Electric field strength measurement method, device, computer equipment and storage medium

Abstract

The present application relates to a method, device, computer equipment and storage medium for measuring electric field strength. By obtaining a voltage signal at a target position at a preset distance from a transmission line in the electric field to be measured, and obtaining the temperature and humidity of the electric field to be measured, the voltage signal, temperature and humidity obtained above are input into a prediction model, and the electric field strength output by the prediction model is obtained as the electric field strength corresponding to the target position in the electric field to be measured. Among them, the prediction model can be obtained by training a preset machine learning algorithm based on multiple known temperatures, multiple known humidity and multiple known voltage signals. Compared with the traditional method of measuring the electric field strength by a method based on nematic liquid crystal photonic crystal fiber penetration, this scheme uses the voltage signal at a preset distance from the transmission line in the electric field to be measured, and considers factors such as the temperature and humidity of the electric field to be measured, and obtains the electric field strength of the target position through a prediction model, thereby improving the measurement accuracy of the electric field strength.

Description

Technical Field

[0001] The present application relates to the field of power monitoring technology, and in particular to an electric field strength measurement method, device, computer equipment and storage medium. Background Art

[0002] The transmission line conductors in the power grid are an important part of the power system. The surface of the transmission line conductors usually causes corona discharge due to abnormal field strength, which can cause harm to workers and vehicles driving near the construction. Therefore, it is particularly important to calculate, measure and analyze the field strength on the surface of high-voltage AC transmission lines. At present, the method for measuring electric field strength is usually to measure the electric field strength by penetration based on nematic liquid crystal photonic crystal fiber. However, due to the characteristics of liquid crystal, the accuracy of the electric field strength measured by this method is not high.

[0003] Therefore, the current electric field strength measurement method has the defect of low measurement accuracy. Summary of the invention

[0004] Based on this, it is necessary to provide an electric field strength measurement method, device, computer equipment and storage medium that can improve measurement accuracy in response to the above technical problems.

[0005] A method for measuring electric field strength, the method comprising:

[0006] Acquire a voltage signal of a target position in the electric field to be measured; the target position is a position in the electric field to be measured that is a preset distance from a transmission line;

[0007] Acquiring the temperature and humidity of the electric field to be measured;

[0008] The voltage signal, the temperature and the humidity are input into a prediction model, and the electric field strength output by the prediction model is obtained as the electric field strength corresponding to the target position in the electric field to be measured; the prediction model is based on multiple known temperatures, multiple known humidity and multiple known voltage signals, and is trained by a preset machine learning algorithm.

[0009] In one embodiment, obtaining the temperature and humidity of the electric field to be measured includes:

[0010] Acquiring a first electrical signal corresponding to temperature and a second electrical signal corresponding to humidity sent by a temperature and humidity sensing device, wherein the temperature and humidity sensing device is disposed in the target position;

[0011] The temperature is obtained according to the first electrical signal, and the humidity is obtained according to the second electrical signal.

[0012] In one embodiment, before obtaining the voltage signal at the target position in the electric field to be measured, the method further includes:

[0013] According to the voltage level and wiring method corresponding to the transmission line, a simulation model corresponding to the transmission line is obtained through finite element simulation calculation;

[0014] The simulation modeling is divided into a plurality of grids, and a target position at a preset distance from a transmission line in the electric field to be measured is determined from the plurality of grids.

[0015] In one embodiment, determining a target position at a preset distance from a transmission line in the electric field to be measured from the plurality of grids comprises:

[0016] According to the preset step size corresponding to the target grid at the preset distance from the transmission line, a corresponding auxiliary line is established in the target grid to obtain the target position at the preset distance from the transmission line in the electric field to be measured.

[0017] In one embodiment, dividing the simulation modeling into a plurality of grids includes:

[0018] The simulation modeling is divided into a plurality of grids by a simulated charge method.

[0019] In one embodiment, it also includes:

[0020] Acquire a plurality of known temperatures, a plurality of known humidity levels, and a plurality of known voltage signals;

[0021] Determining the preset machine learning algorithm from a plurality of machine learning algorithms according to the data amount and data structure of the plurality of known temperatures, the plurality of known humidity, and the plurality of known voltage signals;

[0022] According to the preset machine learning algorithm, the corresponding relationship between the known temperature, the known humidity and the known electric field strength corresponding to the known voltage signal is obtained through training to obtain the prediction model.

