An intelligent safety management and control method for power workers based on indoor and outdoor positioning

Abstract

The present invention discloses an intelligent safety management and control method for power workers based on indoor and outdoor positioning, and relates to the technical field of power safety management. The method obtains the indoor and outdoor position data of the power workers through the positioning equipment of the power workers, and performs trajectory analysis according to the preset safe operation area range to determine the safe route and obtain the safety trajectory index. At the same time, the safety impact of the power equipment is evaluated by analyzing the outdoor environmental data, the danger coefficient of the equipment is obtained, and the outdoor risk index is calculated in combination with the behavioral characteristics of the workers in the high-risk area. A comprehensive analysis is performed on the safety trajectory index and the outdoor risk index, and the comprehensive risk index is calculated. The degree of danger of the workers is judged by the dynamic threshold, and the fuzzy control algorithm is used to implement safety management and control of indoor and outdoor power equipment and workers. Real-time monitoring and intelligent management and control of power workers are realized, and the safety and efficiency of power operations are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power safety management, and in particular to an intelligent safety management and control method for power operators based on indoor and outdoor positioning. Background Art

[0002] With the rapid development and modernization of the power industry, the safety issues of power workers have become increasingly prominent. Power operations usually involve high-voltage electrical equipment and complex operating environments, and operators face a variety of potential safety risks, such as electrical accidents, environmental factors, and dynamic changes in the operating area. Therefore, how to effectively monitor and control the safety status of power workers and ensure their safety during the operation process is a key issue in improving the safety and reliability of power system operation. To this end, various types of intelligent safety management and control systems have emerged, aiming to improve the safety and emergency response capabilities of operators through technical means.

[0003] However, the existing methods for the safety management and control of power operations have many shortcomings. Traditional safety monitoring systems often rely on static monitoring and manual judgment, and lack real-time response to the dynamic status of operators and environmental changes, resulting in the inability to identify potential safety hazards in a timely manner. In addition, the environmental adaptability analysis is relatively simple and fails to effectively consider the comprehensive impact of the external environment on power equipment and operators. Therefore, these methods are difficult to meet the needs of the rapidly changing power operation environment in practical applications, reducing the safety level of operators. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention provides an intelligent safety management method for power workers based on indoor and outdoor positioning, which monitors and analyzes the safety status of power workers in real time, aiming to improve the safety of operations and management efficiency. The method obtains the indoor and outdoor location data of the workers through positioning equipment to ensure the real-time and accuracy of the information; determines the safe routes and behavioral characteristics of the workers through trajectory analysis and time series processing, thereby improving the safety of the work path; performs environmental adaptability analysis to help quantify the risk factor of outdoor power equipment and provide a basis for safety decision-making; and realizes intelligent dynamic safety management and control through comprehensive risk index and fuzzy control algorithm to ensure rapid response to potential risks.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent safety management and control method for power workers based on indoor and outdoor positioning, comprising the following steps: S1. Acquiring the indoor and outdoor location data of power workers through the positioning equipment of power workers; S2. Performing trajectory analysis according to the preset safe operation area range and the indoor location data of power workers to determine the safe route of power workers, analyzing the action trajectory and behavioral characteristics of the stay time of power workers through time series, and obtaining the safety trajectory index of power workers; S3. Acquiring outdoor environment data according to the outdoor location data of power workers, performing environmental adaptability analysis on outdoor power equipment, evaluating the degree of safety impact of the outdoor environment on outdoor power equipment, obtaining the risk factor of outdoor power equipment, analyzing the behavioral characteristics of the stay time and movement speed of power workers in high-risk areas according to the risk factor of outdoor power equipment, and obtaining the outdoor risk index of power workers; S4. Comprehensively analyzing the safety trajectory index of power workers and the outdoor risk index of power workers to obtain the comprehensive risk index of power workers, judging the degree of danger of power workers through dynamic thresholds, and performing safety management and control of indoor and outdoor power equipment and power workers through fuzzy control algorithms.

[0006] Furthermore, trajectory analysis is performed based on the preset safe working area range and the indoor location data of the power workers to determine the specific process of the safe route of the power workers as follows: based on the real-time indoor location data of the power workers, the movement trajectory and timestamp of the power workers are recorded, and the indoor location data is matched with the preset safe working area range through the spatial proximity algorithm to identify whether the power workers are in the safe area; through linear interpolation, a smooth trajectory line is generated between adjacent positioning points, the movement trajectory of the power workers is constructed, and the safe route of the power workers in the safe area is drawn.

