Electromagnetic field space distribution measurement method

Abstract

The invention relates to the technical field of electromagnetic field measurement, and discloses an electromagnetic field spatial distribution measurement method, which comprises the following steps of 1, establishing an electromagnetic field measurement monitoring module, a data collection module, a data analysis module, a fault judgment module and a data management module; step 2, an electromagnetic field measurement monitoring module monitors and processes data by using an electromagnetic field space distribution measurement technology and a three-dimensional space electromagnetic field distribution measurement technology; 3, a data collection module collects data of the electromagnetic field measurement monitoring module through a network; 4, transmitting the data to a data analysis module, and carrying out data calculation; 5, performing fault distinguishing on a data calculation result in a fault judgment module; and step 6, optimizing the layout of the monitoring points in the data management module according to a data calculation result, and after the steps of the method are implemented, the method has the advantages of monitoring state parameters and fault abnormal parameters in real time and being capable of carrying out fault pre-judgment.

Description

Technical Field

[0001] The invention relates to the technical field of electromagnetic field measurement, and in particular to a method for measuring electromagnetic field spatial distribution. Background Art

[0002] In practical applications, electromagnetic field spatial distribution measurement technology faces the problem of being unable to monitor state parameters, fault abnormal parameters, and being unable to predict faults in real time. These problems are mainly due to the limitations of existing technologies. For example, traditional electromagnetic field measurement methods often require the electromagnetic signal and position signal to be measured separately, resulting in a cumbersome measurement process and the inability to obtain high-precision electromagnetic field spatial distribution. In addition, the existing electromagnetic field measurement system may interfere with the measured electromagnetic field during measurement, affecting the accuracy of the measurement results. In some cases, the measurement process may take a long time and cannot be completed in one go, resulting in the inability to conduct tests continuously. Especially when the measurement field strength is large, electromagnetic compatibility problems are prone to occur, which may cause disorder or even damage to the measuring equipment, and it is also impossible to complete millimeter-level precision tests. These problems limit the application and development of electromagnetic field measurement technology in the fields of wireless energy transmission technology, radar technology, and electromagnetic compatibility.

[0003] In order to overcome these shortcomings, researchers are committed to developing new measurement methods and systems to achieve automation, high-precision and real-time data processing, and improve the accuracy and efficiency of electromagnetic field spatial distribution measurement. These new technical solutions are designed to reduce interference with the measured electromagnetic field, achieve high-precision measurement and construction of electromagnetic field spatial distribution, meet the measurement needs of small indoor spaces and large outdoor spaces, and meet the needs of real-time continuous measurement positioning and interval sampling measurement positioning. Through these technological advances, the reliability and practicality of electromagnetic field measurement can be effectively improved, providing support for the development of related technical fields. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the shortcomings of the prior art, the present invention provides a method for measuring the spatial distribution of an electromagnetic field, which has the advantages of being able to monitor state parameters, fault abnormality parameters in real time and being able to predict faults, thereby solving the problems faced by the prior art in actual applications, such as being unable to monitor state parameters, fault abnormality parameters in real time and being unable to predict faults.

[0006] (II) Technical solution

[0007] To achieve the above object, the present invention provides the following technical solution: a method for measuring the spatial distribution of an electromagnetic field, comprising the following steps:

[0008] Step 1: Establish an electromagnetic field measurement and monitoring module, a data collection module, a data analysis module, a fault judgment module and a data management module;

[0009] Step 2: The electromagnetic field measurement and monitoring module uses electromagnetic field spatial distribution measurement technology and three-dimensional electromagnetic field distribution measurement technology to monitor and process data;

[0010] Step 3: The data collection module collects data from the electromagnetic field measurement and monitoring module through the network;

[0011] Step 4: Send the data to the data analysis module for data calculation;

[0012] Step 5: Differentiate the faults of the data calculation results in the fault judgment module;

[0013] Step 6: Optimize the monitoring point layout in the data management module based on the data calculation results.

