moment relative to the safety status at the historical moment to obtain at least one adjustment strategy. Thus, the above-mentioned adjustment strategy set is obtained.

[0022] Exemplarily, the decision cost of the adjustment strategy may be determined by taking a weighted sum of the decision execution time of the adjustment strategy, the risk score of the fused data, and the environmental dynamic impact factor.

[0023] For example, the environmental dynamic impact factor can use current environmental parameters to determine the value of the environmental dynamic impact factor, such as the temperature, humidity, and air particle concentration of the current environment.

[0024] Exemplarily, based on the decision costs of the various adjustment strategies, an adjustment strategy with the lowest decision cost is selected from the adjustment strategy set as the target adjustment strategy.

[0025] According to the above implementation, the safety status of the power operation and inspection operation is determined based on the fusion data obtained by fusing the various sensor data collected under the power operation and inspection operation, as well as the risk score of the fusion data. In this way, the safety status of the power operation and inspection operation can be accurately evaluated. Based on the safety status of the power operation and inspection operation, a set of adjustment strategies for safe management and control of the power operation and inspection operation is determined; based on the decision execution time of each adjustment strategy in the adjustment strategy set, the risk score of the fusion data, and the environmental dynamic influencing factor, the decision cost of each adjustment strategy is determined respectively; based on the decision cost of each adjustment strategy, the target adjustment strategy for the power operation and inspection operation is determined in the adjustment strategy set. In this way, corresponding adjustment strategies can be accurately proposed for the power operation and inspection operation to improve the safety of the power operation and inspection operation.

[0026] In one implementation, based on the safety status of the power operation and inspection operation, determining an adjustment strategy set for safety management and control of the power operation and inspection operation includes: The security status and the changing trend of the security status relative to the historical security status are input into a pre-trained adjustment strategy generation model to obtain an adjustment strategy set output by the adjustment strategy generation model.

[0027] Exemplarily, the adjustment strategy generation model can be formulated as follows: ; ; in, Indicates the current security status. Indicates the security status at the last moment. Indicates the change trend of the current security status relative to the security status at the previous moment. represents the set of adjustment strategies output by the adjustment strategy generation model, Represents a pre-trained adjustment policy generation model.

[0028] According to the above implementation, an adjustment strategy set for the electric power operation and inspection work in the current safe state can be accurately generated.

[0029] In one embodiment, the above method may also include: determining the decision effect of the target adjustment strategy when performing safety management and control of power operation and maintenance operations based on the target adjustment strategy; and adjusting the model parameters of the adjustment strategy generation model based on the decision effect of the target adjustment strategy.

[0030] Exemplarily, while the power operation and inspection operations are safely managed based on the target adjustment strategy, data collection is performed for the power operation and inspection operations at the next moment, and the various sensor data collected at the next moment are fused to obtain the fused data at the next moment. Based on the fused data at the next moment and the risk score of the fused data, the decision effect of the target adjustment strategy can be obtained.

[0031] Exemplarily, the safety status of the target adjustment strategy before adjustment, the decision effect after adjustment, and the target adjustment strategy can be used to form a training sample, which is added to a training sample set. The training sample set is used to adjust the model parameters of the adjustment strategy generation model.

[0032] According to the above implementation, the model parameters of the adjustment strategy generation model can be adjusted in real time according to the feedback data of the decision effect of the adjustment strategy, so as to improve the accuracy of the adjustment strategy generation model.

[0033] In one embodiment, based on the decision effect of the target adjustment strategy, the model parameters of the adjustment strategy generation model are adjusted, including: The first formula is used to adjust the model parameters of the adjustment strategy generation model based on the decision effect of the target adjustment strategy; Among them, the first formula includes: ; ; in, represents the adjusted model parameters of the adjustment strategy generation model, represents the model parameters before adjustment of the adjustment strategy generation model, represents the learning rate, represents the objective function; in, represents the number of samples in the training set, represents the safety state corresponding to the i-th training sample, represents the decision effect corresponding to the i-th training sample, represents the decision cost of the adjustment strategy corresponding to the i-th training sample; Among them, a training sample is composed of the safety status of power operation and inspection, the target adjustment strategy and the decision effect of the target adjustment strategy.

[0034] Exemplarily, when the value of the objective function is less than a preset threshold, the adjustment of the model parameters of the adjustment strategy generation model may be stopped; otherwise, the adjustment of the model parameters of the adjustment strategy generation model continues.

