A micron-level magnetic suspension bearing displacement sensing detection system and method

Abstract

The present invention provides a micron-level magnetic suspension bearing displacement sensing detection system and method, which relates to the technical field of magnetic suspension bearings. The system drives an eddy current sensor through an eddy current sensor driving and detection system to detect the displacement signal of a rotor to be measured; the detected rotor displacement signal is processed by an eddy current sensor signal conditioning system and then input into a DSP processor; the method collects the displacement data of the magnetic suspension bearing rotor at the current moment, determines the relationship between the ripple current output by the switch power amplifier in the magnetic suspension bearing and the rotor displacement; establishes a magnetic suspension bearing self-sensing displacement estimation algorithm to estimate the rotor displacement data, and fuses it with the collected rotor displacement data to obtain the fused and corrected rotor displacement data; adopts a Smith delay compensation algorithm to compensate for the delay caused by the self-sensing displacement estimation algorithm; and adopts an integral sliding film variable structure control algorithm to resist parameter perturbations and external interferences of the magnetic suspension bearing displacement control system.

Description

Technical Field

[0001] The present invention relates to the technical field of magnetic suspension bearings, and in particular to a micron-level magnetic suspension bearing displacement sensing detection system and method. Background Art

[0002] Magnetic bearings use electromagnetic force to suspend the rotor in the air, eliminating the friction between the rotor and the stator. Compared with traditional motors, they have the advantages of low operating noise, low energy consumption, and long maintenance cycle. They enable high-speed motors to achieve a major breakthrough in high speed and high power density. Magnetic bearings supported by magnetic bearings are currently a hot research field.

[0003] The stable suspension of the magnetic bearing motor is inseparable from the high-precision displacement information between its rotor and stator. Once there is a large deviation between the displacement information required in the control system and the actual displacement information, the magnetic bearing will lose control, resulting in the inability to stably suspend the magnetic bearing, which will seriously affect the operation of the motor. If the motor rotates at high speed, the inability of the magnetic bearing to stably suspend will cause the motor's rotor to collide with the stator inside the motor, and even cause the rotor to fly out, causing a major accident.

[0004] Since the eddy current sensors currently used in displacement detection of magnetic bearing motors have certain errors due to the influence of magnetic field and eddy current, and the sensorless technology has certain limitations when the motor starts and the speed changes. Therefore, in order to ensure the stable suspension of the magnetic bearing motor, a high-precision displacement detection solution is urgently needed, the existing eddy current sensors are improved, and new sensorless technologies are found. The displacement information of the two displacement detection technologies is effectively integrated and corrected to achieve stable operation of the magnetic bearing motor. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a micron-level magnetic bearing displacement sensing detection system and method in view of the deficiencies in the above-mentioned prior art, improve the existing eddy current sensor detection circuit, and design a sensorless displacement detection technology for magnetic bearings, and further integrate the eddy current sensor displacement data and the displacement data of the self-sensing displacement estimation algorithm on this basis, so as to effectively improve the displacement data accuracy of the magnetic bearing and enhance the stability of the magnetic bearing control system.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: on the one hand, the present invention provides a micron-level magnetic suspension bearing displacement sensing detection system, including a DSP processor, an eddy current sensor driving and detection system and an eddy current sensor signal conditioning system; the eddy current sensor driving and detection system is used to drive the eddy current sensor and detect the displacement signal of the measured rotor; the eddy current sensor signal conditioning system processes the rotor displacement signal detected by the eddy current sensor driving and detection system and inputs it into the DSP processor.

[0007] Preferably, the eddy current sensor driving and detection system comprises a driving circuit, a detection circuit and a first bias and amplification circuit of the eddy current sensor; the output end of the driving circuit is connected to the eddy current sensor coil, and is used to generate an alternating signal to drive the eddy current sensor coil to generate an alternating magnetic field, so that eddy currents are induced on the rotor to form an eddy current effect;

[0008] The detection circuit is used to extract the peak value of the AC signal output by the coil of the eddy current sensor and convert the AC signal into a DC signal; the output end of the detection circuit is connected to the first bias and amplification circuit;

[0009] The first bias and amplifier circuit is used to convert the DC signal output by the detection circuit into a DC voltage proportional to the measured rotor displacement after bias and amplification processing. The output end of the first bias and amplifier circuit is connected to the eddy current sensor signal conditioning system.