[0014] Preferably, the electromagnetic field measurement and monitoring module utilizes electromagnetic field spatial distribution measurement technology to invert electromagnetic field parameters into actual line operation state parameters to realize monitoring of voltage, current, sag, wind deviation and dancing line state parameters; the electromagnetic field measurement and monitoring module utilizes three-dimensional electromagnetic field distribution measurement technology to realize automated, high-precision and real-time data processing.

[0015] Preferably, the data collection module includes an actual monitoring parameter data unit, an electromagnetic field parameter inversion data unit and a three-dimensional electromagnetic field distribution measurement data unit. The actual monitoring parameter data unit obtains actual monitoring parameter data through monitoring equipment and sensors, the electromagnetic field parameter inversion data unit obtains electromagnetic field parameter inversion data through a network, and the three-dimensional electromagnetic field distribution measurement data unit obtains three-dimensional electromagnetic field distribution measurement data through a network. The actual monitoring parameter data unit, the electromagnetic field parameter inversion data unit and the three-dimensional electromagnetic field distribution measurement data unit number the internal data of the unit and then connect to the data analysis module through the network.

[0016] Preferably, the data analysis module includes an electromagnetic field simulation model unit, an electromagnetic field fault prediction unit and an electromagnetic field measurement optimization unit. The electromagnetic field simulation model unit calculates the electromagnetic field simulation model simulation similarity Srl based on the actual monitoring parameter data and the electromagnetic field parameter inversion data. The electromagnetic field fault prediction unit calculates the electromagnetic field fault occurrence probability Zrf based on the actual monitoring parameter data and the electromagnetic field parameter inversion data. The electromagnetic field measurement optimization unit calculates the electromagnetic field measurement optimization index Arp based on the actual monitoring parameter data, the electromagnetic field parameter inversion data and the three-dimensional electromagnetic field distribution measurement data. The electromagnetic field simulation model unit, the electromagnetic field fault prediction unit and the electromagnetic field measurement optimization unit transmit the calculation results to the fault judgment module and the data management module through the network.

[0017] Preferably, the actual monitoring parameter data unit numbers the actual measured current, the actual current fault occurrence times, the actual electric field strength and the actual magnetic field strength according to the actual monitoring parameter data characteristics, and the actual measured current is numbered I s1 ,I s2 ,I s3 ,…I sn , the actual number of current fault occurrences is numbered as m, and the actual electric field strength is numbered as B s1 , B s2 , B s3 , …B sx , the actual magnetic field strength is numbered as D s1 , D s2 , D s3 ,…D sx The electromagnetic field parameter inversion data unit performs data numbering on the electromagnetic field inversion current, the number of electromagnetic field inversion current predicted fault occurrences and the electric field inversion intensity according to the electromagnetic field parameter inversion data characteristics, and the electromagnetic field inversion current is numbered I f1 ,I f2 ,I f3 ,…I fn , the electric field inversion intensity is numbered as B f1 , B f2 , B f3 , …B fx The electromagnetic field inversion current predicts the number of fault occurrences and is numbered v. The three-dimensional electromagnetic field distribution measurement data unit performs data numbering on the three-dimensional space simulation magnetic field strength according to the three-dimensional space electromagnetic field distribution measurement data characteristics. The three-dimensional space simulation magnetic field strength is numbered D l1 , D l2 , D l3 ,…D lx .

[0018] Preferably, the electromagnetic field simulation model unit calculates the electromagnetic field simulation model simulation similarity Srl according to the actual monitoring parameter data and the electromagnetic field parameter inversion data, and the calculation formula is:

[0019]

[0020] In the formula, Srl represents the simulation similarity of the electromagnetic field simulation model, I s1 ,I s2 ,I s3 ,…I sn Indicates the actual measured current, I f1 ,I f2 ,I f3 ,…I fn Represents the electromagnetic field inversion current, I sj ,I fjThey represent the actual measured current and the electromagnetic field inversion current at the i-th measuring point respectively, and n represents the number of current measurements.

