Electric power operation critical edge intelligent early warning system, device and method

Abstract

The invention relates to the technical field of electric power early warning, in particular to an intelligent early warning system, device and method for an electric power operation critical edge. The system comprises an operation live-line identification and positioning module, an electric field critical voltage partition module, an operation live-line distance measurement module and an electric power operation critical early warning module, and can utilize an image acquisition unit to acquire image frames of an environment where an operator is located in real time and perform live-line identification and positioning of the operator. The real-time live-line space positioning of the operating personnel is obtained; operation positioning electric intensity measurement and critical voltage grade evaluation are carried out on the real-time operation process corresponding to the electric power operation personnel in combination with a field intensity sensing unit, so that critical voltage grade subareas where the operation personnel are located are obtained; the radar ranging unit is used for measuring the live-line distance, and the early warning unit is used for carrying out electric power operation early warning processing so as to execute corresponding electric power operation critical edge safety early warning work. According to the invention, intelligent early warning integration of the critical edge of power operation can be realized, and the early warning efficiency can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power warning, and in particular to an intelligent warning system, device and method for the critical edge of power operation. Background Art

[0002] In recent years, with the development of the power grid, the number of power transmission and transformation facilities has increased year by year. Safety accidents caused by insufficient critical operation occur frequently. The difficulty of intelligent warning for the critical edge of power operation is increasing, and the warning requirements are getting higher and higher. However, the protection ability of operators does not match and adapt to the actual situation, and safety accidents occur from time to time.

[0003] The defense requirements for the critical edge involve all levels of the power system, including the power production and consumption system composed of power transformation, power transmission, power distribution and power consumption links, as well as the equipment and facilities on the weak current side composed of substations, converter stations, transmission lines and other high-voltage sides and various detection devices, communication devices, safety protection devices, automatic control devices, monitoring automation, and dispatching automation systems. At present, most of the existing technical means are to measure the necessary critical edges before power on according to relevant regulations and standards, manually set safety channels, safety warning lines, safety signs in advance, formulate relevant systems for the critical edge, compile responsibility measures for the critical edge, and improve the risk classification and defense mechanism for the critical edge, so as to achieve the rigid defense of the critical edge of the operation site, personnel, equipment, etc. However, due to the great difficulty of defending the critical edge of the power system, the defense ability of the construction unit for the critical edge does not match and adapt to the actual situation, and problems such as on-site personnel violating the critical edge operation and operation equipment carrying out operations beyond the distance still exist. Especially in the critical state of power equipment, it is difficult to accurately predict the upcoming danger, resulting in low warning accuracy. Summary of the Invention

[0004] Based on this, it is necessary for the present invention to provide an intelligent warning system, device and method for the critical edge of power operation to solve at least one of the above technical problems.

[0005] To achieve the above object, an intelligent warning system for the critical edge of power operation includes the following modules:

[0006] An operation live identification and positioning module, configured to use an image acquisition unit to collect real-time image frames of the environment where the operator is located and transmit them to the corresponding image recognition component in the control center; perform operation live identification and positioning on the real-time image frames of the environment where the operator is located through the image recognition component to obtain the real-time live space positioning of the operator.

[0007] The electric field critical voltage zoning module is used to perform job positioning and electric field intensity measurement on the real-time operation process corresponding to the power operation personnel based on the real-time live space positioning of the operation personnel and in combination with the field intensity induction unit, so as to obtain the electric field intensity corresponding to the positioning where the operation personnel are located; perform critical voltage level evaluation based on the electric field intensity corresponding to the positioning where the operation personnel are located, so as to obtain the critical voltage level zoning where each operation personnel is located, and upload it to the control center;

[0008] The live operation distance measurement module is used to use the radar ranging unit to measure the live distance between the metal tools held by the power operation personnel corresponding to each operation personnel in the critical voltage level zoning and the live equipment, so as to obtain the live distance between the operation personnel and the live equipment in each voltage level zoning, and upload it to the control center;

[0009] The power operation critical warning module is used to set the safety warning distance corresponding to each voltage level in the control center according to the critical voltage level zoning where each operation personnel is located, and compare the safety warning distance with the live distance between the operation personnel and the live equipment, so as to obtain the critical safety comparison result of the operation personnel; perform power operation warning processing on the critical safety comparison result of the operation personnel through the warning unit, so as to perform the corresponding power operation critical edge safety warning work.

[0010] Furthermore, the live operation identification and positioning module includes the following functions:

[0011] Use the camera component in the image acquisition unit to perform real-time monitoring of the environment where the power operation personnel are located during the real-time operation process, so as to collect the image frames of the environment where the corresponding operation personnel are located in real time;

[0012] Transmit the image frames of the environment where the operation personnel are located to the corresponding image recognition component in the control center through the image transmission component in the image acquisition unit, and use the image recognition component to perform frame screening for live danger on the received image frames of the environment where the operation personnel are located, so as to identify and screen out the image frames corresponding to the live objects held by the power operation personnel with metal tools or close to the high-voltage live edge, and generate the live danger frames where each operation personnel is located;

[0013] Perform time sequence synchronization sorting on the live danger frames where each operation personnel is located, so as to generate the sequence of live danger image frames of the operation personnel;

[0014] Perform live operation identification and positioning of the operation personnel on the sequence of live danger image frames of the operation personnel through the image recognition component, so as to obtain the real-time live space positioning of the operation personnel.

[0015] Furthermore, the performing live operation identification and positioning of the operation personnel on the sequence of live danger image frames of the operation personnel through the image recognition component includes:

[0016] The image recognition component uses Canny edge detection to perform contour topology recognition between the operator and the energized equipment for each image frame in the sequence of images of the operator's energized dangerous images, so as to obtain the contour spatial positions and connection relationships between the operator and the energized equipment within the image frame sequence;

[0017] Based on the contour spatial positions and connection relationships between the operator and the energized equipment within the image frame sequence, perform an energized relative trajectory analysis on each image frame in the sequence of images of the operator's energized dangerous images, and obtain the dynamic trajectory between the relative positions of the operator and the energized equipment within the image frame sequence;

[0018] Obtain the relative spatial positions between the operator and the energized equipment through the dynamic trajectory between the relative positions of the operator and the energized equipment within the image frame sequence, and perform three-dimensional space projection reconstruction on the relative spatial positions between the operator and the energized equipment to generate an energized projection grid of the operator including corresponding spatial coordinates;

[0019] Based on the energized projection grid of the operator including corresponding spatial coordinates, perform real-time energized projection positioning on the relative spatial positions between the operator and the energized equipment to obtain the real-time energized spatial positioning of the operator.

[0020] Further, the electric field critical voltage zoning module includes the following functions:

[0021] Based on the real-time energized spatial positioning of the operator and combined with the field intensity induction unit, perform an energized positioning electric field intensity measurement on the corresponding real-time operation process of the electric power operator, so as to measure the electric field intensity of the electric power operator in the environment corresponding to the real-time energized positioning through the field intensity induction unit, so as to obtain the electric field intensity corresponding to the positioning where the operator is located;

[0022] Calculate the electric field intensity distribution gradient according to the electric field intensity corresponding to the positioning where the operator is located, and obtain the electric field intensity distribution gradient between the positions where the operator is located;

[0023] Based on the electric field intensity distribution gradient between the positions where the operator is located, perform a critical voltage level evaluation determination to obtain the critical voltage level zoning where each operator is located, and upload it to the control center.

[0024] Further, the calculation of the electric field intensity distribution gradient according to the electric field intensity corresponding to the positioning where the operator is located includes:

[0025] Determine the electric field spacing between the two positions where the operator is located pairwise through the positions where the operator is located;

[0026] Perform an electric field intensity difference calculation on the electric field intensities corresponding to the two positions where the operator is located pairwise to obtain the electric field intensity difference between the two positions where the operator is located pairwise;

[0027] Based on the electric field spacing between the positions of each pair, calculate the electric field intensity distribution gradient of the difference in electric field intensity between the positions of each pair, and obtain the electric field intensity distribution gradient between the positions where the operators are located.

[0028] Further, the specific critical voltage level partitions where each operator is located are determined according to the distribution ranges corresponding to the electric field intensity distribution gradients, to obtain the critical voltage level partitions corresponding to the safety voltage level, low voltage level, medium voltage level, high voltage level, extra high voltage level, and ultra high voltage level. Among them, the electric field intensity distribution gradient of the safety voltage level is 0 - 0.05 V / m 2 and the corresponding critical voltage level is 6 V - 42 V; the electric field intensity distribution gradient of the low voltage level is 0.05 - 0.2 V / m 2 and the corresponding critical voltage level is 220 V - 380 V: the electric field intensity distribution gradient of the medium voltage level is 0.2 - 2 V / m 2 and the corresponding critical voltage level is 3.6 kV - 10 kV; the electric field intensity distribution gradient of the high voltage level is 2 - 10 V / m 2 and the corresponding critical voltage level is 110 kV - 220 kV; the electric field intensity distribution gradient of the extra high voltage level is 10 - 30 V / m 2 and the corresponding critical voltage level is 330 kV - 750 kV; the electric field intensity distribution gradient of the ultra high voltage level is greater than 30 V / m 2 and the corresponding critical voltage level is 1000 kV and above for alternating current and ±800 kV and above for direct current.

