A method, early warning method, device and system for identifying field strength azimuth

Abstract

This invention discloses a field strength orientation identification method, early warning method, device, and system, including: acquiring posture and position data of a worker before and after displacement; acquiring electric field data of a charged body before and after the worker's displacement; determining the spatial coordinate system corresponding to the charged body based on the posture and position data of the worker before and after displacement; calculating the relative distance between the worker and the charged body before and after displacement based on the spatial coordinate system; and calculating the electric field strength orientation data of the charged body based on the relative distance between the worker and the charged body before and after displacement, according to a pre-established spatial orientation calculation model of the charged body. This invention differs from most existing algorithms that only compare the electric field strength of the charged body with a threshold for early warning. It can dynamically and in real-time monitor the spatial changes of the charged body relative to an orthogonal flat plate electric field sensor, accurately predicting the spatial direction of the imminent electrical state, thus providing a foundation for early warning of imminent electrical safety.

Description

Technical Field

[0001] This invention relates to the field of power system emergency power warning technology, and in particular to a field strength location identification method, warning method, equipment and system. Background Technology

[0002] With the rapid development of power systems, complex power lines are becoming increasingly common, and a series of environmental impact issues caused by electrostatic effects, magnetic field effects, and corona phenomena are increasingly posing a significant threat to production safety. Undistorted measurement of strong electric field signals under complex electromagnetic environments is of great importance for early warning and monitoring of safety risks for workers.

[0003] There are currently two main methods for measuring power frequency electric fields: electromagnetic induction and optical effects. Traditional electromagnetic induction sensors struggle to accurately measure strong electric fields, especially in non-uniform electric fields and narrow spaces. Furthermore, electromagnetic induction sensors often employ spherical probes with metal spheres as the outer shell. This material and structure significantly affect the measured electric field and limits their application, as they can only measure field strength and not the time-domain waveform. In existing technologies, to reduce safety hazards for workers during power operation and maintenance, electric field early warning devices use electric field sensors to determine the electric field strength of charged bodies and compare it to a threshold to trigger an alarm when the strength exceeds the warning level. However, the electric field radiation area formed by a charged body is a three-dimensional space. Electric field sensors can only determine the magnitude of the field, not its precise location, thus failing to provide accurate warning information for workers and hindering the formation of precise early warnings. Summary of the Invention

[0004] In view of this, the present invention proposes a field strength orientation identification method, early warning method, device, and system to solve the problem that existing power emergency warning systems cannot determine the accurate orientation of the field strength and provide safety guidance for workers. To achieve one, some, or all of the above objectives, or other objectives, the present invention proposes a field strength orientation identification method, comprising:

[0005] Acquire the posture and position data of the operator before and after displacement, and acquire the electric field data of the charged body before and after displacement of the operator;

[0006] Based on the posture and position data of the operator before and after displacement, the three-dimensional spatial coordinate system corresponding to the charged body is determined, and the relative distance of the operator to the charged body before and after displacement is calculated based on the three-dimensional spatial coordinate system.

[0007] Based on the relative distance to the charged body before and after displacement, the electric field strength orientation data of the charged body are calculated according to the pre-established spatial orientation calculation model of the charged body.

[0008] According to a specific implementation method, in the above-mentioned field strength orientation identification method, the pre-established spatial orientation calculation model of the charged body is as follows:

[0009]

[0010] Among them, D′ a_p D′ represents the distance between the worker and the reference point of the electric field of the charged body before the worker's displacement. b_p D′ represents the distance of the worker relative to the electric field reference point of the charged body after displacement. a_b This refers to the displacement distance of the workers.

[0011] According to a specific implementation, the above-mentioned field strength orientation identification method, in acquiring the posture data and position data of the worker before and after displacement, includes:

[0012] Receives initial posture and position data of the worker before and after displacement, monitored by data acquisition equipment.

[0013] The attitude and position data are subjected to Kalman filtering, compensation, and integration to obtain the final attitude and position data before and after displacement.