[0023] In one embodiment, it also includes:

[0024] If the temperature is greater than a preset temperature threshold, a temperature alarm message is output;

[0025] and / or,

[0026] If the humidity is greater than a preset humidity threshold, output a humidity alarm message;

[0027] and / or,

[0028] If the electric field strength is greater than a preset field strength threshold, a field strength warning message is output.

[0029] An electric field strength measuring device, comprising:

[0030] A signal acquisition module, used to acquire a voltage signal at a target position in the electric field to be measured; the target position is a position at a preset distance from a transmission line in the electric field to be measured;

[0031] A temperature and humidity acquisition module, used to acquire the temperature and humidity of the electric field to be measured;

[0032] A field strength acquisition module is used to input the voltage signal, the temperature and the humidity into a prediction model to obtain the electric field strength output by the prediction model as the electric field strength corresponding to the target position in the electric field to be measured; the prediction model is based on multiple known temperatures, multiple known humidity and multiple known voltage signals, and is trained by a preset machine learning algorithm.

[0033] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0034] A computer-readable storage medium stores a computer program, which implements the steps of the above method when executed by a processor.

[0035] The electric field strength measurement method, device, computer equipment and storage medium obtain the voltage signal of the target position at a preset distance from the transmission line in the electric field to be measured, and obtain the temperature and humidity of the electric field to be measured, and then input the obtained voltage signal, temperature and humidity into the prediction model, and obtain the electric field strength output by the prediction model as the electric field strength corresponding to the target position in the electric field to be measured. Among them, the prediction model can be obtained by training a preset machine learning algorithm based on multiple known temperatures, multiple known humidity and multiple known voltage signals. Compared with the traditional method of measuring the electric field strength by the method based on the penetration of nematic liquid crystal photonic crystal fiber, this scheme uses the voltage signal at a preset distance from the transmission line in the electric field to be measured, and considers factors such as the temperature and humidity of the electric field to be measured. The electric field strength of the target position is obtained by the prediction model obtained based on the known temperature, known humidity, known voltage signal and machine learning algorithm, thereby achieving the effect of improving the measurement accuracy of the electric field strength. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is an application environment diagram of an electric field strength measurement method in an embodiment;

[0037] Figure 2 is a schematic flow chart of a method for measuring electric field strength in one embodiment;

[0038] Figure 3 is a schematic flow chart of a method for measuring electric field strength in another embodiment;

[0039] Figure 4is a structural block diagram of an electric field strength measuring device in one embodiment;

[0040] Figure 5 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with 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.

[0042] The electric field strength measurement method provided in this application can be applied to Figure 1 In the application environment shown. Among them, the industrial control terminal 102 can communicate with the electric field and magnetic field sensing device 100 and the temperature and humidity sensing device 104 respectively, wherein the electric field and magnetic field sensing device 100 and the temperature and humidity sensing device 104 can be set in the electric field to be measured at the power grid site. The industrial control terminal 102 can obtain the voltage signal of the target position in the electric field to be measured sent by the electric field and magnetic field sensing device 100, and the industrial control terminal 102 can also obtain the temperature and humidity of the electric field to be measured at the power grid site sent by the temperature and humidity sensing device 104; the industrial control terminal 102 can also input the above-obtained voltage signal, temperature and humidity into the prediction model, and obtain the electric field strength output by the prediction model, so that the industrial control terminal 102 can obtain the electric field strength of the target position in the electric field to be measured. Among them, the industrial control terminal 102 can be but not limited to various personal computers, laptops, smart phones and tablets, and the electric field and magnetic field sensing device 100 and the temperature and humidity sensing device 104 can be implemented by hardware devices or devices embedded with software modules.

[0043] In one embodiment, Figure 2 As shown, a method for measuring electric field strength is provided. Figure 1 The industrial control terminal in the example is used to illustrate, including the following steps:

[0044] Step S202, obtaining a voltage signal at a target position in the electric field to be measured; the target position is a position at a preset distance from a transmission line in the electric field to be measured.