[0029] Further, the operation live distance measurement module includes the following functions:

[0030] Use the radar transmitting component in the radar ranging unit to transmit corresponding ultrasonic beams between the metal tools held by the power operation personnel corresponding to each critical voltage level partition where the operators are located and the live equipment, and monitor and determine the corresponding time duration between transmission and reception by receiving the ultrasonic beams in the radar receiving component while using the data analysis component in the control center;

[0031] Determine the distribution difference in electric field intensity between the operator and the live equipment through the metal tools held by the power operation personnel corresponding to each critical voltage level partition where the operators are located and the live equipment;

[0032] Based on the distribution difference in electric field intensity between the operator and the live equipment, use the electric field influence evaluation calculation formula to evaluate the transmission influence of the transmitted corresponding ultrasonic beams, and obtain the electric field difference transmission influence coefficient corresponding to the ultrasonic beams;

[0033] Among them, the electric field influence evaluation calculation formula is specifically:

[0034]

[0035] In the formula, ε c is the electric field difference transmission influence coefficient, V is the electric field range area between the operator and the energized equipment, r is the electric field spatial position parameter, E(r) is the electric field intensity distribution difference between the operator and the energized equipment at position r, ρ(r) is the ultrasonic propagation frequency of the ultrasonic beam at position r, α is the ultrasonic propagation energy attenuation coefficient of the ultrasonic beam within the corresponding electric field range, and d(r) is the propagation distance of the ultrasonic beam from position r to the ultrasonic propagation target;

[0036] Based on the electric field difference transmission influence coefficient corresponding to the ultrasonic beam, the transmission rate corresponding to the ultrasonic beam is corrected for transmission influence to obtain the ultrasonic transmission correction rate;

[0037] Based on the ultrasonic transmission correction rate and combined with the corresponding time duration between transmission and reception, the live working distance between the metal tools held by the electric power operators in each critical voltage level partition where the operators are located and the energized equipment is measured to obtain the live working distance between the operators and the energized equipment in each voltage level partition, and it is uploaded to the control center.

[0038] Furthermore, the electric power operation critical warning module includes the following functions:

[0039] Set the safety warning distance corresponding to each voltage level in the control center according to the critical voltage level partitions where each operator is located;

[0040] Compare the safety warning distance with the live working distance between the corresponding operator and the energized equipment to obtain the operator critical safety comparison result, including comparison results corresponding to the live working distance being greater than, equal to, or less than the safety warning distance;

[0041] Through the corresponding data analysis component in the control center, perform response analysis on the operator critical safety comparison result. If the live working distance is greater than the safety warning distance, then respond to store the corresponding comparison result in the control center; if the live working distance is equal to the safety warning distance, then respond to generate a corresponding sound warning control signal, and upload the sound warning control signal to the sound warning component through the signal transmission component corresponding to the warning unit to start performing the corresponding electric power operation critical safety sound alarm work; if the live working distance is less than the safety warning distance, then respond to generate corresponding sound and photoelectric warning control signals, and upload the sound and photoelectric warning control signals to the sound warning component and the photoelectric warning component through the signal transmission component corresponding to the warning unit to simultaneously perform the corresponding electric power operation critical sound and light warning work.

[0042] Furthermore, the present invention also provides an intelligent early warning device for the critical edge of power operation, which is used to execute the intelligent early warning system for the critical edge of power operation as described above. The intelligent early warning device for the critical edge of power operation includes a box body, which is in a cylindrical shell structure. A plurality of image acquisition units are arranged on the corresponding outer circumference of the box body in the cylindrical shell structure. The plurality of image acquisition units on the box body are arranged at equal angles. A radar ranging unit is arranged above the image acquisition unit. A field strength induction unit, an early warning unit and a control center are arranged inside the box body. The control center is internally provided with an image recognition component and a data analysis component. The image acquisition unit, the radar ranging unit, the field strength induction unit and the early warning unit are all electrically connected to the control center. The image acquisition unit includes a camera component and an image transmission component. The camera component is electrically connected to the image transmission component. The image transmission component is electrically connected to the image recognition component. The radar ranging unit includes a radar transmitting component and a radar receiving component. The radar transmitting component is electrically connected to the radar receiving component. The radar receiving component is electrically connected to the data analysis component. The early warning unit includes a sound early warning component, a photoelectric early warning component and a signal transmission component. The sound early warning component and the photoelectric early warning component are both electrically connected to the signal transmission component. The signal transmission component is electrically connected to the control center.

[0043] Furthermore, the present invention also provides an intelligent early warning method for the critical edge of power operation. The method is implemented based on the intelligent early warning system for the critical edge of power operation as described above. The intelligent early warning method for the critical edge of power operation includes:

[0044] Using the image acquisition unit to collect the environmental image frames of the operating personnel in real time and transmit them to the corresponding image recognition component in the control center; through the image recognition component, the operating personnel in the environmental image frames of the operating personnel are identified and located for live electricity, so as to obtain the real-time live electricity space positioning of the operating personnel;

[0045] Based on the real-time live electricity space positioning of the operating personnel and combined with the field strength induction unit, the operating positioning electric field strength of the corresponding real-time operation process of the power operating personnel is measured, so as to obtain the electric field strength corresponding to the location where the operating personnel are located; according to the electric field strength corresponding to the location where the operating personnel are located, the critical voltage level assessment is carried out to obtain the critical voltage level partition where each operating personnel is located, and it is uploaded to the control center;

[0046] Using the radar ranging unit to measure the live electricity distance between the metal tools held by the power operating personnel in each critical voltage level partition where the operating personnel are located and the live equipment, so as to obtain the live electricity distance between the operating personnel and the live equipment in each voltage level partition, and upload it to the control center;

[0047] By setting the safety warning distance corresponding to each voltage level according to the critical voltage levels where each operator is located in the control center, and comparing the safety warning distance with the live distance between the operator and the live equipment to obtain the critical safety comparison result of the operator; the warning unit performs power operation warning processing on the critical safety comparison result of the operator to execute the corresponding critical edge safety warning work for power operation.

[0048] Advantages of the present invention:

[0049] 1. The power operation critical edge intelligent early warning system proposed by the present invention is generally composed of an operation live identification and positioning module, an electric field critical voltage zoning module, an operation live distance measurement module, and a power operation critical early warning module. Compared with the prior art, the beneficial effect of this application is that by using image acquisition units arranged at equal angles to collect image frames of the environment where the operator is located in real time and transmitting them to the image recognition component in the control center, the operator can be effectively identified and positioned. The greatest advantage of this process is that it can achieve real-time monitoring, accurately identify whether the operator is in a live environment, and timely locate his specific spatial position. By combining image recognition technology, the system can quickly and accurately judge whether the operator has entered a high-voltage area or other dangerous environments, thereby providing data support for subsequent safety early warning and power operation guarantee. It can not only improve the safety of the operation site, but also reduce human errors, provide an automated detection means, and update the status and position of the operator in real time. This means that the working status of the operator in a dangerous environment will be comprehensively monitored, so that the upcoming danger can be accurately predicted. Secondly, by combining the real-time live spatial positioning of the operator and the field strength induction unit to measure the electric field strength of the environment where the operator is located, this process is of great significance for ensuring the safety of the operator. By real-time monitoring the electric field strength at the position where the operator is located, the system can accurately evaluate the risk level of the power operation and evaluate the critical voltage level according to the electric field strength. This evaluation can not only judge the voltage level zoning where the operator is located, but also further understand the power danger degree of the operation environment, thereby providing a scientific basis for subsequent early warning and safety measures. Through accurate measurement of the electric field strength, the operator and the management personnel can timely understand the potential risks of the operation environment, realize the risk prediction of the power operation, take appropriate safety measures, and ensure the life safety of the operator. Then, by using the radar ranging unit to measure the live distance between the operator and the live equipment, this is a very important safety guarantee measure in the power operation process. By real-time measurement of the live distance, the system can judge whether the safety distance between the operator and the live equipment meets the safety standards of the power operation. Especially for the operator holding a metal tool, the measurement of the live distance is crucial. The application of radar technology can accurately monitor the distance change between the operator and the live equipment in real time and provide accurate data for the management personnel. In this way, the operator can timely know whether he is within the safe range and make necessary adjustments. Combining the voltage level zoning where the operator is located, the system can provide personalized safety distance early warning for each operator, greatly improving the safety of the power operation and reducing electric shock accidents caused by too close distance.Finally, the control center conducts critical safety comparison based on the voltage level zones where the operators are located and the safety warning distances, ensuring that every link of the power operation is within safety control. In this way, it can compare the actual live distance between the operators and the live equipment with the preset safety warning distance, evaluate whether the operators are in a potentially dangerous state. Through the power operation warning unit, the system can timely send out warning signals when it detects that the operators are at the critical safety edge, notify the operators and management personnel to take emergency measures to avoid danger. This process not only improves the safety guarantee ability of the operators, but also provides all-round and real-time safety monitoring for the power operation site, thus improving the accuracy and efficiency of power operation warning.

[0050] 2. The intelligent warning device for the critical edge of power operation proposed by the present invention can highly integrate the camera components through the image acquisition unit, and has a modular selection and installation mode. According to the requirements of the critical edge of power operation, it can collect, identify, analyze and confirm power facilities; through the radar ranging unit, using ultrasonic radar components, the data analysis component can conduct planned analysis on the ultrasonic radar ranging data and distances; through the field strength induction unit, the field strength measurement component measures the electric field strength, and the data analysis can overcome the influence and interference of complex field strengths and accurately judge the field strength; through the warning unit, when the safety distance is exceeded near the power facilities under the corresponding field strength, the sound warning component issues an alarm, and the optoelectronic warning component can emit red warning lights. The signal transmission component has signal reading and storage functions; finally, it is placed on the safety helmets of the operators, and can realize the integration of intelligent warning for the critical edge of power operation, which can effectively reduce the operation complexity of cable channel status warning, improve the warning efficiency, and reduce accidents caused by insufficient safety distances. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Other features, purposes and advantages of the present invention will become more obvious by reading the detailed description of the non-restrictive embodiments with reference to the following drawings:

[0052] Figure 1 It is a schematic diagram of the modules of the intelligent warning system for the critical edge of power operation of the present invention;

[0053] Figure 2 It is a three-dimensional schematic diagram after the intelligent warning device for the critical edge of power operation of the present invention is installed on the safety helmet;

[0054] Figure 2 In the figure, the labels are: 1. Safety helmet; 2. Intelligent warning device for the critical edge of power operation;

[0055] Figure 3 It is a three-dimensional schematic diagram of the intelligent warning device for the critical edge of power operation of the present invention;

[0056] Figure 3 Marked in the figure as: 201, early warning unit; 202, image acquisition unit; 203, radar ranging unit;

[0057] Figure 4 It is a schematic diagram of the electrical connection between the image acquisition unit, the radar ranging unit, the field strength induction unit, and the early warning unit of the present invention and the control center. Detailed implementation mode

[0058] The technical system of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present invention.

