Electric power safety distance measurement monitoring method and device based on laser sensor

Abstract

The invention relates to an electric power safety distance measurement monitoring method and device based on a laser sensor, and relates to the technical field of electric power equipment distance measurement. The method comprises the following steps: acquiring distance information between a target facility and a target obstacle in a power system according to a laser sensor; obtaining dynamic electromagnetic field information of the target facility, and performing parameter estimation on the distance information according to the dynamic electromagnetic field information based on a space parameter estimation technology of the electric power safety distance to obtain space parameters of the electric power safety distance; acquiring position information corresponding to the target facility, and fusing the position information and the spatial parameters of the electric power safety distance based on an information fusion technology of multi-sensor measurement data to obtain a measurement equation of safety distance measurement; and when the updated distance information is out of the preset safe distance range, generating distance alarm information corresponding to the target obstacle. By adopting the method, the distance measurement precision and the distance measurement speed of an electric power safety distance measurement mode can be improved.

Description

Technical Field

[0001] This application relates to the technical field of power equipment ranging, and particularly to a power safety ranging monitoring method, device, computer equipment, computer-readable storage medium, and computer program product based on a laser sensor. Background Art

[0002] The safety and reliability of power equipment are crucial for the operation of the power grid. Detecting and monitoring the working state and distance changes of power equipment can help discover potential faults, overloads, or other abnormal conditions, and take measures in advance to avoid accidents. Therefore, building a power safety ranging monitoring system is very important for ensuring the safe and reliable operation of power equipment and the power system.

[0003] However, current power equipment monitoring technologies have problems such as being limited by the number of sensors, difficult data acquisition, and low real-time performance, resulting in a limited monitoring range, possibly unable to comprehensively cover all key equipment, unable to detect and respond to changes in a timely manner, and being easily affected by electromagnetic interference during the power safety ranging monitoring process, leading to problems of low ranging accuracy and slow ranging speed in the current power safety ranging methods. Summary of the Invention

[0004] Based on this, it is necessary to provide a power safety ranging monitoring method, device, computer equipment, computer-readable storage medium, and computer program product based on a laser sensor for the above technical problems, which can improve the ranging accuracy and ranging speed of the power safety ranging method.

[0005] In a first aspect, an embodiment of this application provides a power safety ranging monitoring method based on a laser sensor. The method includes:

[0006] Obtain the distance information between a target facility and a target obstacle in the power system according to the laser sensor; the target facility is the facility to be monitored in the power system, and the target obstacle is an obstacle within a preset range near the target facility;

[0007] Obtain the dynamic electromagnetic field information of the target facility, and based on the spatial parameter estimation technology of the power safety distance, perform parameter estimation on the distance information according to the dynamic electromagnetic field information to obtain the spatial parameters of the power safety distance;

[0008] Obtain the position information corresponding to the target facility, and based on the information fusion technology of multi-sensor measurement data, fuse the position information with the spatial parameters of the power safety distance to obtain a measurement equation for safe ranging; the measurement equation for safe ranging is used to update the distance information;

[0009] Generate distance warning information corresponding to the target obstacle when the updated distance information is outside the preset safe distance range.

[0010] In one embodiment, the parameter estimation of the distance information according to the dynamic electromagnetic field information to obtain the spatial parameters of the electrical safety distance includes: performing parameter estimation on the distance information according to the dynamic electromagnetic field information to obtain an electrical safety distance estimation result; optimizing the electrical safety distance estimation result to determine the spatial parameters of the electrical safety distance. In one embodiment, the performing parameter estimation on the distance information according to the dynamic electromagnetic field information to obtain an electrical safety distance estimation result includes: based on the time delay method or the phase difference method, calculating the azimuth distance state information of the target obstacle relative to the target facility according to the distance information; performing information fusion on the dynamic electromagnetic field information and the azimuth distance state information to obtain an electromagnetic field superposition output result of the alternating electromagnetic field; performing spatial filtering on the electromagnetic field superposition output result of the alternating electromagnetic field to obtain the electrical safety distance estimation result. In one embodiment, the optimizing the electrical safety distance estimation result to determine the spatial parameters of the electrical safety distance includes: based on the electromagnetic induction law and the magnetic flux continuity principle, setting the ranging coefficients of each sensor in the electrical safety distance estimation result by using the average distribution method to determine the eigenvalue of the charge moving in the wire under the action of the induced electric field; performing multi-sensor fusion filtering on the closed surface to perform fusion calculation on the continuously distributed bound charges in the electrical safety distance estimation result, and obtaining a globally optimal estimation result according to the eigenvalue; using grid meshing to discretize the continuous field domain into a grid discrete node set, optimizing the parameter estimation of the sensing nodes in the globally optimal estimation result, and determining the spatial parameters of the electrical safety distance. In one embodiment, the fusing the position information with the spatial parameters of the electrical safety distance to obtain a measurement equation for safe ranging includes: performing information fusion on various types of the position information and the spatial parameters of the electrical safety distance to obtain a fused electrical safety distance estimation result; according to the fused electrical safety distance estimation result, constructing a measurement equation between the ranging parameter value and the sensor structure as the measurement equation for safe ranging. In one embodiment, the constructing a measurement equation between the ranging parameter value and the sensor structure as the measurement equation for safe ranging according to the fused electrical safety distance estimation result includes: determining the state vector of the measurement frequency band of the electric field sensor according to the fused electrical safety distance estimation result; according to the state vector of the measurement frequency band of the electric field sensor, using grid meshing and measurement parameter identification method to establish an output dynamic state model for electrical safety ranging; based on the control input vector and Gaussian noise in the output dynamic state model for electrical safety ranging, using the state transition matrix to describe the state change process of the system, and constructing the measurement equation for safe ranging between the ranging parameter value and the sensor structure.

[0011] In a second aspect, the present application also provides a power safety ranging and monitoring device based on a laser sensor. The device includes: a distance acquisition module configured to obtain distance information between a target facility and a target obstacle in a power system according to the laser sensor; the target facility being a facility to be monitored in the power system, and the target obstacle being an obstacle within a preset range near the target facility; a parameter estimation module configured to obtain dynamic electromagnetic field information of the target facility, and perform parameter estimation on the distance information according to the dynamic electromagnetic field information based on a spatial parameter estimation technique for power safety distance, so as to obtain spatial parameters of the power safety distance; a parameter fusion module configured to obtain position information corresponding to the target facility, and fuse the position information with the spatial parameters of the power safety distance based on an information fusion technique for multi-sensor measurement data, so as to obtain a measurement equation for safe ranging; the measurement equation for safe ranging being used to update the distance information; and an alarm information generation module configured to generate distance alarm information corresponding to the target obstacle when the updated distance information is outside a preset safe distance range.