[0035] According to the above implementation, the model parameters of the adjustment strategy generation model are continuously adjusted until the value of the objective function is less than a preset threshold, so that the accuracy of the adjustment strategy generation model can be improved.

[0036] In one embodiment, based on the decision execution time of each adjustment strategy in the adjustment strategy set, the risk score of the fused data, and the environmental dynamic impact factor, the decision cost of each adjustment strategy is determined separately, including: taking a weighted sum of the decision execution time of the adjustment strategy, the risk score of the fused data, and the environmental dynamic impact factor to obtain the decision cost of the adjustment strategy.

[0037] For example, the decision cost of adjusting the strategy can be calculated using the following formula: ; in, represents the decision cost of adjusting strategy D, represents the risk score of the fused data at the current moment, represents the environmental dynamic impact factor at the current moment, represents the execution time of adjustment strategy D, , and Represents the weight coefficient.

[0038] According to the above implementation, the decision cost of the adjustment strategy can be obtained by weighted summing the execution time of the adjustment strategy, the risk score of the fused data, and the environmental dynamic impact factor.

[0039] In one embodiment, the method further includes: determining the credibility of each sensor data based on the noise of each sensor data; and performing weighted summation on each sensor data based on the credibility of each sensor data to obtain fused data.

[0040] Exemplarily, the reliability of each type of sensor data is determined using the noise of each type of sensor data.

[0041] For example, the following formula may be used to calculate the credibility of each type of sensor data: ; in, represents the noise variance of the k-th sensor data at the current time t, Represents the credibility of the k-th type of sensor data at the current time t.

[0042] Exemplarily, based on the ratio between the credibility of each type of sensor data and the sum of the credibility of all types of sensor data, the weight of each type of sensor data is determined, and based on the weight of each type of sensor data, each sensor data is weightedly summed to obtain fused data.

[0043] Exemplarily, the weight of each type of sensor data is calculated using the following formula: ; in, represents the weight of the k-th type of sensor data at the current time t, Indicates the total number of sensor data types, Represents the weight of the j-th type of sensor data at the current time t.

[0044] For example, the fusion data may be calculated using the following formula: ; in, represents the fused data at the current time t, Represents the kth type of sensor data at the current time t.

[0045] According to the above implementation, the noise condition of the sensor data can be used to evaluate the credibility of the sensor data, and the credibility of the sensor data can be used to determine the weight coefficient of the sensor data. In this way, the fused data obtained by weighted summation of the sensor data has high credibility and can accurately reflect the original data situation.

[0046] In one embodiment, the above method may further include: scoring each risk factor based on the fused data to obtain a risk value of each risk factor; and performing weighted summation of the risk values ​​of each risk factor based on the weight of each risk factor to obtain a risk score of the fused data.

[0047] Exemplarily, each risk factor corresponds to a threshold center, the distance between the fused data and the threshold center is calculated, and then the risk value of the risk factor is determined by multiplying the distance by the adjustment parameter of the risk factor.

[0048] For example, the risk value of each risk factor may be calculated using the following formula: ; in, represents the risk value of the ith risk factor, represents the adjustment parameter of the ith risk factor, represents the threshold center of the ith risk factor.

[0049] For example, the risk score of the fused data may be calculated using the following formula: ; in, represents the risk score of the fused data at the current time t, represents the total number of risk factors, Represents the weight coefficient of the ith risk factor.

[0050] According to the above implementation, the risk score of the fused data at the current time t can be accurately evaluated.

[0051] In some embodiments, after the risk score of the fused data is calculated, it can be compared with a dynamic warning threshold. If the risk score is greater than the dynamic warning threshold, a warning signal is generated; if the risk score is less than the dynamic warning threshold, no warning signal is generated.

[0052] Alternatively, a numerical value may be used to represent the warning signal. For example, 1 may be used to represent that there is a warning signal at the current moment, and 0 may be used to represent that there is no warning information at the current moment.

[0053] Exemplarily, the dynamic warning threshold can be adjusted according to environmental factors. For example, the current environmental factors are scored to obtain a first value, which is multiplied by the environmental sensitivity coefficient and then added by one to obtain a second value. The second value is multiplied by the initial warning threshold to obtain the dynamic warning threshold.

[0054] In some embodiments, a corresponding warning response strategy may be generated based on the warning signal and the fused data.