[0021] Preferably, the electromagnetic field fault prediction unit calculates the electromagnetic field fault occurrence probability Zrf according to the actual monitoring parameter data and the electromagnetic field parameter inversion data, and the calculation formula is:

[0022]

[0023] In the formula, Zrf represents the probability of electromagnetic field fault occurrence, m represents the number of actual current fault occurrences, n represents the number of current measurements, v represents the number of electromagnetic field inversion current predicted fault occurrences, and t 1 It represents the time interval from the last fault monitoring to the current fault occurrence, t 2 It represents the time interval from the current fault to the predicted fault. e represents the base of the natural logarithm, which is equal to 2.71828.

[0024] Preferably, the electromagnetic field measurement optimization unit calculates the electromagnetic field measurement optimization index Arp according to the actual monitoring parameter data, the electromagnetic field parameter inversion data and the three-dimensional electromagnetic field distribution measurement data, and the calculation formula is:

[0025]

[0026] In the formula, Arp represents the electromagnetic field measurement optimization index, B s1 , B s2 , B s3 , …B sx Indicates the actual electric field strength, B si represents the actual electric field strength at the ith measurement point, D s1 , D s2 , D s3 ,…D sx Indicates the actual magnetic field strength, D si represents the actual magnetic field strength at the i-th measurement point, B f1 , B f2 , B f3 , …B fx represents the electric field inversion intensity, B fi represents the electric field inversion intensity at the ith measurement point, D l1 , D l2 , D l3 ,…D lx Represents the simulated magnetic field strength in three-dimensional space, D li represents the three-dimensional simulated magnetic field intensity of the i-th measurement point, and x represents the total number of measurement points.

[0027] Preferably, the fault judgment module diagnoses electromagnetic field space faults according to the electromagnetic field fault occurrence probability Zrf; the fault judgment module inverts and reverses the electromagnetic field space measurement data according to the electromagnetic field simulation model simulation similarity Srl; the fault judgment module optimizes the layout of electromagnetic field space monitoring points according to the electromagnetic field measurement optimization index Arp.

[0028] Preferably, the management process of the data management module:

[0029] When the probability of electromagnetic field fault Zr>0.1, the motor status is monitored by electrical characteristics, and the working status inside the rotor is deeply analyzed to realize the early warning mechanism of fault;

[0030] When the simulation similarity of the electromagnetic field simulation model Srl≤0.98, a new method for non-contact measurement of three-phase current of overhead transmission lines is used to invert the power frequency magnetic field data to the three-phase current of overhead transmission lines, so as to realize non-contact measurement of line current.

[0031] When the electromagnetic field measurement optimization index Arp<0.95, the parameters of the reasonable configuration of monitoring sensors, signal acquisition and processing, data management, feature extraction, information fusion, pattern classification, state assessment, intelligent judgment and decision prediction are readjusted.

[0032] Compared with the prior art, the present invention provides a method for measuring the spatial distribution of an electromagnetic field, which has the following beneficial effects:

[0033] 1. The present invention calculates the simulation similarity Srl of the electromagnetic field simulation model. When the simulation similarity Srl of the electromagnetic field simulation model is close to 1, it indicates that the simulation model has high accuracy, which helps to more accurately predict the electromagnetic field distribution, thereby improving the reliability of system monitoring and effectively reducing the false alarm rate. This method can monitor state parameters in real time and improve the operating efficiency of the system.

[0034] 2. The present invention calculates the probability of electromagnetic field fault occurrence Zrf and uses the electromagnetic field simulation model simulation similarity Srl to judge the accuracy of the model. When the electromagnetic field simulation model simulation similarity Srl reaches 0.98, it indicates that the simulation model is highly consistent with the actual situation. Therefore, the model can be directly used to predict fault parameters. This method improves the accuracy of fault prediction, and by calculating the probability of electromagnetic field fault occurrence in real time, it can capture abnormal situations that may occur in the electromagnetic field in time, providing the possibility for early warning of the system and taking early preventive measures. Therefore, this real-time performance prevents the occurrence of faults.