[0012] In a third aspect, the present application also provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the following steps are implemented: obtaining distance information between a target facility and a target obstacle in a power system according to a laser sensor; the target facility is a facility to be monitored in the power system, and the target obstacle is an obstacle within a preset range near the target facility; obtaining dynamic electromagnetic field information of the target facility, and based on the spatial parameter estimation technology of the power safety distance, performing parameter estimation on the distance information according to the dynamic electromagnetic field information to obtain the spatial parameters of the power safety distance; obtaining the position information corresponding to the target facility, and based on the information fusion technology of multi-sensor measurement data, fusing the position information with the spatial parameters of the power safety distance to obtain a measurement equation for safe distance measurement; the measurement equation for safe distance measurement is used to update the distance information; in the case where the updated distance information is outside a preset safe distance range, generating distance warning information corresponding to the target obstacle. In a fourth aspect, the present application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon. When the computer program is executed by a processor, the following steps are implemented: obtaining distance information between a target facility and a target obstacle in a power system according to a laser sensor; the target facility is a facility to be monitored in the power system, and the target obstacle is an obstacle within a preset range near the target facility; obtaining dynamic electromagnetic field information of the target facility, and based on the spatial parameter estimation technology of the power safety distance, performing parameter estimation on the distance information according to the dynamic electromagnetic field information to obtain the spatial parameters of the power safety distance; obtaining the position information corresponding to the target facility, and based on the information fusion technology of multi-sensor measurement data, fusing the position information with the spatial parameters of the power safety distance to obtain a measurement equation for safe distance measurement; the measurement equation for safe distance measurement is used to update the distance information; in the case where the updated distance information is outside a preset safe distance range, generating distance warning information corresponding to the target obstacle.

[0013] Fifth aspect, the present application also provides a computer program product. The computer program product includes a computer program which, when executed by a processor, implements the following steps: obtaining distance information between a target facility and a target obstacle in a power system according to a laser sensor; the target facility being a facility to be monitored in the power system, and the target obstacle being an obstacle within a preset range near the target facility; obtaining dynamic electromagnetic field information of the target facility, and based on the spatial parameter estimation technology of the power safety distance, performing parameter estimation on the distance information according to the dynamic electromagnetic field information to obtain the spatial parameters of the power safety distance; obtaining the position information corresponding to the target facility, and based on the information fusion technology of multi-sensor measurement data, fusing the position information with the spatial parameters of the power safety distance to obtain a measurement equation for safe distance measurement; the measurement equation for safe distance measurement being used to update the distance information; and generating distance warning information corresponding to the target obstacle when the updated distance information is outside a preset safe distance range.

[0014] The above-mentioned power safety distance measurement and monitoring method, device, computer device, storage medium and computer program product based on a laser sensor monitor the safety distance between a target facility and an obstacle in a power system in real time through the laser sensor and dynamic electromagnetic field information. First, the laser sensor obtains the actual distance information between the target facility and the target obstacle. Then, the acquisition of dynamic electromagnetic field information helps to evaluate the electromagnetic interference of power facilities at different times. Through the spatial parameter estimation technology of the power safety distance, parameter estimation is performed on the distance information to obtain the applicable safety distance. Furthermore, in combination with the position information of the target facility, using the information fusion technology of multi-sensor measurement data, the position information is fused with the spatial parameters of the power safety distance to form a measurement equation for safe distance measurement, ensuring the timely detection of potential safety hazards. When the updated distance information exceeds the preset safe distance range, the system will generate distance warning information for the target obstacle. Through the fusion of multi-sensor data and spatial parameter estimation, the real-time performance of the power safety distance measurement and monitoring process is improved, the monitoring range is extended, which helps to comprehensively cover all key equipment, and changes can be detected and responded to in a timely manner. The influence of electromagnetic interference that is easily suffered in the power safety distance measurement and monitoring process is avoided, and the accuracy and speed of power safety distance measurement are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 Schematic flowchart of the power safety ranging monitoring method based on a laser sensor in one embodiment;

[0017] Figure 2 Schematic flowchart of the power safety ranging monitoring method based on a laser sensor in another embodiment;

[0018] Figure 3 Schematic diagram of the power safety laser sensing detection principle in one embodiment;

[0019] Figure 4 Overall design structure diagram of the system in one embodiment;

[0020] Figure 5 Hardware structure diagram of the data acquisition and processing module in one embodiment;

[0021] Figure 6 Schematic diagram of the sampling information of the laser sensor in one embodiment;

[0022] Figure 7 Schematic diagram of the power safety ranging output in one embodiment;

[0023] Figure 8 Schematic diagram of the power ranging estimation error in one embodiment;

[0024] Figure 9 Schematic diagram of the comparison of power safety ranging accuracy in one embodiment;

[0025] Figure 10 Schematic diagram of the comparison of the power safety ranging monitoring response time in one embodiment;

[0026] Figure 11 Structural block diagram of the power safety ranging monitoring device based on a laser sensor in one embodiment;

[0027] Figure 12 Internal structure diagram of a computer device in one embodiment. Detailed implementation manners

[0028] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0029] It should be noted that the user information involved in this application (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) are all information and data that have been authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of relevant countries and regions.

[0030] In one embodiment, as Figure 1 shown, a power safety ranging and monitoring method based on a laser sensor is provided. In this embodiment, taking the application of this method to a terminal as an example, it can be understood that this method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0031] S101. Obtain the distance information between the target facility and the target obstacle in the power system according to the laser sensor.

[0032] Among them, the target facility is the facility to be monitored in the power system, such as a certain section of the power line, and the target obstacle is an obstacle within a preset range near the target facility, such as vegetation, animals, and other obstacles. The laser sensor is a device that uses a laser beam for measurement, which can accurately measure the distance between the power line and surrounding obstacles, and provide real-time ranging data to help improve the safety of the power line and the ability to prevent accidents.

[0033] S102. Obtain the dynamic electromagnetic field information of the target facility, and based on the spatial parameter estimation technology of the power safety distance, perform parameter estimation on the distance information according to the dynamic electromagnetic field information to obtain the spatial parameters of the power safety distance.

[0034] Among them, the dynamic electromagnetic field information refers to the real-time change data of the electromagnetic field generated due to current flow and electromagnetic wave propagation around the power facility. These information can reflect the electromagnetic interference, field strength change, etc. generated during the operation of the power facility, and are usually monitored and collected through sensors.