[0010] Preferably, the driving circuit is composed of a power supply VCC1, a voltage regulating circuit and a capacitor three-point oscillation circuit, wherein the power supply VCC1 is the input of the voltage regulating circuit, and the power supply VCC1 also powers the eddy current sensor probe; the voltage regulating circuit provides voltage to the base of the capacitor three-point oscillation circuit; the capacitor three-point oscillation circuit uses transistor T1 to amplify the oscillation signal, thereby generating a high-frequency stable oscillation signal to provide an excitation signal to the eddy current sensor probe to generate an eddy current phenomenon, and the output of the oscillation circuit is superimposed on the output of the voltage regulating circuit, thereby realizing the driving of the eddy current sensor.

[0011] Preferably, the capacitor three-point oscillation circuit is composed of an eddy current sensor probe equivalent inductance L1 and two capacitors C1 and C2 connected in series to form a resonant cavity. In addition, the emitter of the transistor T1 is connected to the connection between the capacitor C1 and the inductor L1, the collector of the transistor is connected to the connection between the capacitors C1 and C2, and the base of the transistor T1 is connected to the output end of the voltage regulation circuit.

[0012] Preferably, the detection circuit is composed of a first detection diode D1, a capacitor C3, a resistor R1, a resistor R2, and a second detection diode D2. The anode of the first detection diode D1 is connected to the output end of the capacitor three-point oscillation circuit, and the cathode is connected to the capacitor C3 and one end of the resistor R1. The other end of the capacitor C3 is connected to the positive electrode of the power supply VCC1 in the drive circuit, the other end of the resistor R1 is connected to one end of the resistor R2, the other end of the resistor R2 is connected to the anode of the second detection diode D2, and the cathode of the second detection diode D2 is grounded; wherein, the power supply VCC1 in the drive circuit, the first detection diode D1 and the capacitor C3 constitute a charging circuit, and the resistor R1, the resistor R2 and the second detection diode D2 constitute a discharging circuit.

[0013] Preferably, the eddy current sensor signal conditioning system comprises: a differential circuit, an adjustable bias power supply VCC2, a voltage follower circuit, a second bias and amplification circuit, a low-pass filter circuit and a limiting circuit;

[0014] The differential circuit is used to remove the same nonlinear interference components in the output signals of the eddy current sensors installed at symmetrical positions on both sides of the stator of the magnetic bearing motor, and the output of the differential circuit is connected to the second bias and amplification circuit;

[0015] The voltage follower circuit is used to isolate the influence of the adjustable bias power supply VCC2 of -7.5V~+7.5V on the signal conditioning system. The input of the voltage follower circuit is the bias voltage. The voltage follower circuit adjusts the magnitude of the bias voltage output by the adjustable bias power supply VCC2 through a sliding resistor. The output of the voltage follower circuit is connected to the second bias and amplification circuit.

[0016] The second bias and amplifier circuit is used to superimpose the output of the voltage follower circuit and the output signal of the differential circuit to amplify them, and the output of the second bias and amplifier circuit is connected to the low-pass filter circuit;

[0017] The low-pass filter circuit is used to filter out the high-frequency components of the output signal of the second bias and amplification circuit to avoid interference from high-frequency signals, and the output of the low-pass filter circuit is connected to the limiting circuit;

[0018] The limiting circuit is used to limit the output of the low-pass filter circuit to between 3.3V and GND. The limiting circuit is connected to the ADC acquisition I / O port of the DSP processor.