[0045] Among them, the electric field to be measured can be an electric field whose electric field strength needs to be measured, and a transmission line can be set in the electric field. The field strength generated by the electric field to be measured can be the field strength of the electric field generated in the vicinity by the transmission line conductor. An electric field and magnetic field sensing device 100 can be set in the electric field to be measured, and the electric field and magnetic field sensing device 100 can sense and collect voltage signals. The electric field and magnetic field sensing device 100 can be set at a target position in the above-mentioned electric field to be measured that is a preset distance from the high-voltage transmission line conductor. The electric field and magnetic field sensing device 100 can detect the strong electric field generated by the high-voltage transmission line and output a voltage signal proportional to the electric field generated by the high-voltage transmission line. The electric field and magnetic field sensing device 100 can send the voltage signal to the industrial control terminal 102, and the industrial control terminal 102 can obtain the above-mentioned voltage signal, thereby obtaining the voltage signal of the target position in the above-mentioned electric field to be measured. Among them, the industrial control terminal 102 may include an electric field and magnetic field sensing main control computing module, and the industrial control terminal 102 may receive the above-mentioned voltage signal through the electric field and magnetic field sensing main control computing module; the target position can be determined from an area within a preset distance range near the transmission line. For example, the area within a preset range near the transmission line can be divided into multiple sub-areas, and the target position is determined from multiple sub-areas.

[0046] Step S204, obtaining the temperature and humidity of the electric field to be measured.

[0047] The electric field to be measured may be the electric field generated at the location where the transmission line is located in the above-mentioned power grid site. Since both temperature and humidity will affect the field strength generated by the transmission line, the influence of the temperature and humidity of the electric field to be measured on the electric field strength needs to be considered when measuring the electric field strength of the electric field to be measured. The industrial control terminal 102 may also obtain the temperature and humidity of the electric field to be measured, such as the temperature and humidity near the transmission line in the electric field to be measured. In order to correspond to the target voltage of the electric field to be measured obtained above, the industrial control terminal 102 may obtain the temperature and humidity at the above-mentioned target location.

[0048] Among them, the above-mentioned temperature and humidity can be collected by the temperature and humidity sensing device 104, and the temperature and humidity sensing device 104 can be set in the above-mentioned electric field to be measured, for example, set in the target position of the above-mentioned electric field to be measured. The temperature and humidity sensing device 104 can be used to collect, detect and collect the temperature and humidity in the above-mentioned electric field to be measured by sensing collection. In some embodiments, the temperature and humidity sensing device 104 can send the collected temperature and humidity to the industrial control terminal 102. For example, after collecting the temperature, the temperature and humidity sensing device set at the above-mentioned target position can send a first electrical signal corresponding to the temperature, and after collecting the humidity, the temperature and humidity sensing device 104 can send a second electrical signal corresponding to the humidity. The industrial control terminal 102 can receive the first electrical signal and the second electrical signal sent by the temperature and humidity sensing device 104, and obtain the temperature corresponding to the electric field to be measured according to the first electrical signal, and obtain the humidity corresponding to the electric field to be measured according to the second electrical signal. Among them, the temperature and humidity sensing device 104 can transform the collected temperature and humidity data into electrical signal form through a preset calculation method and rule, and output it in the form of electrical signal to the industrial control terminal 102. The industrial control terminal 102 can receive the electrical signals corresponding to the temperature and humidity respectively through the electric field and magnetic field sensing main control calculation module, and can restore the electrical signal corresponding to the temperature and the electrical signal corresponding to the humidity to the corresponding temperature data and humidity data, and can perform corresponding processing on the obtained temperature and humidity. In addition, the temperature and humidity sensing device 104 can be composed of a sensor that can detect temperature and humidity, or it can be composed of a sensor group consisting of a temperature sensor and a humidity sensor.

[0049] Step S206, input the voltage signal, temperature and humidity into the prediction model, obtain the electric field strength output by the prediction model, and use it as the electric field strength corresponding to the target position in the electric field to be measured; the prediction model is based on multiple known temperatures, multiple known humidity and multiple known voltage signals, and is trained by a preset machine learning algorithm.

[0050] Among them, the voltage signal can be the voltage signal corresponding to the electric field transmission line to be tested detected by the electric field and magnetic field sensing device 100, and the temperature and humidity can be the temperature and humidity corresponding to the target position detected by the temperature and humidity sensing device 104 in the electric field to be tested. The industrial control terminal 102 can input the above-obtained voltage signal, temperature and humidity into the prediction model, so as to obtain the electric field strength corresponding to the target position in the electric field to be tested output by the prediction model, and the electric field strength can be the electric field strength obtained after considering the influence of temperature and humidity on the electric field strength. Among them, the prediction model can be a model trained by a preset machine learning algorithm based on multiple known temperatures, multiple known humidity and multiple known voltage signals. Among them, the preset machine learning algorithm can be at least one machine learning algorithm determined from multiple preset machine learning algorithms.

