Electric shock risk identification and early warning method and system for power distribution operation

Abstract

The embodiment of the application provides a power distribution operation anti-electric shock risk identification and early warning method and system, which is used in electric shock early warning technical field. The power distribution operation anti-electric shock risk identification and early warning method comprises the following steps: time sequence alignment and grouping packaging of real-time working condition data to obtain synchronous working condition data, electric shock risk quantitative calculation of the synchronous working condition data according to safety regulation parameters and risk weight coefficients to obtain a basic electric shock risk value, real-time interference data is determined according to the synchronous working condition data, scene coupling interference correction of the basic electric shock risk value according to the real-time interference data to obtain an optimized electric shock risk value, conversion of the optimized electric shock risk value into an early warning level according to a risk and early warning mapping rule, and alarm through an early warning mode according to the early warning level. Through scene interference correction and hierarchical early warning linkage, the embodiment of the application realizes accurate identification and hierarchical early warning of electric shock risk in power distribution operation.

Description

Technical Field

[0001] This application relates to the field of electric shock early warning technology, and in particular to a method and system for identifying and warning of electric shock risks during power distribution operations. Background Technology

[0002] With the continuous expansion of urban and rural power distribution networks and the coexistence of various work scenarios such as overhead lines, cable wells, ring main units, transformer substations, and multi-circuit lines on the same pole, the frequency of live-line work, power outage maintenance, and emergency repairs is constantly increasing, making electric shock one of the most significant personal safety risks. Due to factors such as diverse voltage levels, frequent personnel movement, rapid changes in posture, large fluctuations in ambient temperature and humidity, and interference from harmonics and line layouts, the requirements for electric shock risk identification and early warning at work sites have shifted from simply "being able to sound an alarm" to "being able to accurately identify, promptly classify, and adapt to different scenarios."

[0003] Existing methods for identifying electric shock risks in power distribution work mainly fall into three categories: manual monitoring, external fixed monitoring and early warning systems, and wearable proximity warning systems with fixed thresholds. Manual monitoring relies on the experience and judgment of safety supervisors and on-site verbal reminders. Fixed monitoring relies on monitoring equipment deployed at locations such as power poles and ring main units. Wearable solutions mostly trigger audible and visual alarms by setting preset electric field strength thresholds. While these methods can, to some extent, alert workers to stay away from live parts, they are essentially still based on single thresholds or human experience and have not yet formed a comprehensive identification mechanism for multi-source working conditions, different types of electric shock, and scene interference factors at the work site.

[0004] It should be noted that the above content is not necessarily prior art, nor is it intended to limit the scope of patent protection of this application. Summary of the Invention

[0005] This application provides a method and system for identifying and warning of electric shock risks during power distribution operations, in order to solve or alleviate one or more of the technical problems mentioned above.

[0006] One aspect of this application provides a method for identifying and warning of electric shock risks during power distribution operations, the method comprising: Real-time operating data from power distribution work sites is time-aligned and grouped for encapsulation to obtain synchronized operating data. Based on preset safety procedure parameters and preset risk weight coefficients, the electric shock risk is quantified and calculated for the synchronous working condition data to obtain a basic electric shock risk value. Based on the synchronous operating condition data, real-time interference data in the power distribution operation site is determined, and the basic electric shock risk value is corrected for scene coupling interference based on the real-time interference data to obtain an optimized electric shock risk value. According to the preset risk and warning mapping rules, the optimized electric shock risk value is converted into a warning level, so as to trigger an alarm according to the warning level through a preset warning method.

[0007] Optionally, the step of performing time-series alignment and grouping / encapsulation processing on the real-time operating data at the power distribution work site to obtain synchronized operating data includes: The sensor data is collected in real time by a preset mobile sensing device, including instantaneous electric field intensity, worker coordinates, attitude angle, ambient temperature and relative humidity. According to the preset power distribution operation plan, the rated voltage data, operation type code and line layout parameters of the current operation are read from the preset power grid database to form a combination of power distribution and operation parameters, and the total harmonic distortion value of the line is collected in real time through the preset harmonic detector. According to the preset time synchronization window, the sensor data, the power distribution and operation parameter combination, and the total harmonic distortion value are time-aligned and grouped and encapsulated to obtain synchronized operating condition data with the same timestamp.

[0008] Optionally, the step of quantifying the electric shock risk of the synchronous operating condition data based on preset safety procedure parameters and preset risk weighting coefficients to obtain a basic electric shock risk value includes: Based on the preset electric field non-uniformity coefficient, the instantaneous electric field strength, and the rated voltage data, the equivalent straight-line distance between the operator and the live conductor is calculated. The attitude angle is mapped to a risk amplification factor by a preset attitude and risk mapping rule, and the first electric shock risk value is calculated based on the ratio between the equivalent straight distance and the preset minimum safe distance threshold, as well as the risk amplification factor. The pollution level of the work point is obtained from the preset safety procedure parameters based on the work point coordinates in the power distribution work plan. The corresponding pollution correction coefficient is obtained from the preset pollution correction coefficient table based on the pollution level. The corresponding humidity correction coefficient is obtained from the preset humidity correction coefficient table based on the ambient relative humidity. The critical distance for arc breakdown is calculated based on the rated voltage data, the humidity correction factor, and the pollution correction factor. The risk value of arc burn is calculated based on the equivalent straight distance and the critical distance for arc breakdown. Based on the first electric shock risk value, the arc burn risk value, and the work type code, a corresponding first weight coefficient set is obtained from a preset risk weight coefficient library. The first electric shock risk value and the arc burn risk value are then weighted and summed according to the first weight coefficient set to obtain a basic electric shock risk value.

[0009] Optionally, the method further includes: When the line layout parameters are adjacent to a live line, the electromagnetic induction voltage value is calculated based on the electrical parameters of the adjacent live line, and the second electric shock risk value is calculated based on the ratio between the electromagnetic induction voltage value and the preset induction voltage safety threshold. When a preset ground fault sign is obtained, the step voltage value is calculated based on the coordinates of the operator, the coordinates of the work point, and the preset ground potential change data. The third electric shock risk value is calculated based on the ratio of the step voltage value to the preset step voltage safety threshold. According to the job type code, the corresponding second weight coefficient set is obtained from the risk weight coefficient library. Based on the second weight coefficient set and the first weight coefficient set, the first electric shock risk value, the arc burn risk value, the second electric shock risk value and the third electric shock risk value are weighted and summed to obtain the basic electric shock risk value.

[0010] Optionally, the step of determining real-time interference data at the power distribution work site based on the synchronous operating condition data, and then correcting the basic electric shock risk value for scene-coupled interference based on the real-time interference data to obtain an optimized electric shock risk value includes: Based on the relative humidity and ambient temperature in the synchronous operating data, the corresponding basic environmental interference coefficient is obtained from the preset correction coefficient table, and based on the weather data obtained in real time from the preset weather service interface and the pollution level, the real-time environmental adjustment coefficient is obtained from the preset environmental adjustment coefficient set, so as to correct the basic environmental interference coefficient according to the real-time environmental adjustment coefficient to obtain the environmental interference correction coefficient. The corresponding job type correction coefficient is obtained from the correction coefficient table based on the job type code in the synchronous working condition data, and the corresponding line layout correction coefficient is obtained from the correction coefficient table based on the line layout parameters. The harmonic interference correction coefficient is calculated based on the total harmonic distortion value in the synchronous operating condition data using a preset piecewise linear function. Based on the environmental interference correction coefficient, the line layout correction coefficient, the harmonic interference correction coefficient, and the work type correction coefficient, the basic electric shock risk value is adjusted for interference to obtain an optimized electric shock risk value.

[0011] Optionally, the step of converting the optimized electric shock risk value into a warning level according to a preset risk-warning mapping rule, and then triggering an alarm based on the warning level using a preset warning method, includes: The optimized electric shock risk value is compared with a preset set of threshold intervals, wherein the set of threshold intervals includes a attention level interval, a warning level interval, and a danger level interval. When the optimized electric shock risk value falls within the attention level range, the optimized electric shock risk value is converted into a first-level warning instruction according to the risk and warning mapping rule, so as to control the preset target device to emit a preset prompt sound and a preset yellow light according to the first-level warning instruction; When the optimized electric shock risk value falls within the warning level range, the optimized electric shock risk value is converted into a secondary warning instruction according to the risk and warning mapping rule. The target device is then controlled to emit a preset alarm sound and a preset orange light according to the secondary warning instruction, and a preset warning message is sent to a preset on-site monitoring terminal. When the optimized electric shock risk value falls within the dangerous range, the optimized electric shock risk value is converted into a level three warning instruction according to the risk and warning mapping rule. Based on the level three warning instruction, the target device is controlled to emit a preset whistling sound and a preset red light, and a preset emergency alarm message is sent to a preset background management platform.