[0035] Among them, the spatial parameter estimation technology of the power safety distance is a method based on sensor data for calculation and analysis. By processing the real-time measured distance and electromagnetic field data, it estimates the safety distance between the power facility and the obstacle, and can dynamically adjust the evaluation of the safety distance to ensure accuracy under different environmental conditions.

[0036] S103. Obtain the location information corresponding to the target facility, and based on the information fusion technology of multi-sensor measurement data, fuse the location information with the spatial parameters of the power safety distance to obtain the measurement equation for safety ranging.

[0037] Among them, the information fusion technology of multi-sensor measurement data is a technology that integrates data from different sensors to improve measurement accuracy and reliability. In the power system, multiple sensors simultaneously collect environmental information. By preprocessing this data to remove noise and outliers, and then applying a fusion algorithm to integrate the data from different sensors into a more accurate comprehensive measurement result, it can effectively overcome the limitations of a single sensor and provide a more comprehensive environmental perception.

[0038] Among them, the measurement equation for safety ranging is a mathematical expression used to describe the distance relationship between power facilities and obstacles. This equation usually involves the actually measured distance, the set safety distance, and the influence of the dynamic electromagnetic field on the ranging result, and can monitor and evaluate the safety distance between power facilities and obstacles in real time to ensure the safety and reliability of the power system, that is, the measurement equation for safety ranging is used to update the distance information.

[0039] S104, in the case where the updated distance information is outside the preset safety distance range, generate distance warning information corresponding to the target obstacle.

[0040] Among them, the distance warning information is used to prompt the relevant staff of the target facility to take timely measures to eliminate the influence of the obstacle on the facility.

[0041] In the above power safety ranging monitoring method based on a laser sensor, the safety distance between the target facility and the obstacle in the power system is monitored in real time through the laser sensor and dynamic electromagnetic field information. First, the laser sensor obtains the actual distance information between the target facility and the target obstacle. Then, the acquisition of dynamic electromagnetic field information helps to evaluate the electromagnetic interference of the power facility at different times. Through the spatial parameter estimation technology of the power safety distance, the distance information is parameter-estimated to obtain the applicable safety distance. Furthermore, combined with the position information of the target facility, using the information fusion technology of multi-sensor measurement data, the position information is fused with the spatial parameters of the power safety distance to form a measurement equation for safety ranging, ensuring the timely detection of potential safety hazards. When the updated distance information exceeds the preset safety distance range, the system will generate distance warning information for the target obstacle. Through the fusion of data from multiple sensors and spatial parameter estimation, the real-time performance of the power safety ranging monitoring process is improved, the monitoring range is extended to help comprehensively cover all key equipment, and changes are detected and responded to in a timely manner, avoiding the influence of electromagnetic interference that is easily suffered in the power safety ranging monitoring process, and improving the accuracy and speed of power safety ranging.

[0042] In one embodiment, parameter-estimate the distance information according to the dynamic electromagnetic field information to obtain the spatial parameters of the power safety distance, including:

[0043] Estimate the parameters of the distance information based on the dynamic electromagnetic field information to obtain the estimated result of the electrical safety distance;

[0044] Optimize the estimated result of the electrical safety distance to determine the spatial parameters of the electrical safety distance.

[0045] Among them, the estimated result of the electrical safety distance is the corrected distance, and the spatial parameters of the electrical safety distance refer to the minimum safety distance required to ensure the safe operation of electrical facilities and their related factors. These parameters may include: the ranging coefficient of the sensor, the environmental impact factor, etc. By comprehensively considering these spatial parameters, it can be ensured that the electrical facilities are always within the safe range during operation, reducing potential safety risks.

[0046] Among them, the ranging coefficient of the sensor refers to the ranging accuracy of different sensors. For example, the coefficient of the laser sensor is 1.1, and that of the ultrasonic sensor is 0.9. The environmental impact factor is used to reflect the height of surrounding buildings and the vegetation situation.

[0047] Exemplarily, use a laser sensor to measure the distance information between the target object and the sensor, and calculate the azimuth and distance state information of the target object by methods such as time delay or phase difference. Obtain the dynamic electromagnetic field information for electrical safety ranging based on the excitation source frequency, and fuse it with the target azimuth state information. Use the electromagnetic field superposition output result of the alternating electromagnetic field for spatial filtering to obtain an accurate estimate of the electrical safety distance. Through Faraday's law of electromagnetic induction and the principle of magnetic flux continuity, set the ranging coefficient of each sensor by the average distribution method, and deduce the eigenvalue of the charge moving in the wire under the action of the induced electric field. Adopt multi-sensor fusion filtering on the closed surface to realize the fusion calculation of continuously distributed bound charges, and then obtain the global optimal estimate. Use grid division to discretize the continuous field domain into a grid discrete node set, and further optimize the parameter estimation of the sensing nodes for the electrical safety distance. According to the measurement characteristics between each laser sensor, realize the information distribution and centralized filtering processing of the electrical safety distance to comprehensively estimate the spatial parameters of the electrical safety distance.

[0048] In this embodiment, the parameters of the distance information are estimated based on the dynamic electromagnetic field information, and first, the estimated result of the electrical safety distance is obtained. Subsequently, this result is optimized to determine the spatial parameters of the electrical safety distance. This process ensures that under different environmental conditions, the safety distance between electrical facilities and obstacles is accurately evaluated and dynamically adjusted, improving the safety of electrical facilities, reducing potential safety hazards, and ensuring the stable operation of the power system.

[0049] In one embodiment, parameter estimation is performed on the distance information according to the dynamic electromagnetic field information to obtain the power safety distance estimation result, including: based on the time delay method or the phase difference method, calculating the azimuth distance state information of the target obstacle relative to the target facility according to the distance information; performing information fusion on the dynamic electromagnetic field information and the azimuth distance state information to obtain the electromagnetic field superposition output result of the alternating electromagnetic field; performing spatial filtering on the electromagnetic field superposition output result of the alternating electromagnetic field to obtain the power safety distance estimation result.

[0050] Among them, the time delay method refers to calculating the distance between the target object and the sensor by measuring the time difference between the signal transmission and reception; the phase difference method refers to inferring the position and distance state of the target object by comparing the phase difference of the signal.

[0051] Among them, information fusion refers to integrating the information from different sensors to improve the accuracy and reliability of the data; spatial filtering refers to processing the signal to remove noise and extract effective information, thereby improving the measurement accuracy.

[0052] After the above processing, the safety distance between the power facility and the obstacle is obtained, that is, the power safety distance estimation result.