[0007] Furthermore, the behavior characteristics of the action trajectory and residence time of the power workers are analyzed through time series, and the specific process of obtaining the safety trajectory index of the power workers is as follows: according to the action trajectory and timestamp of the power workers, the residence time of the power workers at each inspection location is obtained through time series; the residence time is smoothed through the sliding window algorithm, and the movement frequency, residence time and path deviation degree of the power workers in the safe area are comprehensively analyzed to obtain the safety trajectory index of the power workers.

[0008] Furthermore, the specific process of conducting an environmental adaptability analysis on outdoor power equipment and evaluating the degree of impact of the outdoor environment on the safety of outdoor power equipment is as follows: Based on the outdoor environmental data, the outdoor environmental data is compared with the technical specifications and tolerance range of the power equipment to identify potential environmental risks; the interaction between external environmental factors and power equipment is quantitatively analyzed, a hazard factor model is established, and environmental risks and the safety performance of power equipment are comprehensively evaluated.

[0009] Furthermore, the specific process of obtaining the risk factor of outdoor power equipment is as follows: according to the established risk factor model, quantify the impact of environmental risks on power equipment; combine the technical specifications and tolerance range of power equipment to obtain the risk factor of outdoor power equipment and generate the corresponding risk level.

[0010] Furthermore, the behavioral characteristics of the residence time and movement speed of power workers in high-risk areas are analyzed according to the hazard factor of outdoor power equipment. The specific process of obtaining the outdoor risk index of power workers is as follows: According to the hazard factor of outdoor power equipment, the residence time and movement speed of power workers in high-risk areas are analyzed to identify the behavioral characteristics of power workers; the behavioral performance of power workers in high-risk areas is quantified, and the risk exposure degree of power workers in high-risk areas is analyzed by combining the data of residence time and movement speed to generate an outdoor risk index for power workers.

[0011] Furthermore, the specific process of comprehensive analysis of the safety trajectory index of power workers and the outdoor risk index of power workers is as follows: the safety trajectory index of power workers and the outdoor risk index of power workers are comprehensively calculated with the set safety trajectory index threshold of power workers and the outdoor risk index threshold of power workers to obtain the comprehensive risk index of power workers.

[0012] Furthermore, the specific process of judging the degree of danger of the operators through dynamic thresholds is as follows: comparing the comprehensive risk index of the power operators with the risk threshold; when the comprehensive risk index of the power operators is greater than the first risk threshold, the working status of the power operators is marked as a high-risk status; when the comprehensive risk index of the power operators is less than the first risk threshold and greater than the second risk threshold, the working status of the power operators is marked as a medium-risk status; when the comprehensive risk index of the power operators is less than the second risk threshold, the working status of the power operators is marked as a low-risk status.

[0013] Furthermore, the specific process of safety management and control of indoor and outdoor power equipment and power operators through fuzzy control algorithm is as follows: the comprehensive risk index of power operators is defined as input variables, and the operating status of power equipment and the notification status of power operators are defined as output variables; fuzzy rules are formulated according to the relationship between the comprehensive risk index of power operators and the operating status and notification status of power equipment; fuzzy reasoning is performed according to the fuzzy rules to determine the operating status of power equipment and the notification status of power operators.

[0014] The present invention has the following beneficial effects:

[0015] (1) This method of intelligent safety management and control of power workers based on indoor and outdoor positioning obtains real-time location data for subsequent safety analysis and decision-making, establishes historical data reference, and improves the effectiveness of future safety management and control. By analyzing the movement trajectory of the workers, the safest operation route is determined to reduce safety accidents caused by improper route selection. Combined with the analysis of the stay time, the abnormal behavior of the workers can be identified for timely intervention. The scope of the safe operation area is dynamically adjusted to meet the needs of different working environments.