[0059] In addition, the accompanying drawings are only schematic diagrams of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor systems and / or microcontroller systems.

[0060] It should be understood that although the terms "first", "second", etc. may be used here to describe each unit, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit can be called the second unit, and similarly the second unit can be called the first unit. The term "and / or" used here includes any and all combinations of one or more of the listed associated items.

[0061] To achieve the above object, please refer to Figures 1 to 4 , the present invention provides an intelligent early warning system for the critical edge of electric power operation, and the system includes the following modules:

[0062] The operation live identification and positioning module is used to use the image acquisition unit 202 to collect the image frames of the environment where the operator is located in real time and transmit them to the corresponding image recognition component in the control center; the image recognition component is used to perform operation live identification and positioning on the image frames of the environment where the operator is located to obtain the real-time live space positioning of the operator;

[0063] The electric field critical voltage zoning module is used to perform job positioning and electric field strength measurement on the real-time operation process corresponding to the power operation personnel based on the real-time live space positioning of the operation personnel and in combination with the field strength induction unit, so as to obtain the electric field strength corresponding to the position where the operation personnel are located; perform critical voltage level evaluation according to the electric field strength corresponding to the position where the operation personnel are located, so as to obtain the critical voltage level zoning where each operation personnel is located, and upload it to the control center;

[0064] The live working distance measurement module is used to use the radar ranging unit 203 to measure the live working distance between the metal tools held by the power operation personnel corresponding to each operation personnel in the critical voltage level zoning and the live equipment, so as to obtain the live working distance between the operation personnel and the live equipment in each voltage level zoning, and upload it to the control center;

[0065] The power operation critical warning module is used to set the safety warning distance corresponding to each voltage level in the control center according to the critical voltage level zoning where each operation personnel is located, and compare it with the live working distance between the operation personnel and the live equipment to obtain the critical safety comparison result of the operation personnel; perform power operation warning processing on the critical safety comparison result of the operation personnel through the warning unit 201 to perform the corresponding power operation critical edge safety warning work.

[0066] In the embodiment of the present invention, please refer to Figure 1 As shown, it is a schematic diagram of the modules of the power operation critical edge intelligent warning system of the present invention. In this example, it is applied to the power operation critical edge intelligent warning device 2, and the power operation critical edge intelligent warning device 2 is fixed on the upper part of the safety helmet 1 (such as Figure 2 shown), and the power operation critical edge intelligent warning system includes the following modules:

[0067] S1: The live working identification and positioning module is used to use the image acquisition unit 202 to collect the image frames of the environment where the operation personnel are located in real time and transmit them to the corresponding image recognition component in the control center; perform job personnel live identification and positioning on the image frames of the environment where the operation personnel are located through the image recognition component to obtain the real-time live space positioning of the operation personnel;

[0068] In an embodiment of the present invention, at the power operation site, the intelligent early warning device 2 on the upper part of the safety helmet 1 worn by the operator starts to work. The three image acquisition units 202 evenly distributed at equal angles on the outer circumference of the device are immediately activated. The camera assembly of each unit uses a corresponding image sensor with 12 million pixels, and monitors the 360° environment around the operator in real time at a frame rate of 30 frames per second and a resolution of 1920×1080. For example, during the equipment maintenance operation of a 110 kV substation, the camera assembly captures the picture of the operator holding a metal tool approaching the busbar. After converting the analog video signal into a digital signal, it is transmitted to the image transmission component. The image transmission component uses a low-power Wi-Fi module and sends the image frame in the form of a UDP data packet to the image recognition component in the control center in real time according to the 802.11n protocol. The image recognition component runs based on a processor and uses an improved YOLOv5 algorithm. This algorithm has been trained on a dataset containing 150,000 power operation scene images. After receiving the image frame, the algorithm can identify the operator, live equipment, and metal tools within 0.06 seconds. By calculating the centroid coordinates of the target contour, combined with the pre-calibrated camera parameters, the triangulation method is used to determine the position of the operator in the three-dimensional space, and the real-time live space positioning of the operator is obtained. For example, it is determined that the coordinates of the operator are (3, 2, 1.8) meters, and this positioning information, together with the job number, time stamp, etc., is stored in the "operator positioning table" of the embedded database (SQLite) in the control center.

[0069] S2: Electric field critical voltage zoning module, which is used to perform job positioning electric field strength measurement on the real-time job process corresponding to the power operator based on the real-time live space positioning of the operator and in combination with the field strength induction unit, so as to obtain the electric field strength corresponding to the position where the operator is located; perform critical voltage level evaluation according to the electric field strength corresponding to the position where the operator is located, so as to obtain the critical voltage level zoning where each operator is located, and upload it to the control center;

[0070] In an embodiment of the present invention, after the control center obtains the real-time live-space positioning of the operator, the field intensity induction unit (using a corresponding electric field sensor with a detection range of 0 - 500 kV / m and a resolution of 0.01 kV / m) starts to measure the electric field intensity at the location where the operator is located in real time. In the above-mentioned substation operation, the sensor converts the sensed electric field signal into an analog voltage signal, which is converted into a digital signal by a 16-bit ADC at a sampling frequency of 100 Hz and transmitted to the control center through the SPI communication protocol. The data analysis component of the control center, based on the corresponding processor, uses an IIR filter to remove signal noise and converts the digital signal into the actual electric field intensity value according to the sensor calibration parameters. For example, the measured electric field intensity at a certain moment is 18 kV / m. Then, a critical voltage level assessment is carried out according to the pre-set corresponding rule between the electric field intensity and the voltage level: the electric field intensity distribution gradient of the safety voltage level is 0 - 0.05 V / m 2 and the corresponding critical voltage level is 6 V - 42 V; the electric field intensity distribution gradient of the low voltage level is 0.05 - 0.2 V / m 2 and the corresponding critical voltage level is 220 V - 380 V; the electric field intensity distribution gradient of the medium voltage level is 0.2 - 2 V / m 2 and the corresponding critical voltage level is 3.6 kV - 10 kV; the electric field intensity distribution gradient of the high voltage level is 2 - 10 V / m 2 and the corresponding critical voltage level is 110 kV - 220 kV; the electric field intensity distribution gradient of the extra-high voltage level is 10 - 30 V / m 2 and the corresponding critical voltage level is 330 kV - 750 kV; the electric field intensity distribution gradient of the ultra-high voltage level is greater than 30 V / m 2 and the corresponding critical voltage level is 1000 kV and above for alternating current and ±800 kV and above for direct current. Taking the electric field intensity distribution gradient data of operator D as an example, if the calculated gradient value within a certain period of time is 1.2 V / m 2 , according to the rule, it is determined that the area where the operator is located during this period is the medium voltage level partition. The data analysis component compares and evaluates all the gradient data of the operator during the entire operation process one by one, determines the critical voltage level partition where each operator is located, and uploads the corresponding critical voltage level partition where the operator is located to the control center.

[0071] S3: The operation live distance measurement module is used to measure the live distance between the metal tools held by the power operation personnel corresponding to each operator in the critical voltage level partition and the live equipment by using the radar ranging unit 203, so as to obtain the live distance between the operator and the live equipment in each voltage level partition and upload it to the control center;

[0072] In the embodiment of the present invention, after the control center obtains the critical voltage level zone where the operator is located, the corresponding radar transmitting component (piezoelectric ultrasonic transducer, operating frequency 40 kHz) in the radar ranging unit 203 is activated to transmit an ultrasonic beam between the metal tool held by the operator and the energized equipment. The radar receiving component receives the reflected beam, and the data analysis component of the control center records the transmission and reception duration through a high-precision timer. For example, the duration is 400 μs in a certain measurement. At the same time, the electric field intensities at different positions of the operator and the energized equipment are obtained, the distribution difference of the electric field intensities is calculated, and the electric field difference transmission influence coefficient is calculated using the corresponding formula. And the ultrasonic transmission rate is corrected through the formula v = v0(1 - ε c ), and then the live working distance is calculated according to the formula L = v×Δt / 2. Finally, the live working distances between the operators and the energized equipment in each voltage level zone are obtained and uploaded to the control center.

[0073] S4: The electric power operation critical warning module is used to set the safety warning distance corresponding to each voltage level in the control center according to the critical voltage level zone where each operator is located, and compare the safety warning distance with the live working distance between the operator and the energized equipment to obtain the critical safety comparison result of the operator; the warning unit 201 performs electric power operation warning processing on the critical safety comparison result of the operator to perform the corresponding electric power operation critical edge safety warning work.

[0074] In the embodiment of the present invention, the control center obtains the critical voltage level zone where the operator is located, and sets the safety warning distance according to the built-in voltage level - safety distance comparison table: the safety voltage level zone is 0.1 m; the low voltage level zone is 0.3 m; the medium voltage level zone is 0.6 m; the high voltage level zone is 1 m; the extra-high voltage level zone is 2 m; the ultra-high voltage level zone is 5 m. The live working distance of the operator is retrieved and compared with the safety warning distance. Through a program written in C language and using if-else statements to judge, if the live working distance is greater than the safety warning distance, the comparison result is stored; if they are equal, the data analysis component generates a sound warning control signal (digital coding format, including the operator ID, etc.), which is transmitted to the sound warning component of the warning unit 201 through the Bluetooth module, making it emit an 800 Hz, 1-second alarm sound; if it is less than, both sound and optoelectronic warning control signals are generated at the same time. The sound warning is the same as before, and the optoelectronic warning component flashes a red light at a frequency of 3 times per second to achieve the electric power operation critical edge safety warning. For example, if an operator is in the high voltage level zone and the live working distance of 0.8 m is less than the 1 m safety warning distance, an audible and visual warning is triggered, and finally the corresponding electric power operation critical edge safety warning work is performed.