[0012] Optionally, the method further includes: Calculate the difference between the optimized electric shock risk value and the safety control threshold to obtain the risk deviation amount; When the risk deviation is greater than zero, the corresponding environmental coefficient adjustment, harmonic coefficient adjustment, risk amplification factor adjustment, and sampling period adjustment are obtained from the preset adjustment mapping table based on the risk deviation. The difference between each basic environmental disturbance coefficient in the correction coefficient table and the environmental coefficient adjustment amount is calculated to update the correction coefficient table. The difference between each risk amplification factor in the attitude and risk mapping rule and the risk amplification factor adjustment amount is calculated to update the attitude and risk mapping rule. The difference between the sampling period of the real-time operating data and the adjustment amount of the sampling period is calculated to update the sampling period, and the difference between the preset harmonic segmentation threshold and the adjustment amount of the harmonic coefficient is calculated to update the piecewise linear function.

[0013] Another aspect of this application provides a power distribution operation electric shock risk identification and early warning device, the device comprising: The fusion synchronization module is used to perform time-series alignment and grouping and encapsulation processing on real-time operating data at the power distribution operation site to obtain synchronized operating data. The risk quantification module is used to perform electric shock risk quantification calculation on the synchronous working condition data according to preset safety procedure parameters and preset risk weight coefficients to obtain a basic electric shock risk value. The interference correction module is used to determine the real-time interference data in the power distribution operation site based on the synchronous operating condition data, so as to perform scene coupling interference correction on the basic electric shock risk value based on the real-time interference data and obtain an optimized electric shock risk value. The risk warning module is used to convert the optimized electric shock risk value into a warning level according to a preset risk and warning mapping rule, so as to trigger an alarm according to the warning level through a preset warning method.

[0014] Another aspect of this application provides a computer device, including: At least one processor; and A memory that is communicatively connected to the at least one processor; Wherein: the memory stores instructions that can be executed by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method as described above.

[0015] Another aspect of this application provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the method described above.

[0016] Another aspect of this application provides a computer program product including a computer program that, when executed by a processor, implements the method described above.

[0017] The embodiments of this application employing the above-described technical solution may have the following advantages: 1. By synchronously fusing multiple sources of data, such as instantaneous electric field intensity, personnel coordinates, attitude angle, ambient temperature and humidity, rated voltage, operation type, line layout, and harmonic distortion, and combining them with safety procedure parameters and risk weight coefficients to carry out quantitative calculations, a multi-dimensional comprehensive risk identification is achieved, improving the completeness and accuracy of risk identification.

[0018] 2. By introducing environmental interference correction, line layout correction, harmonic interference correction, and work type correction, scenario coupling correction is performed on the risks under different weather conditions, different line structures, and different working conditions, making the risk values ​​closer to the actual field conditions, thereby reducing the problems of misjudgment and omission caused by complex changes in the field.

[0019] 3. The optimized electric shock risk value is mapped to three levels of early warning: attention, warning, and danger. The system is linked to sound and light signals, on-site monitoring terminals, and the back-end management platform to achieve a layered alarm mechanism from low to high and from on-site to back-end. This can not only remind workers in advance, but also quickly trigger the control response when there is a high risk, thus improving the efficiency of electric shock prevention. Attached Figure Description

[0020] The accompanying drawings exemplify embodiments and form part of the specification, serving together with the textual description to explain exemplary implementations of the embodiments. The illustrated embodiments are for illustrative purposes only and do not limit the scope of the claims. Throughout the drawings, the same reference numerals refer to similar but not necessarily identical elements.

[0021] Figure 1 The schematic diagram illustrates a flowchart of a method for identifying and warning of electric shock risks during power distribution operations according to Embodiment 1 of this application; Figure 2 This schematic diagram illustrates the functional block diagram of the power distribution operation electric shock risk identification and early warning device according to Embodiment 2 of this application; Figure 3 A schematic diagram of the hardware architecture of a computer device according to Embodiment 3 of this application is shown. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0023] It should be noted that the descriptions involving "first," "second," etc., in the embodiments of this application are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one feature. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0024] In the description of this application, it should be understood that the numerical labels before the steps do not indicate the order of the steps, but are only used to facilitate the description of this application and to distinguish each step, and therefore should not be construed as a limitation of this application.

[0025] For ease of understanding, an exemplary runtime environment is provided below: Example 1 like Figure 1 The diagram shown is a flowchart of the method for identifying and warning of electric shock risks during power distribution work provided in this application embodiment. The method for identifying and warning of electric shock risks during power distribution work provided in this application embodiment includes the following steps.

[0026] Step S1: Perform time-series alignment and grouping encapsulation processing on the real-time operating data of the power distribution operation site to obtain synchronized operating data.

[0027] First, it is necessary to collect, integrate, and synchronize data at the power distribution work site. The real-time operating data collected refers to all dynamic information collected during the power distribution work process by various sensors deployed on the wearable devices of the workers and on-site edge computing terminals, reflecting the workers' own status, the surrounding electric field environment, spatial location, meteorological conditions, and the operating status of the power grid lines. Specifically, real-time operating data includes, but is not limited to: instantaneous electric field intensity values ​​obtained by continuous sampling at 10ms intervals from the MEMS electric field sensor on top of the safety helmet and after median filtering; three-dimensional spatial coordinates of the worker's head or torso center point obtained by differential calculation between the real-time dynamic positioning module and the ground reference station, including longitude, latitude, and altitude, with centimeter-level accuracy; body pitch angle, roll angle, and heading angle output at 20ms intervals by the six-axis inertial measurement unit, as well as the hand lifting height estimated by acceleration integration; ambient temperature and relative humidity measured at 100ms intervals by temperature and humidity sensors; total harmonic distortion (THD) values ​​of the line collected by a portable harmonic detector (usually in percentage form); and rated voltage level, work type code, and line layout parameters (such as the number of loops on the same pole, the energized status of adjacent lines, and the spacing between parallel lines) read from the power grid work permit system and geographic information system. All of the above data have their own independent timestamps at the time of collection and have not undergone unified alignment processing, therefore they cannot be directly used for subsequent risk quantification calculations.

[0028] To obtain synchronous operating condition data usable for subsequent calculations, sensor fusion and time-series alignment processing are performed. First, instantaneous electric field strength, worker coordinates, attitude angles, ambient temperature, and relative humidity are collected in real time using pre-set mobile sensing devices to form sensor data. Specifically, after the worker enters the site and begins work, the edge computing terminal initiates multiple parallel acquisition threads. The electric field sensor converts the analog voltage signal into a digital quantity at a 10ms cycle and stores it in a circular buffer of length 5. Every 50ms, the system retrieves the five most recent values ​​from this buffer, sorts them in ascending order, and takes the median value as the effective electric field strength for that period, thereby eliminating high-frequency random noise and single abnormal jumps. The real-time dynamic positioning module outputs differentially corrected three-dimensional coordinates at a 20ms cycle. The system directly takes the last updated coordinate value within each synchronization cycle as the representative value, because the difference between two adjacent coordinates is on the order of centimeters, which is sufficient to meet the accuracy requirements for safe distance calculation. The attitude sensor outputs attitude angles, including pitch, roll, and yaw angles, at 20ms intervals. Simultaneously, it estimates the hand's lift relative to the shoulder using the accelerometer's vertical integration; this height is used to determine if there is a dangerous action of raising the hand into a live area. The temperature and humidity sensor outputs ambient temperature and relative humidity at 100ms intervals. The system maintains the previous values ​​for each 50ms synchronization cycle because temperature and humidity change slowly on a second-scale timescale. All sensor data is timestamped at its respective sampling time and stored in the edge computing terminal's real-time database.

[0029] Secondly, based on the pre-set power distribution work plan, the system reads the rated voltage data, work type code, and line layout parameters of the current work from the pre-set power grid database, forming a power distribution and work parameter combination. A pre-set harmonic detector then collects the total harmonic distortion value of the line in real time. Specifically, before the work begins, the work supervisor scans the work ticket QR code via a mobile terminal or manually enters the work ticket number. The edge computing terminal then obtains detailed information about the work from the power grid company's work ticket system interface, including the line number, rated voltage data (e.g., 10 kV or 35 kV), work type code (e.g., 01 for live-line work, 02 for power outage maintenance of multiple circuits on the same pole, 03 for cable well work, etc.), a description of the power outage area, and the work supervisor's contact information. Simultaneously, the terminal queries the topology of overhead lines and cables within a 50-meter radius of the work point from the power grid geographic information system interface, obtaining parameters such as the number of circuits on the same pole, the energized status of each circuit (updated in real time via switch status), the spacing and energized status of parallel lines, etc. These parameters are organized into a line layout parameter set. In addition, on-site operators clamp the current of a portable harmonic detector to the incoming line or temporary grounding wire of the distribution box. The detector measures the total harmonic distortion (THD) of voltage or current at 200ms intervals and sends the latest reading to the edge computing terminal every 50ms via Bluetooth or Wi-Fi. All the data from the external system (rated voltage, operation type, wiring layout, harmonic distortion) is not naturally aligned with the sensor data in time. For example, the update cycle for harmonic distortion is 200ms, while that of the electric field sensor is 10ms; therefore, time alignment processing is necessary.