[0035] 3. The present invention calculates the electromagnetic field measurement optimization index Arp. The electromagnetic field measurement optimization index Arp integrates actual monitoring data, inversion data and three-dimensional space simulation data, which helps to identify and correct deviations in the measurement process and improve the accuracy of electromagnetic field measurement. The electromagnetic field measurement optimization index Arp can be used to identify which areas require more resource investment, thereby allocating measurement resources more effectively. The electromagnetic field measurement optimization index Arp can also be used as a measure of data quality to help the electromagnetic system screen out reliable data, eliminate possible outliers or erroneous measurements, and enhance the reliability of the overall data of the electromagnetic system. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] See also Figure 1 , a method for measuring the spatial distribution of an electromagnetic field, comprising the following steps:

[0039] Step 1: Establish an electromagnetic field measurement and monitoring module, a data collection module, a data analysis module, a fault judgment module and a data management module;

[0040] Step 2: The electromagnetic field measurement and monitoring module uses electromagnetic field spatial distribution measurement technology and three-dimensional electromagnetic field distribution measurement technology to monitor and process data;

[0041] Step 3: The data collection module collects data from the electromagnetic field measurement and monitoring module through the network;

[0042] Step 4: Send the data to the data analysis module for data calculation;

[0043] Step 5: Differentiate the faults of the data calculation results in the fault judgment module;

[0044] Step 6: Optimize the monitoring point layout in the data management module based on the data calculation results.

[0045] The electromagnetic field measurement and monitoring module utilizes electromagnetic field spatial distribution measurement technology to invert electromagnetic field parameters into actual line operation status parameters to realize monitoring of voltage, current, sag, windage and dancing line status parameters. Through electromagnetic field perception, it realizes monitoring of electromagnetic fields in the space around overhead transmission lines and improves the comprehensive judgment ability of operation status. The electromagnetic field measurement and monitoring module utilizes three-dimensional electromagnetic field distribution measurement technology to realize automatic, high-precision and real-time data processing, and is suitable for electromagnetic field distribution testing in the fields of wireless energy transmission technology, radar technology and electromagnetic compatibility.

[0046] The data collection module includes an actual monitoring parameter data unit, an electromagnetic field parameter inversion data unit and a three-dimensional electromagnetic field distribution measurement data unit. The actual monitoring parameter data unit obtains actual monitoring parameter data through monitoring equipment and sensors, the electromagnetic field parameter inversion data unit obtains electromagnetic field parameter inversion data through the network, and the three-dimensional electromagnetic field distribution measurement data unit obtains three-dimensional electromagnetic field distribution measurement data through the network. The actual monitoring parameter data unit, the electromagnetic field parameter inversion data unit and the three-dimensional electromagnetic field distribution measurement data unit number the internal data of the unit and then connect to the data analysis module through the network.

[0047] The data analysis module includes an electromagnetic field simulation model unit, an electromagnetic field fault prediction unit and an electromagnetic field measurement optimization unit. The electromagnetic field simulation model unit calculates the electromagnetic field simulation model simulation similarity Srl based on the actual monitoring parameter data and the electromagnetic field parameter inversion data. The electromagnetic field fault prediction unit calculates the electromagnetic field fault occurrence probability Zrf based on the actual monitoring parameter data and the electromagnetic field parameter inversion data. The electromagnetic field measurement optimization unit calculates the electromagnetic field measurement optimization index Arp based on the actual monitoring parameter data, the electromagnetic field parameter inversion data and the three-dimensional electromagnetic field distribution measurement data. The electromagnetic field simulation model unit, the electromagnetic field fault prediction unit and the electromagnetic field measurement optimization unit transmit the calculation results to the fault judgment module and the data management module through the network.