[0053] Exemplarily, the distance information between the target object and the sensor is measured based on a laser sensor, and the azimuth and distance state information of the target object is calculated by methods such as time delay or phase difference. The dynamic electromagnetic field information for power safety ranging is obtained based on the excitation source frequency, and it is fused with the target azimuth state information. Spatial filtering is performed using the electromagnetic field superposition output result of the alternating electromagnetic field to obtain an accurate power safety distance estimation.

[0054] In this embodiment, the azimuth and distance state information of the target obstacle is calculated by the time delay method or the phase difference method, and the dynamic electromagnetic field information is fused with the azimuth information to obtain the electromagnetic field superposition output result of the alternating electromagnetic field. Then, through spatial filtering processing, the power safety distance estimation result is obtained; significantly improving the accuracy and real-time performance of the power safety distance, enhancing the safety of the power system, reducing potential safety risks, and ensuring the stable operation of the power facility.

[0055] In one embodiment, the power safety distance estimation result is optimized to determine the spatial parameters of the power safety distance, including: based on the electromagnetic induction law and the magnetic flux continuity principle, using the average distribution method to set the ranging coefficients of each sensor in the power safety distance estimation result, and determining the eigenvalue of the charge moving in the wire being pushed by the induced electric field; using multi-sensor fusion filtering on the closed surface to perform fusion calculation on the bound charges continuously distributed in the power safety distance estimation result, and obtaining the globally optimal estimation result according to the eigenvalue; using grid meshing to discretize the continuous field domain into a grid discrete node set, optimizing the estimation of the sensing node parameters in the globally optimal estimation result, and determining the spatial parameters of the power safety distance.

[0056] Among them, the electromagnetic induction law describes that a changing magnetic field will generate an electromotive force in a conductor, and the magnetic flux continuity principle means that in an ideal lossless case, the magnetic flux is continuous within a closed loop, which means that the magnetic field lines cannot be broken in the middle; the average distribution method means evenly dividing the ranging ability of each sensor to simplify the calculation.

[0057] Among them, the eigenvalue of the charge moving in the wire being pushed by the induced electric field refers to the characteristic quantity of the motion state of the charge in the wire due to the action of the induced electric field caused by the external changing magnetic field during the electromagnetic induction process. These eigenvalues reflect the moving speed, direction of the charge and its response ability to the electric field.

[0058] Exemplarily, through the electromagnetic induction law and the magnetic flux continuity principle, using the average distribution method to set the ranging coefficients of each sensor, the eigenvalue of the charge moving in the wire being pushed by the induced electric field is deduced. Using multi-sensor fusion filtering on the closed surface to achieve the fusion calculation of the continuously distributed bound charges, and then obtaining the globally optimal estimation. Using grid meshing to discretize the continuous field domain into a grid discrete node set, further optimizing the estimation of the sensing node parameters of the power safety distance. According to the measurement characteristics between each laser sensor, the information distribution and centralized filtering processing of the power safety distance are realized to comprehensively estimate the spatial parameters of the power safety distance.

[0059] In this embodiment, based on the electromagnetic induction law and the magnetic flux continuity principle, the ranging coefficients of each sensor are set by the average distribution method, and the eigenvalue of the charge being pushed by the induced electric field is deduced. Using the multi-sensor fusion filtering technology to perform fusion calculation on the continuously distributed bound charges and obtain the globally optimal estimation result. Through grid meshing, the continuous field domain is discretized, and the estimation of the sensing node parameters is optimized; the estimation accuracy and real-time performance of the power safety distance are improved, the safety of the power system is enhanced, and the potential risks are reduced.

[0060] In one embodiment, the position information is fused with the spatial parameters of the electrical safety distance to obtain a measurement equation for safe ranging, including: fusing various types of position information with the spatial parameters of the electrical safety distance to obtain a fused estimation result of the electrical safety distance; and constructing a measurement equation between the ranging parameter value and the sensor structure based on the fused estimation result of the electrical safety distance as the measurement equation for safe ranging.

[0061] Among them, the position information includes the position information of the Global Positioning System (GPS) and the BeiDou Navigation Satellite System (BDS).

[0062] Among them, the measurement equation between the ranging parameter value and the sensor structure refers to describing the relationship between the ranging ability of the sensor and its physical structure through a mathematical model. This equation takes into account the characteristics of the sensor (such as sensitivity, accuracy, response time, etc.) and ranging parameters (such as distance, angle, etc.), and is used to accurately calculate and optimize the ranging result.

[0063] Exemplarily, the measurement equation for safe ranging can be:

[0064]

[0065]

[0066] In the formula, and are Gaussian noises with unknown mean and covariance; the laser sensing measurement matrix for electrical safety ranging , where, ; the measurement matrix of BDS can be considered the same as that of GPS, that is, .

[0067] In this embodiment, by fusing various types of position information with the spatial parameters of the electrical safety distance, a fused estimation result of the electrical safety distance is obtained, and then a measurement equation between the ranging parameter value and the sensor structure is constructed to ensure the accuracy and reliability of safe ranging; the measurement accuracy of the electrical safety distance is improved, the adaptability of the system to environmental changes is enhanced, potential safety risks are reduced, and the stable operation of electrical facilities is ensured.

[0068] In one embodiment, according to the fused power safety distance estimation result, a measurement equation between the ranging parameter value and the sensor structure is constructed as the measurement equation for safety ranging, including: determining the state vector of the electric field sensor measurement band according to the fused power safety distance estimation result; based on the state vector of the electric field sensor measurement band, using grid partitioning and measurement parameter identification method, establishing an output dynamic state model for power safety ranging; based on the control input vector and Gaussian noise in the output dynamic state model of power safety ranging, using the state transition matrix to describe the state change process of the system, and constructing the measurement equation for safety ranging between the ranging parameter value and the sensor structure.

[0069] Among them, the state vector of the electric field sensor measurement band describes the state of the sensor measuring the electric field within a specific frequency range, including signal intensity, waveform, and frequency characteristics within the band, etc.

[0070] Among them, grid partitioning is a method of discretizing continuous space, dividing the measurement area into grids to facilitate numerical calculation and optimization. The measurement parameter identification method is a method of determining the relationship between measurement parameters and their influencing factors to improve measurement accuracy.

[0071] Among them, the output dynamic state model of power safety ranging is used to describe the dynamic behavior of the system under specific conditions, facilitating real-time monitoring and evaluation.