[0016] (2) This intelligent safety management and control method for power workers based on indoor and outdoor positioning can quantify the impact of the environment on the safety of power equipment through the adaptability analysis of the outdoor environment, and provide a scientific basis for the formulation of safety measures. Determining the risk factor of outdoor power equipment helps to identify high-risk areas, facilitate key monitoring and management, and improve the overall safety level. By analyzing the residence time and movement speed of workers in high-risk areas, safety hazards can be discovered in advance and measures can be taken to ensure the safety of workers. The accuracy of management and control can be improved by comprehensively analyzing the safety trajectory index of power workers and the outdoor risk index of power workers. Using dynamic thresholds to judge the degree of danger of workers helps to take different safety management and control measures for different risk levels and improve the efficiency of emergency response. The intelligent management and control of indoor and outdoor power equipment and workers is realized through fuzzy control algorithms, and safety measures can be automatically adjusted according to risk changes, which improves the flexibility and adaptability of safety management and control.

[0017] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flow chart of an intelligent safety management and control method for power workers based on indoor and outdoor positioning of the present invention. DETAILED DESCRIPTION

[0019] The embodiment of the present application solves the problem of insufficient safety management and real-time monitoring of power workers in high-risk areas through an intelligent safety management method for power workers based on indoor and outdoor positioning.

[0020] The overall idea of ​​the problem in the embodiment of this application is as follows:

[0021] The indoor and outdoor location data of power workers are obtained through their positioning equipment.

[0022] Trajectory analysis is performed based on the preset safe operation area and the indoor location data of the power workers to determine the safe routes of the power workers. The action trajectories and behavioral characteristics of the power workers' stay time are analyzed through time series to obtain the power workers' safety trajectory index.

[0023] Based on the outdoor location data of power workers, outdoor environment data is obtained, environmental adaptability analysis is performed on outdoor power equipment, the impact of the outdoor environment on the safety of outdoor power equipment is evaluated, and the hazard factor of outdoor power equipment is obtained. Based on the hazard factor of outdoor power equipment, the behavioral characteristics of power workers' residence time and movement speed in high-risk areas are analyzed to obtain the outdoor risk index of power workers.

[0024] A comprehensive analysis is conducted on the safety trajectory index of power workers and the outdoor risk index of power workers to obtain the comprehensive risk index of power workers. The degree of danger of power workers is judged through dynamic thresholds, and the safety of indoor and outdoor power equipment and power workers is managed and controlled through fuzzy control algorithms.

[0025] See also Figure 1The embodiment of the present invention provides a technical solution: an intelligent safety management and control method for power workers based on indoor and outdoor positioning, comprising the following steps: S1. Acquire the indoor and outdoor location data of the power workers through the positioning device of the power workers; S2. Perform trajectory analysis according to the preset safe operation area range and the indoor location data of the power workers, determine the safe route of the power workers, analyze the action trajectory and the behavioral characteristics of the stay time of the power workers through time series, and obtain the safety trajectory index of the power workers; S3. According to the outdoor location data of the power workers, obtain outdoor environment data, perform environmental adaptability analysis on outdoor power equipment, evaluate the safety impact of the outdoor environment on the outdoor power equipment, obtain the risk factor of the outdoor power equipment, analyze the behavioral characteristics of the stay time and movement speed of the power workers in the high-risk area according to the risk factor of the outdoor power equipment, and obtain the outdoor risk index of the power workers; S4. Comprehensively analyze the safety trajectory index of the power workers and the outdoor risk index of the power workers to obtain the comprehensive risk index of the power workers, judge the degree of danger of the power workers through dynamic thresholds, and perform safety management and control of indoor and outdoor power equipment and power workers through fuzzy control algorithms.

[0026] In this implementation scheme, step S1 obtains the real-time location data of the power operator indoors and outdoors through the positioning device (such as GPS or indoor positioning system) carried by the power operator. The positioning device can track the location of the operator in real time and provide basic data for subsequent safety analysis. Step S2 performs trajectory analysis based on the set safe operation area range and the indoor location data of the operator. By analyzing the movement trajectory and residence time of the operator, the behavioral characteristics can be extracted to calculate the "safety trajectory index". This index reflects the activities of the operator in the safe area and helps to determine its safe route. Step S3 obtains outdoor environmental information such as climate conditions, equipment status, etc. based on the outdoor location data of the operator. Through environmental adaptability analysis, the safety impact of these environmental factors on outdoor power equipment (such as substations, transmission lines, etc.) is evaluated, and then the "risk factor" is obtained. According to the risk factor, the residence time and movement speed of the operator in the high-risk area are analyzed to obtain the "outdoor risk index".