[0051] In the above-mentioned electric field strength measurement method, by obtaining the voltage signal of the target position at a preset distance from the transmission line in the electric field to be measured, and obtaining the temperature and humidity of the electric field to be measured, the voltage signal, temperature and humidity obtained above are input into the prediction model, and the electric field strength output by the prediction model is obtained as the electric field strength corresponding to the target position in the above-mentioned electric field to be measured. Among them, the prediction model can be obtained by training a preset machine learning algorithm based on multiple known temperatures, multiple known humidity and multiple known voltage signals. Compared with the traditional method of measuring the electric field strength by the method based on the penetration of nematic liquid crystal photonic crystal fiber, this scheme uses the voltage signal at a preset distance from the transmission line in the electric field to be measured, and considers factors such as the temperature and humidity of the electric field to be measured. The electric field strength of the target position is obtained by the prediction model obtained based on the known temperature, known humidity, known voltage signal and machine learning algorithm, thereby achieving the effect of improving the measurement accuracy of the electric field strength.

[0052] In one embodiment, before obtaining the voltage signal of the target position in the electric field to be measured, it also includes: obtaining the simulation modeling corresponding to the transmission line through finite element simulation calculation according to the voltage level and wiring method corresponding to the transmission line; dividing the simulation modeling into multiple grids, and determining the target position in the electric field to be measured that is a preset distance away from the transmission line from the multiple grids.

[0053] In this embodiment, the industrial control terminal 102 can obtain the target position where the electric field strength needs to be measured by dividing the grid. The industrial control terminal 102 can obtain the simulation modeling corresponding to the transmission line through finite element simulation calculation according to the voltage level and wiring method of the transmission line in the electric field to be measured. For example, the industrial control terminal 102 can use finite element simulation software to model the simulation object, that is, the transmission line with different voltage levels and different wiring methods to obtain the corresponding simulation model; and the industrial control terminal 102 can also divide the simulation modeling into multiple grids, and determine the target position at a preset distance from the transmission line in the electric field to be measured from the multiple grids. For example, the industrial control terminal 102 can use finite element simulation software to divide the simulation model corresponding to the above-mentioned transmission line into grids, thereby obtaining multiple grids corresponding to the transmission line, and obtaining the target position where the electric field strength needs to be measured from the multiple grids in a specific way. Among them, finite element simulation is to simulate a real physical system, such as the above-mentioned transmission line, by using a mathematical approximation method. By using simple and interacting units, a finite number of unknown quantities can be used to approximate a real system with infinite unknown quantities. Finite element simulation calculation can adapt to various complex shapes and can effectively analyze engineering.

[0054] Through this embodiment, the industrial control terminal 102 can obtain the simulation modeling corresponding to the transmission line through finite element simulation calculation, and determine the target position from multiple grids based on the simulation modeling, so that the electric field strength can be measured at the target position, thereby achieving the effect of improving the measurement accuracy of the electric field strength.

[0055] In one embodiment, a target position at a preset distance from a transmission line in an electric field to be measured is determined from a plurality of grids, including: establishing a corresponding auxiliary line in the target grid according to a preset step size corresponding to the target grid at the preset distance from the transmission line, to obtain the target position at the preset distance from the transmission line in the electric field to be measured.

[0056] In this embodiment, the industrial control terminal 102 can determine the target position where the electric field strength measurement needs to be performed from multiple grids. The industrial control terminal 102 can obtain the solution step size of each grid, and establish a corresponding auxiliary line in the target grid according to the preset step size corresponding to the target grid at a preset distance from the above-mentioned transmission line, and obtain the target position at a preset distance from the transmission line in the electric field to be measured. For example, each grid can be used as a calculation area, and different calculation areas have different calculation accuracy requirements. Therefore, it is necessary to set a grid division method to shorten the calculation time. After setting the solution step size, the industrial control terminal 102 can establish auxiliary lines at specified positions in the above-mentioned simulation modeling, such as the auxiliary lines of the above-mentioned target position, so that the electric field strength distribution can be obtained in the target position to accurately detect the electric field and magnetic field strength of the power grid site.

