Fault identification and adaptive protection method for magnetic suspension high-speed permanent magnet synchronous motor

Abstract

The application discloses a magnetic suspension high-speed permanent magnet synchronous motor fault recognition and self-adaptive protection method and relates to the technical field of motor fault recognition, which comprises the following steps: constructing a full-rank reference variable model; collecting electrical parameters of the magnetic suspension high-speed permanent magnet synchronous motor; identifying the motor parameters of the magnetic suspension high-speed permanent magnet synchronous motor through the full-rank reference variable model to obtain real-time motor parameters of the magnetic suspension high-speed permanent magnet synchronous motor; compensating based on a magnetic suspension bearing control adjustment algorithm to offset the control error of the magnetic suspension bearing caused by the motor parameter change; and regulating and controlling the bearing-rotor dynamics system of the magnetic suspension high-speed permanent magnet synchronous motor based on the compensated control parameters. The application has the advantages that the motor stator resistance, inductance and rotor permanent magnet flux linkage amplitude and other parameter values can be accurately identified, the magnetic suspension bearing controller algorithm compensation can be realized, and the control difficulty of the magnetic suspension bearing is reduced.

Description

Technical Field

[0001] This invention relates to the field of motor fault identification technology, specifically to a fault identification and adaptive protection method for a magnetic levitation high-speed permanent magnet synchronous motor. Background Technology

[0002] Magnetic levitation bearings are a new type of high-performance bearing with no mechanical contact between the rotor and stator. They offer advantages such as high speed, high precision, low power consumption, low noise, long lifespan, no lubrication required, and no oil pollution. However, with product upgrades, the requirements for the overall stability and safety of motor operation are becoming increasingly stringent. As temperature, load, and magnetic saturation levels change, the stator resistance, inductance, and rotor permanent magnet flux linkage amplitude of a magnetic levitation permanent magnet synchronous motor will deviate from their design values ​​at room temperature. For the stator windings, increased temperature leads to increased resistance and reduced efficiency; for the rotor permanent magnet, increased temperature causes a decrease in the rotor permanent magnet flux linkage amplitude, potentially resulting in high-temperature demagnetization. When the actual parameters of the motor differ significantly from their design parameters at room temperature, it can severely impact the performance of the designed control system, even rendering it inoperable. Summary of the Invention

[0003] To address the aforementioned technical issues, a fault identification and adaptive protection method for a high-speed permanent magnet synchronous motor with magnetic levitation is provided. The purpose of this technical solution is to overcome the problems caused by significant parameter changes due to motor temperature rise, which affect the performance of the control system and increase the difficulty of controlling the magnetic levitation bearing.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0005] A fault identification and adaptive protection method for a magnetically levitated high-speed permanent magnet synchronous motor includes:

[0006] Construct a full-rank reference variable model;

[0007] The electrical parameters of the magnetically levitated high-speed permanent magnet synchronous motor are collected. The electrical parameters include the abc three-phase voltage, abc three-phase current, quadrature axis voltage, quadrature axis current, direct axis voltage, and direct axis current.

[0008] Based on the electrical parameters of the magnetic levitation high-speed permanent magnet synchronous motor, the motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor are identified through a full-rank reference variable model to obtain the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor. The motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor include: quadrature axis inductance, direct axis inductance, stator winding resistance and rotor permanent magnet flux linkage amplitude.

[0009] Based on the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor, the control adjustment algorithm of the magnetic levitation bearing is used to compensate for the control error of the magnetic levitation bearing caused by the change of motor parameters.

[0010] The bearing-rotor dynamics system of a magnetically levitated high-speed permanent magnet synchronous motor is controlled based on the compensated control parameters.

[0011] Preferably, the construction of the full-rank reference variable model specifically includes:

[0012] Construct the state equations of a magnetically levitated high-speed permanent magnet synchronous motor in the stator three-phase coordinate system;

[0013] Construct the state equations of a magnetically levitated high-speed permanent magnet synchronous motor in a rotating coordinate system of quadrature and direct axes under steady-state conditions;

[0014] A reference adaptive system is designed using Popov's superstability theory to make the motor parameters of a magnetically levitated high-speed permanent magnet synchronous motor converge to the true values ​​of the motor parameters.