[0055] According to the above implementation mode, a closed-loop safety management process is formed through continuous monitoring, dynamic decision-making and adaptive optimization to ensure maximum safety and efficiency of the entire operation process.

[0056] Figure 2 It is a structural block diagram of a safety control device for electric power operation and inspection operations according to an embodiment of the present invention.

[0057] like Figure 2 As shown, the safety control device for power operation and inspection may include: The safety status assessment module 210 is used to determine the safety status of the power operation and inspection operation based on the fusion data obtained by fusing various sensor data collected during the power operation and inspection operation and the risk score of the fusion data; A strategy set determination module 220, configured to determine an adjustment strategy set for safety management and control of the power operation and inspection operation based on the safety status of the power operation and inspection operation; A decision cost determination module 230, for determining the decision cost of each adjustment strategy in the adjustment strategy set based on the decision execution time of each adjustment strategy, the risk score of the fusion data, and the environmental dynamic impact factor; The target strategy determination module 240 is used to determine a target adjustment strategy for the power operation and inspection task in the adjustment strategy set based on the decision costs of each of the adjustment strategies.

[0058] In one implementation, the policy set determination module 220 is specifically configured to: The security status and the changing trend of the security status relative to the historical security status are input into a pre-trained adjustment strategy generation model to obtain the adjustment strategy set output by the adjustment strategy generation model.

[0059] In one embodiment, it further includes: A decision effect determination module, used to determine the decision effect of the target adjustment strategy when the power operation and inspection operation is safely controlled based on the target adjustment strategy; The model parameter adjustment module is used to adjust the model parameters of the adjustment strategy generation model based on the decision effect of the target adjustment strategy.

[0060] In one implementation, the model parameter adjustment module is specifically used to: Using the first formula, based on the decision effect of the target adjustment strategy, the model parameters of the adjustment strategy generation model are adjusted; Wherein, the first formula includes: ; ; in, represents the adjusted model parameters of the adjustment strategy generation model, represents the model parameters of the adjustment strategy generation model before adjustment, represents the learning rate, represents the objective function; in, represents the number of samples in the training set, represents the safety state corresponding to the i-th training sample, represents the decision effect corresponding to the i-th training sample, represents the decision cost of the adjustment strategy corresponding to the i-th training sample; Among them, a training sample is composed of the safety status of the power operation and inspection operation, the target adjustment strategy and the decision effect of the target adjustment strategy.

[0061] In one implementation, the decision cost determination module 230 is specifically configured to: The decision execution time of the adjustment strategy, the risk score of the fused data, and the environmental dynamic impact factor are weightedly summed to obtain the decision cost of the adjustment strategy.

[0062] In one embodiment, it further includes: A credibility calculation module, used for determining the credibility of each of the sensing data based on the noise of each of the sensing data; The data fusion module is used to perform weighted summation on each of the sensor data based on the credibility of each of the sensor data to obtain the fused data.

[0063] In one embodiment, it further includes: A risk factor calculation module, used to score each risk factor based on the fused data to obtain a risk value of each risk factor; The risk scoring module is used to perform weighted summation on the risk values ​​of each risk factor based on the weight of each risk factor to obtain a risk score of the fused data.

[0064] For the description of specific functions and examples of each module and submodule of the device in the embodiment of the present invention, reference can be made to the relevant description of the corresponding steps in the above method embodiment, which will not be repeated here.

[0065] In the technical solution of the present invention, the acquisition, storage and application of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0066] According to an embodiment of the present invention, the present invention also provides a system and a readable storage medium.

[0067] Figure 3 A schematic block diagram of an example electronic device 800 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 assistants, cellular phones, smart phones, wearable devices, 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.

[0068] like Figure 3 As shown, the device 800 includes a computing unit 801, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 to a random access memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the device 800 can also be stored. The computing unit 801, the ROM 802, and the RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0069] A number of components in the device 800 are connected to the I / O interface 805, including: an input unit 806, such as a keyboard, a mouse, etc.; an output unit 807, such as various types of displays, speakers, etc.; a storage unit 808, such as a disk, an optical disk, etc.; and a communication unit 809, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 809 allows the device 800 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0070] The computing unit 801 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 801 performs the various methods and processes described above, such as a safety control method for power operation and inspection operations. For example, in some embodiments, the safety control method for power operation and inspection operations may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 808. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 800 via the ROM 802 and / or the communication unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the safety control method for power operation and inspection operations described above may be performed. Alternatively, in other embodiments, the computing unit 801 may be configured to execute a safety control method for power operation and inspection operations in any other appropriate manner (for example, by means of firmware).