[0057] In one embodiment, the meshing of the simulation modeling corresponding to the transmission line in the electric field to be measured can be performed by a preset algorithm. For example, the industrial control terminal 102 can mesh the simulation modeling corresponding to the transmission line by the simulated charge method, and divide it into multiple grids. The simulated charge method is one of the main methods for numerical calculation of electrostatic field. The simulated charge method is based on the uniqueness theorem of electrostatic field. The free charges continuously distributed on the surface of the conductor electrode are replaced by a group of discrete charges located inside the conductor. For example, a group of point charges, line charges or ring charges are set inside the conductor. These discrete charges are called simulated charges. Then, the superposition theorem is used to calculate the electric field strength at any point in the field using the analytical formula of these simulated charges. These simulated charges are determined according to the boundary conditions of the field. The key to the simulated charge method is to find and determine the simulated charges.

[0058] Through the above embodiment, the industrial control terminal 102 can obtain multiple grids using the simulated charge method, and obtain the target position using the solution step and auxiliary lines, thereby achieving the effect of improving the measurement accuracy of the electric field strength of the electric field to be measured.

[0059] In one embodiment, it also includes: acquiring multiple known temperatures, multiple known humidity, and multiple known voltage signals; determining a preset machine learning algorithm from multiple machine learning algorithms based on the data volume and data structure of the multiple known temperatures, multiple known humidity, and multiple known voltage signals; and according to the preset machine learning algorithm, training to obtain the corresponding relationship between the known temperature, known humidity, and the known electric field strength corresponding to the known voltage signal to obtain a prediction model.

[0060] In this embodiment, the industrial control terminal 102 can obtain the above prediction model through machine learning training. The industrial control terminal 102 can obtain multiple known temperatures, multiple known humidity and multiple known voltage signals as training data. The industrial control terminal 102 can determine the preset machine learning algorithm that can be used to train the training data from multiple machine learning algorithms according to the data volume and data structure of the multiple known temperatures, multiple known humidity and multiple known voltage signals. For example, the multiple machine learning algorithms can include algorithms in aspects such as decision trees, random forests, artificial neural networks, Bayesian learning, and deep learning. The industrial control terminal 102 can determine a suitable machine learning algorithm according to the size and data structure of the data volume of the above multiple known temperatures, known humidity and known voltage signals. After the industrial control terminal 102 determines the appropriate preset machine learning algorithm, it can train and obtain the corresponding relationship between the known electric field strengths corresponding to the above known temperatures, known humidity and known voltage signals according to the preset machine learning algorithm, so that the industrial control terminal 102 can analyze the influence of temperature and humidity on the electric field strength through the preset machine learning algorithm, and obtain the prediction model of the influence of temperature and humidity on the electric field strength.

[0061] Through this embodiment, the industrial control terminal 102 can use a machine learning algorithm that is compatible with the data volume and data structure of the temperature, humidity and voltage signals to obtain a prediction model for predicting the electric field strength, thereby improving the accuracy of the electric field strength measurement.

[0062] In one embodiment, the method further includes: if the temperature is greater than a preset temperature threshold, outputting a temperature alarm message.

[0063] In this embodiment, the industrial control terminal 102 can warn of data that does not meet the requirements when the temperature, humidity and field strength data exceed the corresponding thresholds. For example, if the industrial control terminal 102 detects that the temperature obtained above is greater than the preset temperature threshold, the industrial control terminal 102 can output temperature warning information. In one embodiment, if the industrial control terminal 102 detects that the humidity obtained above is greater than the preset humidity threshold, the industrial control terminal 102 can output humidity warning information. In one embodiment, if the industrial control terminal 102 detects that the electric field strength obtained above is greater than the preset field strength threshold, the industrial control terminal 102 can output field strength warning information to prompt the staff that the field strength at the target location is abnormal, so that the staff can perform corresponding processing on the transmission line.

[0064] In addition, the industrial control terminal 102 can also display the acquired data such as temperature, humidity and electric field strength, for example, through a display unit of the industrial control terminal 102, such as a display screen.

[0065] Through this embodiment, the industrial control terminal 102 can issue an alarm for illegal data, thereby improving the safety of the power transmission line, and can also display the acquired data, thereby improving the intuitiveness of data acquisition.

