A method and system for on-line detection of insulation of a phase-modulator auxiliary motor without power interruption

Abstract

The application belongs to the technical field of power automation auxiliary detection, and provides a phase modifier auxiliary motor insulation online non-power-off detection method and system. First insulation detection parameters of a motor are collected by combining a motor insulation online monitoring module, first machine room environment parameters collected by a phase modifier ring sampling module, and first aging parameters collected by a phase modifier insulation aging module, to obtain first auxiliary adjustment features. A phase modifier auxiliary detection model is constructed according to the first auxiliary adjustment features and a corresponding phase modifier first control method. Second auxiliary adjustment features obtained by processing a motor to be insulated are input into the phase modifier auxiliary detection model to obtain a second control method of a phase modifier of the motor to be insulated. The working parameters of the phase modifier are controlled according to the second control method of the phase modifier, to assist the motor insulation online non-power-off detection and the subsequent detection and adjustment of the motor insulation detection parameters.

Description

Technical Field

[0001] This invention belongs to the field of power automation auxiliary detection technology, and particularly relates to a method and system for online uninterrupted power detection of motor insulation assisted by a synchronous condenser. Background Technology

[0002] With the continuous expansion of DC transmission capacity, power quality issues are becoming more prominent, and the demand for reactive power in the power grid system is increasing daily. Synchronous condensers, as dedicated reactive power compensation sources, offer advantages such as continuous controllability of output reactive power, flexible adjustment, high precision, and error-free regulation.

[0003] A synchronous condenser is a type of synchronous motor operating under special conditions without mechanical load. By changing the magnitude of its excitation current, it can be controlled whether it absorbs or outputs reactive power from the power system. Under conditions without compensation, the rotor excitation winding current is the rated no-load excitation current, and the terminal voltage is the same as the grid voltage. Since the rotor has no mechanical load, there is almost no current in the stator armature winding, so the condenser does not output reactive power. When the system voltage is low, it operates under excitation, becoming a reactive power source and providing reactive power to the system to raise the system voltage; when the system voltage is high, it operates under excitation, becoming a reactive load and absorbing reactive power from the system to lower the system voltage. In this way, the synchronous condenser injects capacitive or inductive reactive current into the grid, also known as outputting capacitive or inductive reactive power.

[0004] The primary threat to the safe operation of large electric motors stems from their insulation system, determined by the motor's insulation structure, operating environment, and operating conditions. Traditional methods often involve periodic checks using high-voltage insulation testers or megohmmeters during non-operational periods. Motor equipment is also frequently equipped with motor safety control cabinets, which offer protection against phase loss and overcurrent. However, these detection and protection devices cannot display real-time insulation data of the motor's operating status or reflect changes in the actual insulation condition. Consequently, they cannot track internal contamination and insulation values ​​in many critical motor components in real time. This hinders the effective scheduling of preventative maintenance and replacement, leaving the motor's safe operation unsecured and preventing the equipment from reaching its maximum lifespan and being fully utilized.

[0005] It is evident that the existing technology has the following problems:

[0006] Firstly, during online uninterrupted power-on testing of motor insulation, there is a lack of characteristic processing of the phase shifter data, and a lack of automated continuous control and flexible adjustment of the phase shifter to assist in testing. Secondly, there is no parameter setting model for the phase shifter under different online uninterrupted power-on testing environments for motor insulation, and the big data intelligent control algorithm is not fully utilized for precise phase shifter control to achieve accurate online uninterrupted power-on testing of motor insulation under variable adjustment of phase shifter parameters. Summary of the Invention

[0007] To address the aforementioned technical problems, this invention proposes a method and system for online uninterrupted power-off detection of insulation in a synchronous condenser auxiliary motor.

[0008] In a first aspect of the present invention, a method for online uninterrupted power-free insulation detection of a synchronous condenser auxiliary motor is provided, the method comprising:

[0009] S1. Obtain the first insulation detection parameters of the electric motor, the first room environment parameters and the first aging parameters of the synchronous condenser, and obtain the first control method of the synchronous condenser;

[0010] S2. The first insulation detection parameters of the electric motor, the first machine room environment parameters of the synchronous condenser, and the first aging parameters are processed to obtain the first auxiliary adjustment feature;

[0011] S3. Construct an auxiliary detection model for the camera adjustment device based on the first auxiliary adjustment feature and the corresponding first control method of the camera adjustment device;

[0012] S4. Collect the second insulation detection parameters of the motor, the second machine room environmental parameters of the synchronous condenser, and the second aging parameters, and process them to obtain the second auxiliary adjustment features;

[0013] S5. Input the processed second auxiliary adjustment features into the camera condenser auxiliary detection model to obtain the second control method for the camera condenser. Use the second control method to assist and control the changes in the camera condenser's operating parameters. ， Adjusting the operating parameters of the synchronous condenser assists in online uninterrupted power-off testing of motor insulation.