[0027] Step S4. Comprehensively analyze the safety trajectory index and the outdoor risk index to calculate the "comprehensive risk index". The danger level of the operator is determined by the set dynamic threshold. According to the danger level, the fuzzy control algorithm is used to perform intelligent safety management and control on the operating status of indoor and outdoor power equipment and the notification status of the operator. For example, if the operator is found to be in a high-risk state, the system may automatically adjust the operation of the power equipment to reduce the risk, or promptly notify the operator to take necessary safety measures. Positioning device: a device used to determine the location of an object (such as a power operator), usually including GPS and indoor positioning systems. Safe operating area range: a clearly defined safety area where the operator is considered safe when working. Trajectory analysis: using data analysis technology to study the movement routes and behavior patterns of the operator. Safety trajectory index: a quantitative indicator for measuring the activities of the operator in the safety area. Environmental adaptability analysis: assessing the impact of the external environment on the safety of equipment or personnel. Danger coefficient: measuring the potential danger of the equipment in the current environment. Fuzzy control algorithm: a technology that uses fuzzy logic to control the system, suitable for dealing with uncertainty and fuzziness problems.

[0028] Specifically, trajectory analysis is performed based on the preset safe working area range and the indoor location data of the power workers to determine the specific process of the safe route of the power workers as follows: based on the real-time indoor location data of the power workers, the movement trajectory and timestamp of the power workers are recorded, and the indoor location data is matched with the preset safe working area range through the spatial proximity algorithm to identify whether the power workers are in the safe area; through linear interpolation, a smooth trajectory line is generated between adjacent positioning points, the movement trajectory of the power workers is constructed, and the safe route of the power workers in the safe area is drawn.

[0029] In this implementation scheme, the action trajectory and timestamp are recorded: whenever the positioning device updates its position, its action trajectory and the corresponding timestamp are recorded. This forms a time series data set containing multiple location points and time information. Through this data set, the movement history of the operator can be tracked. Spatial proximity algorithm matching: the real-time location data is matched with the preset safe operation area range using the spatial proximity algorithm. The algorithm determines whether the operator is in the safe area by calculating the distance between the operator's current position and the boundary of the safe operation area. Proximity calculation: for each location point, the algorithm determines whether it falls within the preset safe area. If the operator is in the safe area, it means that they are in a relatively safe environment. Generate smooth trajectory lines In order to better visualize the action trajectory of the operator, a linear interpolation method is used to generate smooth trajectory lines between adjacent positioning points. The process of linear interpolation is as follows: for every two adjacent location points, the straight line between them is calculated, and more location points are generated between these points. These generated location points will form a continuous trajectory line, reflecting the movement of the operator. This smooth trajectory line can more clearly represent the movement route of the operator, which is convenient for subsequent analysis and visualization. The constructed smooth trajectory is plotted on a map of the safe area. This allows relevant personnel (such as safety monitors or managers) to visually see the safe route of the power workers and confirm whether they are always within the safe area or whether they deviate from the safe path at a specific point in time.

[0030] Specifically, the specific process of obtaining the power workers' safety trajectory index is as follows: according to the power workers' action trajectory and timestamp, the power workers' residence time at each inspection location is obtained through time series; the residence time is smoothed through the sliding window algorithm, and the movement frequency, residence time and path deviation degree of the power workers in the safe area are comprehensively analyzed to obtain the power workers' safety trajectory index.

[0031] In this implementation plan, the specific steps of the safety trajectory index acquisition process are as follows: Action trajectory data: contains multiple location points and its corresponding timestamp ( ), Dwell time calculation: At each inspection location The duration of stay It can be calculated by the difference of timestamps: ; For the last location point, the last updated timestamp can be used to determine the residence time. Sliding window algorithm smoothing: The sliding window algorithm is used to smooth the residence time to reduce noise and identify trends. The basic idea of ​​the sliding window is to perform local averaging on the data. The specific steps are as follows: Define the window size: Set a window size , for example 3 or 5, depending on the characteristics of the data and the analysis requirements. Smoothed residence time: Calculates the smoothed residence time for each location point ; ;in, (for all dwell times in the window), which can obtain a smooth dwell time series and reduce the impact of sudden events.