[0015] The state equation in the stator three-phase coordinate system is:

[0016] Where, in the formula, The three-phase voltage (abc) of the magnetic levitation high-speed permanent magnet synchronous motor is... For the three-phase current of the magnetic levitation high-speed permanent magnet synchronous motor (a, b, c), For electrical angular velocity, R is the rotor position angle of the motor, and R is the stator winding resistance. For self-perception; For mutual induction, This represents the amplitude of the rotor permanent magnet flux linkage;

[0017] The state equation in the rotating coordinate system of the perpendicular-axis rotor is:

[0018] In the formula, The k-th sampled direct-axis stator voltage, The kth sampled direct-axis stator current, The quadrature-axis stator voltage of the kth sample. The quadrature-axis stator current of the kth sample, It is a direct-axis stator inductor. For quadrature axis stator inductance, The electrical angular velocity of the kth sample.

[0019] Preferably, the reference adaptive system designed using Popov ultrastability theory to converge the motor parameters of the magnetically levitated high-speed permanent magnet synchronous motor to the true values ​​of the motor parameters specifically includes:

[0020] The reference adaptive system is equivalent to a multivariable nonlinear time-varying feedback system;

[0021] The multivariable nonlinear time-varying feedback system includes a forward linear time-invariant module and a nonlinear time-varying feedback module. The forward linear time-invariant module is as follows:

[0022] in, e To compare the error, Let e ​​be the first derivative of e, and Y be the output vector. , , , For direct-axis stator current, For quadrature-axis stator current, For the estimated value of the direct-axis stator current, This is an estimated value for the quadrature-axis stator current. , , It is a direct-axis stator inductor. R is the quadrature-axis stator inductance, and R is the stator winding resistance. For electrical angular velocity, , , , This is an estimated value for the direct-axis stator inductance. This is an estimated value for the quadrature-axis stator inductance. This is an estimated value for the stator winding resistance. For electrical angular velocity, , , Direct-axis stator voltage, Quadrature-axis stator voltage, , This is an estimated value for the amplitude of the rotor permanent magnet flux linkage. , D It is a linear compensation matrix;

[0023] Make the nonlinear time-varying feedback module satisfy the Popov inequality;

[0024] Right now The first inequality is obtained by decomposing the equations:

[0025] in, ;

[0026] The first inequality can be transformed to obtain the second inequality, which is:

[0027] The gain is 1 for nonlinear feedback. The gain 2 is the nonlinear feedback. The gain is 3 for nonlinear feedback;

[0028] The second inequality is decomposed into a third set of inequalities, which are as follows:

[0029] ;

[0030] Based on the third set of inequalities, the adaptive law of the reference adaptive system can be obtained as follows:

[0031] in, The proportional gain is 1. The proportional gain is 2.

[0032] Preferably, the magnetic levitation bearing control adjustment algorithm is as follows:

[0033] To obtain the normal range of motor parameters during the operation of a magnetic levitation high-speed permanent magnet synchronous motor;

[0034] Within the normal range of motor parameter variation, several sets of motor parameter sample groups are generated using a grid search method;

[0035] The optimal control parameters for each group of motor parameter samples are determined based on control experiments.

[0036] Establish a one-to-one mapping relationship between the motor parameter sample group and the corresponding optimal control adjustment parameter, and combine all motor parameter sample groups and the optimal control adjustment parameter group into a magnetic levitation bearing control adjustment database.

[0037] The real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor are retrieved and matched in the magnetic levitation bearing control and adjustment database to obtain the controller control and adjustment parameters corresponding to the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor.

[0038] Preferably, the step of searching and matching the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor in the magnetic levitation bearing control and adjustment database to obtain the controller adjustment parameters corresponding to the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor specifically includes:

[0039] The first motor parameter sample group is defined as the motor parameter sample group in the magnetic bearing control and adjustment database where any motor parameter is greater than the real-time motor parameter of the magnetic levitation high-speed permanent magnet synchronous motor and the comprehensive distance between the motor parameter sample group and the real-time motor parameter of the magnetic levitation high-speed permanent magnet synchronous motor is closest.

[0040] The second motor parameter sample group is defined as the motor parameter sample group in the magnetic bearing control and adjustment database where any motor parameter is less than the real-time motor parameter of the magnetic levitation high-speed permanent magnet synchronous motor and the comprehensive distance between the two is closest.

[0041] Based on the first set of motor parameter samples and the second set of motor parameter samples, the controller adjustment parameters are determined by adjusting the fitting formula.

[0042] The formula for calculating the comprehensive distance is:

[0043] In the formula, S is the composite distance. The resistance value is from the motor parameter sample group. The quadrature-axis inductance in the motor parameter sample set. For the direct-axis inductance in the motor parameter sample set, This refers to the rotor permanent magnet flux linkage amplitude in the motor parameter sample group.