[0075] Further, the live working identification and positioning module includes the following functions:

[0076] The camera component in the image acquisition unit 202 is used to monitor the real-time working environment corresponding to the power operation personnel during the real-time operation process, so as to collect the image frames of the environment where the corresponding operation personnel are located in real time;

[0077] In the embodiment of the present invention, at the power operation site, the intelligent early warning device 2 for the critical edge of power operation is fixed on the upper part of the safety helmet 1 worn by the operation personnel. The box body of the device is in a cylindrical shell structure, and 3 image acquisition units are arranged at equal angles on the outer circumference. The camera component of each image acquisition unit 202 uses a corresponding image sensor, with 12 million pixels and a viewing angle of 120°. It can monitor the real-time working environment within a 360° range around the operation personnel at a frame rate of 30 frames per second and a resolution of 1920×1080. For example, in a certain high-voltage line maintenance operation, when the operation personnel climb the pole to operate, the 3 camera components work simultaneously to capture the pictures of the operation personnel operating live equipment such as handheld tools on the conductor and insulator, as well as the situation of the live edge at a high place around. After converting the analog video signal collected by the camera component into a digital signal, it is transmitted to the image transmission component. The image transmission component uses a low-power Wi-Fi module to send the image frames in the form of UDP data packets to the control center in real time to ensure the uniqueness and time sequence of the images. These image frames are temporarily stored in the high-speed cache of the control center.

[0078] Preferably, the image frames of the environment where the operation personnel are located are transmitted to the corresponding image recognition component in the control center through the image transmission component in the image acquisition unit 202, and the image recognition component is used to screen the received image frames of the environment where the operation personnel are located for live danger frame by frame, so as to identify and screen out the image frames corresponding to the live objects held by the power operation personnel with metal tools or the live edge at a high place nearby, and generate the live danger frames of each operation personnel;

[0079] In an embodiment of the present invention, the image transmission component in the image acquisition unit 202 transmits the image frames of the environment where the operator is located to the control center through the Wi-Fi network. The image recognition component built into the control center is based on a processor and the OpenCV library. After receiving the image frames, the image recognition component first performs noise reduction processing on the images using the Gaussian filtering algorithm to reduce the noise interference caused by factors such as environmental light changes. Then, a cascade classifier based on Haar features is used, combined with a pre-trained power operation scenario model, to identify live objects (such as high-voltage wires, transformers), metal tools (such as pliers, screwdrivers), and live edges at heights (such as live components at the top of utility poles) in the images. Taking an image of a certain operation as an example, when it is detected that the operator is holding metal pliers close to a 10 kV live wire, the image recognition component determines that the image frame is a live danger sub-frame within 0.1 second, copies it from the cache and saves it to the "Live Danger Sub-Frame" folder in the internal storage module of the device. At the same time, information such as the original file name of the image sub-frame, the detected live object category, and the position coordinates is recorded in the "Live Danger Sub-Frame Record Table" of the embedded database (SQLite) in the control center. Image frames without detected live danger are directly deleted from the cache, completing the screening of live danger sub-frames.

[0080] Preferably, the live danger sub-frames of each operator are sorted in chronological order to generate a sequence of live danger image frames of the operator.

[0081] In an embodiment of the present invention, the control center reads all the records of the live danger sub-frames from the "Live Danger Sub-Frame Record Table" of the embedded database, extracts the timestamp information in each record, and uses a sorting program written in C language. With the bubble sort algorithm, the live danger sub-frames are sorted in the order of timestamps. For example, an operator generates 15 live danger sub-frames during a half-hour operation, and the timestamps are "2024-11-15 09:30:05", "2024-11-15 09:30:10", etc. Through the sorting operation, these sub-frames are arranged in chronological order. After sorting, the live danger sub-frames are constructed into a linked list structure in memory and sorted in the sorting order. The file name of each image frame remains in the original format to ensure one-to-one correspondence with the database records, and finally a complete and ordered sequence of live danger image frames of the operator is generated, providing an accurate data sequence for subsequent identification and positioning.

[0082] Preferably, the image recognition component performs live identification and positioning of the operator on the sequence of live danger image frames of the operator to obtain the real-time live space positioning of the operator.

[0083] In an embodiment of the present invention, the image recognition component of the control center processes the generated image frame sequence of the operator's live danger. First, the Shi-Tomasi corner detection algorithm is used to extract the corner features of targets such as the operator, live equipment, and metal tools in the image frame. Then, the optical flow method (Lucas-Kanade method) is adopted to track the targets according to the movement trajectories of the corners between adjacent frames, and the two-dimensional coordinates of the operator in each frame of the image are calculated. At the same time, using a three-dimensional reconstruction algorithm (such as the multi-view stereo vision algorithm), the two-dimensional image coordinates of the operator are converted into three-dimensional space coordinates (x, y, z), and finally the real-time live space positioning of the operator is obtained.

[0084] Further, the operator live recognition and positioning of the operator live danger image frame sequence by the image recognition component includes:

[0085] The Canny edge detection is used by the image recognition component to perform contour topology recognition between the operator and the live equipment in each image frame of the operator live danger image frame sequence, so as to obtain the contour spatial position and connection relationship between the operator and the live equipment in the image frame sequence.

[0086] In an embodiment of the present invention, by wearing a corresponding safety helmet 1 at the electric power operation site, the corresponding image acquisition unit 202 thereon acquires the operator live operation video stream at a frame rate of 30 frames per second. The video stream is split into an image frame sequence and transmitted to the image recognition component in the control center to process the image frame using the Canny edge detection algorithm. First, the image frame is converted into a grayscale image, and the Gaussian filter (kernel size is 5×5, standard deviation is 1.4) is used to denoise the grayscale image to reduce the noise interference in the image. Then, the amplitude and direction of the image gradient are calculated. Through non-maximum suppression, the local maximum values in the gradient direction are retained to refine the edge. Then, two thresholds are set (the low threshold is 50, and the high threshold is 150). The pixel points with gradient amplitude less than the low threshold are suppressed as non-edge points, and the pixel points greater than the high threshold are determined as edge points. For the pixel points between the two, if they are connected to the high-threshold edge points, they are retained, otherwise they are suppressed. In this way, the edge contours of the operator and the live equipment are accurately recognized, and the findContours function of the OpenCV library is used to extract the contours. By calculating geometric features such as the bounding rectangle and centroid of the contours, the contour topology relationship between the operator and the live equipment is determined. For example, if there is an overlapping area between the operator contour and the live equipment contour, the overlapping area and the coordinate range of the overlapping part are recorded; if there is an adjacent relationship between the two, the coordinate information of the adjacent boundary is recorded. Finally, the contour spatial position and connection relationship between the operator and the live equipment in the image frame sequence are obtained.

[0087] Preferably, based on the contour spatial position and connection relationship between the operator and the energized equipment within the image frame sequence, perform an energized relative trajectory analysis on each image frame in the operator's energized dangerous image frame sequence to obtain the dynamic trajectory between the relative positions of the operator and the energized equipment within the image frame sequence;

[0088] In an embodiment of the present invention, by reading the contour spatial position and connection relationship of each image frame in the operator's energized dangerous image frame sequence, taking an example of a power line maintenance operation, the operator is performing an insulator replacement operation on a 10 kV energized line. The image frame sequence contains a total of 300 frames. By using the numpy library of Python to process the data, the centroid coordinates of the contours of the operator and the energized equipment in adjacent frames are used as key nodes. By calculating the displacement vector of the centroid coordinates in adjacent frames, the change trend of the relative position between the operator and the energized equipment is determined. For example, between the 10th frame and the 20th frame, the centroid coordinates of the operator's contour move from (100, 200) to (120, 210), and the centroid coordinates of the energized equipment contour move from (300, 300) to (310, 305). Then it is calculated that the operator moves 10 pixels in the x-axis direction and 5 pixels in the y-axis direction relative to the energized equipment. And by adopting the dynamic time warping (DTW) algorithm, with the goal of minimizing the contour shape difference between adjacent frames, align the contour data of different frames, construct the dynamic trajectory between the relative positions of the operator and the energized equipment, and finally obtain the dynamic trajectory between the relative positions of the operator and the energized equipment within the image frame sequence.

[0089] Preferably, obtain the relative spatial position between the operator and the energized equipment through the dynamic trajectory between the relative positions of the operator and the energized equipment within the image frame sequence, and perform three-dimensional space projection reconstruction on the relative spatial position between the operator and the energized equipment to generate an operator's energized projection grid corresponding to the spatial coordinates;

[0090] In an embodiment of the present invention, by reading the dynamic trajectory data between the relative positions of the operator and the energized equipment, and using the principle of multi-view geometry, the coordinates of each key node in the dynamic trajectory in the three-dimensional space are calculated by the triangulation method. Taking a certain key node as an example, the pixel point corresponding to the node is found in the corresponding dynamic trajectory. According to the internal parameter matrix (such as focal length, principal point coordinates) and external parameter matrix (rotation matrix, translation vector) of the camera, the three-dimensional coordinates (x, y, z) of the node in the world coordinate system are calculated by a formula. The three-dimensional coordinates of all key nodes in the dynamic trajectory are calculated to obtain the three-dimensional data of the relative spatial position between the operator and the energized equipment. And by using the MeshPy library to perform three-dimensional spatial projection reconstruction on the three-dimensional spatial position data, setting the grid resolution to 0.01m, importing the three-dimensional models of the operator and the energized equipment into MeshPy, and constructing an operator energized projection grid containing spatial coordinates in the three-dimensional space according to the relative spatial position data. For example, the three-dimensional model of the operator is represented as a grid composed of multiple triangular patches, and the vertex coordinates of each patch correspond to the actual positions in the three-dimensional space. The energized equipment is also presented in the form of a grid. Finally, the generated operator energized projection grid is stored in the storage system of the control center in the OBJ file format.