[0072] Exemplarily, according to the state vector of the electric field sensor measurement band, using grid partitioning and measurement parameter identification method, an output dynamic state model for power safety ranging is established. Considering the control input vector and Gaussian noise, using the state transition matrix to describe the state change process of the system, and further constructing the measurement equation between the ranging parameter value and the sensor structure. Combining the observation vectors of GPS and BDS, according to the measurement matrix and the laser sensing measurement matrix, the measurement information equation for power safety ranging is derived, including the influencing factors of Gaussian noise.

[0073] In this embodiment, based on the fused power safety distance estimation result, the state vector of the electric field sensor is determined, a dynamic state model is established through grid partitioning and measurement parameter identification method, and the state transition matrix is used to describe the state change of the system, constructing the measurement equation between the ranging parameter and the sensor structure; improving the accuracy and robustness of power safety ranging, effectively reducing the influence of noise, and enhancing the adaptability of the system to the dynamic environment.

[0074] In another embodiment, as Figure 3 shown, a power safety ranging monitoring method based on a laser sensor is provided, including the following steps:

[0075] S201, Based on the time delay method or the phase difference method, calculate the azimuth distance state information of the target obstacle relative to the target facility according to the distance information.

[0076] S202, Perform information fusion on the dynamic electromagnetic field information and the azimuth distance state information to obtain the electromagnetic field superposition output result of the alternating electromagnetic field.

[0077] S203, Perform spatial filtering on the electromagnetic field superposition output result of the alternating electromagnetic field to obtain the power safety distance estimation result.

[0078] S204, Based on the electromagnetic induction law and the principle of magnetic flux continuity, set the ranging coefficients of each sensor in the power safety distance estimation result using the average distribution method, and determine the eigenvalue of the moving charge in the wire being pushed by the induced electric field.

[0079] S205, Adopt multi-sensor fusion filtering on a closed surface to perform fusion calculation on the continuously distributed bound charges in the power safety distance estimation result, and obtain the global optimal estimation result according to the eigenvalue.

[0080] S206, Use grid meshing to discretize the continuous field domain into a grid discrete node set, optimize the estimation of the sensing node parameters in the global optimal estimation result, and determine the spatial parameters of the power safety distance.

[0081] S207, Perform information fusion on various types of position information and the spatial parameters of the power safety distance to obtain the fused power safety distance estimation result.

[0082] S208, Determine the state vector of the measurement frequency band of the electric field sensor according to the fused power safety distance estimation result.

[0083] S209, According to the state vector of the measurement frequency band of the electric field sensor, use grid meshing and the measurement parameter identification method to establish the output dynamic state model of the power safety ranging.

[0084] S210, Based on the control input vector and Gaussian noise in the output dynamic state model of the power safety ranging, use the state transition matrix to describe the state change process of the system, and construct the measurement equation of the safety ranging between the ranging parameter value and the sensor structure.

[0085] It should be noted that the specific limitations of the above steps can be referred to the specific limitations of a power safety ranging monitoring method based on a laser sensor described above, and will not be elaborated here.

[0086] In one embodiment, the research on the related power safety ranging monitoring system design method has received great attention. The following describes the implementation methods of the ranging technology in two embodiments, specifically including:

[0087] The ranging technology in the first embodiment designs a power line safety distance monitoring and warning system based on multiple lidars. A single-line lidar is installed on the pan-tilt motor. The spatial position relationship between 4 lidars is calibrated according to the least square principle. The real-time point cloud data collected by 4 sets of devices is transmitted to the data processing platform through network communication for visual display, safety distance monitoring and alarm. However, the dynamic performance of this system for power safety ranging monitoring is poor.

[0088] The ranging technology in the second embodiment proposes a power construction machinery safety warning and control system based on edge computing technology. This system selects a linear frequency modulation continuous wave ranging radar based on the X-band as the basic detection means, and the front-end monitoring device adopts edge computing technology to achieve safety monitoring. However, the stability of this system for power safety monitoring is poor.

[0089] Based on this, the embodiments of the present application provide a power safety ranging monitoring method based on a laser sensor. The following refers to Figures 3 to 10 , and describes in detail the power safety ranging monitoring method based on a laser sensor with a specific embodiment. It should be understood that the following description is only an exemplary illustration and not a specific limitation of the application.

[0090] The power safety ranging monitoring method provided by the present application corresponds to a power safety ranging monitoring system based on a laser sensor. Among them, the laser sensor is a device that uses a laser beam for measurement, which can accurately measure the distance between the power line and surrounding obstacles and provide real-time ranging data to help improve the safety of the power line and the ability to prevent accidents.

[0091] The power safety ranging monitoring method provided by the present application has great potential in realizing dynamic monitoring and real-time alarm of the operation area. First, the overall design of the power safety ranging monitoring system is carried out. Secondly, based on the principles of a spatial parameter estimation technology based on power safety distance and an information fusion technology based on multi-sensor measurement data, the information distribution and centralized filtering processing of power safety ranging are realized according to the measurement characteristics between each laser sensor. Finally, combined with the transmission stability control design method, the human-computer interaction design of the power safety monitoring system is realized, and the bus information transmission and interaction of power safety ranging are realized by using the VIX bus control technology.

[0092] In terms of the overall design architecture of the monitoring system, in order to realize the design of the power safety ranging monitoring system based on laser sensors, first, the overall structure of the system is designed. The power laser sensor is used to collect information for power safety sensing ranging monitoring. Combining RFID technology, the information collection and networking control module of the power safety laser sensing ranging monitoring system is constructed. Based on the methods of drain detection and inversion layer detection, inrush current detection of power safety laser sensing is carried out. The power safety laser sensing detection principle is as Figure 3 shown.

[0093] The ZigBee Internet of Things protocol is used to realize the Internet of Things networking design of the power safety laser sensing ranging monitoring. The I / O control protocol is used for the transceiver conversion design of the power safety laser sensing ranging monitoring system. Through the design of the power amplification module, the synchronous bus control of the power safety laser sensing ranging monitoring system is realized. The system is divided into an input layer, an intermediate layer, and an output layer. The S3C 6410A is used for the embedded kernel control of power safety laser sensing. N sensing nodes are used to detect the current load of power safety laser sensing, and the overall structure is as Figure 4 shown.

[0094] In terms of the analysis of the system function module components, on the basis of the overall design architecture, combining RFID technology, the information collection and networking control module of the power safety laser sensing ranging monitoring system is constructed. The terminal data collection module of the power safety laser sensing ranging monitoring realizes the AD sampling function of data. The Hall current sensor is used for data collection, and component module design is carried out on the output Hall current of the collected power safety laser sensing. The hardware structure diagram of the data collection and processing module of the power safety laser sensing ranging monitoring system is as Figure 5 shown.