[0014] Furthermore, the first insulation detection parameter is obtained by processing the first insulation resistance, first voltage, first leakage current, first dielectric loss factor of the motor and the first temperature parameter of the motor.

[0015] The second insulation detection parameter is obtained by processing the second insulation resistance, second voltage, second leakage current, second dielectric loss factor of the motor and the second temperature parameter of the motor.

[0016] Furthermore, the first computer room environmental parameters include the first ambient temperature, first humidity, and first wind speed of the computer room where the synchronous condenser is located;

[0017] The second environmental parameters of the computer room include the second ambient temperature, second humidity, and second wind speed of the computer room where the synchronous condenser is located.

[0018] Furthermore, the first aging parameter is obtained by processing the maximum temperature data of the first rotor of the synchronous condenser, the first maximum vibration frequency at the stator winding end, and the first insulation resistance value of the synchronous condenser.

[0019] The second aging parameter is obtained by processing the maximum temperature data of the second rotor of the synchronous condenser, the second maximum vibration frequency of the stator winding end, and the second insulation resistance value of the synchronous condenser.

[0020] Furthermore, the synchronous condenser-assisted detection model includes a classifier based on the Fisher criterion, a support vector machine improved based on motor insulation detection parameters and synchronous condenser aging parameters, and a neural network model.

[0021] Furthermore, the first auxiliary adjustment feature is obtained by concatenating the first insulation detection parameters of the motor, the first machine room environment parameters of the synchronous condenser, and the first aging parameter vector; the second auxiliary adjustment feature is obtained by concatenating the second insulation detection parameters of the motor, the second machine room environment parameters of the synchronous condenser, and the second aging parameter vector.

[0022] A synchronous condenser-assisted online uninterrupted power-off detection system for motor insulation is also provided, comprising a motor insulation online monitoring module, a synchronous condenser ambient sampling module, a synchronous condenser insulation aging module, a synchronous condenser auxiliary adjustment feature processing module, a synchronous condenser auxiliary detection model construction module, and a synchronous condenser control and management module, characterized in that:

[0023] The online insulation monitoring module for the electric motor is used to collect the first insulation detection parameter and the second insulation detection parameter of the electric motor.

[0024] The synchronous condenser ring acquisition module is connected to the Internet and used to collect environmental parameters of the first and second computer rooms of the synchronous condenser room.

[0025] The synchronous condenser insulation aging module is used to collect the first aging parameter and the second aging parameter of the synchronous condenser.

[0026] The synchronous condenser auxiliary adjustment feature processing module: receives the first insulation detection parameters of the motor, the first machine room environment parameters of the synchronous condenser, and the first aging parameter feature processing to obtain a first auxiliary adjustment feature; and is also used to receive the second insulation detection parameters of the motor, the second machine room environment parameters of the synchronous condenser, and the second aging parameter feature processing to obtain a second auxiliary adjustment feature.

[0027] The synchronous condenser auxiliary detection model construction module: receives the first auxiliary adjustment feature transmitted by the synchronous condenser auxiliary adjustment feature processing module and the first control method of the synchronous condenser stored by the synchronous condenser control management module, and constructs a synchronous condenser auxiliary detection model based on the first auxiliary adjustment feature and the first control method of the synchronous condenser.

[0028] The synchronous condenser control and management module stores the first control method of the synchronous condenser, receives the second auxiliary adjustment feature from the synchronous condenser auxiliary adjustment feature processing module, and calls the synchronous condenser auxiliary detection model to process the second auxiliary adjustment feature to obtain the second control method of the synchronous condenser. Based on the second control method of the synchronous condenser, it assists in and controls the changes in the working parameters of the synchronous condenser.