[0091] Preferably, based on the operator energized projection grid corresponding to the spatial coordinates, real-time energized projection positioning of the relative spatial position between the operator and the energized equipment is performed to obtain the real-time energized spatial positioning of the operator.

[0092] In an embodiment of the present invention, by reading the operator energized projection grid corresponding to the spatial coordinates from the storage system of the control center and rendering it into a real-time three-dimensional projection grid, setting the rendering frame rate to 30 frames per second to ensure the real-time display. By obtaining the three-dimensional coordinate data of the relative positions of the operator and the energized equipment at the current moment, the corresponding grid cell is found in the three-dimensional projection grid, and the grid cell is marked as the spatial position where the operator is currently located. For example, if the current three-dimensional coordinates of the operator are (2, 3, 1.5), then the grid cell corresponding to the coordinates is found in the projection grid and its color is set to red for highlighting. The real-time energized spatial positioning information of the operator (including three-dimensional coordinates, grid cell number, etc.) is transmitted to the server of the control center through the Modbus TCP protocol, and the relative position relationship between the operator and the energized equipment is intuitively displayed in the form of a three-dimensional model, and finally the real-time energized spatial positioning of the operator is obtained.

[0093] Furthermore, the electric field critical voltage zoning module includes the following functions:

[0094] Based on the real-time live-space positioning of the operator and combined with the field strength induction unit, the real-time operation process corresponding to the power operator is subjected to operation positioning and electric field strength measurement, so as to measure the electric field strength of the power operator in the environment where the real-time live positioning is located in real time through the field strength induction unit, and obtain the electric field strength corresponding to the positioning where the operator is located;

[0095] In the embodiment of the present invention, during the power operation process, when the control center completes the real-time live-space positioning of the operator through the image recognition component, the field strength induction unit starts to work. The field strength induction unit adopts an electric field sensor based on the principle of capacitive coupling. This sensor has high sensitivity and can detect the electric field strength in the range of 0.1V / m - 100kV / m. Taking the equipment maintenance operation of a substation as an example, when the operator is performing maintenance on a 110kV transformer, the field strength induction unit measures the electric field strength of the operator in the current positioning environment in real time. The sensor converts the induced electric field signal into a voltage signal, and converts the analog voltage signal into a digital signal through a 16-bit ADC (Analog-to-Digital Converter) at a sampling frequency of 100Hz, and transmits it to the control center. After receiving the data, the control center uses the built-in data analysis component to process the digital signal. The data analysis component runs based on a microcontroller, removes the noise interference in the signal through a digital filtering algorithm (such as an IIR filter), and then converts the processed digital signal into the actual electric field strength value according to the calibration parameters of the sensor. For example, after calculation, the electric field strength corresponding to the current positioning of the operator is 25kV / m, and information such as the operation number, personnel ID, positioning location, and electric field strength value is recorded. Finally, the electric field strength corresponding to the positioning where the operator is located is obtained.

[0096] Preferably, the electric field strength distribution gradient is calculated according to the electric field strength corresponding to the positioning where the operator is located, and the electric field strength distribution gradient between the positions where the operator is located is obtained;

[0097] In the embodiment of the present invention, after the control center has obtained the real-time live-space positioning data of the operator at different positions, it starts to determine the electric field distance between two adjacent positions. The control center calculates based on the three-dimensional coordinate data (x, y, z) stored in the embedded database (SQLite). This table records the positioning information of each operator at different times, so as to use the distance formula between two points in space Perform operations to calculate the electric field spacing between each two positions, and extract from the embedded database by the control center the electric field intensity data corresponding to the operator at different positioning times. This table details the electric field intensity of the operator at each positioning. Use a script program written in Python to calculate the electric field intensity corresponding to each pair of positions where the operator is located. Calculate the electric field intensity difference by direct subtraction. The formula is ΔE = E2 - E1, where E1 and E2 are the electric field intensity values at two positioning times respectively. At the same time, read the electric field spacing and electric field intensity difference data between each pair of positions of the operator from the previous steps, and use a data analysis component running on a microcontroller to calculate the electric field intensity distribution gradient according to the formula G = ΔE / d, where G is the electric field intensity distribution gradient, ΔE is the electric field intensity difference, and d is the electric field spacing, and finally obtain the electric field intensity distribution gradient between the positions where the operator is located.

[0098] Preferably, based on the electric field intensity distribution gradient between the positions where the operator is located, conduct a critical voltage level assessment and determination to obtain the critical voltage level partition where each operator is located, and upload it to the control center.

[0099] In the embodiment of the present invention, the data analysis component of the control center reads the electric field intensity distribution gradient data between the positions where the operator is located from the previous steps, and conducts a critical voltage level assessment according to the pre-set corresponding rule between the electric field intensity distribution gradient and the voltage level. The setting rule is: the electric field intensity distribution gradient of the safety voltage level is 0 - 0.05 V / m 2 and the corresponding critical voltage level is 6 V - 42 V; the electric field intensity distribution gradient of the low voltage level is 0.05 - 0.2 V / m 2 and the corresponding critical voltage level is 220 V - 380 V; the electric field intensity distribution gradient of the medium voltage level is 0.2 - 2 V / m 2 and the corresponding critical voltage level is 3.6 kV - 10 kV; the electric field intensity distribution gradient of the high voltage level is 2 - 10 V / m 2 and the corresponding critical voltage level is 110 kV - 220 kV; the electric field intensity distribution gradient of the extra high voltage level is 10 - 30 V / m 2 and the corresponding critical voltage level is 330 kV - 750 kV; the electric field intensity distribution gradient of the ultra high voltage level is greater than 30 V / m 2 and the corresponding critical voltage level is 1000 kV and above for alternating current and ±800 kV and above for direct current. Taking the electric field intensity distribution gradient data of operator D as an example, if the calculated gradient value within a certain period of time is 1.2 V / m 2, according to the rules, it is determined that the area where the operator is located during this period is the medium-voltage level partition. The data analysis component compares and evaluates all gradient data of the operator during the entire operation process one by one, determines the critical voltage level partition where each operator is located, and uploads the corresponding critical voltage level partition where the operator is located to the control center.

[0100] Further, the calculation of the electric field intensity distribution gradient according to the electric field intensity corresponding to the location where the operator is located includes:

[0101] Determine the electric field spacing between two locations by the locations where the operators are located.

[0102] In the embodiment of the present invention, after the control center has obtained the real-time charged spatial location data of the operator at different locations, it starts to determine the electric field spacing between two locations. The control center calculates based on the three-dimensional coordinate data (x, y, z) stored in the embedded database (SQLite). This table records the location information of each operator at different times. For example, the coordinates of operator A at time t1 are (10, 5, 3), and the coordinates at time t2 are (12, 6, 3). Using a calculation program written in C language, according to the distance formula between two points in space perform the operation. Taking the locations of operator A at t1 and t2 as an example, substituting the coordinate values into the formula, we can get d≈2.24 meters, that is, the electric field spacing between these two locations is about 2.24 meters. The program traverses all the location data of this operator in the database, calculates the electric field spacing between each two locations, and finally obtains the electric field spacing between two locations.

[0103] Preferably, calculate the electric field intensity difference between the electric field intensities corresponding to two locations where the operator is located to obtain the electric field intensity difference between two locations.

[0104] In the embodiment of the present invention, the control center extracts the electric field intensity data corresponding to the operator at different location times from the embedded database. This table details the electric field intensity at each time when the operator is located. For example, the electric field intensity of operator B at time t3 is 22 kV / m, and the electric field intensity at time t4 is 27 kV / m. Using a script program written in Python, calculate the electric field intensities corresponding to two locations where the operator is located, and calculate the electric field intensity difference by direct subtraction. The formula is ΔE = E2 - E1, where E1 and E2 are the electric field intensity values at two location times respectively. Taking operator B at t3 and t4 as an example, substituting the data into the formula, we can get ΔE = 27 - 22 = 5 kV / m, that is, the electric field intensity difference between these two locations is 5 kV / m. The script program processes the electric field intensity data of all two-location combinations of the operator in turn, and finally obtains the electric field intensity difference between two locations.

[0105] Preferably, based on the electric field spacing between two positions, the electric field strength distribution gradient between the two positions is calculated to obtain the electric field strength distribution gradient between the positions where the operators are located.

[0106] In the embodiment of the present invention, the control center reads the electric field spacing and electric field strength difference data between the two positions of the operators from the previous steps respectively. For example, it is obtained that the electric field spacing between position 1 and position 2 of operator C is 3 meters, and the electric field strength difference is 6 kV / m. Using the data analysis component based on the microcontroller operation, the electric field strength distribution gradient is calculated according to the formula G = ΔE / d, where G is the electric field strength distribution gradient, ΔE is the electric field strength difference, and d is the electric field spacing. Substituting the relevant data of operator C into the formula, G = 6 / 3 = 2 kV / m can be obtained. 2 That is, the electric field strength distribution gradient between these two positions of operator C is 2 kV / m. 2 The data analysis component traverses and calculates the two-position data of all operators. These gradient data will be used to evaluate the voltage danger level of the area where the operators are located, and finally the electric field strength distribution gradient between the positions where the operators are located is obtained.

[0107] Further, the critical voltage level partitions where each operator is located are specifically determined according to the distribution ranges corresponding to the electric field strength distribution gradients, and the critical voltage level partitions corresponding to the safe voltage level, low voltage level, medium voltage level, high voltage level, extra high voltage level and ultra high voltage level are determined. Among them, the electric field strength distribution gradient of the safe voltage level is 0 - 0.05 V / m. 2 And the corresponding critical voltage level is 6 V - 42 V; the electric field strength distribution gradient of the low voltage level is 0.05 - 0.2 V / m. 2 And the corresponding critical voltage level is 220 V - 380 V: the electric field strength distribution gradient of the medium voltage level is 0.2 - 2 V / m. 2 And the corresponding critical voltage level is 3.6 kV - 10 kV; the electric field strength distribution gradient of the high voltage level is 2 - 10 V / m. 2 And the corresponding critical voltage level is 110 kV - 220 kV; the electric field strength distribution gradient of the extra high voltage level is 10 - 30 V / m. 2 And the corresponding critical voltage level is 330 kV - 750 kV; the electric field strength distribution gradient of the ultra high voltage level is greater than 30 V / m. 2 And the corresponding critical voltage level is 1000 kV and above for alternating current and ±800 kV and above for direct current.