[0030] Finally, according to the preset time synchronization window, the sensor data, power distribution and operation parameter combinations, and total harmonic distortion (THD) values ​​are time-aligned and grouped for encapsulation to obtain synchronized operating condition data with the same timestamp. Specifically, a real-time operating system runs within the edge computing terminal, which includes a hardware timer interrupt with a period of 50ms. Each time an interruption occurs, the system performs the following alignment and encapsulation actions: It retrieves the median of the last 5 samples from the electric field sensor buffer as the electric field strength E for the current period; it retrieves the last updated coordinates (X, Y, Z) from the real-time dynamic positioning module; it retrieves the last updated pitch angle, roll angle, and hand lift height from the attitude sensor; it retrieves the most recently measured ambient temperature and relative humidity from the temperature and humidity sensor; it reads the pre-loaded rated voltage data and work type code from the work ticket system cache; it reads the current period's line layout parameter package (including the number of circuits on the same pole, adjacent energized markers, and parallel line spacing) from the geographic information system cache; and it reads the most recently measured total harmonic distortion from the harmonic detector cache (if the timestamp of this measurement differs from the current interruption time by more than 100ms, the previous valid value is used). All of these fields are written into a predefined data structure, the first field of which is the current interruption system clock count value (accurate to ms), serving as a unified timestamp. At this point, a complete synchronous operating condition data structure is constructed. All fields in each frame of synchronized working condition data correspond to the working site status within the same 50ms time synchronization window, eliminating the time misalignment problem caused by different sampling rates and transmission delays of different sensors.

[0031] Step S2: Based on the preset safety procedure parameters and preset risk weight coefficients, perform electric shock risk quantification calculation on the synchronous working condition data to obtain the basic electric shock risk value.

[0032] Since the safe distance thresholds for different voltage levels are different, and the proportions of various electric shock risks vary significantly in different work scenarios, the electric field strength or distance values ​​cannot be directly used as risk values. Instead, a series of physical transformations and weightings must be used to map the original measured values ​​to a unified risk scoring range.

[0033] First, based on the preset electric field non-uniformity coefficient, instantaneous electric field strength, and rated voltage data, the equivalent straight-line distance between the worker and the live conductor is calculated. It should be understood that the electric field sensor measures the spatial electric field strength at the worker's head position. This electric field strength is inversely proportional to the voltage level of the live conductor and the distance between the worker and the live conductor. In the ideal case of a single-circuit overhead line with no nearby interference, the product of electric field strength and distance is approximately equal to the product of voltage and electric field non-uniformity coefficient. Specifically, the rated voltage data U and instantaneous electric field strength E are read from the synchronous operating condition data. The electric field non-uniformity coefficient k is retrieved from the preset safety procedure parameters. This coefficient is determined by the line layout: 0.8 for a single-circuit overhead line, 1.2 for a double-circuit line on the same pole, and 1.5 for a four-circuit or higher line on the same pole. The equivalent straight-line distance d is then calculated using the formula d = (k × U) / E. When the electric field strength increases or the rated voltage decreases, the calculated distance decreases, indicating that the worker is closer to the live conductor. Before calculation, the system checks if E is less than 0.01 kV / m. If it is, the distance is directly determined to be infinite, and subsequent related risk values ​​are set to 0 to avoid division by zero errors. The equivalent straight-line distance converts the electric field strength into an intuitive spatial distance, which can then be compared with various distance thresholds specified in safety regulations.

[0034] At the same spatial distance, the probability of accidental contact increases exponentially when workers are in unstable postures such as bending over or raising their hands. Therefore, this application maps posture angles to risk amplification factors using a posture-risk mapping rule, and calculates a first electric shock risk value based on the equivalent straight-line distance and this risk amplification factor. The first electric shock risk value represents the risk of electric shock from direct contact, i.e., the danger of workers' bodies or hand tools directly touching a live conductor. First, the pitch and roll angles of the workers are read from the synchronous working condition data. In this embodiment, the posture-risk mapping rule is a predefined judgment logic: if the absolute value of the pitch angle is greater than 30 degrees, it indicates that the worker's body is excessively leaning forward or backward; or if the absolute value of the roll angle is greater than 20 degrees, it indicates that the body is excessively tilted to the side; or if the hand lifting height obtained from the posture sensor integration is greater than 30 centimeters, it indicates that the worker has made a dangerous action that may cause their hand or head to enter within the safe distance of the live conductor. When any of the above conditions are met, the risk amplification factor α is set to 1.5; otherwise, it is set to 1.0. Then, the minimum safe distance threshold ds corresponding to the current rated voltage is retrieved from the preset safety procedure parameters. The ratio of the equivalent straight-line distance d to the threshold ds is calculated. However, it should be noted that the closer the distance, the greater the risk. Therefore, ds is divided by d, and then multiplied by 100 to normalize the result to the range of 0 to 100. The normalized median value is multiplied by the risk amplification factor α and truncated to the range of 0 to 100 to obtain the first electric shock risk value R1.

[0035] Because the insulation strength of air and the flashover voltage on the insulator surface vary significantly with humidity and pollution levels, the probability of arc breakdown in high humidity or high pollution environments is much higher than in dry and clean environments at the same distance and voltage. Therefore, this application introduces two correction coefficients (i.e., humidity correction coefficient and pollution correction coefficient) to adjust the calculated critical arc breakdown distance. First, the pollution level of the work point is obtained from the preset safety regulations parameters based on the work point coordinates in the power distribution work plan. Then, the corresponding pollution correction coefficient is obtained from the preset pollution correction coefficient table based on the pollution level, and the corresponding humidity correction coefficient is obtained from the preset humidity correction coefficient table based on the ambient relative humidity. The pollution level is an enumerated identifier characterizing the long-term degree of contamination on the insulator surface of the equipment corresponding to the work location, divided into levels 0, I, II, III, and IV. This data is pre-stored in the power grid geographic information system and can be matched based on the work point coordinates. The pollution correction factor table in this application provides the numerical coefficient corresponding to each pollution level. For example, level 0 corresponds to 1.0, level I to 0.95, level II to 0.85, level III to 0.70, and level IV to 0.50. Simultaneously, the ambient relative humidity is read from the synchronous operating data. The humidity correction factor table maps the relative humidity range to coefficient values: 0.9 for relative humidity < 30%, 1.0 for 30% to 50%, 0.95 for 50% to 70%, 0.85 for 70% to 80%, 0.70 for 80% to 90%, and 0.50 for relative humidity > 90%. The pollution correction factor and humidity correction factor are obtained by looking up the table.

[0036] Arc burns are the second most serious form of injury after direct contact electric shock in live-line work and emergency repair scenarios. To assess the possibility of arc discharge between workers and live conductors, resulting in burns, this application calculates the critical arc breakdown distance based on rated voltage data, humidity correction factors, and pollution correction factors. Furthermore, it calculates the arc burn risk value based on the relationship between the equivalent straight-line distance and the critical arc breakdown distance. According to the known air insulation strength coefficient Ka = 500 kV / m under standard atmospheric conditions (obtainable through experimental statistics), the critical arc breakdown distance da is calculated as da = U / (Ka × Kh × Kp), where Kh is the humidity correction factor and Kp is the pollution correction factor. This represents the maximum distance at which an air gap can withstand an air gap without breakdown at a given voltage level. Higher humidity or more severe pollution results in smaller humidity and pollution correction factors Kh and Kp, leading to a larger critical arc breakdown distance da, meaning that arc discharge may occur at greater distances. After obtaining the critical arc breakdown distance *da*, the equivalent straight-line distance *d* is compared with the critical arc breakdown distance *da*. If *d* ≥ 2 *da*, the arc risk is considered negligible, and the arc burn risk value *R4* is set to 0. If *d* < *da*, it is considered to be within the arc breakdown range, and the risk reaches its maximum value of 100. If *d* is between *da* and 2 *da*, it is calculated linearly: *R4* = ×200, and truncate the result to between 0 and 100.

[0037] In scenarios involving only direct contact and arc burns, the basic electric shock risk value is calculated by weighting the first electric shock risk value and the arc burn risk value obtained above. In this application, the weighting coefficients used in this operation (i.e., the first set of weighting coefficients) are stored in a preset risk weighting coefficient library. This library is organized according to different work type codes. For example, for 10 kV live-line work, the direct contact electric shock risk weight w1 is 0.55, and the arc burn risk weight w4 is 0.45 (where the first set of weighting coefficients must satisfy: w1 + w4 = 1). Based on the work type code obtained above, w1 and w4 can be directly read from the coefficient library, and the basic electric shock risk value Rb = w1 × R1 + w4 × R4. The result of this weighted summation ranges from 0 to 100; a larger value indicates a higher overall electric shock risk. Different work types have different main risk sources. The weighting coefficients can guide the system to focus on the most likely accident type in the current scenario, avoiding the average distribution of weights which could overwhelm the main risks.