[0048] The actual monitoring parameter data unit numbers the actual measured current, the actual current fault occurrence times, the actual electric field strength and the actual magnetic field strength according to the actual monitoring parameter data characteristics, and the actual measured current is numbered I s1 ,I s2 ,I s3 ,…I sn , the actual number of current fault occurrences is numbered as m, and the actual electric field strength is numbered as B s1 , B s2 , B s3 ,…B sx , the actual magnetic field strength is numbered as D s1 , D s2 , Ds3 ,…D sx The electromagnetic field parameter inversion data unit performs data numbering on the electromagnetic field inversion current, the number of electromagnetic field inversion current predicted fault occurrences and the electric field inversion intensity according to the electromagnetic field parameter inversion data characteristics, and the electromagnetic field inversion current is numbered I f1 ,I f2 ,I f3 ,…I fn , the electric field inversion intensity is numbered as B f1 , B f2 , B f3 , …B fx The electromagnetic field inversion current predicts the number of fault occurrences and is numbered v. The three-dimensional electromagnetic field distribution measurement data unit performs data numbering on the three-dimensional space simulation magnetic field strength according to the three-dimensional space electromagnetic field distribution measurement data characteristics. The three-dimensional space simulation magnetic field strength is numbered D l1 , D l2 , D l3 ,…D lx .

[0049] The electromagnetic field simulation model unit calculates the electromagnetic field simulation model simulation similarity Srl based on the actual monitoring parameter data and the electromagnetic field parameter inversion data. The calculation formula is:

[0050]

[0051] In the formula, Srl represents the simulation similarity of the electromagnetic field simulation model, I s1 ,I s2 ,I s3 ,…I sn Indicates the actual measured current, I f1 ,I f2 ,I f3 ,…I fn Represents the electromagnetic field inversion current, I sj ,I fj They represent the actual measured current and the electromagnetic field inversion current at the i-th measuring point respectively, and n represents the number of current measurements.

[0052] By calculating the simulation similarity Srl of the electromagnetic field simulation model, an important indicator for measuring the accuracy of the electromagnetic field simulation model is obtained. When the simulation similarity Srl of the electromagnetic field simulation model is close to 1, it means that the simulation measurement accuracy of the electromagnetic field simulation model is high. When the simulation similarity Srl of the electromagnetic field simulation model is far away from 1, it means that the simulation measurement accuracy of the electromagnetic field simulation model is low. It is necessary to use a new method for non-contact measurement of three-phase current of overhead transmission lines, and to use the inversion and reverse deduction method from power frequency magnetic field data to three-phase current of overhead transmission lines to realize non-contact measurement of line current, so as to improve the simulation measurement accuracy of the simulation model, thereby judging the accuracy and effectiveness of real-time monitoring of state parameters using electromagnetic field simulation models.

[0053] The advantage is that when the simulation similarity Srl of the electromagnetic field simulation model is close to 1, it means that the simulation model has high accuracy, which helps to more accurately predict the electromagnetic field distribution, thereby improving the reliability of system monitoring and effectively reducing the false alarm rate. This method can monitor state parameters in real time and improve the operating efficiency of the system.

[0054] The electromagnetic field fault prediction unit calculates the electromagnetic field fault occurrence probability Zrf based on the actual monitoring parameter data and the electromagnetic field parameter inversion data. The calculation formula is:

[0055]

[0056] In the formula, Zrf represents the probability of electromagnetic field fault occurrence, m represents the number of actual current fault occurrences, n represents the number of current measurements, v represents the number of electromagnetic field inversion current predicted fault occurrences, and t 1 It represents the time interval from the last fault monitoring to the current fault occurrence, t 2 It represents the time interval from the current fault to the predicted fault. e represents the base of the natural logarithm, which is equal to 2.71828.