[0032] After obtaining the smoothed dwell time, a comprehensive analysis is performed to extract the behavioral characteristics of power workers: Movement frequency: Movement frequency It can be defined as the number of moves per unit time, the degree of path deviation: the degree of path deviation This can be evaluated by calculating the distance between the actual walking path of the power worker and the ideal safe path, usually using the Euclidean distance: ;here, is the actual location of the power operator. is the set safe path position, The horizontal coordinate of the point corresponding to the actual position of the power operator, Indicates the horizontal coordinate of the point corresponding to the set safe path position, Indicates the ordinate of the point corresponding to the actual position of the power operator. The process of obtaining the safety trajectory index is as follows: the results of the above analysis are combined to obtain the safety trajectory index of the power operator. , ;in, is the weight coefficient of motion frequency, represents the weight coefficient for the smoothed average of the dwell time, The weight coefficient representing the degree of path deviation represents the importance of each factor in the calculation of the safety trajectory index (the sum of the weights is 1). is the smoothed mean of the residence time. Used to indicate the degree of path deviation. The closer the value is to 1, the closer it is to the safe path.

[0033] Specifically, the specific process of conducting an environmental adaptability analysis on outdoor power equipment and evaluating the degree of impact of the outdoor environment on the safety of outdoor power equipment is as follows: Based on the outdoor environmental data, the outdoor environmental data is compared with the technical specifications and tolerance range of the power equipment to identify potential environmental risks; the interaction between external environmental factors and power equipment is quantitatively analyzed, a hazard factor model is established, and environmental risks and the safety performance of power equipment are comprehensively evaluated.

[0034] In this implementation scheme, data related to the outdoor environment are obtained through sensors and other devices, including temperature, humidity, wind speed, rainfall, radiation intensity meteorological data, as well as electromagnetic interference, air pollution and other external factors. Comparison with the technical specifications of power equipment: The collected environmental data is compared with the technical specifications of the power equipment (such as the temperature range allowed by the equipment, the humidity tolerance range, electromagnetic compatibility, wind resistance level, etc.). For example, if the operating temperature range of a certain device is -10℃ to 40℃, and the current ambient temperature is 50℃, potential temperature risks may be identified. The results of the comparison are used to identify the risk that the environmental data exceeds the technical tolerance range of the equipment. For example, if the humidity tolerance range of a certain power equipment is 40%-60%, but the current humidity is 80%, this indicates that the humidity may pose a threat to the performance or safety of the equipment, and there is a humidity risk. Quantitatively analyze the interaction between each environmental factor and the operating status of the equipment. For example, high temperature may accelerate the aging of internal components of the equipment, and excessive humidity may cause short circuit risks. These interactions can be quantitatively analyzed through experimental data, historical fault records or simulation models to calculate the specific impact of the environment on the equipment.

[0035] Specifically, the specific process of obtaining the hazard factor of outdoor power equipment is as follows: according to the established hazard factor model, quantify the impact of environmental risks on power equipment; combine the technical specifications and tolerance range of power equipment to obtain the hazard factor of outdoor power equipment and generate the corresponding risk level.

[0036] In this implementation plan, the process of calculating the risk factor is as follows: using the risk factor model, the impact of various environmental factors is summarized into a comprehensive risk factor. It indicates the safety risk level of the equipment in the current environment. The calculation formula of the risk factor of outdoor power equipment is as follows: ; In the above formula: Indicates the risk factor of outdoor electrical equipment. Indicates actual values ​​of environmental factors (actual temperature, actual humidity, actual wind speed, actual rainfall, actual radiation intensity), Indicates The safety threshold of the device under various environmental factors, that is, the maximum range allowed by the technical specifications of the device. Indicates The weight of the impact of environmental factors on the equipment. Different environmental factors have different impacts on equipment safety, so the weight coefficient To characterize their relative importance, the weights are usually determined by empirical data such as the equipment's usage scenarios and historical failure data. Indicates the number of environmental factors involved, such as temperature, humidity, and wind speed. , can be divided into different risk levels. For example: When smaller (such as , indicating that environmental conditions have little impact on power equipment and are considered low risk. In the middle range (such as ), indicating that the equipment is facing certain environmental pressure during operation, which is a medium risk; When larger (such as ), indicating that the environment has a serious impact on the device and there is a high possibility of device failure or damage, which is a high risk.