[0038] In one optional implementation, after obtaining the arc burn risk value, the calculation of induced voltage electric shock risk (i.e., the second electric shock risk value) and step voltage electric shock risk (i.e., the third electric shock risk value) is further added to adapt to special scenarios such as power outage maintenance, multiple circuits on the same pole, and cable well operations.

[0039] First, determine if there are any adjacent energized lines in the line layout parameters. If so, calculate the electromagnetic induction voltage value based on the electrical parameters of the adjacent energized lines, including but not limited to the line layout parameters and current carrying capacity.

[0040] First, based on the power distribution work plan and the coordinates of the work point, the current carrying capacity Ia of the adjacent live lines is retrieved from the preset power grid database. The electromagnetic induction voltage value is calculated based on the current carrying capacity, fault distance, and pollution correction factor. In this application, the calculation of the induced voltage uses a simplified electromagnetic induction model: Ui = M × Ia × f × Lc, where M is the mutual inductance coefficient. When the line layout parameters are lines on the same pole, M is taken as 2.0 microhenries per meter; when the line layout parameters are parallel lines, M is taken as 1.2 microhenries per meter. f is the power grid frequency of 50 Hz. Lc is the coupling length. When the line layout parameters are lines on the same pole, Lc is taken as half of the pole span (approximately 50 meters); when the line layout parameters are parallel lines, Lc is taken as the length of the parallel section in the line layout parameters. After obtaining the induced voltage value Ui, the induced voltage safety threshold Uis (usually 36 volts) is retrieved from the preset safety procedure parameters. The second electric shock risk value is then expressed as: The second electric shock risk value calculation identifies the induced voltage generated on the de-energized line due to electromagnetic coupling from nearby live lines during power outage operations. This voltage is potentially fatal and highly concealed. The electrical parameters of the nearby live lines include, but are not limited to, line layout parameters and current carrying capacity.

[0041] Simultaneously, when a ground fault flag is obtained from the preset work registration system based on the work point coordinates, a step voltage risk calculation is performed. The ground fault flag is a Boolean identifier with a value of "fault present" or "no fault present." This flag originates from the substation's zero-sequence current over-limit alarm or the fault description in the work ticket system. If the flag indicates a fault, the corresponding soil resistivity ρ is obtained from the preset geographic information system based on the worker's coordinates. The fault distance is then calculated based on the work point coordinates and the worker's coordinates. The fault distance refers to the straight-line horizontal distance between the worker's current location and the predicted or real-time detected ground fault point. This distance is calculated by performing Euclidean distance calculations between the worker's three-dimensional coordinates and the fault point coordinates obtained from the power grid geographic information system. It should be understood that the ground potential change data used in the calculation refers to a set of empirical parameters or numerical models pre-stored in the edge computing terminal or the back-end safety management platform to describe the spatial distribution characteristics of the surface potential around the ground fault point. This data is generated based on the physical process of current diffusion during a ground fault. When a fault current is injected into a grounding electrode (such as a tower grounding electrode or a substation grounding grid), the current diffuses in the soil, causing different potential values ​​at different locations on the ground surface relative to infinity (or a reference ground). The magnitude of the potential is closely related to the fault current value, soil resistivity, straight-line distance from the fault point, and the geometry of the grounding electrode. To quickly calculate step voltage in actual operation sites without having to solve complex electromagnetic field equations in real time each time, the system pre-constructs grounding potential change data using one of the following two methods.

[0042] The first method is based on theoretical calculations using the standard grounding hemispherical model. For independent tower grounding electrodes or vertical grounding electrodes, they can be equivalently represented as hemispherical grounding bodies in engineering practice. In this case, the relationship between the surface potential V(r) at a horizontal distance r from the fault point, the fault current If, and the soil resistivity ρ satisfies the formula V(r) = ... / (2πr). The system pre-stores the potential-distance curves under different combinations of fault current ranges (e.g., 0 to 100 amperes, 100 to 500 amperes, 500 to 1000 amperes, etc.) and different soil resistivity ranges (e.g., 0 to 100 ohm-meters, 100 to 300 ohm-meters, 300 to 600 ohm-meters, etc.) in the form of a lookup table. This lookup table is the preset grounding potential change data. In actual calculation, the system locates the corresponding potential-distance curve from the lookup table based on the currently read fault current If and soil resistivity ρ, and then inputs the fault distance to obtain the potential value at that point. Then, it calculates the potential difference between the known point (i.e., the point whose potential value is obtained by looking up the table by inputting the fault distance) and the new coordinate point obtained by superimposing the natural stride of a human body on the known point, which is the step voltage value.

[0043] The second approach is based on refined data pre-calculated using on-site measurements or electromagnetic simulation software (such as CDEGS). For complex grounding grids or multiple grounding electrodes connected in parallel, the system uses the finite element method or boundary element method to model the grounding system at a specific work site offline. Inputting parameters such as the actual soil layering structure, grounding electrode size and burial depth, and fault current amplitude, the system simulates and calculates a surface potential distribution cloud map of the entire area surrounding the fault point. This cloud map is discretized into grid point data, with each grid point containing coordinates and a corresponding potential value, stored as preset grounding potential change data. During actual operation, the system performs bilinear interpolation on the grid data based on the relative position (fault distance and direction) between the operator's current coordinates and the fault point coordinates to obtain the potential value at that point, and then calculates the step voltage value.

[0044] After obtaining the step voltage value, retrieve the step voltage safety threshold from the safety regulations. Generally, 125 volts is used near non-grounded electrodes, and 50 volts is used around grounded electrodes. This determines the third electric shock risk value. ,in, This is the step voltage value. This is the step voltage safety threshold. By calculating the third electric shock risk value, the potential difference that may occur between the worker's feet when a ground fault occurs is identified. This risk is particularly prominent in narrow areas such as cable wells and the base of towers.

[0045] Finally, based on the work type code, the second electric shock risk value, and the third electric shock risk value, the corresponding second weight coefficient set is obtained from the risk weight coefficient library. This second weight coefficient set includes the induced voltage weight w2 and the step voltage weight w3. Based on the first weight coefficient set, the weighted summation expression is expanded to four or more terms (where the first weight coefficient set and the second weight coefficient set must satisfy: w1 + w2 + w3 + w4 = 1). For example, in a scenario of multiple circuits on the same pole during power outage maintenance, the weight coefficients are w1 = 0.20, w2 = 0.60, w3 = 0.15, and w4 = 0.05. At this time, the basic electric shock risk value Rb = w1 × R1 + w2 × R2 + w3 × R3 + w4 × R4.

[0046] Step S3: Determine the real-time interference data in the power distribution operation site based on the synchronous operating condition data, and perform scene coupling interference correction on the basic electric shock risk value based on the real-time interference data to obtain an optimized electric shock risk value.

[0047] The real-time interference data includes correction coefficients for four types of scenario factors that can alter the accuracy of electric field measurements or the actual probability of electric shock: environmental interference correction coefficient, line layout correction coefficient, harmonic interference correction coefficient, and work type correction coefficient. In real power distribution work sites, the measurements from electric field sensors are affected by various factors such as ambient temperature and humidity, rain and fog, electric field superposition between lines, and grid harmonics, causing the instantaneous electric field strength used in step S2 to deviate from the true value when calculating the equivalent straight-line distance. Furthermore, different work types have different inherent risk levels, which also need to be reflected in the risk scoring. Without correction, the basic electric shock risk value may generate numerous false alarms due to artificially inflated electric fields in rainy or foggy weather, or may result in missed alarms in scenarios with multiple lines on the same pole due to improper amplification of electric field superposition.