[0057] By calculating the probability of electromagnetic field fault occurrence Zrf as the identification of system early warning, the accuracy of the electromagnetic field simulation model is first judged according to the simulation similarity Srl of the electromagnetic field simulation model. When the simulation similarity Srl>0.98, the electromagnetic field simulation model is directly used to predict the fault parameters, and the probability of electromagnetic field fault occurrence Zrf is calculated. Through the electromagnetic field fault probability Zrf, the fault judgment module makes a judgment based on the size of the electromagnetic field fault probability Zrf. When the electromagnetic field fault probability Zr>0.1, the motor is monitored by electrical characteristics, and then the working state inside the rotor is deeply analyzed to realize the early warning mechanism of faults.

[0058] The advantages are: by calculating the probability of electromagnetic field fault occurrence Zrf, and using the electromagnetic field simulation model simulation similarity Srl to judge the accuracy of the model, when the electromagnetic field simulation model simulation similarity Srl reaches 0.98, it shows that the simulation model is highly consistent with the actual situation, so the model can be directly used to predict the fault parameters. This method improves the accuracy of fault prediction, and by calculating the probability of electromagnetic field fault occurrence in real time, it can capture possible abnormal situations in the electromagnetic field in time, providing the possibility for early warning of the system and taking early preventive measures. Therefore, this real-time performance prevents the occurrence of faults.

[0059] The electromagnetic field measurement optimization unit calculates the electromagnetic field measurement optimization index Arp based on the actual monitoring parameter data, electromagnetic field parameter inversion data and three-dimensional electromagnetic field distribution measurement data. The calculation formula is:

[0060]

[0061] In the formula, Arp represents the electromagnetic field measurement optimization index, B s1 , B s2 , B s3 , …B sx Indicates the actual electric field strength, B si represents the actual electric field strength at the ith measurement point, D s1 , D s2 , D s3 ,…D sx Indicates the actual magnetic field strength, D si represents the actual magnetic field strength at the i-th measurement point, B f1 , B f2 , B f3 , …B fx represents the electric field inversion intensity, B fi represents the electric field inversion intensity at the ith measurement point, D l1 , D l2 , D l3 ,…D lx Represents the simulated magnetic field strength in three-dimensional space, D li represents the three-dimensional simulated magnetic field intensity of the i-th measurement point, and x represents the total number of measurement points.

[0062] The advantages are: by calculating the electromagnetic field measurement optimization index Arp, the electromagnetic field measurement optimization index Arp integrates actual monitoring data, inversion data and three-dimensional space simulation data, which helps to identify and correct deviations in the measurement process and improve the accuracy of electromagnetic field measurement. The electromagnetic field measurement optimization index Arp can be used to identify which areas require more resource investment, thereby allocating measurement resources more effectively. The electromagnetic field measurement optimization index Arp can also be used as a measure of data quality to help the electromagnetic system screen out reliable data, eliminate possible outliers or erroneous measurements, and enhance the reliability of the overall data of the electromagnetic system.

[0063] The fault judgment module diagnoses electromagnetic field space faults according to the electromagnetic field fault occurrence probability Zrf; the fault judgment module inverts and reverses the electromagnetic field space measurement data according to the electromagnetic field simulation model simulation similarity Srl; the fault judgment module optimizes the layout of electromagnetic field space monitoring points according to the electromagnetic field measurement optimization index Arp.

[0064] Management process of data management module:

[0065] When the probability of electromagnetic field fault Zr>0.1, the motor is monitored by electrical characteristics, and the working state inside the rotor is analyzed in depth to realize the early warning mechanism of fault;

[0066] When the simulation similarity of the electromagnetic field simulation model Srl≤0.98, a new method for non-contact measurement of three-phase current of overhead transmission lines is used to invert the power frequency magnetic field data to the three-phase current of overhead transmission lines, so as to realize non-contact measurement of line current.

[0067] When the electromagnetic field measurement optimization index Arp<0.95, the parameters of the reasonable configuration of monitoring sensors, signal acquisition and processing, data management, feature extraction, information fusion, pattern classification, state assessment, intelligent judgment and decision prediction are readjusted.