[0071] 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.

[0072] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0073] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. 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.

[0074] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer 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 pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0075] The systems and techniques described herein may be implemented in a computing system that includes back-end 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 front-end 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 back-end components, middleware components, or front-end 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), and the Internet.

[0076] A computer 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 relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0077] 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 disclosed in the present invention can be achieved, and this document does not limit this.

[0078] 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 principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A safety control method for power operation and inspection, characterized in that: include: Determine the safety status of the power operation and inspection operation based on the fusion data obtained by fusing various sensor data collected during the power operation and inspection operation and the risk score of the fusion data; Based on the safety status of the power operation and inspection operation, determining an adjustment strategy set for safety management and control of the power operation and inspection operation; Determining the decision cost of each adjustment strategy based on the decision execution time of each adjustment strategy in the adjustment strategy set, the risk score of the fused data, and the environmental dynamic impact factor; Based on the decision costs of the respective adjustment strategies, a target adjustment strategy for the power operation and inspection task is determined in the adjustment strategy set.

2. The method according to claim 1, characterized in that The step of determining a set of adjustment strategies for performing safety management and control on the power operation and inspection operation based on the safety status of the power operation and inspection operation includes: The security status and the changing trend of the security status relative to the historical security status are input into a pre-trained adjustment strategy generation model to obtain the adjustment strategy set output by the adjustment strategy generation model.

3. The method according to claim 2, characterized in that Also includes: Under the condition that the power operation and inspection operation is safely controlled based on the target adjustment strategy, determining the decision effect of the target adjustment strategy; Based on the decision effect of the target adjustment strategy, the model parameters of the adjustment strategy generation model are adjusted.

4. The method according to claim 3, characterized in that The step of adjusting the model parameters of the adjustment strategy generation model based on the decision effect of the target adjustment strategy includes: Using the first formula, based on the decision effect of the target adjustment strategy, the model parameters of the adjustment strategy generation model are adjusted; Wherein, the first formula includes: ； ； in, represents the adjusted model parameters of the adjustment strategy generation model, represents the model parameters of the adjustment strategy generation model before adjustment, represents the learning rate, represents the objective function; in, represents the number of samples in the training set, represents the safety state corresponding to the i-th training sample, represents the decision effect corresponding to the i-th training sample, represents the decision cost of the adjustment strategy corresponding to the i-th training sample; Among them, a training sample is composed of the safety status of the power operation and inspection operation, the target adjustment strategy and the decision effect of the target adjustment strategy.

5. The method according to claim 1, characterized in that The step of determining the decision cost of each adjustment strategy based on the decision execution time of each adjustment strategy in the adjustment strategy set, the risk score of the fusion data, and the environmental dynamic impact factor includes: The decision execution time of the adjustment strategy, the risk score of the fused data, and the environmental dynamic impact factor are weightedly summed to obtain the decision cost of the adjustment strategy.

6. The method according to claim 1, characterized in that Also includes: Determining the credibility of each of the sensor data based on the noise of each of the sensor data; Based on the credibility of each of the sensor data, weighted sum is performed on each of the sensor data to obtain the fusion data.

7. The method according to claim 1, characterized in that Also includes: Based on the fused data, scoring each risk factor to obtain a risk value of each risk factor; Based on the weights of the risk factors, the risk values ​​of the risk factors are weighted and summed to obtain the risk score of the fused data.

8. A safety control device for power operation and inspection, characterized in that: include: A safety status assessment module, used to determine the safety status of the power operation and inspection operation based on fusion data obtained by fusing various sensor data collected during the power operation and inspection operation and a risk score of the fusion data; A strategy set determination module, used to determine an adjustment strategy set for safety management and control of the power operation and inspection operation based on the safety status of the power operation and inspection operation; A decision cost determination module, used to determine the decision cost of each adjustment strategy based on the decision execution time of each adjustment strategy in the adjustment strategy set, the risk score of the fusion data, and the environmental dynamic impact factor; The target strategy determination module is used to determine the target adjustment strategy for the power operation and inspection operation in the adjustment strategy set based on the decision costs of each of the adjustment strategies.

9. A safety control system for power operation and inspection, comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-7.

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