[0108] Further, the operating live distance measurement module includes the following functions:

[0109] The radar emission group 203 in the radar ranging unit is used to emit corresponding ultrasonic beams between the metal tools held by the power operation personnel corresponding to the power operation personnel in each critical voltage level partition where the operation personnel are located and the live equipment, and the corresponding duration between emission and reception is monitored and determined by receiving the ultrasonic beam in the radar receiving component and using the data analysis component in the control center while receiving the ultrasonic beam;

[0110] In the embodiment of the present invention, at the power operation site, after the control center completes the determination of the critical voltage level partition of the operation personnel, the radar ranging unit is started. The radar emission component 203 of the radar ranging unit 203 uses a piezoelectric ultrasonic transducer, and the working frequency of the transducer is 40 kHz, and it can emit ultrasonic beams with a wavelength of about 8.5 mm. Taking an operation personnel in the high-voltage level partition (110 kV - 220 kV) as an example, he is using a metal wrench to perform maintenance operations on the live equipment. The radar emission component on the safety helmet emits ultrasonic beams to the space area between the metal wrench held by the operation personnel and the live equipment, and the emission angle is 15°, ensuring that the beam covers the target area. The radar receiving component also uses a piezoelectric ultrasonic transducer (matching the model of the emission component) to monitor and receive the reflected ultrasonic beam in real time. The data analysis component in the control center runs based on the processor, and records the emission time t1 and the reception time t2 of the ultrasonic beam through a high-precision timer (with a resolution of up to 1 μs). For example, in a certain measurement, the emission time t1 is 10:00:00.000001, and the reception time t2 is 10:00:00.000501. Thus, the duration between emission and reception is determined to be 500 μs, and finally the corresponding duration between emission and reception is determined.

[0111] Preferably, the electric field intensity distribution difference between the operation personnel and the live equipment is determined between the metal tools held by the power operation personnel corresponding to the power operation personnel in each critical voltage level partition where the operation personnel are located and the live equipment;

[0112] In the embodiment of the present invention, the control center retrieves data from the embedded database to determine the electric field intensity distribution difference between the operation personnel and the live equipment in each critical voltage level partition where the operation personnel are located. Taking the operation personnel in the high-voltage level partition as an example, the electric field intensity E1 = 18 kV / m at the position x1 where the operation personnel is close to the live equipment is obtained, and the electric field intensity E2 = 12 kV / m at a position farther away from the live equipment (position x2). The electric field intensity distribution difference is calculated through the formula ΔE = E1 - E2. Substituting the data, we can get ΔE = 18 - 12 = 6 kV / m. For multiple measurement positions between the operation personnel and the live equipment, the electric field intensity distribution difference between adjacent positions is calculated in turn, and finally the electric field intensity distribution difference between the operation personnel and the live equipment is determined.

[0113] Preferably, based on the difference in the electric field intensity distribution between the operator and the energized equipment, the transmission influence of the corresponding ultrasonic beam emitted is evaluated using the electric field influence evaluation calculation formula to obtain the electric field difference transmission influence coefficient corresponding to the ultrasonic beam;

[0114] In the embodiment of the present invention, by combining the electric field range area between the operator and the energized equipment (i.e., the area range between the operator and the energized equipment), the electric field spatial position parameter, the difference in the electric field intensity distribution at position r between the operator and the energized equipment, the ultrasonic propagation frequency corresponding to the ultrasonic beam (fixed at 40 kHz), the ultrasonic propagation energy attenuation coefficient of the ultrasonic beam within the corresponding electric field range (obtained by linearly interpolating according to the attenuation coefficient table tested in different electric field intensity environments, for example, at an electric field intensity of 15 kV / m, the corresponding energy attenuation coefficient is obtained by looking up the table and interpolating, which is 0.02), and the propagation distance of the ultrasonic beam from the corresponding position to the ultrasonic propagation target, a suitable electric field influence evaluation calculation formula is constructed for calculation to quantitatively obtain the corresponding transmission influence coefficient of the ultrasonic beam within this electric field range, and finally the electric field difference transmission influence coefficient corresponding to the ultrasonic beam is obtained. In addition, this electric field influence evaluation calculation formula can also use any ultrasonic transmission attenuation analysis method in the art to replace the process of transmission influence evaluation, and is not limited to this electric field influence evaluation calculation formula.

[0115] Among them, the electric field influence evaluation calculation formula is specifically:

[0116]

[0117] In the formula, ε c is the electric field difference transmission influence coefficient, V is the electric field range area between the operator and the energized equipment, r is the electric field spatial position parameter, E(r) is the difference in the electric field intensity distribution at position r between the operator and the energized equipment, ρ(r) is the ultrasonic propagation frequency of the ultrasonic beam at position r, α is the ultrasonic propagation energy attenuation coefficient of the ultrasonic beam within the corresponding electric field range, and d(r) is the propagation distance of the ultrasonic beam from position r to the ultrasonic propagation target;

[0118] The present invention has obtained an electric field influence evaluation calculation formula through the use of a specific mathematical model and verification for evaluating the transmission influence of the corresponding ultrasonic beam emitted. This formula fully considers the electric field difference transmission influence coefficient ε c, the electric field range area V between the operator and the energized equipment, the electric field spatial position parameter r, the electric field strength distribution difference E(r) at the position r between the operator and the energized equipment, the ultrasonic propagation frequency ρ(r) of the ultrasonic beam at the position r, the ultrasonic propagation energy attenuation coefficient α of the ultrasonic beam within the corresponding electric field range, the propagation distance d(r) of the ultrasonic beam from the position r to the ultrasonic propagation target, and the transmission influence coefficient ε according to the electric field difference c The mutual correlation relationships among the above parameters constitute a functional relationship This formula can achieve the process of evaluating the transmission influence of the emitted corresponding ultrasonic beam. At the same time, by comprehensively considering various factors such as the electric field strength distribution difference, ultrasonic propagation frequency, and energy attenuation coefficient between the operator and the energized equipment, this formula can accurately evaluate the transmission influence of the ultrasonic beam in the actual power operation environment. This enables more accurate prediction of the propagation situation of the ultrasonic beam in a complex electric field environment during power operations, avoiding the errors that may occur in traditional methods. In power operations, the distance between the operator and the energized equipment directly affects the safety risk. By using this formula to evaluate the propagation influence of ultrasonic waves, the accuracy of ultrasonic ranging can be ensured, and thus the actual live distance between the operator and the energized equipment can be accurately calculated. This formula not only considers the electric field strength distribution difference but also factors such as ultrasonic propagation frequency and attenuation coefficient, making the evaluation more comprehensive and detailed. In this way, the optimization of ultrasonic ranging technology can be achieved in a complex electric field environment, thereby enhancing the reliability and applicability of the system. Additionally, based on this formula, the transmission rate of the ultrasonic beam can be corrected to make it more adaptable to the complex electric field environment in power operations. This adjustment can significantly improve the accuracy of ultrasonic ranging, reduce errors caused by environmental changes, and thus improve the accuracy and efficiency of the entire operation process. Through this formula, the live distance between the operator and the energized equipment can be accurately measured, and relevant data can be further corrected, thereby ensuring the safety of each link in power operations, avoiding the error accumulation caused by traditional electric field analysis methods, and providing more accurate real-time data support for the control center.

[0119] Preferably, the transmission influence of the ultrasonic beam is corrected based on the transmission influence coefficient of the electric field difference corresponding to the ultrasonic beam to obtain the ultrasonic transmission correction rate;

[0120] In the embodiment of the present invention, the control center reads the transmission influence coefficient of the electric field difference corresponding to the ultrasonic beam and combines the standard propagation rate v0 = 340 m / s of ultrasonic waves in the air to correct the transmission rate of the ultrasonic beam. The correction formula is v = v0(1 - ε c ), for example, if the calculated transmission influence coefficient of the electric field difference ε c= 0.35, substituting the data into the formula gives v = 340×(1 - 0.35)= 221 m / s, that is, the ultrasonic transmission correction rate is obtained as 221 m / s, and finally the corresponding ultrasonic transmission correction rate is obtained.

[0121] Preferably, based on the ultrasonic transmission correction rate and in combination with the corresponding duration between transmission and reception, the live working distance between the metal tools held by the power workers corresponding to each operator in the critical voltage level partition and the live equipment is measured to obtain the live working distance between the operators and the live equipment in each voltage level partition, and uploaded to the control center.

[0122] In the embodiment of the present invention, the ultrasonic transmission correction rate v and the corresponding duration Δt between transmission and reception in the critical voltage level partition where each operator is located are obtained through the control center, and the live working distance is measured according to the formula L = v×Δt / 2 (considering the round-trip propagation of ultrasonic waves). Taking an operator as an example, in the corresponding high-voltage level partition, the ultrasonic transmission correction rate v = 221 m / s and the transmission and reception duration Δt = 500 μs = 5×10 -4 s, substituting the above parameter data into the formula gives L = 221×5×10 -4 / 2 = 0.05525 m = 5.525 cm, that is, the live working distance between the operator and the live equipment is obtained as 5.525 cm, and the above same calculation is carried out in each partition, and finally the live working distance between the operators and the live equipment in each voltage level partition is obtained and uploaded to the control center.