[0048] First, based on the relative humidity and ambient temperature in the synchronized operating data, the system retrieves the corresponding basic environmental interference coefficient from a pre-set correction coefficient table. Then, based on real-time weather data and pollution levels obtained from a pre-set weather service interface, the system retrieves real-time environmental adjustment coefficients from a pre-set environmental adjustment coefficient set. These real-time environmental adjustment coefficients are used to correct the basic environmental interference coefficients, resulting in an environmental interference correction coefficient. The pre-set correction coefficient table stores the basic environmental interference coefficients using a combined index of relative humidity and temperature ranges. For example, when the relative humidity is between 30% and 50% and the temperature is between 10 and 30 degrees Celsius, the basic environmental interference coefficient is 1.00; when the relative humidity is between 70% and 80%, the basic environmental interference coefficient decreases to 0.85; and when the relative humidity exceeds 90%, the basic environmental interference coefficient decreases to 0.50. Simultaneously, the system obtains current weather data through a pre-set weather service interface (e.g., accessing real-time rainfall radar data from a meteorological department or manually inputting weather conditions by operators). The weather data is categorized into four levels: no rain, light rain, moderate rain, and heavy rain or above. The pollution level is an enumerated value obtained by matching the coordinates of the work point from preset safety procedure parameters. A preset environmental adjustment coefficient set stores real-time environmental adjustment coefficients for different combinations of weather levels and pollution levels. For example, the real-time environmental adjustment coefficient is 0.95 for light rain and pollution level I; 0.85 for moderate rain and pollution level II; and 0.70 for heavy rain and pollution level III or higher. The final value of the environmental interference correction coefficient is obtained by multiplying the basic environmental interference coefficient by the real-time environmental adjustment coefficient. This product is limited to between 0.50 and 1.00. High humidity and rainfall can change the dielectric constant of air, causing varying degrees of artificially inflated measurements from the electric field sensor. By reducing the environmental interference correction coefficient, the weight of the basic risk value can be reduced in the correction process, avoiding unnecessary warnings caused by measurement errors. For example, during power outage maintenance work in cable tunnels or outdoor ring main units, if it rains, the electric field sensor may misinterpret the coupling signal caused by humidity as the electric field of a charged body. Without correction, it will generate a false alarm, causing the workers to shut down the warning device.

[0049] Simultaneously, the corresponding work type correction coefficient is obtained from the correction coefficient table based on the work type code in the synchronous operating data, and the corresponding line layout correction coefficient is obtained from the correction coefficient table based on the line layout parameters. The work type code has already been obtained from the work ticket system in step S1, including types such as ground routine power outage maintenance, multi-circuit line power outage maintenance on the same pole, 10kV live-line work, emergency repair work, and indoor ring main unit work. In the above correction coefficient table, each work type corresponds to a work type correction coefficient. For example, ground routine power outage maintenance is assigned a coefficient of 1.00, multi-circuit line power outage maintenance on the same pole is assigned a coefficient of 1.20, 10kV live-line work is assigned a coefficient of 1.30, emergency repair work is assigned a coefficient of 1.25, and indoor ring main unit work is assigned a coefficient of 0.90. This coefficient reflects the inherent risk level differences of different work types. Live-line work and emergency repairs have a significantly higher electric shock accident rate than routine power outage maintenance due to their complexity and time constraints. Therefore, a coefficient greater than 1 is needed to amplify the risk value and improve the early warning sensitivity. The line layout correction coefficient is obtained based on the line layout parameters in the synchronous operating data. The line layout parameters include information such as the number of circuits on the same pole, the energized status of the working line, the energized status of adjacent lines, and the spacing between parallel lines. In this embodiment, the line layout correction coefficient is obtained from the correction coefficient table according to the following rules: 1.00 for a single circuit with no adjacent energized lines; 1.30 for a double circuit on the same pole with the working line de-energized and the other circuit energized; 1.50 for four or more circuits on the same pole with multiple circuits energized; 1.20 for parallel line spacing less than 10 meters with adjacent energized lines; and 1.10 for parallel line spacing between 10 and 20 meters. If the working line itself is energized (i.e., live-line work is underway), the coefficient obtained from the table needs to be multiplied by 0.80 for reduction, because the risk of direct contact has already been fully reflected in the first electric shock risk value in step S2, and there is no need to over-amplify it due to adjacent lines. The range of the line layout correction coefficient is limited to between 1.00 and 1.50. Because multiple circuits on the same pole or adjacent parallel lines create a superposition effect of electric fields, the actual electric field strength at the location of workers is higher than that under single-circuit operation, thus increasing the probability of electric shock from induced voltage and direct contact. For example, when a 10 kV line is de-energized for maintenance, another 10 kV line on the same pole remains energized. Although workers are in contact with the de-energized line, electromagnetic induction will induce a dangerous voltage on the de-energized line, and the electric field strength in the space will also increase due to the superposition. Therefore, a line layout correction factor greater than 1 is needed to amplify the basic risk value.

[0050] Meanwhile, this application calculates harmonic interference correction coefficients based on the total harmonic distortion (THD) value in the synchronous operating condition data using a preset piecewise linear function. The THD value in the synchronous operating condition data is the harmonic content of line voltage or current expressed as a percentage. Harmonic components can couple into the measurement bandwidth of the electric field sensor, causing the electric field strength reading to be artificially high, thus making the equivalent straight-line distance calculated in step S2 too small, leading to false alarms. The piecewise linear function used in this application divides the range of THD values ​​into multiple intervals, each interval corresponding to a harmonic interference correction coefficient. The specific rules are as follows: When the total harmonic distortion (THD) is less than or equal to 5%, the harmonic interference correction coefficient is 1.00; when the THD is greater than 5% and less than or equal to 10%, the coefficient linearly decreases from 1.00 to 0.95; when the THD is greater than 10% and less than or equal to 20%, the coefficient linearly decreases from 0.95 to 0.85; when the THD is greater than 20% and less than or equal to 30%, the coefficient linearly decreases from 0.85 to 0.75; and when the THD is greater than 30%, the coefficient is 0.60. The linear interpolation calculation method is as follows: for THD values ​​falling within the interval boundaries, the boundary coefficient is directly taken; for values ​​within the interval, the calculation is performed proportionally. For example, when THD is 12%, it is first determined to fall within the 10% to 20% range, with a range length of 10% and a coefficient difference of 0.10. The coefficient decreases from 0.95 at 10% by (12-10) / 10 = 0.2, therefore the coefficient is 0.95 - 0.2 × 0.10 = 0.93. The harmonic interference correction coefficient ranges from 0.60 to 1.00. When there are many nonlinear loads (such as frequency converters and rectifiers) in the power distribution line, harmonics will cause the output signal of the electric field sensor to contain additional frequency components, resulting in the measured value deviating from the true power frequency electric field strength. By reducing the harmonic interference correction coefficient, the artificially high risk value caused by harmonics can be suppressed, avoiding issuing warnings when there is no actual risk of electric shock. For example, in the power distribution lines of urban commercial areas, a large number of switching power supply devices will generate high harmonics. If no correction is made, workers may receive continuous false alarms due to harmonic interference during power outage maintenance.

[0051] Finally, based on the environmental interference correction coefficient, line layout correction coefficient, harmonic interference correction coefficient, and work type correction coefficient obtained above, the basic electric shock risk value is corrected for interference. Specifically, the four correction coefficients are multiplied to obtain a comprehensive correction coefficient Kt, which is limited to between 0.50 and 1.50 to prevent overcorrection caused by a single extreme coefficient. Then, the basic electric shock risk value Rb obtained in step S2 is multiplied by the comprehensive correction coefficient Kt to obtain the corrected accurate comprehensive risk value Rr, i.e., Rr = Rb × Kt. The accurate comprehensive risk value is also truncated to the range of 0 to 100, serving as the final optimized electric shock risk value output. The four independent interference factors—environment, line, harmonics, and work type—are coupled together in a product form and act on the basic risk value simultaneously. Since the impact of these factors on risk is multiplicative rather than additive (for example, when high humidity and high harmonics coexist, the degree of artificial electric field elevation is the superposition of their effects, which is represented by multiplication in the correction coefficient), the use of multiplication is reasonable. Through this correction, the system can reduce false alarms in complex scenarios with rain, fog, and harmonics by lowering the environmental and harmonic correction coefficients; and in scenarios with multiple circuits on the same pole and live-line work, it can enhance warning sensitivity by increasing the correction coefficients for line layout and work type. The final optimized electric shock risk value has eliminated various measurement interferences and truly reflects the degree of electric shock danger faced by workers in the current work scenario.

[0052] Step S4: According to the preset risk and warning mapping rules, the optimized electric shock risk value is converted into a warning level, so as to trigger an alarm according to the warning level through a preset warning method.

[0053] The optimized electric shock risk value is a continuously varying numerical value between 0 and 100. However, workers cannot directly perceive the degree of danger from this value, and supervisors cannot monitor the value changes in real time. Therefore, it is necessary to map this continuous value to discrete, intuitive warning levels and trigger corresponding audible and visual alarms and notifications. The preset risk and warning mapping rules divide the optimized electric shock risk value range into three continuous threshold intervals: the attention level interval, the warning level interval, and the danger level interval. In this embodiment, the attention level interval corresponds to a risk value greater than 30 and less than or equal to 60, indicating a potential electric shock hazard, requiring workers to remain vigilant; the warning level interval corresponds to a risk value greater than 60 and less than or equal to 90, indicating that the safe distance threshold is approaching, posing a moderate to high risk of electric shock; the danger level interval corresponds to a risk value greater than 90 and less than or equal to 100, indicating that the safe distance threshold has been exceeded, posing an immediate risk of electric shock. Furthermore, a risk value less than or equal to 30 falls within the safety level interval, where no warnings are triggered to maintain a quiet working environment and avoid unnecessary interference with workers.