[0095] Using RFID and sensor fusion processing technology, the output voltage stabilization control of the power safety laser sensing ranging monitoring is realized. The hardware module of the system is mainly composed of the power safety laser sensing terminal data collection module, the interrupt control module, and the human-computer interaction module. A 2-bit embedded SoC security chip is used as the main control chip of the power safety laser sensing ranging monitoring system. Combining the system hardware design of power safety laser sensing, safety control is realized.

[0096] In terms of the spatial parameter estimation of the power safety distance, a laser sensor is used to detect the target azimuth information of power ranging. Combining the spatial parameter estimation results of the power safety distance, sensing information fusion tracking and identification are carried out. First, the laser sensing technology emits a beam of laser to the target object, and then receives the reflected laser signal. The distance to the target object is calculated by measuring the time delay or phase difference of the laser. The target azimuth state estimation information parameters of power ranging are expressed as ; The dynamic electromagnetic field information quantity for power safety ranging is obtained according to the excitation source frequency . When the transmission line operates normally, through the laser sensing information distribution, and The information quantities represented are subjected to spatial filtering, and the electromagnetic field superposition output result of the alternating electromagnetic field is expressed as , According to the alternating voltage and electrical information distribution principle, there are:

[0097] (1)

[0098] (2)

[0099] In the formula, Represents the alternating voltage information distribution principle, Represents the alternating voltage information of the alternating electromagnetic field, Represents the alternating voltage function of the alternating electromagnetic field, Represents the information distribution coefficient, Represents the alternating information quantity; Represents the alternating electrical information distribution principle, Represents the alternating electrical information of the alternating electromagnetic field, Represents the alternating electrical function of the alternating electromagnetic field. According to the electromagnetic induction law and the magnetic flux continuity principle, the following can be obtained:

[0100] (3)

[0101] In the formula, Represents the information distribution function, Represents the alternating information. The ranging coefficient of the distribution laser sensor is set by the average distribution method, and the moving charges in the wire are pushed by the induced electric field to obtain the characteristic value of power ranging:

[0102] (4)

[0103] In the formula, Represents the information quantity. It can be seen that the value range of the characteristic value of power ranging is , Thus, it is easy to obtain , .

[0104] On any closed surface, multi-sensor fusion filtering is adopted to obtain , According to the discretized analog charge detection, the fusion calculation formula of the continuously distributed bound charges is expressed as follows:

[0105] (5)

[0106] (6)

[0107] In the formula, represents the discretized analog charge function, represents the discretized alternating voltage information, represents the discretized alternating voltage function. The global estimate obtained according to formula (5) is the optimal unbiased. By using grid meshing to discretize the continuous field domain into a grid discrete node set, it can be proved that: , that is, the global optimal estimate is better than each local estimate. At this time, the calculation formula for the parameter estimation of the sensing node for power safety ranging is as follows:

[0108] (7)

[0109] (8)

[0110] Wherein, represents the parameter estimation of the sensing node for power safety ranging, and are the th virtual discretized statistical eigenvalue and the correction value at the moment. According to the measurement characteristics between each laser sensor, the information distribution and centralized filtering processing of power safety ranging are realized.

[0111] Generally speaking, this application is based on the above method of using a laser sensor to measure the distance information between the target object and the sensor, and calculates the azimuth and distance state information of the target object through methods such as time delay or phase difference. Based on the excitation source frequency, the dynamic electromagnetic field information of power safety ranging is obtained, and it is fused with the target azimuth state information. The output result of the electromagnetic field superposition of the alternating electromagnetic field is used for spatial filtering to obtain an accurate power safety distance estimate. Through Faraday's law of electromagnetic induction and the principle of magnetic flux continuity, the ranging coefficients of each sensor are set by the average distribution method, and the eigenvalue of the charge moving in the wire under the action of the induced electric field is deduced. Multi-sensor fusion filtering is adopted on the closed surface to realize the fusion calculation of continuously distributed bound charges, and then the global optimal estimate is obtained. The continuous field domain is discretized into a grid discrete node set by using grid meshing to further optimize the parameter estimation of the sensing node for power safety distance. According to the measurement characteristics between each laser sensor, the information distribution and centralized filtering processing of power safety distance are realized to comprehensively estimate the spatial parameters of power safety distance.

[0112] In the aspect of power safety ranging sensing information fusion, based on the above-mentioned spatial parameter estimation of the power safety distance, the power safety ranging sensing information is fused. By using the methods of grid dissection and measurement parameter identification, the state vector of the measurement frequency band of the electric field sensor is obtained as: ; In the case where the measured electric field strength changes, the output dynamic state model of the power safety ranging is obtained as follows:

[0113] (9)

[0114] Where, is the known deterministic control input vector. When the induced charge changes, it is assumed that ; is Gaussian noise with an unknown mean, is Gaussian noise with a time-varying variance, is the known output parameter. By accurately measuring the conduction current through the laser sensor, the state transition matrix of the power safety ranging is obtained as , where:

[0115] (10)

[0116] Therefore, the observation vectors of the Global Positioning System (GPS) and the BeiDou Navigation Satellite System (BDS) can be selected as: , at this time, the ranging parameter value is related to the structure of the sensor, and the measurement equation of the safe ranging is obtained as:

[0117] (11)

[0118] (12)

[0119] In the formula, and are Gaussian noises with unknown means and covariances; the laser sensing measurement matrix of the power safety ranging is , where, ; The measurement matrix of the BDS can be considered the same as that of the GPS, that is, .

[0120] Generally speaking, this application fuses the measurement data obtained by sensors such as laser sensors, GPS, and BDS to obtain a more accurate and comprehensive estimation of the electrical safety distance. According to the state vector of the measurement frequency band of the electric field sensor, a dynamic output state model for electrical safety ranging is established using grid dissection and measurement parameter identification methods. Considering the control input vector and Gaussian noise, the state transition matrix is used to describe the state change process of the system, and further a measurement equation between the ranging parameter values and the sensor structure is constructed. Combining the observation vectors of GPS and BDS, according to the measurement matrix and the laser sensing measurement matrix, the measurement information equation for electrical safety ranging is derived, including the influencing factors of Gaussian noise.

[0121] In summary, combined with the hardware circuit design, the hardware device of the sensor consists of a front-end amplifier circuit, a filter circuit, a level boosting circuit, a clock circuit, and a reset circuit. According to the circuit design results, combined with the transmission stability control design method, the human-computer interaction design of the electrical safety ranging and safety monitoring system is realized, and the VIX bus control technology is adopted to realize the bus information transmission and interaction of the electrical safety ranging.