[0123] Further, the power operation critical warning module includes the following functions:

[0124] Setting the safety warning distance corresponding to each voltage level in the control center according to the critical voltage level partition where each operator is located;

[0125] In the embodiment of the present invention, at the power operation site, the control center sets safety warning distances according to the critical voltage level zones where each operator is located. The data analysis component built into the control center operates based on the processor and operates by accessing the voltage level - safety distance comparison table pre - stored in the embedded database (SQLite). The comparison table clearly stipulates that: the safety warning distance corresponding to the safety voltage level zone is 0.1 m; the safety warning distance corresponding to the low - voltage level zone is 0.3 m; the safety warning distance corresponding to the medium - voltage level zone is 0.6 m; the safety warning distance corresponding to the high - voltage level zone is 1 m; the safety warning distance corresponding to the extra - high - voltage level zone is 2 m; the safety warning distance corresponding to the ultra - high - voltage level zone is 5 m. Taking an operator in the high - voltage level zone (110 kV - 220 kV) as an example, the control center obtains the voltage level zone information of this operator from the previous records, automatically sets 1 m as the corresponding safety warning distance according to the comparison table, and stores the set information together with data such as the operation number, personnel ID, and voltage level zone in the "safety warning distance table". For all operators, the control center completes the setting of the safety warning distance corresponding to each voltage level one by one in this way, ensuring that each operator has a corresponding safety distance standard.

[0126] Preferably, the safety warning distance is compared with the live distance between the corresponding operator and the live equipment to obtain the critical safety comparison result of the operator, including comparison results corresponding to the live distance being greater than, equal to, or less than the safety warning distance.

[0127] In the embodiment of the present invention, the control center separately retrieves the safety warning distance and live distance data corresponding to each operator from the previous steps. Taking operator A in the high - voltage level zone as an example, the safety warning distance of 1 m is obtained from the "safety warning distance table", and the live distance between him / her and the live equipment is obtained as 0.8 m. Through a comparison program written in C language, the live distance is compared with the safety warning distance. The if - else statement is used in the program for judgment. If the live distance is greater than the safety warning distance, the comparison result of "greater than" is output; if the live distance is equal to the safety warning distance, the comparison result of "equal to" is output; if the live distance is less than the safety warning distance, the comparison result of "less than" is output. In the example of operator A, since 0.8 m is less than 1 m, the program outputs the comparison result of "less than". The control center stores the comparison result of each operator together with information such as the operation number, personnel ID, voltage level zone, safety warning distance, and live distance in the "critical safety comparison result table" to provide accurate data support for subsequent response analysis.

[0128] Preferably, by performing response analysis on the critical safety comparison results of the operators on the corresponding data analysis component in the control center, if the live working distance is greater than the safety warning distance, the corresponding comparison results will be stored in the control center; if the live working distance is equal to the safety warning distance, a corresponding sound warning control signal will be generated, and the sound warning control signal will be uploaded to the sound warning component through the signal transmission component corresponding to the warning unit 201 to start the corresponding critical safety sound alarm work for the power operation; if the live working distance is less than the safety warning distance, a corresponding sound and optoelectronic warning control signal will be generated, and the sound and optoelectronic warning control signal will be uploaded to the sound warning component and the optoelectronic warning component through the signal transmission component corresponding to the warning unit 201 to simultaneously perform the corresponding critical sound and light warning work for the power operation.

[0129] In the embodiment of the present invention, the data analysis component of the control center reads the critical safety comparison result data of the operators from the "Critical Safety Comparison Result Table" and performs response analysis. Taking operator B as an example, if the comparison result is "greater than" (assuming the safety warning distance is 0.6 meters and the live working distance is 0.8 meters), the data analysis component directly stores the comparison result and related information such as the operation number, personnel ID, and voltage level partition in the embedded database of the control center through a C language program without performing additional warning operations. If the comparison result is "equal to" (assuming the safety warning distance is 1 meter and the live working distance is 1 meter), the data analysis component runs a Python script to generate a sound warning control signal. The signal adopts a digital coding format and contains information such as a warning start instruction and the operator ID. The signal is wirelessly uploaded to the sound warning component on the warning unit 201 through the signal transmission component (Bluetooth module HC-05) of the warning unit 201. After receiving the signal, the sound warning component immediately emits an alarm sound with a frequency of 800 Hz and a duration of 1 second to remind the operator that the critical safety distance has been reached. If the comparison result is "less than" (assuming the safety warning distance is 2 meters and the live working distance is 1.5 meters), the data analysis component generates both a sound and an optoelectronic warning control signal at the same time. The sound warning control signal is similar to the above "equal to" situation, and the optoelectronic warning control signal controls the optoelectronic warning component on the warning unit 201 to flash a red light at a frequency of 3 times per second. The two signals are synchronously uploaded to the sound warning component and the optoelectronic warning component through the signal transmission component, enabling both to perform the critical sound and light warning work for the power operation, thereby effectively reminding the operator to take safety measures in a timely manner and avoid danger.

[0130] Furthermore, the present invention also provides a critical edge intelligent warning device 2 for power operation (such as Figure 3As shown in the figure, it is used to execute the power operation critical edge intelligent early warning system as described above. The power operation critical edge intelligent early warning device 2 includes a box body, which is in a cylindrical shell structure. A number of image acquisition units 202 are arranged on the outer circumference corresponding to the cylindrical shell structure of the box body. The number of image acquisition units 202 on the box body are arranged at equal angles. A radar ranging unit 203 is arranged above the image acquisition unit 202. A field strength induction unit, an early warning unit 201 and a control center are arranged inside the box body. The control center is built with an image recognition component and a data analysis component. The image acquisition unit 202, the radar ranging unit 203, the field strength induction unit and the early warning unit 201 are all electrically connected to the control center (as Figure 4 shown in the figure). The image acquisition unit 202 includes a camera component and an image transmission component. The camera component is electrically connected to the image transmission component, and the image transmission component is electrically connected to the image recognition component. The radar ranging unit 203 includes a radar transmitting component and a radar receiving component. The radar transmitting component is electrically connected to the radar receiving component, and the radar receiving component is electrically connected to the data analysis component. The early warning unit 201 includes a sound early warning component, a photoelectric early warning component and a signal transmission component. The sound early warning component and the photoelectric early warning component are both electrically connected to the signal transmission component, and the signal transmission component is electrically connected to the control center.

[0131] Furthermore, the present invention also provides a power operation critical edge intelligent early warning method, which is implemented based on the power operation critical edge intelligent early warning system as described above. This power operation critical edge intelligent early warning method includes:

[0132] Using the image acquisition unit 202 to collect the environmental image frames of the operators in real time and transmit them to the corresponding image recognition component in the control center; performing operator live identification and positioning on the environmental image frames of the operators through the image recognition component to obtain the real-time live space positioning of the operators;

[0133] Based on the real-time live space positioning of the operators and combined with the field strength induction unit, performing operation positioning electric field strength measurement on the corresponding real-time operation process of the power operation personnel to obtain the electric field strength corresponding to the positioning where the operators are located; performing critical voltage level evaluation based on the electric field strength corresponding to the positioning where the operators are located to obtain the critical voltage level partitions where each operator is located and uploading them to the control center;

[0134] Using the radar ranging unit 203 to measure the live distance between the metal tools held by the power operation personnel and the live equipment in the critical voltage level partitions where each operator is located to obtain the live distance between the operators and the live equipment in each voltage level partition and uploading it to the control center;

[0135] By setting the safety warning distance corresponding to each voltage level according to the critical voltage levels where each operator is located in the control center, and comparing the safety warning distance with the live distance between the operator and the live equipment, the critical safety comparison result of the operator can be obtained; the warning unit 201 performs power operation warning processing on the critical safety comparison result of the operator to perform the corresponding power operation critical edge safety warning work.

[0136] Therefore, from any perspective, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the application document are intended to be included in the present invention.

[0137] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features invented herein.

Claims

1. An intelligent early warning system for the critical edge of power operation, characterized in that Applied to the critical edge intelligent warning device for electric power operations, the critical edge intelligent warning device for electric power operations is fixed on the upper part of the safety helmet. The critical edge intelligent warning system for electric power operations includes the following modules: The operation live identification and positioning module is used to use the image acquisition unit to collect the image frames of the environment where the operator is located in real time and transmit them to the corresponding image recognition component in the control center; the image recognition component performs operation live identification and positioning on the image frames of the environment where the operator is located to obtain the real-time live space positioning of the operator. The electric field critical voltage zoning module is used to perform operation positioning electric field strength measurement on the corresponding real-time operation process of the electric power operator based on the real-time live space positioning of the operator and in combination with the field strength induction unit to obtain the electric field strength corresponding to the location where the operator is located; perform critical voltage level evaluation according to the electric field strength corresponding to the location where the operator is located to obtain the critical voltage level zoning where each operator is located, and upload it to the control center. The operation live distance measurement module is used to use the radar ranging unit to measure the live distance between the metal tools held by the electric power operators in each critical voltage level zoning where the operators are located and the live equipment to obtain the live distance between the operators and the live equipment in each voltage level zoning, and upload it to the control center. The critical warning module for electric power operations is used to set the safety warning distance corresponding to each voltage level in the control center according to the critical voltage level zoning where each operator is located, and compare the safety warning distance with the live distance between the operator and the live equipment to obtain the critical safety comparison result of the operator; the warning unit performs electric power operation warning processing on the critical safety comparison result of the operator to perform the corresponding critical edge safety warning work for electric power operations.

2. The power operation critical edge intelligent early warning system according to claim 1, characterized in that The operation live identification and positioning module includes the following functions: Use the camera component in the image acquisition unit to perform real-time monitoring of the environment where the electric power operator is located during the corresponding real-time operation process to collect the image frames of the environment where the corresponding operator is located in real time. Transmit the image frames of the environment where the operator is located to the corresponding image recognition component in the control center through the image transmission component in the image acquisition unit, and use the image recognition component to perform live danger frame screening on the received image frames of the environment where the operator is located to identify and screen out the image frames corresponding to the live objects of the metal tools held by the electric power operator or the live edge near the high place, and generate the live danger frames where each operator is located. Perform time sequence synchronization sorting on the live danger frames where each operator is located to generate a sequence of live danger image frames of the operator. Perform operation live identification and positioning on the sequence of live danger image frames of the operator through the image recognition component to obtain the real-time live space positioning of the operator.