[0054] When executing the warning level conversion, the edge computing terminal compares the optimized electric shock risk value with the boundary values ​​of the three threshold ranges mentioned above. First, it determines whether the risk value is greater than 30 and less than or equal to 60; if so, it is identified as a warning level. Then, according to the risk-warning mapping rule, the warning level is converted to a Level 1 warning command. The Level 1 warning command includes three parameters: sound pressure level, sound pattern, and light flashing frequency. It controls the preset target device (i.e., the smart safety helmet worn by the worker or a portable warning terminal) to emit a preset warning sound, a slow, evenly spaced "beep, beep" sound with a sound pressure level of 70 decibels, sufficient to be heard by workers in a noisy power distribution work environment without causing panic. Simultaneously, it controls the LED indicator to emit a preset yellow light, flashing 60 times per minute. The reason for emitting yellow light is that yellow represents "warning" or "caution" in industrial safety color codes, effectively attracting the worker's visual attention without triggering an emergency response. For example, in 10 kV live-line work, when the worker gradually approaches the live conductor but has not yet entered the danger zone, the optimized electric shock risk value may rise from 25 to 45, falling into the attention level range. At this time, the first-level warning reminds the worker to "maintain a safe distance" through sound and yellow light to prevent them from unconsciously continuing to approach.

[0055] When the optimized electric shock risk value is greater than 60 and less than or equal to 90, the system identifies it as a warning level and converts it into a Level 2 warning command according to the mapping rules. The Level 2 warning command controls the target equipment to emit a preset alarm sound, a rapid, high-frequency "beep beep beep" sound, with the sound pressure level increased to 85 decibels, to forcibly interrupt the worker's current operation and raise their alertness; simultaneously, it controls the LED indicator to emit a preset orange light, flashing at a frequency of 120 times per minute. Orange represents "danger" or "warning" in industrial safety color coding and has a stronger warning effect than yellow. In addition, the Level 2 warning command also triggers the sending of a preset warning message to a preset on-site monitoring terminal. The on-site monitoring terminal can be a tablet computer, smart bracelet, or walkie-talkie held by the monitor. The warning message includes "Danger! Please stop the dangerous action immediately!" as well as the name, location coordinates, and risk value of the current worker. Upon receiving this message, the monitor can immediately command the worker to stop and retreat via voice or wireless communication. For example, in a scenario where multiple circuits on the same pole are being repaired during a power outage, workers may fail to detect the risk in time due to the presence of induced voltage. When the optimized electric shock risk value rises from 55 to 75, a level two warning is triggered, and the workers themselves receive an urgent orange alarm. At the same time, a warning window pops up on the monitor's terminal, and the monitor immediately orders the workers to evacuate the area through a loudspeaker.

[0056] When the optimized electric shock risk value is greater than 90 and less than or equal to 100, the system identifies it as a dangerous level and converts it into a Level 3 warning command according to the mapping rules. The Level 3 warning command controls the target equipment to emit a preset shriek sound. This shriek sound is a continuous high-frequency sound with a sound pressure level of 100 decibels, which has extremely strong penetrating power and a sense of urgency, enabling the operator to make an instinctive avoidance reaction in the shortest possible time. At the same time, it controls the LED indicator to emit a preset red light, increasing the flashing frequency to 240 times per minute. Red represents "emergency" or "prohibition" in industrial safety color codes. The red light combined with the high-frequency flashing is clearly visible even in strong sunlight. In addition, the Level 3 warning command also triggers the sending of preset emergency alarm information to a preset background management platform. In this embodiment, the background management platform is the power grid company's safety monitoring center or dispatch center. The emergency alarm information includes the GPS coordinates of the work location, the operator's identification, the current optimized electric shock risk value, the trigger time, and a snapshot of the on-site operating parameters (electric field strength, distance, attitude angle, etc. in the most recent second). Upon receiving this information, the back-end management platform displays a red alarm window on the large screen and automatically dials the work supervisor and the emergency command center. For example, during emergency repair operations, if workers neglect safe distances in their haste to restore power, causing the optimized electric shock risk value to jump instantly from 80 to 95, a level-three warning is immediately triggered. The worker's helmet emits a piercing whistling sound and flashes a red light, forcing them to immediately retreat. Simultaneously, the back-end management platform receives an emergency alarm, and the dispatcher confirms the situation on-site via remote video and initiates the emergency response procedure.

[0057] To achieve closed-loop adjustment and dynamically optimize the sensitivity of risk calculation, the system automatically improves its identification capability after the warning level transition and when the risk continues to exceed the limit, thus avoiding missed detections. First, the difference between the optimized electric shock risk value and the safety control threshold is calculated to obtain the risk deviation. The safety control threshold is a pre-set fixed value of 60, which is the boundary between the attention level and the warning level. When the optimized electric shock risk value is greater than 60, the risk deviation is positive, indicating that the current risk has exceeded the safety control target and parameter adjustment is required. Specifically, based on the magnitude of the risk deviation, the system retrieves four types of adjustment quantities from a pre-set adjustment quantity mapping table: environmental coefficient adjustment, harmonic coefficient adjustment, risk amplification factor adjustment, and sampling period adjustment. The adjustment mapping table is a lookup table that maps risk deviation ranges (such as 0 to 5, 5 to 10, 10 to 15, etc.) to specific adjustment values. For example, when the risk deviation is 8, the environmental coefficient adjustment is 0.03, the harmonic coefficient adjustment is 0.02, the risk amplification factor adjustment is 0.10, and the sampling period adjustment is 5ms.

[0058] After obtaining the adjustment amount, the system performs four update operations. First, it calculates the difference between each basic environmental interference coefficient in the correction coefficient table and the environmental coefficient adjustment amount. That is, it subtracts the environmental coefficient adjustment amount from each basic environmental interference coefficient to obtain a new basic environmental interference coefficient, which is then used to update the correction coefficient table. This operation reduces the environmental interference correction coefficient, thereby reducing the suppression of the basic risk value and weakening the inhibitory effect of environmental factors on risk in subsequent calculations, making the system more sensitive to the identification of real risks. Second, it calculates the difference between each risk amplification factor in the attitude and risk mapping rules and the risk amplification factor adjustment amount. That is, it adds the risk amplification factor adjustment amount to each risk amplification factor (because the amplification effect needs to be increased) to obtain a new risk amplification factor, which is then used to update the attitude and risk mapping rules. This results in a larger risk amplification factor for operators in the same attitude, thereby improving the response sensitivity to dangerous actions. Third, it calculates the difference between the sampling period of the real-time operating data and the sampling period adjustment amount. That is, it subtracts the sampling period adjustment amount from the current sampling period to obtain a shorter sampling period, for example, shortening it from 50ms to 45ms or 30ms. Shorter sampling periods mean that the electric field sensor and positioning module collect data at a higher frequency, enabling them to capture minute changes in distance more quickly and trigger higher-level warnings earlier when risks escalate rapidly. Fourth, the preset harmonic segmentation thresholds and harmonic coefficient adjustments are compared using a difference calculation. Specifically, the harmonic coefficient adjustment is subtracted from each segment boundary value (e.g., 5%, 10%, 20%, 30%) in the harmonic piecewise linear function to obtain new segment boundary values, thus updating the piecewise linear function. This operation makes the harmonic interference correction coefficient smaller for the same total harmonic distortion, further reducing the suppression of risk values ​​by harmonics and improving the ability to identify the true electric field. All updated parameters are immediately written to the dynamic storage area of ​​the edge computing terminal and take effect at the start of the next 50ms cycle (or the updated sampling period). Through this closed-loop adjustment mechanism, the system can automatically increase sensitivity when risks continuously exceed limits, ensuring the timeliness and accuracy of warnings in high-risk scenarios.

[0059] Example 2 like Figure 2 The diagram shown illustrates the functional block diagram of a power distribution operation electric shock risk identification and early warning device according to an embodiment of this application. This device can be divided into one or more program modules, which are stored in a storage medium and executed by one or more processors to complete the embodiment of this application. The program module referred to in this embodiment is a series of computer program instruction segments capable of performing a specific function. The following description will specifically introduce the function of each program module in this embodiment. Figure 2As shown, the power distribution operation electric shock risk identification and early warning device 1000 may include: a fusion synchronization module 1100, a risk quantification module 1200, an interference correction module 1300, a risk early warning module 1400, and a deviation optimization module 1500, wherein: The fusion synchronization module 1100 is used to perform time-series alignment and grouping and encapsulation processing on real-time operating data at the power distribution operation site to obtain synchronized operating data. The risk quantification module 1200 is used to perform electric shock risk quantification calculation on the synchronous working condition data according to preset safety procedure parameters and preset risk weight coefficients to obtain a basic electric shock risk value. The interference correction module 1300 is used to determine the real-time interference data in the power distribution operation site based on the synchronous operating condition data, so as to perform scene coupling interference correction on the basic electric shock risk value based on the real-time interference data to obtain an optimized electric shock risk value. The risk warning module 1400 is used to convert the optimized electric shock risk value into a warning level according to a preset risk and warning mapping rule, so as to trigger an alarm according to the warning level through a preset warning method.