[0066] In one embodiment, Figure 3 As shown, Figure 3 FIG. 1 is a flow chart of a method for measuring electric field strength in another embodiment. The method includes the following steps:

[0067] The industrial control terminal 102 may first use finite element simulation software to model the simulation object, ie, high-voltage lines of different voltage levels and different wiring methods, to obtain a corresponding simulation model for calculation.

[0068] Then the industrial control terminal 102 can use the simulation software to mesh the simulation model using the simulated charge method. Different calculation areas have different calculation accuracy requirements, so it is necessary to set the meshing method to shorten the calculation time. After setting the solution step, the auxiliary line of the specified position is established in the model to obtain the electric field strength distribution at the specified position. In this way, the electric field strength of the electric field to be measured at the power grid site can be accurately detected.

[0069] The industrial control terminal 102 can set an electric field and magnetic field sensing device 100 and a temperature and humidity sensing device 104 in the electric field to be measured. In some embodiments, the above-mentioned industrial control terminal 102 can also be set in the electric field to be measured. The electric field and magnetic field sensing device 100 and the temperature and humidity sensing device 104 can be directly integrated in the industrial control terminal 102 to collect corresponding data in the form of hardware or software modules.

[0070] The above-mentioned electric field and magnetic field sensing device 100 can collect electric field and magnetic field information at the power grid site and output a voltage signal to the industrial control terminal 102. The electric field and magnetic field sensing device 100 mainly detects the close distance of the high-voltage transmission line conductors of the electric field to be measured in the power grid site. The strong electric field generated by the power grid site transmission line causes the electric field and magnetic field sensing module to output a voltage signal proportional to it. The signal is then transmitted to the electric field and magnetic field sensing main control computing module in the industrial control terminal 102 for data training, calculation, analysis and preprocessing.

[0071] A temperature and humidity sensing device 104, such as a temperature and humidity sensor, can also be provided in the electric field to be tested at the power grid site. The industrial control terminal 102 can use the temperature and humidity sensing device 104 to measure the temperature and humidity of the environment around the electric field and magnetic field control measurement of the power grid's high-voltage transmission line. The temperature and humidity sensing device 104 can convert the detected temperature or humidity data into an electrical signal according to its own calculation method and rules, and send it in the form of an electrical signal to the electric field and magnetic field sensing main control computing module in the industrial control terminal 102.

[0072] The industrial control terminal 102 can use the voltage signal, temperature and humidity data obtained above to obtain the electric field strength at the target location using a prediction model. Among them, the industrial control terminal 102 can first train the prediction model, which can be used to calculate the influence of temperature and humidity on the field strength. For example, the industrial control terminal 102 can determine a suitable machine learning algorithm based on multiple known temperatures, multiple known humidity and multiple known voltage signals, according to the size and data structure of the data volume of multiple known temperatures, multiple known humidity and multiple known voltage signals. The machine learning algorithm can include algorithms in aspects such as decision trees, random forests, artificial neural networks, Bayesian learning, and deep learning. The industrial control terminal 102 can use the electric field and magnetic field sensing main control computing module, use the above corresponding machine learning algorithm, analyze the influence of temperature and humidity on the electric field strength, and obtain the corresponding relationship between the temperature, humidity and the electric field strength corresponding to the voltage signal, so as to obtain a prediction model of the influence of temperature and humidity on the electric field strength. In actual measurement, the industrial control terminal 102 can input the above-obtained temperature, humidity and voltage signals into the above-mentioned prediction model, and use the electric field and magnetic field sensing main control calculation module to calculate the electric field strength through the above-mentioned prediction model to obtain the detection result of the electric field strength. The industrial control terminal 102 can also use the local data processing module to display the obtained electric field strength, state, temperature and humidity through the local display unit, for example, through the display screen of the industrial control terminal 102. The industrial control terminal 102 can also use the local alarm unit to issue an alarm of the corresponding information after detecting that the temperature, humidity or field strength exceeds the set corresponding threshold.

[0073] In addition, the data communication between the electric field and magnetic field sensing main control computing module in the industrial control terminal 102 and the local data processing module in the industrial control terminal 102 can be carried out by wired connection or by wireless communication. If wireless communication is carried out, the electric field and magnetic field sensing main control computing module can send the above data to the wireless communication receiving unit of the local data processing module through the wireless communication protocol transmission mode of the wireless communication transmitting module for data reception, so that the industrial control terminal 102 can use the local data processing module to process the data.