[0044] Preferably, the regulation fitting formula is as follows:

[0045] In the formula, K is the controller adjustment parameter. These are the optimal control parameters corresponding to the second set of motor parameter samples. These are the optimal control parameters corresponding to the first set of motor parameter samples. This represents the combined distance between the second set of motor parameter samples and the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor. The comprehensive distance between the first set of motor parameter samples and the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor;

[0046] The controller's adjustment parameters include at least: proportional adjustment coefficient, integral time constant, derivative coefficient, and integral coefficient.

[0047] Preferably, the bearing-rotor dynamics system of the magnetically levitated high-speed permanent magnet synchronous motor, which is controlled based on the compensated control parameters, specifically includes:

[0048] The high-speed data acquisition and processing module acquires and processes the electromagnet-rotor gap, electromagnet current, and rotor speed output from the sensors in the magnetic levitation bearing.

[0049] The low-speed data acquisition and processing module acquires and processes the input current, input voltage, inter-board temperature, power amplifier capacitor voltage, electromagnet temperature, charging and discharging status feedback signal, driver IC status feedback signal, and main and auxiliary relay status signals in the power amplifier of the magnetic levitation bearing.

[0050] The fault diagnosis and protection module acquires the data output from the high-speed data acquisition and processing module and the low-speed data acquisition and processing module, performs fault diagnosis, outputs fault diagnosis signals and fault protection signals, and provides fault protection for the magnetic levitation bearing.

[0051] The data communication module sends fault diagnosis signals and fault protection signals to the debugging software. The debugging software then stores and analyzes the data to achieve real-time monitoring and debugging of the magnetic levitation bearing.

[0052] The levitation control calculation module outputs control signals to control the levitation of the magnetic levitation bearing when the fault protection is not triggered.

[0053] The control signals include a gap loop control algorithm and a current loop control algorithm;

[0054] The gap loop control algorithm includes:

[0055] In the formula, The total desired control current is output for the gap loop. To control the desired control current required to keep the spindle suspended at the X-axis rotation center, To control the desired control current required to keep the spindle suspended at the Y-axis rotation center, For bias current, K p K is the proportional adjustment coefficient. d K is the differential coefficient. i The integral coefficient;

[0056] The current loop control algorithm is as follows:

[0057] In the formula, This is the output duty cycle value. Zero-position current, To detect the actual current, K c is the integration time constant.

[0058] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0059] A system for fault identification and adaptive protection algorithms of magnetic levitation bearings and motors is established. By identifying motor parameters, the detected changing values ​​of parameters such as stator resistance, inductance, and rotor permanent magnet flux linkage amplitude of the permanent magnet synchronous motor are transmitted to the magnetic levitation bearing controller via a frequency converter. The magnetic levitation bearing controller uses algorithm compensation to offset the impact of motor parameter changes on the magnetic levitation bearing. This scheme can obtain a set of full-rank reference variable models and simultaneously identify multiple parameter values ​​such as stator resistance, inductance, and rotor permanent magnet flux linkage amplitude. This enables algorithm compensation by the magnetic levitation bearing controller to offset the impact of motor parameter changes on the magnetic levitation bearing, thereby reducing the control difficulty of the magnetic levitation bearing. Attached Figure Description

[0060] Figure 1 This is a flowchart of the fault identification and adaptive protection method for high-speed permanent magnet synchronous motors with magnetic levitation proposed in this scheme;

[0061] Figure 2 This is a block diagram of the magnetic levitation high-speed permanent magnet synchronous motor control system in this scheme;

[0062] Figure 3 This is a flowchart of the magnetic levitation bearing control and adjustment algorithm in this scheme;

[0063] Figure 4 This is a flowchart of the method for obtaining the controller adjustment parameters corresponding to the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor in this scheme.

[0064] Figure 5 The flowchart shows the method for regulating the bearing-rotor dynamics system of a magnetically levitated high-speed permanent magnet synchronous motor based on compensated control parameters in this scheme.

[0065] Figure 6 This is a block diagram of the controller intelligent system in this solution;

[0066] Figure 7 This is a schematic diagram of the electronic device structure of the present invention;

[0067] Figure 8 This is a schematic diagram of the computer-readable storage medium structure of the present invention. Detailed Implementation

[0068] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0069] Reference Figure 1 As shown, a fault identification and adaptive protection method for a magnetic levitation high-speed permanent magnet synchronous motor includes:

[0070] Construct a full-rank reference variable model;

[0071] The electrical parameters of the magnetically levitated high-speed permanent magnet synchronous motor are collected, including the three-phase voltage (abc), three-phase current (abc), quadrature-axis voltage, quadrature-axis current, direct-axis voltage, and direct-axis current.