[0060] As an optional embodiment, the fusion synchronization module 1100 is used for: The sensor data is collected in real time by a preset mobile sensing device, including instantaneous electric field intensity, worker coordinates, attitude angle, ambient temperature and relative humidity. According to the preset power distribution operation plan, the rated voltage data, operation type code and line layout parameters of the current operation are read from the preset power grid database to form a combination of power distribution and operation parameters, and the total harmonic distortion value of the line is collected in real time through the preset harmonic detector. According to the preset time synchronization window, the sensor data, the power distribution and operation parameter combination, and the total harmonic distortion value are time-aligned and grouped and encapsulated to obtain synchronized operating condition data with the same timestamp.

[0061] As an optional embodiment, the risk quantification module 1200 is used for: Based on the preset electric field non-uniformity coefficient, the instantaneous electric field strength, and the rated voltage data, the equivalent straight-line distance between the operator and the live conductor is calculated. The attitude angle is mapped to a risk amplification factor by a preset attitude and risk mapping rule, and the first electric shock risk value is calculated based on the ratio between the equivalent straight distance and the preset minimum safe distance threshold, as well as the risk amplification factor. The pollution level of the work point is obtained from the preset safety procedure parameters based on the work point coordinates in the power distribution work plan. The corresponding pollution correction coefficient is obtained from the preset pollution correction coefficient table based on the pollution level. The corresponding humidity correction coefficient is obtained from the preset humidity correction coefficient table based on the ambient relative humidity. The critical distance for arc breakdown is calculated based on the rated voltage data, the humidity correction factor, and the pollution correction factor. The risk value of arc burn is calculated based on the equivalent straight distance and the critical distance for arc breakdown. Based on the first electric shock risk value, the arc burn risk value, and the work type code, a corresponding first weight coefficient set is obtained from a preset risk weight coefficient library. The first electric shock risk value and the arc burn risk value are then weighted and summed according to the first weight coefficient set to obtain the basic electric shock risk value.

[0062] As an optional embodiment, the risk quantification module 1200 is further configured to: When the line layout parameters are adjacent to a live line, the electromagnetic induction voltage value is calculated based on the electrical parameters of the adjacent live line, and the second electric shock risk value is calculated based on the ratio between the electromagnetic induction voltage value and the preset induction voltage safety threshold. When a preset ground fault sign is obtained, the step voltage value is calculated based on the coordinates of the operator, the coordinates of the work point, and the preset ground potential change data. The third electric shock risk value is calculated based on the ratio of the step voltage value to the preset step voltage safety threshold. According to the job type code, the corresponding second weight coefficient set is obtained from the risk weight coefficient library. Based on the second weight coefficient set and the first weight coefficient set, the first electric shock risk value, the arc burn risk value, the second electric shock risk value and the third electric shock risk value are weighted and summed to obtain the basic electric shock risk value.

[0063] As an optional embodiment, the interference correction module 1300 is further configured to: Based on the relative humidity and ambient temperature in the synchronous operating data, the corresponding basic environmental interference coefficient is obtained from the preset correction coefficient table, and based on the weather data obtained in real time from the preset weather service interface and the pollution level, the real-time environmental adjustment coefficient is obtained from the preset environmental adjustment coefficient set, so as to correct the basic environmental interference coefficient according to the real-time environmental adjustment coefficient to obtain the environmental interference correction coefficient. The corresponding job type correction coefficient is obtained from the correction coefficient table based on the job type code in the synchronous working condition data, and the corresponding line layout correction coefficient is obtained from the correction coefficient table based on the line layout parameters. The harmonic interference correction coefficient is calculated based on the total harmonic distortion value in the synchronous operating condition data using a preset piecewise linear function. Based on the environmental interference correction coefficient, the line layout correction coefficient, the harmonic interference correction coefficient, and the work type correction coefficient, the basic electric shock risk value is adjusted for interference to obtain an optimized electric shock risk value.

[0064] As an optional embodiment, the risk warning module 1400 is used for: The optimized electric shock risk value is compared with a preset set of threshold intervals, wherein the set of threshold intervals includes a attention level interval, a warning level interval, and a danger level interval. When the optimized electric shock risk value falls within the attention level range, the optimized electric shock risk value is converted into a first-level warning instruction according to the risk and warning mapping rule, so as to control the preset target device to emit a preset prompt sound and a preset yellow light according to the first-level warning instruction; When the optimized electric shock risk value falls within the warning level range, the optimized electric shock risk value is converted into a secondary warning instruction according to the risk and warning mapping rule. The target device is then controlled to emit a preset alarm sound and a preset orange light according to the secondary warning instruction, and a preset warning message is sent to a preset on-site monitoring terminal. When the optimized electric shock risk value falls within the dangerous range, the optimized electric shock risk value is converted into a level three warning instruction according to the risk and warning mapping rule. Based on the level three warning instruction, the target device is controlled to emit a preset whistling sound and a preset red light, and a preset emergency alarm message is sent to a preset background management platform.

[0065] Optionally, the power distribution operation electric shock risk identification and early warning device 1000 further includes a deviation optimization module 1500, which is used for: Calculate the difference between the optimized electric shock risk value and the safety control threshold to obtain the risk deviation amount; When the risk deviation is greater than zero, the corresponding environmental coefficient adjustment, harmonic coefficient adjustment, risk amplification factor adjustment, and sampling period adjustment are obtained from the preset adjustment mapping table based on the risk deviation. The difference between each basic environmental disturbance coefficient in the correction coefficient table and the environmental coefficient adjustment amount is calculated to update the correction coefficient table. The difference between each risk amplification factor in the attitude and risk mapping rule and the risk amplification factor adjustment amount is calculated to update the attitude and risk mapping rule. The difference between the sampling period of the real-time operating data and the adjustment amount of the sampling period is calculated to update the sampling period, and the difference between the preset harmonic segmentation threshold and the adjustment amount of the harmonic coefficient is calculated to update the piecewise linear function.

[0066] Example 3 Figure 3 This illustration schematically shows a hardware architecture diagram of a computer device 10000 suitable for implementing a method for identifying and warning of electric shock risks during power distribution operations, according to Embodiment 3 of this application. In some embodiments, the computer device 10000 may be a smartphone, a target device, a tablet computer, a personal computer, a vehicle terminal, a game console, a virtual device, a workbench, a digital assistant, a set-top box, a robot, or other terminal device. In other embodiments, the computer device 10000 may be a rack server, a blade server, a tower server, or a cabinet server (including a standalone server or a server cluster composed of multiple servers), etc. Figure 3 As shown, the computer device 10000 includes, but is not limited to: a memory 10010, a processor 10020, and a network interface 10030 that can communicate and be linked with each other via a system bus. Wherein: The memory 10010 includes at least one type of computer-readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 10010 may be an internal storage module of a computer device 10000, such as the hard disk or memory of the computer device 10000. In other embodiments, the memory 10010 may also be an external storage device of the computer device 10000, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 10000. Of course, the memory 10010 may also include both the internal storage module and the external storage device of the computer device 10000. In this embodiment, the memory 10010 is typically used to store the operating system and various application software installed on the computer device 10000, such as the program code for a method for identifying and warning of electric shock risks in power distribution operations. Furthermore, the memory 10010 can also be used to temporarily store various types of data that have already been converted into the optimized electric shock risk value according to preset risk and warning mapping rules, or that will be converted into the optimized electric shock risk value according to preset risk and warning mapping rules.

[0067] In some embodiments, processor 10020 may be a central processing unit (CPU), controller, microcontroller, microprocessor, or other chip. Processor 10020 is typically used to control the overall operation of computer device 10000, such as performing control and processing related to data interaction or communication with computer device 10000. In this embodiment, processor 10020 is used to run program code stored in memory 10010 or process data.

[0068] Network interface 10030 may include a wireless network interface or a wired network interface, which is typically used to establish a communication link between computer device 10000 and other computer devices. For example, network interface 10030 is used to connect computer device 10000 to an external terminal via a network, establishing a data transmission channel and communication link between computer device 10000 and the external terminal. The network may be an intranet, the Internet, Global System for Mobile Communication (GSM), Wideband Code Division Multiple Access (WCDMA), 4G network, 5G network, Bluetooth, Wi-Fi, or other wireless or wired networks.

[0069] It should be pointed out that, Figure 3 Only computer devices with components 10010-10030 are shown; however, it should be understood that it is not required to implement all of the shown components, and more or fewer components may be implemented instead.