[0068] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for measuring the spatial distribution of an electromagnetic field, characterized in that: The following steps are involved: Step 1: Establish an electromagnetic field measurement and monitoring module, a data collection module, a data analysis module, a fault judgment module and a data management module; Step 2: The electromagnetic field measurement and monitoring module uses electromagnetic field spatial distribution measurement technology and three-dimensional electromagnetic field distribution measurement technology to monitor and process data; Step 3: The data collection module collects data from the electromagnetic field measurement and monitoring module through the network; Step 4: Send the data to the data analysis module for data calculation; Step 5: Differentiate the faults of the data calculation results in the fault judgment module; Step 6: Optimize the monitoring point layout in the data management module based on the data calculation results.

2. The electromagnetic field spatial distribution measurement method according to claim 1, characterized in that: The electromagnetic field measurement and monitoring module utilizes electromagnetic field spatial distribution measurement technology to invert electromagnetic field parameters into actual line operation state parameters to realize monitoring of voltage, current, sag, wind deviation and dancing line state parameters; the electromagnetic field measurement and monitoring module utilizes three-dimensional electromagnetic field distribution measurement technology to realize automatic, high-precision and real-time data processing.

3. The electromagnetic field spatial distribution measurement method according to claim 2, characterized in that: The data collection module includes an actual monitoring parameter data unit, an electromagnetic field parameter inversion data unit and a three-dimensional electromagnetic field distribution measurement data unit. The actual monitoring parameter data unit obtains actual monitoring parameter data through monitoring equipment and sensors, the electromagnetic field parameter inversion data unit obtains electromagnetic field parameter inversion data through a network, and the three-dimensional electromagnetic field distribution measurement data unit obtains three-dimensional electromagnetic field distribution measurement data through a network. The actual monitoring parameter data unit, the electromagnetic field parameter inversion data unit and the three-dimensional electromagnetic field distribution measurement data unit number the internal data of the unit and then connect to the data analysis module through the network.

4. The electromagnetic field spatial distribution measurement method according to claim 3, characterized in that: The data analysis module includes an electromagnetic field simulation model unit, an electromagnetic field fault prediction unit and an electromagnetic field measurement optimization unit. The electromagnetic field simulation model unit calculates the electromagnetic field simulation model simulation similarity Srl based on the actual monitoring parameter data and the electromagnetic field parameter inversion data. The electromagnetic field fault prediction unit calculates the electromagnetic field fault occurrence probability Zrf based on the actual monitoring parameter data and the electromagnetic field parameter inversion data. The electromagnetic field measurement optimization unit calculates the electromagnetic field measurement optimization index Arp based on the actual monitoring parameter data, the electromagnetic field parameter inversion data and the three-dimensional electromagnetic field distribution measurement data. The electromagnetic field simulation model unit, the electromagnetic field fault prediction unit and the electromagnetic field measurement optimization unit transmit the calculation results to the fault judgment module and the data management module through the network.

5. The electromagnetic field spatial distribution measurement method according to claim 3, characterized in that: The actual monitoring parameter data unit performs data numbering on the actual measured current, the actual current fault occurrence times, the actual electric field strength and the actual magnetic field strength according to the actual monitoring parameter data characteristics. The actual measured current is numbered I s1 ,I s2 ,I s3 ,…I sn , the actual number of current fault occurrences is numbered as m, and the actual electric field strength is numbered as B s1 , B s2 , B s3 ,…B sx , the actual magnetic field strength is numbered as D s1 , D s2 , D s3 ,…D sx The electromagnetic field parameter inversion data unit performs data numbering on the electromagnetic field inversion current, the number of electromagnetic field inversion current predicted fault occurrences and the electric field inversion intensity according to the electromagnetic field parameter inversion data characteristics, and the electromagnetic field inversion current is numbered I f1 ,I f2 ,I f3 ,…I fn , the electric field inversion intensity is numbered as B f1 , B f2 , B f3 ,…B fx The electromagnetic field inversion current predicts the number of fault occurrences and is numbered v. The three-dimensional electromagnetic field distribution measurement data unit performs data numbering on the three-dimensional space simulation magnetic field strength according to the three-dimensional space electromagnetic field distribution measurement data characteristics. The three-dimensional space simulation magnetic field strength is numbered D l1 , D l2 , D l3 ,…D lx .