[0019] On the other hand, the present invention also provides a micron-level magnetic bearing displacement sensing detection method, comprising the following steps:

[0020] Step S1: Use the micron-level magnetic bearing displacement sensing detection system to collect the displacement data of the magnetic bearing rotor at the current time k ;

[0021] Step S2: determining the relationship between the ripple current output by the switching power amplifier in the magnetic bearing and the rotor displacement;

[0022] First, the electromagnet coil in the magnetic bearing is equivalent to resistance and inductance. The equivalent inductance is used to describe the circuit parameters of the induced electromotive force effect caused by the change of coil current in the coil or in another coil. The induced electromotive force induced by the equivalent inductance is the same as the ripple current of the switching power amplifier. Related, the total output current of the switching power amplifier is , ,in is the effective output DC amount in the total current, is the ripple current output by the switching power amplifier, so the voltage applied to the magnetic bearing coil is , is the equivalent resistance, is the equivalent inductance, is an imaginary unit; the equivalent inductance is: , represents the magnetic permeability in vacuum, Indicates the number of turns of the electromagnet coil in the magnetic bearing, Represents the cross-sectional area of ​​the core in the electromagnet coil in the magnetic bearing; the ripple current is obtained from this With rotor displacement The calculation formula between is as follows: ,in, is the switching angular frequency of the switching power amplifier;

[0023] Step S3: Establishing a magnetic bearing self-sensing displacement estimation algorithm;

[0024] Step S31: The DSP processor collects the total current of the discrete output of the switching power amplifier. ;

[0025] Step S32: Discretize the total current Conduct preliminary processing;

[0026] Step S33: Designing a biorthogonal spline wavelet function based on a multi-resolution filter bank to extract the discrete total current output by the switching power amplifier High frequency ripple current in ;

[0027] Step S331: Obtain the ripple current in the discrete domain after passing through the typical filter group based on the working principle of the typical filter group The total current of the switching amplifier output Relationship: ,in, , and , They are the analysis filter and reconstruction filter designed considering anti-aliasing conditions and biorthogonal conditions respectively; represents the ripple current in the discrete domain, represents the total output current of the switching amplifier in the discrete domain, z is a complex frequency domain variable in the discrete domain, and -z is used to examine the behavior of the filter at negative frequencies;

[0028] Step S332: Construct the frequency domain expression of the quadratic spline function according to the symmetry and fidelity requirements of extracting the high-frequency component of the ripple current of the magnetic bearing ,Right now , is the frequency;

[0029] Step S333: designing a decomposition filter and a reconstruction filter;

[0030] In order to eliminate Give The aliasing phenomenon caused by ;

[0031] Introducing anti-aliasing conditions ;

[0032] So we can get the decomposition filter : ;

[0033] Simplifying, we get: ;

[0034] Perform discrete domain transformation to obtain: ;

[0035] According to the anti-aliasing condition, the , , , as shown in the following formula: , , ;

[0036] By decomposition filter , With reconstruction filter , Obtain the biorthogonal spline wavelet function;

[0037] Step S334: Constructing a scaling function based on a typical filter bank and wavelet function , the total output current of the discrete magnetic bearing switching power amplifier Perform wavelet decomposition as shown in the following formula:

[0038] , where i, j are the resolution orders, k is the offset, are the approximate coefficients of discrete wavelet transform, is the detail coefficient of discrete wavelet; , ;

[0039] Step S335: Use a multi-resolution analysis filter group to decompose, extract, and reconstruct the total current data of the discrete magnetic bearing switch power amplifier output after wavelet decomposition to obtain a ripple current containing displacement information. ;

[0040] The typical filter bank is combined into a multi-resolution analysis filter bank, which consists of decomposition filters. , Decompose k times to get the resolution Ripple current data under; Extraction resolution The results of biorthogonal spline wavelet decomposition are , , and the reconstruction filter , , for resolution The biorthogonal spline wavelet decomposition results extracted from , Reconstruct the ripple current containing displacement information ;

[0041] Step S34: Analyze the ripple current containing displacement information , take the absolute value, and then enter the low-pass filter to filter out the high-frequency components, thereby obtaining the required rotor displacement signal;

[0042] Step S35: Ripple current With rotor displacement The calculation formula between the two can demodulate the rotor displacement data;