[0122] To verify the application performance of this application in realizing electrical safety ranging monitoring, experimental test analysis is carried out. The sensor bandwidth is 10 kHz to 200 kHz, the power frequency electric field is 60 Hz, the amplitude of the electrical ranging level input signal is 2 V, the maximum input voltage of the measurement signal is ±2 V, the type of the laser sensor is a three-axis omnidirectional, magnetic field coil, electric field plate, electromagnetic field integrated probe, the communication interface of the electrical safety monitoring adopts serial communication, the baud rate is 4800 kbps, and the supply voltage is 6 V to 12 V.

[0123] The highest range of the laser sensor is set to 100 kV / m, and the horizontal displacement deviation threshold is 0.35 m. According to the above settings, the sampling information of the laser sensor is obtained as Figure 6 shown.

[0124] Taking Figure 6 the electrical safety ranging information collected by the laser sensor as a sample, electrical safety ranging is carried out, and the ranging output is obtained as Figure 7 shown.

[0125] Analysis Figure 7 shows that when this application performs electrical safety ranging, it can realize the estimation of electrical sensing information. Through sensor measurement and electric field calibration, the electrical safety distance estimation is realized, and the ranging estimation error is tested, as Figure 8 shown.

[0126] Analysis Figure 8 shows that the estimation error of the electrical safety ranging of the system of this application is small and can converge quickly. The ranging accuracy of different systems is tested, and the comparison results are as Figure 9 shown.

[0127] Analysis Figure 9 It is known that the highest power safety ranging accuracy of this application is 98.6%. The highest power safety ranging accuracy of the ranging technology in the first embodiment is 90.2%, and the highest power safety ranging accuracy of the ranging technology in the second embodiment is 88.6%. Compared with the above two systems, the power safety ranging accuracy of the system of this application is relatively high. This is because the ranging system in this application performs information fusion on the measurement data obtained by sensors such as laser sensors, GPS, and BDS to obtain a more accurate and comprehensive estimate of the power safety distance. By comprehensively utilizing the advantages of different sensors, the accuracy and reliability of the target state are improved.

[0128] To further verify the effectiveness of this application, the monitoring response times of different systems are tested, and the comparison results are as Figure 10 shown.

[0129] It should be noted that in Figure 9 and Figure 10 , the system of this application refers to the ranging system obtained by implementing the power safety ranging monitoring method based on laser sensors provided in this application. The first system refers to the ranging system obtained by implementing the ranging technology in the first embodiment. Correspondingly, the second system refers to the ranging system obtained by implementing the ranging technology in the second embodiment.

[0130] From Figure 10 it can be seen that the fastest power safety ranging monitoring response time of this application is 0.5 ms. The fastest power safety ranging monitoring response time of the ranging technology in the first embodiment is 2.8 ms, and the fastest power safety ranging monitoring response time of the ranging technology in the second embodiment is 2.2 ms. Compared with the two ranging systems in the second embodiment, the power safety ranging monitoring response time of the system of this application is relatively fast. This is because this application uses a laser sensor to measure the distance information between the target object and the sensor, and calculates the azimuth and distance state information of the target object through methods such as time delay or phase difference. To improve the accuracy and practicality of the power safety monitoring system.

[0131] The power ranging estimation errors of different systems are tested, and the comparison results are shown in Table 1.

[0132] Table 1 Power ranging estimation errors of different systems / m

[0133]

[0134] As can be seen from Table 1, the minimum power ranging estimation error in the system of this application is 1.12 m, the minimum power ranging estimation error of the ranging technology in the first embodiment is 2.03 m, and the minimum power ranging estimation error of the ranging technology in the second embodiment is 2.08 m. Compared with the two literature systems, the power ranging estimation error of this application is the smallest. This is because the invention discretizes the continuous field into a grid discrete node set by grid division, and further optimizes the sensing node parameter estimation of the power safety distance. According to the measurement characteristics between each laser sensor, information distribution and centralized filtering processing of the power safety distance are realized to comprehensively estimate the spatial parameters of the power safety distance. Thus, the power ranging estimation error is reduced.

[0135] It should be understood that although the steps in the flowcharts involved in the above-mentioned embodiments are sequentially shown according to the indication of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps in other steps.

[0136] Based on the same inventive concept, an embodiment of this application also provides a laser sensor-based power safety ranging monitoring device for implementing the above-mentioned laser sensor-based power safety ranging monitoring method. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the following laser sensor-based power safety ranging monitoring device can refer to the limitations on the laser sensor-based power safety ranging monitoring method in the above text, and will not be repeated here.

[0137] In one embodiment, as Figure 11 shown, a laser sensor-based power safety ranging monitoring device is provided, including: a distance acquisition module 1101, a parameter estimation module 1102, a parameter fusion module 1103, and an alarm information generation module 1104, where:

[0138] The distance acquisition module 1101 is configured to obtain distance information between a target facility and a target obstacle in a power system according to a laser sensor; the target facility is a facility to be monitored in the power system, and the target obstacle is an obstacle within a preset range near the target facility;

[0139] A parameter estimation module 1102, configured to obtain dynamic electromagnetic field information of a target facility, estimate parameters of distance information based on a spatial parameter estimation technique for the power safety distance, and obtain spatial parameters of the power safety distance according to the dynamic electromagnetic field information;

[0140] A parameter fusion module 1103, configured to obtain location information corresponding to the target facility, fuse the location information with the spatial parameters of the power safety distance based on an information fusion technique for multi-sensor measurement data, so as to obtain a measurement equation for safe ranging; the measurement equation for safe ranging is used to update the distance information;

[0141] An alarm information generation module 1104, configured to generate distance alarm information corresponding to the target obstacle when the updated distance information is outside a preset safe distance range.

[0142] In one embodiment, the device is configured to: estimate parameters of the distance information according to the dynamic electromagnetic field information to obtain an estimated result of the power safety distance; optimize the estimated result of the power safety distance to determine the spatial parameters of the power safety distance.

[0143] In one embodiment, the device is configured to: calculate the azimuth distance state information of the target obstacle relative to the target facility based on the time delay method or the phase difference method according to the distance information; fuse the dynamic electromagnetic field information with the azimuth distance state information to obtain an electromagnetic field superposition output result of the alternating electromagnetic field; perform spatial filtering on the electromagnetic field superposition output result of the alternating electromagnetic field to obtain an estimated result of the power safety distance.