[0072] Based on the electrical parameters of the magnetic levitation high-speed permanent magnet synchronous motor, the motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor are identified through a full-rank reference variable model to obtain the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor. The motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor include: quadrature axis inductance, direct axis inductance, stator winding resistance and rotor permanent magnet flux linkage amplitude.

[0073] Based on the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor, the control adjustment algorithm of the magnetic levitation bearing is used to compensate for the control error of the magnetic levitation bearing caused by the change of motor parameters.

[0074] The bearing-rotor dynamics system of a magnetically levitated high-speed permanent magnet synchronous motor is controlled based on the compensated control parameters.

[0075] This solution establishes a system for fault identification and adaptive protection algorithms for magnetic levitation bearings and motors. By identifying motor parameters, the detected changes in parameters such as stator resistance, inductance, and rotor permanent magnet flux linkage amplitude of the permanent magnet synchronous motor are transmitted to the magnetic levitation bearing controller via a frequency converter. The magnetic levitation bearing controller uses algorithm compensation to offset the impact of changes in motor parameters on the magnetic levitation bearing.

[0076] Reference Figure 2 As shown, the magnetic levitation high-speed permanent magnet synchronous motor using the above method includes two parts: the stator and rotor of the permanent magnet synchronous motor and the stator and rotor of the magnetic levitation bearing. The permanent magnet synchronous motor frequency converter and the magnetic levitation bearing controller together constitute an integrated magnetic levitation high-speed permanent magnet synchronous motor control system. The permanent magnet synchronous motor frequency converter and the magnetic levitation bearing controller communicate bidirectionally. The frequency converter provides the necessary operating power to the controller and has built-in power failure protection. When the system power supply fails, this function can ensure the bus voltage while enabling the high-speed motor to decelerate and stop quickly, thereby allowing the bearing to quickly reach the safe speed range and avoiding damage caused by high-speed bearing loss of float. By identifying the motor parameters, the detected changes in parameters such as the stator resistance, inductance, and rotor permanent magnet flux amplitude of the permanent magnet synchronous motor are transmitted to the magnetic levitation bearing controller via the frequency converter. The magnetic levitation bearing controller uses algorithm compensation to offset the impact of changes in motor parameters on the magnetic levitation bearing.

[0077] Constructing a full-rank reference variable model specifically includes:

[0078] Construct the state equations of a magnetically levitated high-speed permanent magnet synchronous motor in the stator three-phase coordinate system;

[0079] Construct the state equations of a magnetically levitated high-speed permanent magnet synchronous motor in a rotating coordinate system of quadrature and direct axes under steady-state conditions;

[0080] A reference adaptive system is designed using Popov's superstability theory to make the motor parameters of a magnetically levitated high-speed permanent magnet synchronous motor converge to the true values ​​of the motor parameters.

[0081] The state equations of the stator in the three-phase coordinate system are:

[0082] Where, in the formula, The three-phase voltage (abc) of the magnetic levitation high-speed permanent magnet synchronous motor is... For the three-phase current of the magnetic levitation high-speed permanent magnet synchronous motor (a, b, c), For electrical angular velocity, R is the rotor position angle of the motor, and R is the stator winding resistance. For self-perception; For mutual induction, This represents the amplitude of the rotor permanent magnet flux linkage;

[0083] The state equations in the rotating coordinate system of the perpendicular and perpendicular shaft rotor are:

[0084] In the formula, The k-th sampled direct-axis stator voltage, The kth sampled direct-axis stator current, The quadrature-axis stator voltage of the kth sample. The quadrature-axis stator current of the kth sample, It is a direct-axis stator inductor. For quadrature axis stator inductance, The electrical angular velocity of the kth sample.

[0085] The reference adaptive system designed using Popov's ultrastability theory to converge the motor parameters of a magnetically levitated high-speed permanent magnet synchronous motor to their true values ​​specifically includes:

[0086] The reference adaptive system is equivalent to a multivariable nonlinear time-varying feedback system;

[0087] The multivariable nonlinear time-varying feedback system includes a forward linear time-invariant module and a nonlinear time-varying feedback module. The forward linear time-invariant module is as follows:

[0088] in, e To compare the error, Let e ​​be the first derivative of e, and Y be the output vector. , , , For direct-axis stator current, For quadrature-axis stator current, For the estimated value of the direct-axis stator current, This is an estimated value for the quadrature-axis stator current. , , It is a direct-axis stator inductor. R is the quadrature-axis stator inductance, and R is the stator winding resistance. For electrical angular velocity, , , , This is an estimated value for the direct-axis stator inductance. This is an estimated value for the quadrature-axis stator inductance. This is an estimated value for the stator winding resistance. For electrical angular velocity, , , Direct-axis stator voltage, Quadrature-axis stator voltage, , This is an estimated value for the amplitude of the rotor permanent magnet flux linkage. , D It is a linear compensation matrix;