[0043] Step S4: using a magnetic bearing self-sensing displacement estimation algorithm to estimate rotor displacement data, and fusing it with the rotor displacement data collected by a micron-level displacement detection system to obtain fused and corrected rotor displacement data;

[0044] Step S41: initializing the displacement signal fusion correction parameters of the micron-level magnetic bearing displacement sensing detection system and the self-sensing displacement estimation based on the Kalman filter according to the mathematical model of the magnetic bearing self-sensing displacement estimation algorithm, the physical model of the magnetic bearing system and the sensor characteristics;

[0045] The state space equation is established based on the mathematical model of the magnetic bearing self-sensing displacement estimation algorithm. , where A is the state matrix, B is the input matrix, is the displacement state at the previous moment, is the input of the self-sensing displacement estimation at the previous moment, which is related to the ripple current of the switching power amplifier Related, is the process disturbance, that is, the disturbance of the displacement state from time k-1 to time k, It follows a normal distribution. ; Considering the physical model of the magnetic bearing system and the characteristics of the sensor, the initial covariance matrix is ​​given , , and the measurement matrix ,in, is the covariance matrix of the process disturbance, is the covariance matrix of the state measurement error, is the state estimation error of the magnetic bearing system, Used to construct the measurement vector ;

[0046] Step S42: Establish a priori state estimate at time k : The rotor displacement state after fusion correction at the previous moment And the ripple current at the previous moment , get the prior state estimate of the rotor displacement at the current moment ,in , ;

[0047] Step S43: Calculate the error covariance matrix of the rotor displacement prior state estimate at the current moment ,in, , is the posterior state estimation covariance matrix of the previous moment, represents the transpose of the system matrix;

[0048] Step S44: Acquire displacement data collected by the micron-level displacement detection system And estimate the measurement error , integrated into the measurement vector ,in, is the state measurement error of the micron-level displacement detection system, It follows a normal distribution. ;

[0049] Step S45: Calculate the Kalman filter gain and fuse the measurement vector With the prior state estimate , get the current fused magnetic bearing displacement data ,in, is the Kalman filter gain ;

[0050] This achieves the fusion correction of the displacement data obtained by the eddy current sensor and the self-sensing displacement estimation value, and obtains the displacement data of the magnetic suspension bearing at the current moment;

[0051] Step S46: Update time , update the posterior state estimate covariance matrix ,in is the identity matrix;

[0052] Step S5: In addition, considering that the self-sensing displacement estimation algorithm has a delay, which will affect the dynamic performance of the magnetic bearing displacement control system, the Smith delay compensation algorithm is used to compensate for the delay caused by the self-sensing displacement estimation algorithm, as shown in the following formula: ,in, The transfer function of the magnetic bearing displacement control system considering the delay of the self-sensing displacement estimation algorithm is: is the Smith delay compensation transfer function for the delay of the self-sensing displacement estimation algorithm, The transfer function of the magnetic bearing displacement control system for Smith delay compensation of the magnetic bearing displacement control is: for The output variable, for The input variables are: s is the Laplace variable; With delay ,Right now , is the transfer function of the actual magnetic bearing displacement control system, The delay of the self-sensing displacement estimation algorithm of the magnetic bearing displacement control system is calculated. To offset the system delay factor, the system transfer function is estimated according to the response of the magnetic bearing displacement control system, and the Smith delay compensation transfer function is designed accordingly. ,in and In order to estimate the system parameters of the actual magnetic bearing displacement control system; at the same time, in order to eliminate the delay effect, it is necessary to perform PI control on the error between the estimated system transfer function and the actual system transfer function, that is, ,in is the proportional link coefficient, is the integration link coefficient;

[0053] Step S6: using an integral sliding film variable structure control algorithm to resist parameter perturbations and external interferences of the magnetic bearing displacement control system, thereby improving the robustness of the magnetic bearing self-sensing displacement estimation algorithm;

[0054] Step S61: simplifying the calculation formula between ripple current and rotor displacement;

[0055] According to the calculation formula between ripple current and rotor displacement in step S2, since the equivalent electromagnet resistance R is small, it is ignored. The calculation formula between ripple current and rotor displacement is simplified to: ;