[0070] In this embodiment, the power distribution operation electric shock risk identification and early warning method stored in memory 10010 can also be divided into one or more program modules and executed by one or more processors (such as processor 10020) to complete the embodiment of this application.

[0071] Obviously, those skilled in the art should understand that the modules or steps of the embodiments of this application described above can be implemented using general-purpose computer devices. They can be centralized on a single computer device or distributed across a network of multiple computer devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computer device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the embodiments of this application are not limited to any particular combination of hardware and software.

[0072] It should be noted that the above are merely preferred embodiments of this application and do not limit the scope of patent protection of this application. Any equivalent structural or procedural changes made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of this application.

Claims

1. A method for identifying and warning of electric shock risks during power distribution operations, characterized in that, The method includes: Real-time operating data from power distribution work sites is time-aligned and grouped for encapsulation to obtain synchronized operating data. Based on preset safety procedure parameters and preset risk weight coefficients, the electric shock risk is quantified and calculated for the synchronous working condition data to obtain a basic electric shock risk value. Based on the synchronous operating condition data, real-time interference data in the power distribution operation site is determined, and the basic electric shock risk value is corrected for scene coupling interference based on the real-time interference data to obtain an optimized electric shock risk value. According to the preset risk and warning mapping rules, the optimized electric shock risk value is converted into a warning level, so as to trigger an alarm according to the warning level through a preset warning method.

2. The method according to claim 1, characterized in that, The process of performing time-series alignment and grouping / encapsulation on real-time operating data at the power distribution work site to obtain synchronized operating data includes: The sensor data is collected in real time by a preset mobile sensing device, including instantaneous electric field intensity, worker coordinates, attitude angle, ambient temperature and relative humidity. According to the preset power distribution operation plan, the rated voltage data, operation type code and line layout parameters of the current operation are read from the preset power grid database to form a combination of power distribution and operation parameters, and the total harmonic distortion value of the line is collected in real time through the preset harmonic detector. According to the preset time synchronization window, the sensor data, the power distribution and operation parameter combination, and the total harmonic distortion value are time-aligned and grouped and encapsulated to obtain synchronized operating condition data with the same timestamp.

3. The method according to claim 2, characterized in that, The step of quantifying the electric shock risk based on preset safety procedure parameters and preset risk weight coefficients to obtain a basic electric shock risk value includes: Based on the preset electric field non-uniformity coefficient, the instantaneous electric field strength, and the rated voltage data, the equivalent straight-line distance between the operator and the live conductor is calculated. The attitude angle is mapped to a risk amplification factor by a preset attitude and risk mapping rule, and the first electric shock risk value is calculated based on the ratio between the equivalent straight distance and the preset minimum safe distance threshold, as well as the risk amplification factor. The pollution level of the work point is obtained from the preset safety procedure parameters based on the work point coordinates in the power distribution work plan. The corresponding pollution correction coefficient is obtained from the preset pollution correction coefficient table based on the pollution level. The corresponding humidity correction coefficient is obtained from the preset humidity correction coefficient table based on the ambient relative humidity. The critical distance for arc breakdown is calculated based on the rated voltage data, the humidity correction factor, and the pollution correction factor. The risk value of arc burn is calculated based on the equivalent straight distance and the critical distance for arc breakdown. Based on the first electric shock risk value, the arc burn risk value, and the work type code, a corresponding first weight coefficient set is obtained from a preset risk weight coefficient library. The first electric shock risk value and the arc burn risk value are then weighted and summed according to the first weight coefficient set to obtain a basic electric shock risk value.

4. The method according to claim 3, characterized in that, After obtaining the arc burn risk value, the method further includes: When the line layout parameters are adjacent to a live line, the electromagnetic induction voltage value is calculated based on the electrical parameters of the adjacent live line, and the second electric shock risk value is calculated based on the ratio between the electromagnetic induction voltage value and the preset induction voltage safety threshold. When a preset ground fault sign is obtained, the step voltage value is calculated based on the coordinates of the operator, the coordinates of the work point, and the preset ground potential change data. The third electric shock risk value is calculated based on the ratio of the step voltage value to the preset step voltage safety threshold. According to the job type code, the corresponding second weight coefficient set is obtained from the risk weight coefficient library. Based on the second weight coefficient set and the first weight coefficient set, the first electric shock risk value, the arc burn risk value, the second electric shock risk value and the third electric shock risk value are weighted and summed to obtain the basic electric shock risk value.

5. The method according to claim 3, characterized in that, The real-time interference data includes environmental interference correction coefficients, line layout correction coefficients, harmonic interference correction coefficients, and work type correction coefficients. The step of determining the real-time interference data at the power distribution work site based on the synchronous operating condition data, and then applying scene-coupled interference correction to the basic electric shock risk value based on the real-time interference data to obtain an optimized electric shock risk value, includes: Based on the relative humidity and ambient temperature in the synchronous operating data, the corresponding basic environmental interference coefficient is obtained from the preset correction coefficient table, and based on the weather data obtained in real time from the preset weather service interface and the pollution level, the real-time environmental adjustment coefficient is obtained from the preset environmental adjustment coefficient set, so as to correct the basic environmental interference coefficient according to the real-time environmental adjustment coefficient to obtain the environmental interference correction coefficient. The corresponding job type correction coefficient is obtained from the correction coefficient table based on the job type code in the synchronous working condition data, and the corresponding line layout correction coefficient is obtained from the correction coefficient table based on the line layout parameters. The harmonic interference correction coefficient is calculated based on the total harmonic distortion value in the synchronous operating condition data using a preset piecewise linear function. Based on the environmental interference correction coefficient, the line layout correction coefficient, the harmonic interference correction coefficient, and the work type correction coefficient, the basic electric shock risk value is adjusted for interference to obtain an optimized electric shock risk value.

6. The method according to claim 1, characterized in that, The step of converting the optimized electric shock risk value into a warning level according to a preset risk and warning mapping rule, and then triggering an alarm based on the warning level using a preset warning method, includes: The optimized electric shock risk value is compared with a preset set of threshold intervals, wherein the set of threshold intervals includes a attention level interval, a warning level interval, and a danger level interval. When the optimized electric shock risk value falls within the attention level range, the optimized electric shock risk value is converted into a first-level warning instruction according to the risk and warning mapping rule, so as to control the preset target device to emit a preset prompt sound and a preset yellow light according to the first-level warning instruction; When the optimized electric shock risk value falls within the warning level range, the optimized electric shock risk value is converted into a secondary warning instruction according to the risk and warning mapping rule. The target device is then controlled to emit a preset alarm sound and a preset orange light according to the secondary warning instruction, and a preset warning message is sent to a preset on-site monitoring terminal. When the optimized electric shock risk value falls within the dangerous range, the optimized electric shock risk value is converted into a level three warning instruction according to the risk and warning mapping rule. Based on the level three warning instruction, the target device is controlled to emit a preset whistling sound and a preset red light, and a preset emergency alarm message is sent to a preset background management platform.

7. The method according to claim 5, characterized in that, The method further includes: Calculate the difference between the optimized electric shock risk value and the safety control threshold to obtain the risk deviation amount; When the risk deviation is greater than zero, the corresponding environmental coefficient adjustment, harmonic coefficient adjustment, risk amplification factor adjustment, and sampling period adjustment are obtained from the preset adjustment mapping table based on the risk deviation. The difference between each basic environmental disturbance coefficient in the correction coefficient table and the environmental coefficient adjustment amount is calculated to update the correction coefficient table. The difference between each risk amplification factor in the attitude and risk mapping rule and the risk amplification factor adjustment amount is calculated to update the attitude and risk mapping rule. The difference between the sampling period of the real-time operating data and the adjustment amount of the sampling period is calculated to update the sampling period, and the difference between the preset harmonic segmentation threshold and the adjustment amount of the harmonic coefficient is calculated to update the piecewise linear function.

8. A device for identifying and warning of electric shock risks during power distribution operations, applied to the method for identifying and warning of electric shock risks during power distribution operations as described in claim 1, characterized in that, The device includes: The fusion synchronization module is used to perform time-series alignment and grouping and encapsulation processing on real-time operating data at the power distribution operation site to obtain synchronized operating data. The risk quantification module is used to perform electric shock risk quantification calculation on the synchronous working condition data according to preset safety procedure parameters and preset risk weight coefficients to obtain a basic electric shock risk value. The interference correction module is used to determine the real-time interference data in the power distribution operation site based on the synchronous operating condition data, so as to perform scene coupling interference correction on the basic electric shock risk value based on the real-time interference data and obtain an optimized electric shock risk value. The risk warning module is used to convert the optimized electric shock risk value into a warning level according to a preset risk and warning mapping rule, so as to trigger an alarm according to the warning level through a preset warning method.

9. A computer device, characterized in that, include: 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 to enable the at least one processor to perform the method of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the method as described in any one of claims 1 to 7.

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