[0014] According to a specific implementation, in the above-mentioned field strength orientation identification method, the step of acquiring the electric field data of the charged body before and after the worker's displacement includes:

[0015] The system receives electric field data before and after displacement from the data acquisition device, performs FFT and Kalman filtering on the electric field data, and obtains the processed electric field data before and after displacement.

[0016] Another aspect of the present invention provides a power operation early warning method, comprising:

[0017] The electric field orientation data of the charged body are calculated using the above-mentioned electric field orientation identification method.

[0018] In addition, the movement behavior of the workers can be identified based on the posture and position data of the workers before and after displacement.

[0019] A comprehensive early warning information is generated by combining the identified movement behavior of workers with the electric field strength and location data of charged bodies.

[0020] According to a specific implementation, in the above-mentioned power operation early warning method, the step of identifying the worker's movement behavior based on the acquired posture data and position data before and after the worker's displacement includes:

[0021] Receive air pressure data monitored by data acquisition equipment.

[0022] Calculate the altitude based on the air pressure data;

[0023] The movement behavior of the workers is identified based on the altitude and the posture and position data before and after the displacement.

[0024] In another aspect, the present invention provides an electronic device including a processor, a network interface, and a memory, wherein the processor, the network interface, and the memory are interconnected, wherein the memory is used to store a computer program, the computer program including program instructions, and the processor is configured to invoke the program instructions to execute the above-described field strength orientation identification method or the above-described power operation early warning method.

[0025] In another aspect, the present invention provides a power operation early warning system, comprising: a data acquisition device and an electronic device;

[0026] The data acquisition device is used to collect posture and position data of the operator before and after displacement, and send them to the electronic device;

[0027] The electronic device is used to calculate the electric field strength orientation data of the reference point using the above-mentioned electric field strength orientation identification method; and to identify the movement behavior of the operator based on the acquired posture data and position data before and after the operator's displacement; and to generate comprehensive early warning information by combining the identified movement behavior of the operator with the electric field strength orientation data of the charged body.

[0028] According to one specific implementation, in the above-mentioned power operation early warning system, the data acquisition equipment includes: an accelerometer, a gyroscope, a barometer, and an orthogonal flat-plate electric field sensor.

[0029] Implementing the embodiments of the present invention will have the following beneficial effects:

[0030] The method provided in this invention, based on multidimensional electric field intensity vector measurement using an orthogonal flat-plate electric field sensor, pre-constructs a three-dimensional spatial distribution relationship and orientation identification model of the orthogonal components of a charged body. Simultaneously, it combines dynamic monitoring of the attitude data from the orthogonal flat-plate electric field sensor with the pre-constructed orientation identification model to predict the orientation of the charged body relative to the sensor. This enables multidimensional identification of the energized state of risk sources in complex scenarios. Unlike most existing algorithms that rely solely on comparing the electric field intensity of the charged body with a threshold for early warning, this invention dynamically and in real-time monitors the spatial changes of the charged body relative to the orthogonal flat-plate electric field sensor, accurately predicting the spatial direction of the energized state and providing a foundation for energized safety early warning. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] in:

[0033] Figure 1 This is a schematic diagram of the field strength orientation identification method in one embodiment;

[0034] Figure 2 This is a schematic diagram of the spatial composite field orientation measurement decomposition of an orthogonal flat-panel sensor in one embodiment;

[0035] Figure 3a This is a schematic diagram of spatial rotation measurement using an orthogonal flat plate sensor in one embodiment. Figure 1 ;

[0036] Figure 3b This is a schematic diagram of spatial rotation measurement using an orthogonal flat plate sensor in one embodiment. Figure 2 ;

[0037] Figure 3c Schematic diagram 3 shows the spatial rotation measurement of an orthogonal flat plate sensor in one embodiment;

[0038] Figure 4 This is a schematic diagram showing the relationship between the measured values ​​of the orthogonal flat plate sensor and the distance to the charged body in one embodiment;

[0039] Figure 5 This is a schematic diagram of the location data processing flow in one embodiment;