[0089] Make the nonlinear time-varying feedback module satisfy the Popov inequality;

[0090] Right now The first inequality is obtained by decomposing the equations:

[0091] in, ;

[0092] The first inequality can be transformed to obtain the second inequality, which is:

[0093] The gain is 1 for nonlinear feedback. The gain 2 is the nonlinear feedback. The gain is 3 for nonlinear feedback;

[0094] The second inequality is decomposed into a third set of inequalities, which are as follows:

[0095] ;

[0096] Based on the third set of inequalities, the adaptive law of the reference adaptive system can be obtained as follows:

[0097] in, The proportional gain is 1. The proportional gain is 2.

[0098] The parameter identification technology for permanent magnet synchronous motors (PMSMs) using identification algorithm models and reference adaptive systems has been widely applied. However, when the identification algorithm is based on an underranked reference variable model, relying solely on a set of sampled input / output states cannot guarantee that the identification result correctly converges to the actual value. For the state equations of a PMSM, there are four parameters to be identified: the direct and quadrature axis inductances, the stator winding resistance, and the rotor permanent magnet flux linkage amplitude. The rank of the state equations is 2. Therefore, relative to these four parameters, the steady-state state equations constitute an underranked reference model.

[0099] The core of permanent magnet synchronous motor parameter identification technology is to obtain a set of full-rank reference variable models that can simultaneously identify the actual values ​​of parameters such as stator winding resistance, rotor permanent magnet flux linkage amplitude, and inductance. Therefore, in this scheme, the model reference adaptive system is designed using Popov ultra-stable theory.

[0100] Reference Figure 3 As shown, the specific control and adjustment algorithm for the magnetic levitation bearing is as follows:

[0101] To obtain the normal range of motor parameters during the operation of a magnetic levitation high-speed permanent magnet synchronous motor;

[0102] Within the normal range of motor parameter variation, several sets of motor parameter sample groups are generated using a grid search method;

[0103] The optimal control parameters for each group of motor parameter samples are determined based on control experiments.

[0104] Establish a one-to-one mapping relationship between the motor parameter sample group and the corresponding optimal control adjustment parameter, and combine all motor parameter sample groups and the optimal control adjustment parameter group into a magnetic levitation bearing control adjustment database.

[0105] The real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor are retrieved and matched in the magnetic levitation bearing control and adjustment database to obtain the controller control and adjustment parameters corresponding to the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor.

[0106] Reference Figure 4 As shown, the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor are retrieved and matched in the magnetic levitation bearing control and adjustment database to obtain the controller adjustment parameters corresponding to the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor. These parameters specifically include:

[0107] The first motor parameter sample group is defined as the motor parameter sample group in the magnetic bearing control and adjustment database where any motor parameter is greater than the real-time motor parameter of the magnetic levitation high-speed permanent magnet synchronous motor and the comprehensive distance between the motor parameter sample group and the real-time motor parameter of the magnetic levitation high-speed permanent magnet synchronous motor is closest.

[0108] The second motor parameter sample group is defined as the motor parameter sample group in the magnetic bearing control and adjustment database where any motor parameter is less than the real-time motor parameter of the magnetic levitation high-speed permanent magnet synchronous motor and the comprehensive distance between the two is closest.

[0109] Based on the first set of motor parameter samples and the second set of motor parameter samples, the controller adjustment parameters are determined by adjusting the fitting formula.

[0110] The formula for calculating the total distance is:

[0111] In the formula, S is the composite distance. The resistance value is from the motor parameter sample group. The quadrature-axis inductance in the motor parameter sample set. For the direct-axis inductance in the motor parameter sample set, This refers to the rotor permanent magnet flux linkage amplitude in the motor parameter sample group.

[0112] The specific formula for regulating the fitting is as follows:

[0113] In the formula, K is the controller adjustment parameter. These are the optimal control parameters corresponding to the second set of motor parameter samples. These are the optimal control parameters corresponding to the first set of motor parameter samples. This represents the combined distance between the second set of motor parameter samples and the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor. The comprehensive distance between the first set of motor parameter samples and the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor;

[0114] The controller's adjustment parameters include at least the proportional adjustment coefficient, integral time constant, derivative coefficient, and integral coefficient.

[0115] In this scheme, a linear fitting database is used to regulate the PID control parameters of the bearing-rotor dynamics system under different motor conditions. By constructing a magnetic levitation bearing control adjustment database and searching and matching it with the actual motor parameter states, a first motor parameter sample group and a second motor parameter sample group that are adapted to the actual motor parameter states are obtained. The controller control parameters are adjusted by linear fitting, which can realize the adjustment of controller control parameters under any motor parameter state.