[0056] So the calculation formula between ripple current and rotor displacement can be obtained as: ;

[0057] Step S62: designing a switching function of an integral sliding film variable structure control system of a magnetic bearing displacement control system;

[0058] The reference position of the rotor of the magnetic bearing displacement control system is set to , select the position of the magnetic bearing rotor and the rate of change of position As the state variable of the magnetic bearing displacement control system, the rotor displacement error of the magnetic bearing displacement control system is , that is, the error between the expected displacement and the actual position of the magnetic bearing rotor. The error change rate is obtained by derivation: , that is, the error between the rotor displacement change rate and the expected rotor displacement change rate; and then design the switching function of the integral sliding film variable structure control system , as shown in the following formula: , where c is the proportional term coefficient greater than 0, is the integral term coefficient greater than 0;

[0059] Step S63: Design a control law for an integral sliding film variable structure control system suitable for a magnetic bearing displacement control system ;

[0060] Since the input of the magnetic bearing displacement control system is the ripple current of the switching power amplifier , so the control law of the magnetic bearing displacement control system is ;

[0061] The control law of the integral sliding mode variable structure control system is designed by the exponential reaching law. The exponential reaching law is shown in the following formula: ,in, For the switch function The exponential reaching law of is the coefficient of the uniform convergence law greater than 0, is the symbolic function, is the switching function term coefficient greater than 0;

[0062] Derivative of the switching function: ;

[0063] Also because ,therefore ;

[0064] because , Substituting into the above formula, we can get: ;

[0065] In addition , so the calculation formula between ripple current and rotor displacement is: ;

[0066] Displace the rotor Substitute the calculation formula into , and take , then the control law of the integral sliding film variable structure control of the magnetic bearing displacement control system is obtained , as shown in the following formula: .

[0067] The beneficial effect of adopting the above technical scheme is that: the present invention provides a micron-level magnetic suspension bearing displacement sensing detection system and method, taking into account that the eddy current sensor used for magnetic suspension bearing displacement detection is affected by the magnetic field and eddy current and has certain errors, and the sensorless technology has certain limitations when the motor starts and the speed changes. Therefore, in order to ensure the stable suspension of the magnetic suspension bearing motor, the existing eddy current sensor is improved and a new sensorless technology is found, and the displacement information of the two displacement detection technologies is effectively integrated and corrected to improve the reliability of the magnetic suspension bearing. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 The eddy current sensor driving and detection system circuit provided by the embodiment of the present invention, wherein (a) is a driving circuit, and (b) is a detection circuit and a first bias and amplification circuit;

[0069] Figure 2 The eddy current sensor signal conditioning system circuit provided by the embodiment of the present invention, wherein (a) is a differential circuit, a voltage follower circuit and a second bias and amplification circuit, and (b) is a low-pass filter circuit, a limiter circuit and a voltage follower circuit;

[0070] Figure 3 A structural block diagram of a micron-level magnetic bearing displacement sensing detection method provided by an embodiment of the present invention;

[0071] Figure 4 A flow chart of a micron-level magnetic bearing displacement sensing detection method provided by an embodiment of the present invention;

[0072] Figure 5 Schematic diagram of a sensor-equipped magnetic bearing and a sensorless magnetic bearing provided in an embodiment of the present invention, wherein (a) is a sensor-equipped magnetic bearing, and (b) is a sensorless magnetic bearing;

[0073] Figure 6 An equivalent schematic diagram of self-sensing displacement estimation of a magnetic bearing provided by an embodiment of the present invention;

[0074] Figure 7 A flow chart of a self-sensing displacement estimation algorithm for a magnetic bearing provided by an embodiment of the present invention;

[0075] Figure 8A self-sensing displacement estimation operation framework diagram of a magnetic bearing provided by an embodiment of the present invention;

[0076] Fig. 9 A control structure for a displacement self-sensing estimation algorithm provided in an embodiment of the present invention;

[0077] Fig.10 A schematic diagram of using the Smith delay compensation algorithm to compensate for the delay of the self-sensing displacement estimation algorithm provided by an embodiment of the present invention;

[0078] Fig.11 A flowchart of the control law design process of an integral sliding film variable structure control system applicable to a magnetic bearing displacement control system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0079] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0080] In this embodiment, a micron-level magnetic suspension bearing displacement sensing detection system includes a DSP processor, an eddy current sensor driving and detection system, and an eddy current sensor signal conditioning system; the eddy current sensor driving and detection system is used to drive the eddy current sensor and detect the displacement signal of the rotor being measured; the eddy current sensor signal conditioning system processes the rotor displacement signal detected by the eddy current sensor driving and detection system and inputs it into the DSP processor.