6. The electromagnetic field spatial distribution measurement method according to claim 5, characterized in that: The electromagnetic field simulation model unit calculates the electromagnetic field simulation model simulation similarity Srl according to the actual monitoring parameter data and the electromagnetic field parameter inversion data, and the calculation formula is: In the formula, Srl represents the simulation similarity of the electromagnetic field simulation model, I s1 ,I s2 ,I s3 ,…I sn Indicates the actual measured current, I f1 ,I f2 ,I f3 ,…I fn Represents the electromagnetic field inversion current, I sj ,I fj They represent the actual measured current and the electromagnetic field inversion current at the i-th measuring point respectively, and n represents the number of current measurements.

7. The electromagnetic field spatial distribution measurement method according to claim 5, characterized in that: The electromagnetic field fault prediction unit calculates the electromagnetic field fault occurrence probability Zrf according to the actual monitoring parameter data and the electromagnetic field parameter inversion data, and the calculation formula is: In the formula, Zrf represents the probability of electromagnetic field fault occurrence, m represents the number of actual current fault occurrences, n represents the number of current measurements, v represents the number of electromagnetic field inversion current predicted fault occurrences, t1 represents the time interval from the last monitored fault to the current fault, t2 represents the time interval from the current fault to the predicted fault, and e represents the base of the natural logarithm, which is equal to 2.71828.

8. The electromagnetic field spatial distribution measurement method according to claim 5, characterized in that: The electromagnetic field measurement optimization unit calculates the electromagnetic field measurement optimization index Arp according to the actual monitoring parameter data, the electromagnetic field parameter inversion data and the three-dimensional electromagnetic field distribution measurement data, and the calculation formula is: In the formula, Arp represents the electromagnetic field measurement optimization index, B s1 , B s2 , B s3 ,…B sx Indicates the actual electric field strength, B si represents the actual electric field strength at the ith measurement point, D s1 , D s2 , D s3 ,…D sx Indicates the actual magnetic field strength, D si represents the actual magnetic field strength at the i-th measurement point, B f1 , B f2 , B f3 ,…B fx represents the electric field inversion intensity, B fi represents the electric field inversion intensity at the ith measurement point, D l1 , D l2 , D l3 ,…D lx Represents the simulated magnetic field strength in three-dimensional space, D li represents the three-dimensional simulated magnetic field intensity of the ith measurement point, and x represents the total number of measurement points.

9. The electromagnetic field spatial distribution measurement method according to claim 8, characterized in that: The fault judgment module diagnoses electromagnetic field space faults according to the electromagnetic field fault occurrence probability Zrf; the fault judgment module inverts and reverses the electromagnetic field space measurement data according to the electromagnetic field simulation model simulation similarity Srl; the fault judgment module optimizes the layout of electromagnetic field space monitoring points according to the electromagnetic field measurement optimization index Arp.

10. The electromagnetic field spatial distribution measurement method according to claim 9, characterized in that: The management process of the data management module: When the probability of electromagnetic field fault Zr>0.1, the motor status is monitored by electrical characteristics, and the working status inside the rotor is deeply analyzed to realize the early warning mechanism of fault; When the simulation similarity of the electromagnetic field simulation model Srl≤0.98, a new method for non-contact measurement of three-phase current of overhead transmission lines is used to invert the power frequency magnetic field data to the three-phase current of overhead transmission lines, so as to realize non-contact measurement of line current. When the electromagnetic field measurement optimization index Arp<0.95, the parameters of the reasonable configuration of monitoring sensors, signal acquisition and processing, data management, feature extraction, information fusion, pattern classification, state assessment, intelligent judgment and decision prediction are readjusted.

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