[0116] Reference Figure 5 As shown, the bearing-rotor dynamics system of a magnetically levitated high-speed permanent magnet synchronous motor, controlled based on compensated control parameters, specifically includes:

[0117] The high-speed data acquisition and processing module acquires and processes the electromagnet-rotor gap, electromagnet current, and rotor speed output from the sensors in the magnetic levitation bearing.

[0118] The low-speed data acquisition and processing module acquires and processes the input current, input voltage, inter-board temperature, power amplifier capacitor voltage, electromagnet temperature, charging and discharging status feedback signal, driver IC status feedback signal, and main and auxiliary relay status signals in the power amplifier of the magnetic levitation bearing.

[0119] The fault diagnosis and protection module acquires the data output from the high-speed data acquisition and processing module and the low-speed data acquisition and processing module, performs fault diagnosis, outputs fault diagnosis signals and fault protection signals, and provides fault protection for the magnetic levitation bearing.

[0120] The data communication module sends fault diagnosis signals and fault protection signals to the debugging software. The debugging software then stores and analyzes the data to achieve real-time monitoring and debugging of the magnetic levitation bearing.

[0121] The levitation control calculation module outputs control signals to control the levitation of the magnetic levitation bearing when the fault protection is not triggered.

[0122] The control signals include gap loop control algorithm and current loop control algorithm;

[0123] The gap loop control algorithm includes:

[0124] In the formula, The total desired control current is output for the gap loop. To control the desired control current required to keep the spindle suspended at the X-axis rotation center, To control the desired control current required to keep the spindle suspended at the Y-axis rotation center, For bias current, K p K is the proportional adjustment coefficient.d K is the differential coefficient. i The integral coefficient;

[0125] The current loop control algorithm is as follows:

[0126] In the formula, This is the output duty cycle value. Zero-position current, To detect the actual current, K c is the integration time constant.

[0127] The controller is designed for a standard 5-DOF magnetic levitation bearing system. The system includes two radial bearings and one axial bearing. Each set of radial bearings needs to control the movement in two dimensions. The core of the control is to calculate based on the feedback position and current signals and then output control commands. The control commands are amplified by the switch drive circuit and input to the current driver, which in turn controls the current of the magnetic levitation bearing coil to make the bearing operate stably.

[0128] The controller intelligent system block diagram is as follows: Figure 6 As shown, the system mainly includes a gap loop, a current loop, and a feedforward circuit. When the fault diagnosis and protection module does not output a fault protection signal, the levitation control calculation module acquires the data output by the high-speed data acquisition and processing module, applies the control algorithm composed of the gap loop and the current loop to perform calculations, outputs a PWM control signal, and performs levitation control on the magnetic levitation bearing based on the PWM control signal. The system includes a high-speed data acquisition and processing module, a low-speed data acquisition and processing module, a fault diagnosis and protection module, a data communication module, and a levitation control calculation module, as well as a magnetic levitation bearing control method.

[0129] Furthermore, the method according to the embodiments of this application can also be achieved by means of... Figure 7 The architecture of the electronic device shown is used to implement this. For example... Figure 7 As shown, the electronic device 500 may include a bus 501, one or more CPUs 502, a read-only memory (ROM) 503, a random access memory (RAM) 504, a communication port 505 connected to a network, an input / output component 506, a hard disk 507, etc. The storage device in the electronic device 500, such as the ROM 503 or the hard disk 507, may store the fault identification and adaptive protection method for a magnetically levitated high-speed permanent magnet synchronous motor provided in this application. The electronic device 500 may also include a user interface 508. Of course, Figure 7 The architecture shown is merely exemplary and can be omitted as needed when implementing different devices. Figure 7 One or more components in the illustrated electronic device.

[0130] Figure 8This is a schematic diagram of a computer-readable storage medium structure provided in one embodiment of this application. Figure 8 The diagram illustrates a computer-readable storage medium 600 according to one embodiment of this application. The computer-readable storage medium 600 stores computer-readable instructions. When executed by a processor, the computer-readable instructions can perform a fault identification and adaptive protection method for a magnetically levitated high-speed permanent magnet synchronous motor according to an embodiment of this application, as described with reference to the above figures. The storage medium 600 includes, but is not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0131] In summary, the advantages of this invention are: it can accurately identify multiple parameter values ​​such as motor stator resistance, inductance, and rotor permanent magnet flux linkage amplitude; it can achieve magnetic bearing controller algorithm compensation, offsetting the impact of motor parameter changes on the magnetic bearing and reducing the control difficulty of the magnetic bearing.