[0081] In this embodiment, the eddy current sensor driving and detection system is as follows: Figure 1 As shown, it includes a driving circuit, a detection circuit and a first bias and amplification circuit of an eddy current sensor; the output end of the driving circuit is connected to the coil of the eddy current sensor, and is used to generate an alternating signal to drive the coil of the eddy current sensor to generate an alternating magnetic field, so that eddy currents are induced on the rotor to form an eddy current effect;

[0082] The detection circuit is used to extract the peak value of the AC signal output by the coil of the eddy current sensor and convert the AC signal into a DC signal; the output end of the detection circuit is connected to the first bias and amplification circuit;

[0083] The first bias and amplifier circuit is used to convert the DC signal output by the detection circuit into a DC voltage proportional to the measured rotor displacement after bias and amplification processing. The output end of the first bias and amplifier circuit is connected to the eddy current sensor signal conditioning system.

[0084] The driving circuit is composed of a power supply VCC1, a voltage regulating circuit and a capacitor three-point oscillation circuit, wherein the power supply VCC1 is the input of the voltage regulating circuit, and the power supply VCC1 also powers the eddy current sensor probe; the voltage regulating circuit provides voltage to the base of the capacitor three-point oscillation circuit; the capacitor three-point oscillation circuit uses a transistor T1 to amplify the oscillation signal, thereby generating a high-frequency stable oscillation signal to provide an excitation signal to the eddy current sensor probe to generate an eddy current phenomenon, and the output of the oscillation circuit is superimposed on the output of the voltage regulating circuit, thereby realizing the driving of the eddy current sensor.

[0085] The capacitor three-point oscillation circuit is composed of an eddy current sensor probe equivalent inductance L1 and two capacitors C1 and C2 connected in series to form a resonant cavity. In addition, the emitter of the transistor T1 is connected to the connection between the capacitor C1 and the inductor L1, the collector of the transistor is connected to the connection between the capacitors C1 and C2, and the base of the transistor T1 is connected to the output end of the voltage regulation circuit.

[0086] The detection circuit is composed of a first detection diode D1, a capacitor C3, a resistor R1, a resistor R2, and a second detection diode D2. The anode of the first detection diode D1 is connected to the output end of the capacitor three-point oscillation circuit, and the cathode is connected to one end of the capacitor C3. The other end of the capacitor C3 is connected to the positive electrode of the power supply VCC1 in the drive circuit. One end of the resistor R1 is connected to the capacitor C3 and the cathode end of the first detection diode D1, and the other end is connected to one end of the resistor R2. The other end of the resistor R2 is connected to the anode of the second detection diode D2, and the cathode of the second detection diode D2 is grounded. Among them, the power supply VCC1 in the drive circuit, the first detection diode D1 and the capacitor C3 constitute a charging circuit, and the resistor R1, the resistor R2 and the second detection diode D2 constitute a discharging circuit.

[0087] In this embodiment, the eddy current sensor signal conditioning system is as follows: Figure 2 As shown, it includes: a differential circuit, an adjustable bias power supply VCC2, a voltage follower circuit, a second bias and amplification circuit, a low-pass filter circuit and a limiting circuit;

[0088] The differential circuit is used to remove the same nonlinear interference components in the output signals of the eddy current sensors installed at symmetrical positions on both sides of the stator of the magnetic bearing motor, and the output of the differential circuit is connected to the second bias and amplification circuit;

[0089] The voltage follower circuit is used to isolate the influence of the adjustable bias power supply VCC2 of -7.5V~+7.5V on the signal conditioning system. The input of the voltage follower circuit is the bias voltage. The voltage follower circuit adjusts the magnitude of the bias voltage output by the adjustable bias power supply VCC2 through a sliding resistor. The output of the voltage follower circuit is connected to the second bias and amplification circuit.