[0040] Figure 6 This is a schematic diagram of the pitch and roll Kalman estimation data processing flow in one embodiment;

[0041] Figure 7 This is a schematic diagram of the field strength data processing flow in one embodiment;

[0042] Figure 8 This is a schematic diagram of a power operation early warning method in one embodiment;

[0043] Figure 9 Here is a flowchart of the behavior recognition process for power workers in one embodiment;

[0044] Figure 10 Here is a flowchart of the data processing for the movement speed of power workers in one embodiment;

[0045] Figure 11 This is a schematic diagram of the operation method of the power operation early warning system in one embodiment;

[0046] Figure 12 This is a schematic diagram of the electronic device structure in one embodiment. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] Example 1

[0049] Figure 1 An exemplary embodiment of the present invention illustrates a field strength orientation identification method, comprising:

[0050] Acquire the posture and position data of the operator before and after displacement, and acquire the electric field data of the charged body before and after displacement of the operator;

[0051] Based on the posture and position data of the operator before and after displacement, the three-dimensional spatial coordinate system corresponding to the charged body is determined, and the relative distance of the operator to the charged body before and after displacement is calculated based on the three-dimensional spatial coordinate system.

[0052] Based on the relative distance to the charged body before and after displacement, the electric field strength orientation data of the charged body are calculated according to the pre-established spatial orientation calculation model of the charged body.

[0053] The method provided in this embodiment, based on multi-dimensional electric field intensity vector measurement using an orthogonal flat-plate electric field sensor, pre-constructs a three-dimensional spatial distribution relationship and orientation identification model of the orthogonal components of a charged body. Simultaneously, it combines dynamic monitoring of the attitude data from the orthogonal flat-plate electric field sensor (carried by the operator, monitoring attitude and position through operator posture data). Based on the pre-constructed orientation identification model, it achieves orientation prediction of the charged body relative to the orthogonal flat-plate electric field sensor, enabling multi-dimensional identification of the energized state of risk sources in complex scenarios. Unlike most existing algorithms that only compare the electric field intensity of the charged body with a threshold for early warning, this invention can dynamically and in real-time monitor the spatial changes of the charged body relative to the orthogonal flat-plate electric field sensor, accurately predicting the spatial direction of the energized state, thus providing a foundation for energized safety early warning. Example 2

[0054] In one possible implementation, the pre-established spatial orientation calculation model for the charged body is as follows:

[0055]

[0056] Among them, D′ a_pD′ represents the distance between the worker and the reference point of the electric field of the charged body before the worker's displacement. b_p D′ represents the distance of the worker relative to the electric field reference point of the charged body after displacement. a_b Displacement distance of the workers

[0057] Specifically, the spatial orientation calculation model of the charged body is established using the following method:

[0058] The measurement value of the orthogonal flat plate electric field sensor is the magnitude of the orthogonal component of the spatial field strength E, denoted as |E|. x |、|E y |、|E z | satisfies the following relationship:

[0059]

[0060] like Figure 2 The diagram illustrates a charged body spatial coordinate system (x, y, z) constructed based on the posture and position data of the worker before and after displacement (points A and B in the diagram). Point P is the location of the charged body's electric field source within this spatial coordinate system. P is a fixed point. The orientation algorithm provided in this embodiment derives the position of point P relative to the worker using the relationship between electric field strength and distance, and the worker's spatial displacement via a three-point spatial positioning method. The position coordinates are denoted as (P...). x ,P y ,P z An orthogonal flat-plate electric field sensor measures the electric field strength at point P in space (i.e., where the worker is located). The position of point A is denoted as (A...). x A y A z The measured electric field strength value is recorded as E. ax E ay E az The combined field strength is E a .

[0061] The orthogonal flat-plate electric field sensor is moved to point B in space to measure the electric field intensity at point P. The position of point B is denoted as (B0). x B y B z The measured electric field strength value is recorded as E. bx E by E bz The combined field strength is E b .