[0029] Furthermore, the synchronous condenser-assisted detection model includes a classifier based on the Fisher criterion, a support vector machine improved based on motor insulation detection parameters and synchronous condenser aging parameters, and a neural network model.

[0030] This invention firstly involves characterizing the data from the synchronous condenser during online uninterrupted power-on testing of motor insulation, enabling automated continuous control and flexible adjustment of the synchronous condenser to assist in testing. Secondly, it establishes auxiliary testing models for the synchronous condenser under different online uninterrupted power-on testing environments for motor insulation, fully utilizing big data intelligent control algorithms for precise synchronous condenser control to achieve accurate online uninterrupted power-on testing of motor insulation under variable synchronous condenser parameter adjustment. Through effective processing of relevant synchronous condenser parameter data and the construction of an improved support vector machine based on motor insulation testing parameters and synchronous condenser aging parameters, modifications have been made to the traditional machine learning model to improve the accuracy of insulation monitoring. This not only significantly reduces manual inspection and correction time but also improves the accuracy of online motor insulation monitoring.

[0031] Further embodiments and improvements of the present invention will be described in conjunction with the accompanying drawings and specific examples. Attached Figure Description

[0032] Figure 1 This is a flowchart of an online uninterrupted power-off detection method for the insulation of a synchronous condenser auxiliary motor according to the present invention;

[0033] Figure 2 This is a schematic diagram of an online uninterrupted power detection system for the insulation of a synchronous condenser auxiliary motor according to the present invention;

[0034] Figure 3 This is a schematic diagram of the distribution of the synchronous condenser in the power grid in this invention;

[0035] Figure 4 This is a schematic diagram of the support vector machine in this invention;

[0036] Figure 5 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0037] The invention will now be further described in conjunction with the accompanying drawings and specific embodiments.

[0038] In a first aspect, this invention provides a method and system for online uninterrupted power detection of insulation of a synchronous condenser-assisted motor. In this embodiment, the synchronous condensers are distributed in the power grid as follows: Figure 3 As shown.

[0039] In a first aspect of the invention, a method for online uninterrupted power-free insulation detection of a synchronous condenser auxiliary motor is provided, as shown in the appendix. Figure 1 As shown, the method includes:

[0040] S1. Obtain the first insulation detection parameters of the motor, the first room environment parameters and the first aging parameters of the synchronous condenser, and obtain the first control method of the corresponding synchronous condenser;

[0041] S2. The first insulation detection parameters of the electric motor, the first machine room environment parameters of the synchronous condenser, and the first aging parameters are processed to obtain the first auxiliary adjustment feature;

[0042] S3. Construct an auxiliary detection model for the camera adjustment device based on the first auxiliary adjustment feature and the corresponding first control method of the camera adjustment device;

[0043] S4. Collect the second insulation detection parameters of the motor, the second room environment parameters and the second aging parameters of the synchronous condenser, and process them to obtain the second auxiliary adjustment features;

[0044] S5. Input the processed second auxiliary adjustment feature into the synchronous condenser auxiliary detection model to obtain the second control method of the synchronous condenser. According to the second control method, assist and control the change of the synchronous condenser's working parameters, assist the online uninterrupted detection of motor insulation, and adjust the motor insulation detection parameters detected subsequently.

[0045] In this embodiment, calculations are performed based on the influence of the motor insulation parameters on the working parameters of the synchronous condenser, so that the feature vector input to the model can be used for adaptive feature selection.

[0046] Furthermore, the first insulation detection parameter of the motor is obtained by processing the first insulation resistance, first voltage, first leakage current, first dielectric loss factor and the first temperature parameter of the motor.

[0047] The second insulation detection parameter is obtained by processing the second insulation resistance, second voltage, second leakage current, second dielectric loss factor of the motor, and the second temperature parameter of the motor. The processing formula is as follows:

[0048]

[0049] In the formula P im The first insulation detection parameter or the second insulation detection parameter of the motor is δ, which is the first dielectric loss factor or the second dielectric loss factor, and is less than 0.5. m I represents the first or second temperature parameter of the motor. c The first or second leakage current is a tiny current in the motor insulation layer; U is the first or second operating voltage of the motor; R i It is the first or second insulation resistance of the motor winding to ground.

[0050] Furthermore, the first environmental parameters of the camera adjustment room include the first ambient temperature, first humidity, and first wind speed of the camera adjustment room.