[0090] The second bias and amplifier circuit is used to superimpose the output of the voltage follower circuit and the output signal of the differential circuit to amplify them, and the output of the second bias and amplifier circuit is connected to the low-pass filter circuit;

[0091] The low-pass filter circuit is used to filter out the high-frequency components of the output signal of the second bias and amplification circuit to avoid interference from high-frequency signals, and the output of the low-pass filter circuit is connected to the limiting circuit;

[0092] The limiting circuit is used to limit the output of the low-pass filter circuit to between 3.3V and GND. The limiting circuit is connected to the ADC acquisition I / O port of the DSP processor.

[0093] In this embodiment, a micron-level magnetic bearing displacement sensing detection method is provided. Figure 3-Figure 5 As shown, compared with the displacement detection method with a sensor, this method omits the sensor device and specifically includes the following steps:

[0094] Step S1: Use the micron-level magnetic bearing displacement sensing detection system to collect the displacement data of the magnetic bearing rotor at the current time k ;

[0095] Step S2: Determine the relationship between the ripple current output by the switching power amplifier in the magnetic bearing and the rotor displacement, such as Figure 6 As shown;

[0096] First, the electromagnet coil in the magnetic bearing is equivalent to resistance and inductance. The equivalent inductance is used to describe the circuit parameters of the induced electromotive force effect caused by the change of coil current in the coil or in another coil. The induced electromotive force induced by the equivalent inductance is the same as the ripple current of the switching power amplifier. Related, the total output current of the switching power amplifier is , ,in is the effective output DC amount in the total current, is the ripple current output by the switching power amplifier, so the voltage applied to the magnetic bearing coil is , is the equivalent resistance, L is the equivalent inductance, is an imaginary unit; where the equivalent inductance is: , represents the magnetic permeability in vacuum, Indicates the number of turns of the electromagnet coil in the magnetic bearing, Represents the cross-sectional area of ​​the core in the electromagnet coil in the magnetic bearing; the ripple current is obtained from this With rotor displacement The calculation formula between is as follows: ,in, is the switching angular frequency of the switching power amplifier;

[0097] Step S3: Establish a magnetic bearing self-sensing displacement estimation algorithm, such as Figure 7 , Figure 8 , Fig. 9 As shown;

[0098] Step S31: The DSP processor collects the total current of the discrete output of the switching power amplifier. ; Since the data collected by the DSP processor is discrete, The total current output by the switching power amplifier is discrete data.

[0099] Step S32: Discretize the total current Conduct preliminary processing;

[0100] Step S33: Designing a biorthogonal spline wavelet function based on a multi-resolution filter bank to extract the discrete total current output by the switching power amplifier High frequency ripple current in ;

[0101] Step S331: Obtain the ripple current in the discrete domain after passing through the typical filter group based on the working principle of the typical filter group The total current of the switching amplifier output Relationship: ,in, , and , They are the analysis filter and reconstruction filter designed considering anti-aliasing conditions and biorthogonal conditions respectively; represents the ripple current in the discrete domain, represents the total output current of the switching amplifier in the discrete domain, z is a complex frequency domain variable in the discrete domain, and -z is used to examine the behavior of the filter at negative frequencies;

[0102] Step S332: Determine the frequency domain expression of the quadratic spline function according to the requirements of symmetry and fidelity of extracting the high-frequency component of the ripple current of the magnetic bearing ,Right now , is the frequency;

[0103] Step S333: designing a decomposition filter and a reconstruction filter;

[0104] In order to eliminate Give The aliasing phenomenon caused by ;

[0105] Introducing anti-aliasing conditions ;

[0106] So we can get the decomposition filter : ;

[0107] Simplifying, we get: ;

[0108] Perform discrete domain transformation to obtain: ;