3. The power operation critical edge intelligent early warning system according to claim 2, characterized in that, The operation live identification and positioning of the sequence of live danger image frames of the operator through the image recognition component includes: The image recognition component uses Canny edge detection to perform contour topology recognition between the operator and the energized equipment for each image frame in the sequence of operator energized dangerous image frames, so as to obtain the contour spatial position and connection relationship between the operator and the energized equipment within the image frame sequence; Based on the contour spatial position and connection relationship between the operator and the energized equipment within the image frame sequence, perform energized relative trajectory analysis on each image frame in the sequence of operator energized dangerous image frames to obtain the dynamic trajectory between the relative positions of the operator and the energized equipment within the image frame sequence; Obtain the relative spatial position between the operator and the energized equipment through the dynamic trajectory between the relative positions of the operator and the energized equipment within the image frame sequence, and perform three-dimensional space projection reconstruction on the relative spatial position between the operator and the energized equipment to generate an operator energized projection grid corresponding to spatial coordinates; Based on the operator energized projection grid corresponding to spatial coordinates, perform real-time energized projection positioning on the relative spatial position between the operator and the energized equipment to obtain the real-time energized spatial positioning of the operator.

4. The power operation critical edge intelligent early warning system according to claim 1, characterized in that, The electric field critical voltage zoning module includes the following functions: Based on the real-time energized spatial positioning of the operator and in combination with the field strength induction unit, perform operation positioning electric field strength measurement on the corresponding real-time operation process of the electric power operator, so as to measure the electric field strength of the electric power operator in the environment corresponding to the real-time energized positioning through the field strength induction unit, so as to obtain the electric field strength corresponding to the positioning where the operator is located; Calculate the electric field strength distribution gradient according to the electric field strength corresponding to the positioning where the operator is located to obtain the electric field strength distribution gradient between the positions where the operator is located; Based on the electric field strength distribution gradient between the positions where the operator is located, perform critical voltage level evaluation and determination to obtain the critical voltage level zoning where each operator is located and upload it to the control center.

5. The power operation critical edge intelligent early warning system according to claim 4, wherein The calculation of the electric field strength distribution gradient according to the electric field strength corresponding to the positioning where the operator is located includes: Determine the electric field spacing between two positions where the operator is located by pairwise determination between the positions where the operator is located; Perform electric field strength difference calculation on the electric field strengths corresponding to pairwise positions where the operator is located to obtain the electric field strength difference between pairwise positions where the operator is located; Based on the electric field spacing between pairwise positions where the operator is located, perform electric field strength distribution gradient calculation on the electric field strength difference between pairwise positions where the operator is located to obtain the electric field strength distribution gradient between the positions where the operator is located.

6. The power operation critical edge intelligent early warning system according to claim 4, characterized in that The specific critical voltage level partitions where each operator is located are determined according to the distribution ranges corresponding to the distribution gradients of the electric field intensity, and the critical voltage level partitions corresponding to the safe voltage level, low voltage level, medium voltage level, high voltage level, extra high voltage level, and ultra high voltage level are determined. Among them, the distribution gradient of the electric field intensity of the safe voltage level is 0 - 0.05 V / m 2 and the corresponding critical voltage level is 6 V - 42 V; the distribution gradient of the electric field intensity of the low voltage level is 0.05 - 0.2 V / m 2 and the corresponding critical voltage level is 220 V - 380 V: the distribution gradient of the electric field intensity of the medium voltage level is 0.2 - 2 V / m 2 and the corresponding critical voltage level is 3.6 kV - 10 kV; the distribution gradient of the electric field intensity of the high voltage level is 2 - 10 V / m 2 and the corresponding critical voltage level is 110 kV - 220 kV; the distribution gradient of the electric field intensity of the extra high voltage level is 10 - 30 V / m 2 and the corresponding critical voltage level is 330 kV - 750 kV; the distribution gradient of the electric field intensity of the ultra high voltage level is greater than 30 V / m 2 and the corresponding critical voltage level is 1000 kV and above for alternating current and ±800 kV and above for direct current.

7. The power operation critical edge intelligent early warning system according to claim 1, characterized in that, The operation energized distance measurement module includes the following functions: Use the radar transmitting component in the radar ranging unit to transmit corresponding ultrasonic beams between the metal tools held by the electric power operators corresponding to each operator in the critical voltage level zoning and the energized equipment, and monitor and determine the corresponding time duration between transmission and reception by receiving the ultrasonic beam in the radar receiving component and using the data analysis component in the control center; Determine the electric field strength distribution difference between the operator and the energized equipment through the metal tools held by the electric power operators corresponding to each operator in the critical voltage level zoning and the energized equipment; Based on the difference in the electric field intensity distribution between the operator and the energized equipment, the transmission impact of the corresponding ultrasonic beam is evaluated using the electric field impact evaluation calculation formula, and the electric field difference transmission impact coefficient corresponding to the ultrasonic beam is obtained; Among them, the specific electric field impact evaluation calculation formula is: where ε c is the influence coefficient of electric field difference transmission, V is the electric field range area between the operator and the energized equipment, r is the electric field spatial position parameter, E(r) is the electric field intensity distribution difference between the operator and the energized equipment at position r, ρ(r) is the ultrasonic propagation frequency of the ultrasonic beam at position r, α is the ultrasonic propagation energy attenuation coefficient of the ultrasonic beam within the corresponding electric field range, and d(r) is the propagation distance of the ultrasonic beam from position r to the ultrasonic propagation target; Based on the electric field difference transmission impact coefficient corresponding to the ultrasonic beam, the transmission rate corresponding to the ultrasonic beam is corrected for transmission impact to obtain the ultrasonic transmission correction rate; Based on the ultrasonic transmission correction rate and combined with the corresponding duration between transmission and reception, the live working distance between the metal tools held by the power operators in the critical voltage level partition where each operator is located and the energized equipment is measured to obtain the live working distance between the operators and the energized equipment in each voltage level partition, and it is uploaded to the control center.

8. The power operation critical edge intelligent early warning system according to claim 1, characterized in that The power operation critical warning module includes the following functions: Set the safety warning distance corresponding to each voltage level in the control center according to the critical voltage level partition where each operator is located; Compare the safety warning distance with the live working distance between the corresponding operator and the energized equipment to obtain the critical safety comparison result of the operator, including the comparison results corresponding to the live working distance being greater than, equal to, or less than the safety warning distance; Through the corresponding data analysis component in the control center, respond to the critical safety comparison result of the operator. If the live working distance is greater than the safety warning distance, then store the corresponding comparison result in the control center; if the live working distance is equal to the safety warning distance, then generate the corresponding sound warning control signal, and upload the sound warning control signal to the sound warning component through the signal transmission component corresponding to the warning unit to start the corresponding power operation critical safety sound alarm work; If the live working distance is less than the safety warning distance, then generate the corresponding sound and photoelectric warning control signals, and upload the sound and photoelectric warning control signals to the sound warning component and the photoelectric warning component through the signal transmission component corresponding to the warning unit to simultaneously perform the corresponding power operation critical sound and light warning work.

9. An intelligent early warning device for the critical edge of electric power operation, characterized in that, For implementing the power operation critical edge intelligent early warning system described in any one of claims 1-8, the power operation critical edge intelligent early warning device includes a box body, the box body is in the shape of a cylindrical shell structure, and a plurality of image acquisition units are arranged on the corresponding outer circumference of the box body in the shape of a cylindrical shell structure. The plurality of image acquisition units on the box body are arranged at equal angles. A radar ranging unit is arranged above the image acquisition unit. A field strength induction unit, an early warning unit and a control center are arranged inside the box body. The control center is internally provided with an image recognition component and a data analysis component. The image acquisition unit, the radar ranging unit, the field strength induction unit and the early warning unit are all electrically connected to the control center. The image acquisition unit includes a camera component and an image transmission component. The camera component is electrically connected to the image transmission component. The image transmission component is electrically connected to the image recognition component. The radar ranging unit includes a radar transmitting component and a radar receiving component. The radar transmitting component is electrically connected to the radar receiving component. The radar receiving component is electrically connected to the data analysis component. The early warning unit includes a sound early warning component, an optoelectronic early warning component and a signal transmission component. The sound early warning component and the optoelectronic early warning component are both electrically connected to the signal transmission component. The signal transmission component is electrically connected to the control center.

10. A critical edge intelligent early warning method for power operation, characterized in that, The method is implemented based on the power operation critical edge intelligent early warning system described in claim 1. The power operation critical edge intelligent early warning method includes: Using the image acquisition unit to collect the image frames of the environment where the operator is located in real time and transmit them to the corresponding image recognition component in the control center; using the image recognition component to perform charged identification and positioning on the image frames of the environment where the operator is located to obtain the real-time charged space positioning of the operator; Based on the real-time charged space positioning of the operator and combined with the field strength induction unit, perform operation positioning electric field strength measurement on the corresponding real-time operation process of the power operation personnel to obtain the electric field strength corresponding to the position where the operator is located; perform critical voltage level evaluation according to the electric field strength corresponding to the position where the operator is located to obtain the critical voltage level partition where each operator is located, and upload it to the control center; Using the radar ranging unit to measure the charged distance between the metal tools held by the power operation personnel corresponding to each operator in the critical voltage level partition and the charged equipment to obtain the charged distance between the operator and the charged equipment in each voltage level partition, and upload it to the control center; By setting the safety early warning distance corresponding to each voltage level in the control center according to the critical voltage level partition where each operator is located, and comparing the safety early warning distance with the charged distance between the operator and the charged equipment to obtain the critical safety comparison result of the operator; using the early warning unit to perform power operation early warning processing on the critical safety comparison result of the operator to perform the corresponding power operation critical edge safety early warning work.

Images