[0074] Through this embodiment, the industrial control terminal 102 obtains the electric field strength at the target location based on the known temperature, known humidity, known voltage signal and the prediction model obtained by the machine learning algorithm, thereby achieving the effect of improving the measurement accuracy of the electric field strength.

[0075] It should be understood that although Figure 2 and 3 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 2 and 3 At least part of the steps may include multiple steps or multiple stages. These steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed in turn or alternately with other steps or at least part of the steps or stages in other steps.

[0076] In one embodiment, Figure 4 As shown, an electric field strength measurement device is provided, including: a signal acquisition module 500, a temperature and humidity acquisition module 502 and a field strength acquisition module 504, wherein:

[0077] The signal acquisition module 500 is used to acquire a voltage signal at a target position in the electric field to be measured; the target position is a position at a preset distance from the transmission line in the electric field to be measured.

[0078] The temperature and humidity acquisition module 502 is used to acquire the temperature and humidity of the electric field to be measured.

[0079] The field strength acquisition module 504 is used to input the voltage signal, temperature and humidity into the prediction model to obtain the electric field strength output by the prediction model as the electric field strength corresponding to the target position in the electric field to be measured; the prediction model is based on multiple known temperatures, multiple known humidity and multiple known voltage signals, and is trained by a preset machine learning algorithm.

[0080] In one embodiment, the temperature and humidity acquisition module 502 is specifically used to acquire a first electrical signal corresponding to the temperature and a second electrical signal corresponding to the humidity sent by a temperature and humidity sensing device; the temperature and humidity sensing device is set in a target position; the temperature is obtained according to the first electrical signal, and the humidity is obtained according to the second electrical signal.

[0081] In one embodiment, the above-mentioned device also includes: a division module, which is used to obtain the simulation modeling corresponding to the transmission line through finite element simulation calculation according to the voltage level and wiring method corresponding to the transmission line; divide the simulation modeling into multiple grids, and determine the target position at a preset distance from the transmission line in the electric field to be measured from the multiple grids.

[0082] In one embodiment, the above-mentioned division module is specifically used to establish corresponding auxiliary lines in the target grid according to the preset step size corresponding to the target grid at a preset distance from the transmission line, so as to obtain the target position at the preset distance from the transmission line in the electric field to be measured.

[0083] In one embodiment, the above-mentioned device also includes: a training module, which is used to obtain multiple known temperatures, multiple known humidity and multiple known voltage signals; determine a preset machine learning algorithm from multiple machine learning algorithms based on the data volume and data structure of the multiple known temperatures, multiple known humidity and multiple known voltage signals; according to the preset machine learning algorithm, train to obtain the corresponding relationship between the known temperature, known humidity and the known electric field strength corresponding to the known voltage signal to obtain a prediction model.

[0084] In one embodiment, the above-mentioned division module is specifically used to divide the simulation modeling into multiple grids through the simulated charge method.

[0085] In one embodiment, the above device further includes: a first alarm module, configured to output temperature alarm information if the temperature is greater than a preset temperature threshold.

[0086] In one embodiment, the above device further includes: a second alarm module, configured to output humidity alarm information if the humidity is greater than a preset humidity threshold.

[0087] In one embodiment, the above device further includes: a third alarm module, configured to output field strength alarm information if the electric field strength is greater than a preset field strength threshold.

[0088] For the specific definition of the electric field strength measuring device, please refer to the definition of the electric field strength measuring method above, which will not be repeated here. Each module in the above electric field strength measuring device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0089] In one embodiment, a computer device is provided. The computer device may be an industrial control terminal, and its internal structure diagram may be as follows: Figure 5 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used 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 communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, an electric field strength measurement method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0090] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure 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 certain components, or have a different arrangement of components.

[0091] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the above-mentioned electric field strength measurement method when executing the computer program.

[0092] 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 above-mentioned electric field strength measurement method is implemented.

[0093] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and 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 embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0094] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, 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, they should be considered to be within the scope of this specification.