[0062] The distance D from point A to point P in space a_p for:

[0063]

[0064] The distance D from point B to point P in space b_p for:

[0065]

[0066] The distance D from point A to point B in space a_b for:

[0067]

[0068] With point A in space as the center, D a_p Draw a circle with radius B; center at point D. b_p Draw a circle with radius P. The two circles will intersect at point P. Let the angle between the line connecting points B and P and the horizontal plane be θ. Therefore, according to trigonometric functions, we can obtain:

[0069]

[0070] The location of point P can be identified by calculating the angle θ.

[0071] Furthermore, because the electric field intensity components along the x, y, and z axes of an orthogonal flat-plate electric field sensor exhibit a relationship of change with the rotation angle when the same position is rotated 90°, the electric field intensity measured on that surface is maximum when one side faces the charged body, and vice versa. Additionally, at the same position, the vector sum and electric field intensity of the x, y, and z components remain essentially unchanged, such as... Figures 3a-3c As shown.

[0072] The orthogonal flat-plate electric field sensor was placed in various scenarios (double-circuit, single-circuit, cross-pass, transformer, etc.) at different distances (0.7m, 1.4m, 2.1m, 2.8m, 3.5m, 4.2m, 4.9m, 5.6m) from a 10kV charged conductor for experiments. The experimental results show that the measured value of the orthogonal flat-plate electric field sensor has an exponential relationship with the distance from the charged conductor. Figure 4 As shown.

[0073] In a 10kV power distribution network scenario, the distance between the orthogonal flat plate electric field sensor and the charged body is calculated based on the functional relationship between the measured values ​​of the orthogonal flat plate electric field sensor and the distance to the charged body.

[0074] In summary, the charged body orientation recognition technology combines the principle of spatial three-point positioning, the invariance of comprehensive field strength measured by orthogonal flat plate sensors at the same position under different postures, the positive correlation between the measured field strength and the distance to the field source, and the spatial displacement under motion state to construct an algorithm model capable of dynamically recognizing the orientation of charged bodies.

[0075] Furthermore, considering sensor measurement errors and noise interference, points A and B are taken as the centers of circles, and |E| is used as the delimiter for each circle. a |、|E b When drawing a circle with radius d, there may be cases where the circles intersect at non-unique points. Introducing d...ax d ay d az d bx d by d bz d abx d aby d abz The measurement error parameters are used to find a unique intersection point, which ensures that the calculation has a solution.

[0076] Therefore, the distance D′ from point A to point P in space a_p for:

[0077]

[0078] Therefore, the distance from point B to point P in space is D′. b_p for:

[0079]

[0080] Therefore, the distance D′ from point A to point B in space a_b for:

[0081]

[0082] With point A in space as the center, D′ a_p Draw a circle with radius D', centered at point B in space. b_p Draw a circle with radius P. The two circles will intersect at point P. Let the angle between the line connecting points B and P and the horizontal plane be θ. Therefore, according to trigonometric functions, we can obtain:

[0083] However, since orthogonal planar sensors perform non-directional (isotropic) measurements of the electric field, the measured value is the position |E| at a certain point. x |、|E y |、|E z | It lacks directionality. As shown in Table 1, there are at most 8 spatial distribution scenarios for calculating the location of the field source:

[0084] Table 2-1 Distribution of Field Source Locations

[0085] Orthogonal components Spatial coordinate quadrants <![CDATA[E x >0,E y >0,E z >0]]> First Quadrant <![CDATA[E x <0,E y >0,E z >0]]> Second Quadrant <![CDATA[E x <0,E y <0,E z >0]]> Third Quadrant <![CDATA[E x >0,E y <0,E z >0]]> Fourth Quadrant <![CDATA[E x >0,E y >0,E z <0]]> Fifth Quadrant <![CDATA[E x <0,E y >0,E z <0]]> Sixth Quadrant <![CDATA[E x <0,E y <0,E z <0]]> Seventh Quadrant <![CDATA[E x >0,E y <0,E z <0]]> Eighth Quadrant

[0086] Using inertial navigation coordinates as the spatial coordinate system, and combining the operator's behavior and posture data with the difference in electric field before and after displacement, the quadrant of the charged body's spatial coordinates is determined (the spatial coordinate system corresponding to the charged body divides space into 8 regions; therefore, determining the coordinate system first facilitates the description of spatial position and distance calculation). A suitable d is then calculated and selected. ax d ay d az dbx d by d bz d abx d aby d abz Substitute the parameters into equations 2.6, 2.7, and 2.8 to calculate D′. a_p 、D′ b_p 、D′ a_b Substituting into Equation 2.9, we obtain the azimuth θ of the field source, thus achieving the purpose of real-time estimation of the current field strength azimuth.