[0051] The second environmental parameters of the computer room include the second ambient temperature, second humidity, and second wind speed of the computer room where the synchronous condenser is located.

[0052] In this embodiment, calculations are performed based on the impact of the camera aging parameters on the camera operating parameters, so that the feature vector input to the model can be used for adaptive feature selection.

[0053] Furthermore, the first aging parameter is obtained by processing the maximum temperature data of the first rotor of the synchronous condenser, the first maximum vibration frequency at the stator winding end, and the first insulation resistance value of the synchronous condenser.

[0054] The second aging parameter is obtained by processing the maximum temperature data of the second rotor of the synchronous condenser, the second maximum vibration frequency of the stator winding end, and the second insulation resistance value of the synchronous condenser.

[0055] The processing formula is:

[0056]

[0057] In the formula P am To adjust the first aging parameter or the second aging parameter of the camera, R mt To adjust the maximum temperature data of the first or second rotor of the camera, S mv R is the first or second maximum vibration frequency at the stator winding end. sc To adjust the value of the first insulation resistance or the second insulation resistance of the camera.

[0058] Furthermore, the synchronous condenser-assisted detection model includes a classifier based on the Fisher criterion, a support vector machine improved based on motor insulation detection parameters and synchronous condenser aging parameters, and a neural network model.

[0059] Furthermore, the calculation formula for the support vector machine improved based on motor insulation detection parameters and phase shifter aging parameters is as follows:

[0060]

[0061] Where ω and b are the normal vector and intercept of the hyperplane, respectively, and S c For either the first auxiliary adjustment feature or the second auxiliary adjustment feature, P am To adjust the first aging parameter or the second aging parameter of the camera, P im For the first insulation detection parameter or the second insulation detection parameter of the motor, P(S) c () refers to the first control method or the second control method for adjusting the camera.

[0062] Furthermore, S c The vector splicing is obtained by combining the motor insulation detection parameters, the synchronous condenser room environmental parameters, and the synchronous condenser aging parameters. The splicing can be divided into horizontal splicing and vertical splicing. In this embodiment, the vector feature combination method of horizontal splicing is adopted.

[0063] A synchronous condenser-assisted motor insulation online uninterrupted power detection system is also provided, as shown in the attached figure. Figure 2 As shown, it includes an online monitoring module for motor insulation, a synchronous condenser ambient sampling module, a synchronous condenser insulation aging module, a synchronous condenser auxiliary adjustment feature processing module, a synchronous condenser auxiliary detection model construction module, and a synchronous condenser control and management module, characterized in that:

[0064] The online insulation monitoring module for the electric motor is used to collect the first insulation detection parameter and the second insulation detection parameter of the electric motor.

[0065] The synchronous condenser ring acquisition module is connected to the Internet and used to collect environmental parameters of the first and second computer rooms of the synchronous condenser room.

[0066] The synchronous condenser insulation aging module is used to collect the first aging parameter and the second aging parameter of the synchronous condenser.

[0067] The synchronous condenser auxiliary adjustment feature processing module: receives the first insulation detection parameters of the motor, the first machine room environment parameters of the synchronous condenser, and the first aging parameter feature processing to obtain a first auxiliary adjustment feature; and is also used to receive the second insulation detection parameters of the motor, the second machine room environment parameters of the synchronous condenser, and the second aging parameter feature processing to obtain a second auxiliary adjustment feature.

[0068] The synchronous condenser auxiliary detection model construction module: receives the first auxiliary adjustment feature transmitted by the synchronous condenser auxiliary adjustment feature processing module and the first control method of the synchronous condenser stored by the synchronous condenser control management module, and constructs a synchronous condenser auxiliary detection model based on the first auxiliary adjustment feature and the first control method of the synchronous condenser.

[0069] The synchronous condenser control and management module stores the first control method of the synchronous condenser, receives the second auxiliary adjustment feature from the synchronous condenser auxiliary adjustment feature processing module, and calls the synchronous condenser auxiliary detection model to process the second auxiliary adjustment feature to obtain the second control method of the synchronous condenser. Based on the second control method of the synchronous condenser, it assists in and controls the changes in the working parameters of the synchronous condenser.