[0132] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A method for fault identification and adaptive protection of a magnetically levitated high-speed permanent magnet synchronous motor, characterized in that, include: Construct the state equations of a magnetically levitated high-speed permanent magnet synchronous motor in the stator three-phase coordinate system; Construct the state equations of a magnetically levitated high-speed permanent magnet synchronous motor in a rotating coordinate system of quadrature and direct axes under steady-state conditions; A reference adaptive system is designed using Popov's superstability theory to make the motor parameters of a magnetically levitated high-speed permanent magnet synchronous motor converge to the true values ​​of the motor parameters. The electrical parameters of the magnetically levitated high-speed permanent magnet synchronous motor are collected. The electrical parameters include the abc three-phase voltage, abc three-phase current, quadrature axis voltage, quadrature axis current, direct axis voltage, and direct axis current. Based on the electrical parameters of the magnetic levitation high-speed permanent magnet synchronous motor, the motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor are identified through a full-rank reference variable model to obtain the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor. The motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor include: quadrature axis inductance, direct axis inductance, stator winding resistance and rotor permanent magnet flux linkage amplitude. Based on the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor, the control adjustment algorithm of the magnetic levitation bearing is used to compensate for the control error of the magnetic levitation bearing caused by the change of motor parameters. The bearing-rotor dynamics system of a magnetically levitated high-speed permanent magnet synchronous motor is controlled based on the compensated control parameters. The bearing-rotor dynamics system of the magnetically levitated high-speed permanent magnet synchronous motor, which is controlled based on the compensated control parameters, specifically includes: The high-speed data acquisition and processing module acquires and processes the electromagnet-rotor gap, electromagnet current, and rotor speed output from the sensors in the magnetic levitation bearing. The low-speed data acquisition and processing module acquires and processes the input current, input voltage, inter-board temperature, power amplifier capacitor voltage, electromagnet temperature, charging and discharging status feedback signal, driver IC status feedback signal, and main and auxiliary relay status signals in the power amplifier of the magnetic levitation bearing. The fault diagnosis and protection module acquires the data output from the high-speed data acquisition and processing module and the low-speed data acquisition and processing module, performs fault diagnosis, outputs fault diagnosis signals and fault protection signals, and provides fault protection for the magnetic levitation bearing. The data communication module sends fault diagnosis signals and fault protection signals to the debugging software. The debugging software then stores and analyzes the data to achieve real-time monitoring and debugging of the magnetic levitation bearing. The levitation control calculation module outputs control signals to control the levitation of the magnetic levitation bearing when the fault protection is not triggered. The control signals include a gap loop control algorithm and a current loop control algorithm; The gap loop control algorithm includes: In the formula, The total desired control current is output for the gap loop. To control the desired control current required to keep the spindle suspended at the X-axis rotation center, To control the desired control current required to keep the spindle suspended at the Y-axis rotation center, For bias current, K p K is the proportional adjustment coefficient. d K is the differential coefficient. i The integral coefficient; The current loop control algorithm is as follows: In the formula, This is the output duty cycle value. Zero-position current, To detect the actual current, K c is the integration time constant.

2. The method for fault identification and adaptive protection of a magnetically levitated high-speed permanent magnet synchronous motor according to claim 1, characterized in that, The state equation in the stator three-phase coordinate system is: Where, in the formula, The three-phase voltage (abc) of the magnetic levitation high-speed permanent magnet synchronous motor is... For the three-phase current of the magnetic levitation high-speed permanent magnet synchronous motor (a, b, c), For electrical angular velocity, R is the rotor position angle of the motor, and R is the stator winding resistance. For self-perception; For mutual induction, This represents the amplitude of the rotor permanent magnet flux linkage. The state equation in the rotating coordinate system of the perpendicular-axis rotor is: In the formula, The k-th sampled direct-axis stator voltage, The kth sampled direct-axis stator current, The quadrature-axis stator voltage of the kth sample. The quadrature-axis stator current of the kth sample, It is a direct-axis stator inductor. For quadrature axis stator inductance, The electrical angular velocity of the kth sample.