[0087] According to one possible implementation, in the above field strength orientation identification method, such as Figure 5 , 6 As shown, acquiring the posture and position data of the worker before and after displacement includes:

[0088] Receives initial posture and position data of the worker before and after displacement, monitored by data acquisition equipment.

[0089] The attitude and position data are subjected to Kalman filtering, compensation, and integration to obtain the final attitude and position data before and after displacement.

[0090] According to one possible implementation, in the above field strength orientation identification method, such as Figure 7 As shown, acquiring the electric field data of the charged body before and after the worker's displacement includes:

[0091] The system receives electric field data before and after displacement from the data acquisition device, performs FFT and Kalman filtering on the electric field data, and obtains the processed electric field data before and after displacement.

[0092] Example 3

[0093] Another aspect of the present invention, such as Figure 8 As shown, a power operation early warning method is also provided, including:

[0094] The electric field orientation data of the charged body are calculated using the above-mentioned electric field orientation identification method.

[0095] In addition, the movement behavior of the workers can be identified based on the posture and position data of the workers before and after displacement.

[0096] A comprehensive early warning information is generated by combining the identified movement behavior of workers with the electric field strength and location data of charged bodies.

[0097] The comprehensive early warning information includes route guidance information, etc.

[0098] It is understandable that in complex environments such as high-altitude mountainous areas, temperature, humidity, atmospheric conditions, and ultraviolet radiation are often unpredictable. Individual tolerance levels vary under different conditions, and the workload of each person should be effectively balanced. However, workers often neglect their own capacity due to teamwork, leading to serious consequences such as fatigue, shortness of breath, dizziness, and rapid heart rate. Therefore, how to manage the personal safety of workers in complex working environments is also a problem that emergency power warning systems need to address.

[0099] In this embodiment, the movement status of the workers is obtained by recognizing their movement behavior. Based on the movement status, the physical condition of the workers is monitored. Combined with the field strength and orientation information, the workers are guided to take a route so that they can safely avoid the corresponding non-electric field radiation space and ensure their personal safety. This method uses intelligent sensing of the orientation of charged bodies and real-time analysis of the workers' work behavior to provide early warning of electric field risk sources for the workers during the operation, reduce the risk of operation, and prevent safety accidents.

[0100] According to one possible implementation, the above-mentioned power operation early warning method further includes: a position correction step after identifying the worker's movement behavior based on the acquired posture and position data before and after the worker's displacement. The position correction step includes: determining whether the identified worker movement behavior is a large-amplitude movement (e.g., climbing, jumping, or exceeding normal walking speed), and correcting the worker's posture and position data based on the movement behavior to correct the electric field strength orientation data of the charged body, thereby correcting the large electric field measurement error caused by the worker's movement. According to one possible implementation, in the above-mentioned power operation early warning method, the identification of the worker's movement behavior based on the acquired posture and position data before and after the worker's displacement includes:

[0101] Receive air pressure data monitored by data acquisition equipment.

[0102] Calculate the altitude based on the air pressure data;

[0103] The movement behavior of the workers is identified based on the altitude and the posture and position data before and after the displacement.

[0104] Specifically, in power distribution network operations, the risk of electrical contact is highest when workers are climbing and approaching hazardous electric field sources. Therefore, the change in the vertical displacement of workers is the most important parameter to be assessed in risk monitoring and has a significant weight in risk prediction models. Confirming the tower base location (altitude point) is a prerequisite for identifying climbing behavior. The tower base location is identified by comprehensively analyzing data on the number of steps taken by workers, their posture angles, and altitude, and then searching for model features.