[0070] Furthermore, the synchronous condenser-assisted detection model includes a classifier based on the Fisher criterion, a support vector machine improved based on motor insulation detection parameters and synchronous condenser aging parameters, and a neural network model. The principle of the support vector machine model in this embodiment is described in Appendix [reference needed]. Figure 4 As shown.

[0071] Furthermore, the calculation formula for the support vector machine improved based on motor insulation detection parameters and phase shifter aging parameters is as follows:

[0072]

[0073] Where ω and b are the normal vector and intercept of the hyperplane, respectively, and S c For either the first auxiliary adjustment feature or the second auxiliary adjustment feature, P am To adjust the first aging parameter or the second aging parameter of the camera, P im For the first insulation detection parameter or the second insulation detection parameter of the motor, P(S) c () refers to the first control method or the second control method for adjusting the camera.

[0074] In this embodiment, according to P(S) c The value of P(S) is used to set the synchronous condenser control method. The settings for the synchronous condenser parameters in the synchronous condenser control method include the synchronous condenser's rotational speed, excitation current, and power factor. c If the value of P(S) is less than 0, the rotation speed of the camera is set to 3000 rpm, the excitation current to 300A, and the power factor to 0.89. c If the value of ) is equal to 0 or greater than 0, then those skilled in the art shall set the corresponding speed, excitation current and power factor of the synchronous condenser, which will not be elaborated here.

[0075] This invention firstly involves characterizing the data from the synchronous condenser during online uninterrupted power-on testing of motor insulation, enabling automated continuous control and flexible adjustment of the synchronous condenser to assist in testing. Secondly, it establishes auxiliary testing models for the synchronous condenser under different online uninterrupted power-on testing environments for motor insulation, fully utilizing big data intelligent control algorithms for precise synchronous condenser control to achieve accurate online uninterrupted power-on testing of motor insulation under variable synchronous condenser parameter adjustment. Through effective processing of relevant synchronous condenser parameter data and the construction of an improved support vector machine based on motor insulation testing parameters and synchronous condenser aging parameters, modifications have been made to the traditional machine learning model to improve the accuracy of insulation monitoring. This not only significantly reduces manual inspection and correction time but also improves the accuracy of online motor insulation monitoring.

[0076] Of course, it is understood that each embodiment of the present invention can achieve one of the effects on its own, and the combination of multiple embodiments of the present invention can achieve all the above effects. However, it is not required that each embodiment of the present invention achieve all the above advantages and effects, because each embodiment of the present invention can constitute a separate technical solution and make one or more contributions to the prior art.

[0077] For any module structures not specifically defined in this invention, the existing technical specifications shall prevail. The existing technical specifications mentioned in the foregoing background and specific embodiments sections are considered part of this invention and are used to understand the meaning of certain technical features or parameters. The scope of protection of this invention is determined by the actual contents of the claims.

Claims

1. An on-line detection method of insulation of an auxiliary motor of a phase modifier, characterized in that, The method comprises: S1. Obtain a first insulation detection parameter of the motor, a first machine room environment parameter and a first aging parameter of the phase modifier, and obtain a first control method of the phase modifier; S2. Process the first insulation detection parameter of the motor, the first machine room environment parameter and the first aging parameter of the phase modifier to obtain a first auxiliary adjustment feature; S3. Construct a phase modifier auxiliary detection model according to the first auxiliary adjustment feature and the first control method of the corresponding phase modifier; S4. Collect a second insulation detection parameter of the motor, a second machine room environment parameter and a second aging parameter of the phase modifier, and process to obtain a second auxiliary adjustment feature; S5. Input the processed second auxiliary adjustment feature into the phase modifier auxiliary detection model to obtain a second control method of the phase modifier, assist and control the change of the working parameter of the phase modifier according to the second control method, and assist the motor insulation online non-stop detection by adjusting the working parameter of the phase modifier; The first insulation detection parameter is obtained by processing the first insulation resistance, the first voltage, the first leakage current, the first dielectric loss factor and the first temperature parameter of the motor; The second insulation detection parameter is obtained by processing the second insulation resistance, the second voltage, the second leakage current, the second dielectric loss factor and the second temperature parameter of the motor, and the processing formula is: ； wherein said first insulation detection parameter or said second insulation detection parameter is a temperature of the electric motor, said first or second dielectric loss factor is less than 0.5, said first or second temperature parameter is a temperature of the electric motor, said first or second micro-current is a leakage current of an insulation layer of the electric motor, said first or second operating voltage is a voltage of the electric motor, said first or second insulation resistance is an insulation resistance of a winding of the electric motor to ground. The first aging parameter is obtained by processing the first rotor maximum temperature data, the first maximum vibration frequency of the stator winding end and the first insulation resistance value of the phase modifier; The second aging parameter is obtained by processing the second rotor maximum temperature data, the second maximum vibration frequency of the stator winding end and the second insulation resistance value of the phase modifier, and the processing formula is: ； wherein is the first or second aging parameter of the phase modifier, is the first or second rotor maximum temperature data of the phase modifier, is the first or second maximum vibration frequency of the stator winding end, is the first or second insulation resistance value of the phase modifier.