[0037] Specifically, the behavioral characteristics of the residence time and movement speed of power workers in high-risk areas are analyzed according to the hazard factor of outdoor power equipment. The specific process of obtaining the outdoor risk index of power workers is as follows: According to the hazard factor of outdoor power equipment, the residence time and movement speed of power workers in high-risk areas are analyzed to identify the behavioral characteristics of power workers; the behavioral performance of power workers in high-risk areas is quantified, and the risk exposure degree of power workers in high-risk areas is analyzed by combining the data of residence time and movement speed to generate an outdoor risk index for power workers.

[0038] In this implementation scheme, high-risk areas refer to areas where the risk factor of power equipment is higher. Based on the risk factor generated in the previous step, high-risk areas around the equipment can be delineated. The behavior of power workers entering these areas will be closely monitored. Behavioral characteristics include the residence time and movement speed of power workers in these high-risk areas. Staying for a long time or moving slowly may mean higher risk exposure. The behavior of workers in high-risk areas is quantified by two parameters: residence time and movement speed: residence time refers to the duration of the worker in the high-risk area. The longer the stay time, the longer the exposure to the high-risk environment, which increases the potential danger. Movement speed: refers to the speed at which the worker moves in the high-risk area. If the worker moves slowly in the high-risk area, it may mean that there is a more complex or dangerous working environment in the area, further increasing the risk. The process of calculating the outdoor risk index of power workers is as follows, and the formula is as follows: ;Formula explanation; : The outdoor risk index of power workers reflects the overall risk exposure of workers in high-risk areas. : The length of time that power workers stay in high-risk areas. The longer the stay, the higher the risk. : The speed of movement of power workers. The slower the movement speed, the higher the risk. The risk factor of outdoor power equipment indicates the degree of danger of the environment in which the power equipment is located. The higher the risk of the equipment, the higher the risk index of the operator in the area. An adjustment factor is used to adjust the sensitivity of the formula to ensure that the calculated results are consistent with the actual risk assessment.

[0039] Specifically, the specific process of comprehensive analysis of the safety trajectory index of power workers and the outdoor risk index of power workers is as follows: the safety trajectory index of power workers and the outdoor risk index of power workers are comprehensively calculated with the set safety trajectory index threshold of power workers and the outdoor risk index threshold of power workers to obtain the comprehensive risk index of power workers.

[0040] In this implementation plan, the calculation formula for the comprehensive risk index of power workers is obtained:

[0041] ; Formula explanation: CRI: Comprehensive Risk Index for power workers, used to comprehensively evaluate the safety risk level of workers. STI: Safety Trajectory Index for power workers, which reflects whether the workers' indoor movement trajectory deviates from the safe area, as well as the rationality of their stay time and movement route. : The preset safety trajectory index threshold serves as a benchmark for measuring whether the operator's indoor behavior meets safety standards. : The preset outdoor risk index threshold serves as a benchmark for determining whether workers are exposed to outdoor high-risk areas for too long. and They represent the impact weights of the safety trajectory index and outdoor risk index on the comprehensive risk. These two coefficients can be flexibly adjusted according to different working environments and safety priorities.

[0042] Specifically, the specific process of judging the degree of danger of operators through dynamic thresholds is as follows: comparing the comprehensive risk index of power operators with the risk threshold; when the comprehensive risk index of power operators is greater than the first risk threshold, marking the working status of power operators as high-risk status; when the comprehensive risk index of power operators is less than the first risk threshold and greater than the second risk threshold, marking the working status of power operators as medium-risk status; when the comprehensive risk index of power operators is less than the second risk threshold, marking the working status of power operators as low-risk status.

[0043] In this implementation scheme, risk threshold comparison: the calculated comprehensive risk index (CRI) is compared with the preset first risk threshold and second risk threshold. These thresholds are dynamically adjusted according to historical data, operating environment and relevant safety standards to ensure that they are adapted to different operating conditions and power operating environments; high risk state: when the comprehensive risk index (CRI) of the operator is greater than the first risk threshold, it means that the operator faces extremely high risk. In this case, the operator's working status is marked as a high-risk state, and the system will immediately take emergency measures, such as sending an alarm to the security monitoring center, suspending operations, or providing additional safety protection measures. Medium risk state: when the comprehensive risk index (CRI) is between the first risk threshold and the second risk threshold, it means that the operator's risk level is moderate, there is a certain risk but it has not yet reached the level of emergency. At this time, the operator's working status is marked as a medium-risk state, and the system may prompt the operator to be vigilant or adjust his work behavior, such as optimizing the work route or shortening the stay time in a certain area. Low risk state: when the comprehensive risk index (CRI) is less than the second risk threshold, it means that the operator's risk is low, and the working environment and behavioral characteristics are within a relatively safe range. The operator's working status is marked as low-risk and can proceed with the work normally. The system only needs to perform routine monitoring.