3. The method for fault identification and adaptive protection of a magnetically levitated high-speed permanent magnet synchronous motor according to claim 2, characterized in that, The reference adaptive system designed using Popov's ultrastability theory to converge the motor parameters of a magnetically levitated high-speed permanent magnet synchronous motor to their true values ​​specifically includes: The reference adaptive system is equivalent to a multivariable nonlinear time-varying feedback system; The multivariable nonlinear time-varying feedback system includes a forward linear time-invariant module and a nonlinear time-varying feedback module. The forward linear time-invariant module is as follows: in, e To compare the error, Let e ​​be the first derivative of e, and Y be the output vector. , , , For direct-axis stator current, For quadrature-axis stator current, For the estimated value of the direct-axis stator current, This is an estimated value for the quadrature-axis stator current. , , It is a direct-axis stator inductor. R is the quadrature-axis stator inductance, and R is the stator winding resistance. For electrical angular velocity, , , , This is an estimated value for the direct-axis stator inductance. This is an estimated value for the quadrature-axis stator inductance. This is an estimated value for the stator winding resistance. For electrical angular velocity, , , Direct-axis stator voltage, Quadrature-axis stator voltage, , This is an estimated value for the amplitude of the rotor permanent magnet flux linkage. , D It is a linear compensation matrix; Make the nonlinear time-varying feedback module satisfy the Popov inequality; Right now The first inequality is obtained by decomposing the equations: in, ; The first inequality can be transformed to obtain the second inequality, which is: The gain is 1 for nonlinear feedback. The gain 2 is the nonlinear feedback. The gain is 3 for nonlinear feedback; The second inequality is decomposed into a third set of inequalities, which are as follows: ; Based on the third set of inequalities, the adaptive law of the reference adaptive system can be obtained as follows: in, The proportional gain is 1. The proportional gain is 2.

4. The method for fault identification and adaptive protection of a magnetically levitated high-speed permanent magnet synchronous motor according to claim 3, characterized in that, The specific control and adjustment algorithm for the magnetic levitation bearing is as follows: To obtain the normal range of motor parameters during the operation of a magnetic levitation high-speed permanent magnet synchronous motor; Within the normal range of motor parameter variation, several sets of motor parameter sample groups are generated using a grid search method; The optimal control parameters for each group of motor parameter samples are determined based on control experiments. Establish a one-to-one mapping relationship between the motor parameter sample group and the corresponding optimal control adjustment parameter, and combine all motor parameter sample groups and the optimal control adjustment parameter group into a magnetic levitation bearing control adjustment database. The real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor are retrieved and matched in the magnetic levitation bearing control and adjustment database to obtain the controller control and adjustment parameters corresponding to the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor.

5. The method for fault identification and adaptive protection of a magnetically levitated high-speed permanent magnet synchronous motor according to claim 4, characterized in that, The step of searching and matching the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor in the magnetic levitation bearing control and adjustment database to obtain the controller adjustment parameters corresponding to the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor specifically includes: The first motor parameter sample group is defined as the motor parameter sample group in the magnetic bearing control and adjustment database where any motor parameter is greater than the real-time motor parameter of the magnetic levitation high-speed permanent magnet synchronous motor and the comprehensive distance between the motor parameter sample group and the real-time motor parameter of the magnetic levitation high-speed permanent magnet synchronous motor is closest. The second motor parameter sample group is defined as the motor parameter sample group in the magnetic bearing control and adjustment database where any motor parameter is less than the real-time motor parameter of the magnetic levitation high-speed permanent magnet synchronous motor and the comprehensive distance between the two is closest. Based on the first set of motor parameter samples and the second set of motor parameter samples, the controller adjustment parameters are determined by adjusting the fitting formula. The formula for calculating the comprehensive distance is: In the formula, S is the composite distance. The resistance value is from the motor parameter sample group. The quadrature-axis inductance in the motor parameter sample set. For the direct-axis inductance in the motor parameter sample set, This refers to the rotor permanent magnet flux linkage amplitude in the motor parameter sample group.

6. The method for fault identification and adaptive protection of a magnetically levitated high-speed permanent magnet synchronous motor according to claim 5, characterized in that, The specific formula for regulating the fitting process is as follows: In the formula, K is the controller adjustment parameter. These are the optimal control parameters corresponding to the second set of motor parameter samples. These are the optimal control parameters corresponding to the first set of motor parameter samples. This represents the combined distance between the second set of motor parameter samples and the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor. The comprehensive distance between the first set of motor parameter samples and the real-time motor parameters of the magnetic levitation high-speed permanent magnet synchronous motor; The controller's adjustment parameters include at least: proportional adjustment coefficient, integral time constant, derivative coefficient, and integral coefficient.

7. An electronic device, characterized in that, include: At least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform a fault identification and adaptive protection method for a magnetically levitated high-speed permanent magnet synchronous motor as described in any one of claims 1-6.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements a fault identification and adaptive protection method for a magnetically levitated high-speed permanent magnet synchronous motor as described in any one of claims 1-6.

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