[0105] Because the operator places the equipment in their head position during movement, the equipment's placement is relatively fixed. Therefore, by calculating the Z-axis (vertical) acceleration, we can obtain a sinusoidal trajectory for climbing the tower. The second step is Z-axis (vertical) acceleration peak detection. We recorded the previous Z-axis (vertical) acceleration and direction of movement. By observing the change in Z-axis (vertical) acceleration, we can determine the current acceleration direction and compare it with the previously saved acceleration direction. If they are opposite, meaning the peak value has just passed, the tower climbing logic is entered for tower base identification; otherwise, it is discarded. The third step determines whether the operator is walking. If the operator is walking, it may be on a steep slope, lowering the confidence zone for tower base identification; otherwise, tower base identification continues. The fourth step monitors whether the altitude changes synchronously and in the same direction, and whether the height difference meets the typical single-step tower climbing height range for a person. If the height change meets the requirements, the current position is confirmed as the tower base height; otherwise, tower base identification continues. The climbing process after the tower base position is determined will be a key monitoring process for electric field risks. The data processing flow is as follows: Figure 9 The motion speed processing flow is as follows: Figure 10 As shown.

[0106] In another aspect, the present invention provides a power operation early warning system, comprising:

[0107] Data acquisition equipment and electronic equipment;

[0108] The data acquisition device is used to collect posture and position data of the operator before and after displacement, and send them to the electronic device;

[0109] The electronic device is used to calculate the electric field strength azimuth data of the reference point using the above-mentioned electric field strength azimuth identification method; and to identify the movement behavior of the operator based on the acquired posture data and position data of the operator before and after displacement; and to generate comprehensive early warning information by combining the identified movement behavior of the operator with the electric field strength azimuth data of the charged body.

[0110] The data acquisition equipment includes: an accelerometer, a gyroscope, a barometer, and an orthogonal flat-plate electric field sensor.

[0111] The implementation process of the early warning algorithm of the early warning system is as follows: Figure 11 As shown, the main algorithm steps are as follows:

[0112] S1. Hardware platform initialization;

[0113] S2. Initialize the orthogonal flat-plate electric field sensor, accelerometer, gyroscope, and barometer sensors;

[0114] S3. Sensor data reading;

[0115] S4. Sensor data preprocessing, including accelerometer and gyroscope Kalman filtering, barometer low-pass filtering, field strength FFT calculation, and Kalman filtering.

[0116] S5. Based on accelerometer and gyroscope attitude calculation, obtain the movement speed and displacement of the operator;

[0117] S6. Step counting calculation based on accelerometer;

[0118] S7. Substitute the charged body spatial orientation calculation model to calculate the spatial position of the charged body.

[0119] The early warning system provided in this embodiment uses orthogonal flat-plate electric field sensors, barometers, gyroscopes, and accelerometer sensors as hardware foundations to perceive and fuse data on electrostatic field distribution, worker posture, and worker displacement. This allows for the measurement of electrostatic field changes under dynamic worker conditions, and the derivation of the spatial distribution of charged bodies and safe distances. This improves the effectiveness of early prediction and assessment of risk sources, fully ensuring worker safety.

[0120] Another aspect of the present invention, such as Figure 12 As shown, an electronic device is also provided, which includes a processor, a network interface, and a memory. The processor, the network interface, and the memory are interconnected. The memory is used to store a computer program, which includes program instructions. The processor is configured to call the program instructions to execute the search optimization method described above.

[0121] In another aspect, the present invention provides a computer storage medium storing program instructions which, when executed by at least one processor, are used for the method of proactively issuing electronic invoices in a guided parking lot according to the present invention.

[0122] In embodiments of the present invention, the processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0123] The various methods, steps, and logic diagrams disclosed in the embodiments of this invention can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The processor reads information from the storage medium and, in conjunction with its hardware, completes the steps of the above methods.

[0124] The storage medium can be memory, such as volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.