[0044] Specifically, the specific process of safety management and control of indoor and outdoor power equipment and power operators through fuzzy control algorithm is as follows: define the comprehensive risk index of power operators as input variables, and define the operating status of power equipment and the notification status of power operators as output variables; formulate fuzzy rules based on the relationship between the comprehensive risk index of power operators and the operating status and notification status of power equipment; perform fuzzy reasoning based on fuzzy rules to determine the operating status of power equipment and the notification status of power operators.

[0045] In this implementation scheme, the input variable is the comprehensive risk index of power workers, which is obtained based on the safety trajectory index and outdoor risk index of the workers, reflecting the safety risk level of the workers in the current environment. Output variable: Power equipment operation status: Normal: The equipment is within the safe operation range and no fault or risk occurs. Shutdown: The equipment stops operating due to fault or safety reasons. Power worker notification status: Danger: There are major safety hazards and immediate measures need to be taken. Warning: There are certain risks, and vigilance needs to be increased and countermeasures need to be prepared. Safe: The workers are in a safe area and do not need to pay special attention. Fuzzy rules are formulated based on the relationship between input variables and output variables. The following are some possible examples of fuzzy rules: If the CRI is high (high risk), the power equipment operation status is shutdown and the notification status is dangerous. If the CRI is medium (medium risk), the power equipment operation status is normal and the notification status is warning. If the CRI is low (low risk), the power equipment operation status is normal and the notification status is safe. Through fuzzy reasoning, the input variables are processed to generate corresponding output variables. The process generally includes the following steps: Fuzzification: Fuzzify the comprehensive risk index (CRI) of power workers and convert it into a fuzzy set (such as low, medium, and high). Apply fuzzy rules: According to the established fuzzy rules, map the relationship between input variables and output variables. Reasoning process: Use the fuzzy reasoning mechanism to generate a fuzzy output set. For example, if the comprehensive risk index of a power worker is 0.8 (high risk), then through fuzzy reasoning, input: CRI=0.8, according to the fuzzy rule, "if the CRI is high, the power equipment operation status is shutdown and the notification status is dangerous", so · Power equipment operation status: shutdown, notification status: dangerous On the contrary, if the comprehensive risk index of a power worker is 0.3 (low risk), it is obtained: Input: CRI=0.3; according to the fuzzy rule, "if the CRI is low, the power equipment operation status is normal and the notification status is safe", so: Power equipment operation status: normal, notification status: safe.

[0046] In summary, this application has at least the following effects:

[0047] This paper proposes an intelligent safety management and control method for power workers based on indoor and outdoor positioning. Through real-time positioning and trajectory analysis, the activities of power workers can be effectively monitored to ensure that they work in a safe area and reduce the risk of accidents. Environmental adaptability analysis and calculation of hazard coefficients can timely identify potential safety hazards and provide targeted safety warnings and protective measures for workers. By comprehensively analyzing the safety trajectory index and outdoor risk index, a dynamically adjusted safety management and control strategy can be implemented, and risk assessment and safety measures can be updated according to real-time data to enhance the flexibility and safety of operations. By using time series analysis of residence time and movement speed, the behavioral characteristics of workers in different environments can be deeply understood, helping to formulate more effective safety management policies. Through real-time monitoring of the status of workers and equipment, the power operation process can be optimized, work efficiency can be improved, and the loss of working hours caused by safety issues can be reduced. Combining positioning equipment with intelligent analysis algorithms, intelligent management of power operations can be realized, and the scientific and technological content and modernization level of power safety management can be improved.