2. The method of claim 1, wherein: The first machine room environment parameter comprises the first environment temperature, the first humidity and the first wind speed of the machine room where the phase modifier is located; The second machine room environment parameter comprises the second environment temperature, the second humidity and the second wind speed of the machine room where the phase modifier is located.

3. The method of claim 1, wherein: The phase modifier auxiliary detection model comprises a classifier based on Fisher criterion, a support vector machine improved based on the motor insulation detection parameter and the phase modifier aging parameter, and a neural network model, and the calculation formula of the support vector machine improved based on the motor insulation detection parameter and the phase modifier aging parameter is as follows: ； where ω b are the normal vector and the intercept of the hyperplane, respectively, is the first or second auxiliary adjustment feature, is the first or second aging parameter of the phase modifier, is the first or second insulation detection parameter of the electric motor, is the first or second control method of the phase modifier.

4. The method of claim 3, wherein: The first auxiliary adjustment feature is obtained by splicing the first insulation detection parameter of the motor, the first machine room environment parameter of the phase modifier, and the first aging parameter vector, The second auxiliary adjustment feature is obtained by splicing the second insulation detection parameter of the motor, the second machine room environment parameter of the phase modifier, and the second aging parameter vector.

5. A phase modifier auxiliary motor insulation online non-stop detection system, which realizes the method of any one of claims 1-4, and comprises a motor insulation online monitoring module, a phase modifier ring sampling module, a phase modifier insulation aging module, a phase modifier auxiliary adjustment feature processing module, a phase modifier auxiliary detection model construction module and a phase modifier control management module, wherein: The motor insulation online monitoring module is used for collecting the first insulation detection parameter and the second insulation detection parameter of the motor. The phase modifier ring acquisition module is connected with the Internet to acquire the first and second machine room environment parameters of the phase modifier machine room. The phase modifier insulation aging module is configured to acquire the first and second aging parameters of the phase modifier. The phase modifier auxiliary adjustment feature processing module is configured to receive the first insulation detection parameter of the motor, the first machine room environment parameter of the phase modifier and the first aging parameter to obtain a first auxiliary adjustment feature, and to receive the second insulation detection parameter of the motor, the second machine room environment parameter of the phase modifier and the second aging parameter to obtain a second auxiliary adjustment feature. The phase modifier auxiliary detection model construction module is configured to receive the first auxiliary adjustment feature transmitted by the phase modifier auxiliary adjustment feature processing module and the first control method of the phase modifier stored by the phase modifier control management module, and to construct a phase modifier auxiliary detection model according to the first auxiliary adjustment feature and the first control method of the phase modifier. The phase modifier control management module is configured to store the first control method of the phase modifier, to receive the second auxiliary adjustment feature of the phase modifier auxiliary adjustment feature processing module, to process the second auxiliary adjustment feature by calling the phase modifier auxiliary detection model to obtain a second control method of the phase modifier, and to assist and control the change of the working parameter of the phase modifier according to the second control method of the phase modifier.

6. The phase modifier auxiliary motor insulation online non-power-off detection system of claim 5, wherein: The phase modifier auxiliary detection model comprises a classifier based on Fisher criterion, a support vector machine improved based on motor insulation detection parameters and phase modifier aging parameters, and a neural network model, and the calculation formula of the support vector machine improved based on motor insulation detection parameters and phase modifier aging parameters is as follows: ； where ω b are respectively the normal vector and the intercept of the hyperplane, is the first or the second auxiliary adjustment feature, is the first or the second aging parameter of the phase modifier, is the first or the second insulation detection parameter of the electric motor, is the first or the second control method of the phase modifier.

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