[0125] Among them, non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory.

[0126] Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (Synchlink DRAM, SLDRAM), and direct memory bus RAM (DRRAM).

[0127] The storage media described in the embodiments of the present invention are intended to include, but are not limited to, these and any other suitable types of memory.

[0128] It should be understood that the system disclosed in this invention can be implemented in other ways. For example, the division of modules is merely a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the communication connection between modules can be through some interfaces, indirect coupling or communication connections between servers or units, and can be electrical or other forms.

[0129] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one processing unit. The integrated unit described above can be implemented in hardware or as a software functional unit.

[0130] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0131] The above description discloses only preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Therefore, equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A method for identifying the orientation of an electric field, characterized in that: include: The system acquires the posture and position data of the operator before and after displacement, and the electric field data of the charged body before and after displacement. The operator carries an orthogonal flat plate electric field sensor to measure the electric field data of the charged body. The distance between the orthogonal flat plate electric field sensor and the charged body is calculated from the measurement value of the orthogonal flat plate electric field sensor. Based on the posture and position data of the operator before and after displacement, the three-dimensional spatial coordinate system corresponding to the charged body is determined, and the relative distance of the operator to the charged body before and after displacement is calculated based on the three-dimensional spatial coordinate system. Based on the relative distance to the charged body before and after displacement, the electric field strength orientation data of the charged body are calculated according to the pre-established spatial orientation calculation model of the charged body. The pre-established spatial orientation calculation model for the charged body is as follows: in, This represents the distance of the worker relative to the electric field reference point of the charged body before displacement. This represents the distance of the worker relative to the electric field reference point of the charged body after displacement. This refers to the displacement distance of the workers.

2. The field strength orientation identification method as described in claim 1, characterized in that: The acquisition of the worker's posture and position data before and after displacement includes: Receives initial posture and position data of the worker before and after displacement, monitored by data acquisition equipment. The attitude and position data are subjected to Kalman filtering, compensation, and integration to obtain the final attitude and position data before and after displacement.

3. The field strength orientation identification method as described in claim 1, characterized in that: The acquisition of electric field data of charged bodies before and after the worker's displacement includes: The system receives electric field data before and after displacement from the data acquisition device, performs FFT and Kalman filtering on the electric field data, and obtains processed electric field data before and after displacement.

4. A method for early warning of power operations, characterized in that: include: The electric field orientation identification method according to any one of claims 1 to 3 is used to calculate the electric field orientation data of the charged body; In addition, the movement behavior of the workers can be identified based on the posture and position data of the workers before and after displacement. Comprehensive early warning information is generated by combining the identified movement behavior of workers with the electric field strength and location data of charged bodies.

5. The power operation early warning method as described in claim 4, characterized in that, The step of recognizing the worker's motion behavior based on the acquired posture and position data before and after displacement includes: Receive air pressure data monitored by data acquisition equipment. Calculate the altitude based on the air pressure data; The movement behavior of the workers is identified based on the altitude and the posture and position data before and after the displacement.

6. An electronic device, characterized in that: The device includes a processor, a network interface, and a memory, which are interconnected. The memory stores a computer program, which includes program instructions. The processor is configured to invoke the program instructions to execute the field strength orientation identification method as described in any one of claims 1 to 3, or the power operation early warning method as described in claims 4 to 5.

7. A power operation early warning system, characterized in that: include: Data acquisition equipment and electronic equipment; The data acquisition device is used to collect posture and position data of the operator before and after displacement, and send them to the electronic device; The electronic device is used to calculate the electric field strength orientation data of the reference point using the electric field strength orientation identification method according to any one of claims 1 to 3; and to identify the movement behavior of the operator based on the acquired posture data and position data before and after the operator's displacement; and to generate comprehensive early warning information by combining the identified movement behavior of the operator with the electric field strength orientation data of the charged body.

8. The power operation early warning system as described in claim 7, characterized in that: The data acquisition equipment includes: accelerometer, gyroscope, barometer, and orthogonal flat-plate electric field sensor.

Images