[0048] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0049] The present invention is described with reference to flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0050] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0051] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0052] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0053] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An intelligent safety management and control method for power workers based on indoor and outdoor positioning, characterized in that: The following steps are involved: S1. Obtaining indoor and outdoor location data of power workers through the positioning equipment of power workers; S2. Conduct trajectory analysis based on the preset safe operation area and the indoor location data of the power workers to determine the safe route of the power workers, analyze the action trajectory and behavior characteristics of the power workers' stay time through time series analysis, and obtain the safety trajectory index of the power workers; S3. Based on the outdoor location data of the power workers, obtain the outdoor environment data, perform environmental adaptability analysis on the outdoor power equipment, evaluate the impact of the outdoor environment on the safety of the outdoor power equipment, obtain the risk factor of the outdoor power equipment, analyze the behavioral characteristics of the power workers' stay time and movement speed in the high-risk area based on the risk factor of the outdoor power equipment, and obtain the outdoor risk index of the power workers; S4. Comprehensively analyze the safety trajectory index of power workers and the outdoor risk index of power workers to obtain the comprehensive risk index of power workers, determine the danger level of power workers through dynamic thresholds, and conduct safety management and control of indoor and outdoor power equipment and power workers through fuzzy control algorithms; The specific process of performing trajectory analysis based on the preset safe operation area and the indoor location data of the power operator to determine the safe route of the power operator is as follows: According to the real-time indoor location data of power workers, the movement trajectory and timestamp of power workers are recorded, and the indoor location data is matched with the preset safe operation area through the spatial proximity algorithm to identify whether the power workers are in a safe area; Generate smooth trajectory lines between adjacent positioning points through linear interpolation, construct the action trajectory of power workers, and draw safe routes for power workers in safe areas; The specific process of obtaining the safety trajectory index of power workers by analyzing the action trajectory and the behavior characteristics of the stay time of power workers through time series is as follows: According to the movement trajectory and timestamp of the power workers, the stay time of the power workers at each inspection location is obtained through time series; The dwell time is smoothed by a sliding window algorithm, and the movement frequency, dwell time and path deviation degree of power workers in the safe area are comprehensively analyzed to obtain the safety trajectory index of power workers. The specific process of performing environmental adaptability analysis on outdoor power equipment and evaluating the impact of the outdoor environment on the safety of outdoor power equipment is as follows: Based on the outdoor environmental data, compare the outdoor environmental data with the technical specifications and tolerance range of the power equipment to identify potential environmental risks; Quantitatively analyze the interaction between external environmental factors and power equipment, establish a risk factor model, and conduct a comprehensive assessment of environmental risks and the safety performance of power equipment; The specific process of obtaining the risk factor of outdoor power equipment is as follows: Quantify the impact of environmental risks on power equipment based on the established risk factor model; Combine the technical specifications and tolerance range of power equipment to obtain the risk factor of outdoor power equipment and generate the corresponding risk level; The specific process of analyzing the behavior characteristics of the residence time and movement speed of power workers in high-risk areas according to the risk factor of outdoor power equipment to obtain the outdoor risk index of power workers is as follows: According to the risk factor of outdoor power equipment, analyze the residence time and movement speed of power workers in high-risk areas and identify the behavioral characteristics of power workers; Quantify the behavior of power workers in high-risk areas, combine the data of residence time and movement speed, analyze the risk exposure of power workers in high-risk areas, and generate an outdoor risk index for power workers; The specific process of comprehensive analysis of the safety trajectory index of power workers and the outdoor risk index of power workers is as follows: Comprehensively calculate the safety trajectory index of the power operator and the outdoor risk index of the power operator with the set safety trajectory index threshold of the power operator and the outdoor risk index threshold of the power operator to obtain the comprehensive risk index of the power operator; The specific process of judging the danger level of operators through dynamic thresholds is as follows: Compare the comprehensive risk index of power workers with the risk threshold; When the comprehensive risk index of the power operator is greater than the first risk threshold, the working status of the power operator is marked as a high-risk status; When the comprehensive risk index of the power operator is less than the first risk threshold and greater than the second risk threshold, the working state of the power operator is marked as a medium risk state; When the comprehensive risk index of the power operator is less than the second risk threshold, the working state of the power operator is marked as a low risk state; The specific process of safety management and control of indoor and outdoor power equipment and power workers through fuzzy control algorithm is as follows: The comprehensive risk index of power workers is defined as the input variable, and the operating status of power equipment and the notification status of power workers are defined as the output variables; According to the relationship between the comprehensive risk index of power workers and the operating status and notification status of power equipment, fuzzy rules are formulated; Fuzzy reasoning is performed based on fuzzy rules to determine the operating status of power equipment and the notification status of power operators.

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