[0144] In one embodiment, the device is configured to: based on the electromagnetic induction law and the magnetic flux continuity principle, set the ranging coefficients of each sensor in the estimated result of the power safety distance by using the average distribution method, and determine the eigenvalue of the movement of the charge in the wire driven by the induced electric field; perform multi-sensor fusion filtering on a closed surface to perform fusion calculation on the bound charges continuously distributed in the estimated result of the power safety distance, and obtain a globally optimal estimated result according to the eigenvalue; use grid partitioning to discretize the continuous field domain into a grid discrete node set, optimize the parameter estimation of the sensing nodes in the globally optimal estimated result, and determine the spatial parameters of the power safety distance.

[0145] In one embodiment, the device is configured to: fuse various types of location information with the spatial parameters of the power safety distance to obtain a fused estimated result of the power safety distance; according to the fused estimated result of the power safety distance, construct a measurement equation between the ranging parameter value and the sensor structure as the measurement equation for safe ranging.

[0146] In one embodiment, the apparatus is configured to: determine a state vector of the measurement frequency band of the electric field sensor according to the fused power safety distance estimation result; establish an output dynamic state model for power safety distance measurement by using grid subdivision and measurement parameter identification method according to the state vector of the measurement frequency band of the electric field sensor; and construct a measurement equation for the safety distance between the ranging parameter value and the sensor structure by using the state transition matrix to describe the state change process of the system based on the control input vector and Gaussian noise in the output dynamic state model for power safety distance measurement.

[0147] Each module in the above power safety distance measurement monitoring apparatus based on a laser sensor can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0148] In one embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 12 shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communicating with external terminals in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a power safety distance measurement monitoring method based on a laser sensor.

[0149] Those skilled in the art can understand that Figure 12 the structure shown in

[0150] is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0151] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0152] In one embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0153] Those of ordinary skill in the art can understand that all or part of the processes in the above method embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above method embodiments. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0154] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0155] The embodiments described above merely represent several implementation manners of the present application. Their descriptions are relatively specific and detailed, but they should not be construed as limitations on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A power safety ranging and monitoring method based on a laser sensor, characterized in that, The method includes: Obtaining distance information between a target facility and a target obstacle in a power system according to a laser sensor; the target facility is a facility to be monitored in the power system, and the target obstacle is an obstacle within a preset range near the target facility; Obtaining dynamic electromagnetic field information of the target facility, and based on the spatial parameter estimation technology of the power safety distance, performing parameter estimation on the distance information according to the dynamic electromagnetic field information to obtain spatial parameters of the power safety distance; Obtaining position information corresponding to the target facility, and based on the information fusion technology of multi-sensor measurement data, fusing the position information with the spatial parameters of the power safety distance to obtain a measurement equation for safe distance measurement; the measurement equation for safe distance measurement is used to update the distance information; Generating distance warning information corresponding to the target obstacle when the updated distance information is outside a preset safe distance range.

2. The method according to claim 1, wherein The performing parameter estimation on the distance information according to the dynamic electromagnetic field information to obtain spatial parameters of the power safety distance includes: Performing parameter estimation on the distance information according to the dynamic electromagnetic field information to obtain an estimation result of the power safety distance; Optimizing the estimation result of the power safety distance to determine the spatial parameters of the power safety distance.

3. The method according to claim 2, characterized in that The performing parameter estimation on the distance information according to the dynamic electromagnetic field information to obtain an estimation result of the power safety distance includes: Based on the time delay method or the phase difference method, calculating azimuth distance state information of the target obstacle relative to the target facility according to the distance information; Fusing the dynamic electromagnetic field information with the azimuth distance state information to obtain an electromagnetic field superposition output result of the alternating electromagnetic field; Performing spatial filtering on the electromagnetic field superposition output result of the alternating electromagnetic field to obtain the estimation result of the power safety distance.

4. The method according to claim 2, wherein The optimizing the estimation result of the power safety distance to determine the spatial parameters of the power safety distance includes: Based on Faraday's law of electromagnetic induction and the principle of magnetic flux continuity, setting ranging coefficients of each sensor in the estimation result of the power safety distance by using the average distribution method to determine the eigenvalue of the movement of charges in the wire driven by the induced electric field; Performing multi-sensor fusion filtering on a closed surface to perform fusion calculation on the bound charges continuously distributed in the estimation result of the power safety distance, and obtaining a globally optimal estimation result according to the eigenvalue; Discretizing the continuous field domain into a grid discrete node set by using grid partitioning, optimizing the parameter estimation of the sensing nodes in the globally optimal estimation result, and determining the spatial parameters of the power safety distance.

5. The method according to claim 1, characterized in that The fusing the position information with the spatial parameters of the power safety distance to obtain a measurement equation for safe distance measurement includes: Fusing various types of the position information with the spatial parameters of the power safety distance to obtain a fused estimation result of the power safety distance; According to the fused estimation result of the power safety distance, constructing a measurement equation between the ranging parameter value and the sensor structure as the measurement equation for safe distance measurement.

6. The method according to claim 5, wherein Constructing a measurement equation between the ranging parameter value and the sensor structure according to the fused power safety distance estimation result as the measurement equation for the safe ranging, including: Determining the state vector of the measurement frequency band of the electric field sensor according to the fused power safety distance estimation result; Establishing an output dynamic state model for the power safe ranging by using grid division and measurement parameter identification method according to the state vector of the measurement frequency band of the electric field sensor; Based on the control input vector and Gaussian noise in the output dynamic state model for the power safe ranging, using the state transition matrix to describe the state change process of the system, and constructing the measurement equation for the safe ranging between the ranging parameter value and the sensor structure.

7. A power safety ranging and monitoring device based on a laser sensor, characterized in that, The device includes: A distance acquisition module, configured to acquire distance information between a target facility and a target obstacle in the power system according to a laser sensor; the target facility is a facility to be monitored in the power system, and the target obstacle is an obstacle within a preset range near the target facility; A parameter estimation module, configured to acquire the dynamic electromagnetic field information of the target facility, and perform parameter estimation on the distance information according to the dynamic electromagnetic field information based on the spatial parameter estimation technology of the power safety distance to obtain the spatial parameters of the power safety distance; A parameter fusion module, configured to acquire the position information corresponding to the target facility, and fuse the position information and the spatial parameters of the power safety distance based on the information fusion technology of multi-sensor measurement data to obtain a measurement equation for safe ranging; the measurement equation for safe ranging is used to update the distance information; An alarm information generation module, configured to generate distance alarm information corresponding to the target obstacle when the updated distance information is outside the preset safe distance range.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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