[0095] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for measuring electric field strength, characterized in that: The method comprises: Obtain a voltage signal of a target position in the electric field to be measured; the target position is a position in the electric field to be measured that is a preset distance away from a transmission line; the step of determining the target position comprises: obtaining a simulation model corresponding to the transmission line through finite element simulation calculation according to the voltage level and wiring method corresponding to the transmission line; dividing the simulation model into a plurality of grids, and determining a target position in the electric field to be measured that is a preset distance away from the transmission line from the plurality of grids; each of the grids is a calculation area, and different calculation areas have different calculation accuracy requirements; determining the target position in the electric field to be measured that is a preset distance away from the transmission line from the plurality of grids comprises: establishing a corresponding auxiliary line in the target grid according to a preset step size corresponding to a target grid that is a preset distance away from the transmission line, and obtaining a target position in the electric field to be measured that is a preset distance away from the transmission line; Acquiring the temperature and humidity of the electric field to be measured; The voltage signal, the temperature and the humidity are input into a prediction model, and the electric field strength output by the prediction model is obtained as the electric field strength corresponding to the target position in the electric field to be measured; the training step of the prediction model includes: obtaining multiple known temperatures, multiple known humidity and multiple known voltage signals; determining a preset machine learning algorithm from multiple machine learning algorithms according to the data volume and data structure of the multiple known temperatures, multiple known humidity and multiple known voltage signals; according to the preset machine learning algorithm, training to obtain the corresponding relationship between the known temperature, known humidity and the known electric field strength corresponding to the known voltage signal, and obtaining the prediction model.

2. The method according to claim 1, characterized in that The step of obtaining the temperature and humidity of the electric field to be measured comprises: Acquiring a first electrical signal corresponding to temperature and a second electrical signal corresponding to humidity sent by a temperature and humidity sensing device, wherein the temperature and humidity sensing device is disposed in the target position; The temperature is obtained according to the first electrical signal, and the humidity is obtained according to the second electrical signal.

3. The method according to claim 1, characterized in that The step of dividing the simulation modeling into a plurality of grids comprises: The simulation modeling is divided into a plurality of grids by a simulated charge method.

4. The method according to any one of claims 1 to 3, characterized in that: Also includes: If the temperature is greater than a preset temperature threshold, a temperature alarm message is output.

5. The method according to any one of claims 1 to 3, characterized in that: Also includes: If the humidity is greater than a preset humidity threshold, a humidity alarm message is output.

6. The method according to any one of claims 1 to 3, characterized in that: Also includes: If the electric field strength is greater than a preset field strength threshold, a field strength warning message is output.

7. An electric field strength measuring device, characterized in that: The device comprises: A signal acquisition module, for acquiring a voltage signal at a target position in the electric field to be measured; the target position is a position in the electric field to be measured that is a preset distance away from a transmission line; and also includes a division module, for obtaining a simulation modeling corresponding to the transmission line through finite element simulation calculation according to the voltage level and wiring method corresponding to the transmission line; the simulation modeling is divided into a plurality of grids, and a target position in the electric field to be measured that is a preset distance away from the transmission line is determined from the plurality of grids; each of the grids is a calculation area, and different calculation areas have different calculation accuracy requirements; and is specifically used to establish a corresponding auxiliary line in the target grid according to a preset step size corresponding to a target grid that is a preset distance away from the transmission line, so as to obtain a target position in the electric field to be measured that is a preset distance away from the transmission line; A temperature and humidity acquisition module, used to acquire the temperature and humidity of the electric field to be measured; A field strength acquisition module is used to input the voltage signal, the temperature and the humidity into a prediction model, and obtain the electric field strength output by the prediction model as the electric field strength corresponding to the target position in the electric field to be measured; the prediction model is based on multiple known temperatures, multiple known humidity and multiple known voltage signals, and is obtained through training with a preset machine learning algorithm; it also includes a training module, which is used to obtain multiple known temperatures, multiple known humidity and multiple known voltage signals; according to the data volume and data structure of the multiple known temperatures, multiple known humidity and multiple known voltage signals, the preset machine learning algorithm is determined from multiple machine learning algorithms; according to the preset machine learning algorithm, the corresponding relationship between the known temperature, the known humidity and the known electric field strength corresponding to the known voltage signal is trained to obtain the prediction model.

8. The device according to claim 7, characterized in that The temperature and humidity acquisition module is used to: Acquiring a first electrical signal corresponding to temperature and a second electrical signal corresponding to humidity sent by a temperature and humidity sensing device, wherein the temperature and humidity sensing device is disposed in the target position; The temperature is obtained according to the first electrical signal, and the humidity is obtained according to the second electrical signal.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

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

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