[0109] According to the anti-aliasing condition, the , , , as shown in the following formula: , , ;

[0110] By decomposition filter , With reconstruction filter , Obtain the biorthogonal spline wavelet function;

[0111] Step S333: Constructing a scaling function based on a typical filter bank and wavelet function , the total output current of the discrete magnetic bearing switching power amplifier Perform wavelet decomposition as shown in the following formula: , where i, j are the resolution orders, k is the offset, are the approximate coefficients of discrete wavelet transform, is the detail coefficient of discrete wavelet; , ;

[0112] Step S334: Use a multi-resolution analysis filter bank to decompose, extract and reconstruct the total current data of the discrete magnetic bearing switch power amplifier output after wavelet decomposition to obtain a ripple current containing displacement information. ;

[0113] The typical filter bank is combined into a multi-resolution analysis filter bank, which consists of decomposition filters. , Decompose k times to get the resolution Ripple current data under; Extraction resolution The results of biorthogonal spline wavelet decomposition are , , and the reconstruction filter , , for resolution The biorthogonal spline wavelet decomposition results extracted from , Reconstruct the ripple current containing displacement information ;

[0114] Step S34: Analyze the ripple current containing displacement information , take the absolute value, and then enter the low-pass filter to filter out the high-frequency components, thereby obtaining the required rotor displacement signal;

[0115] Step S35: Ripple current With rotor displacement The calculation formula between the two can demodulate the rotor displacement data;

[0116] Step S4: using a magnetic bearing self-sensing displacement estimation algorithm to estimate rotor displacement data, and fusing it with the rotor displacement data collected by a micron-level displacement detection system to obtain fused and corrected rotor displacement data;

[0117] Step S41: initializing the displacement signal fusion correction parameters of the micron-level magnetic bearing displacement sensing detection system and the self-sensing displacement estimation based on the Kalman filter according to the mathematical model of the magnetic bearing self-sensing displacement estimation algorithm, the physical model of the magnetic bearing system and the sensor characteristics;

[0118] The state space equation is established based on the mathematical model of the magnetic bearing self-sensing displacement estimation algorithm. , where A is the state matrix, B is the input matrix, is the displacement state at the previous moment, is the input of the self-sensing displacement estimation at the previous moment, which is related to the ripple current of the switching power amplifier Related, is the process disturbance, that is, the disturbance of the displacement state from time k-1 to time k, It follows a normal distribution. ; Considering the physical model of the magnetic bearing system and the characteristics of the sensor, the initial covariance matrix is ​​given , , and the measurement matrix ,in, is the covariance matrix of the process disturbance, is the covariance matrix of the state measurement error, is the state estimation error of the magnetic bearing system, Used to construct the measurement vector ;

[0119] Step S42: Establish a priori state estimate at time k : The rotor displacement state after fusion correction at the previous moment And the ripple current at the previous moment , get the prior state estimate of the rotor displacement at the current moment ,in , ;

[0120] Step S43: Calculate the error covariance matrix of the rotor displacement prior state estimate at the current moment ,in , is the posterior state estimation covariance matrix of the previous moment, represents the transpose of the system matrix;

[0121] Step S44: Acquire displacement data collected by the micron-level displacement detection system And estimate the measurement error , integrated into the measurement vector ,in, is the state measurement error of the micron-level displacement detection system, It follows a normal distribution. ;

[0122] Step S45: Calculate the Kalman filter gain and fuse the measurement vector With the prior state estimate , get the current fused magnetic bearing displacement data ,in, is the Kalman filter gain ; Thus, the displacement data obtained by the eddy current sensor and the self-sensing displacement estimation value are fused and corrected to obtain the displacement data of the magnetic bearing at the current moment;

[0123] Step S46: Update time , update the posterior state estimate covariance matrix ,in is the identity matrix;

[0124] Step S5: In addition, considering that there is a delay in the self-sensing displacement estimation algorithm, it will affect the dynamic performance of the magnetic bearing displacement control system, such as Fig.10 As shown, the Smith delay compensation algorithm is used to compensate for the delay caused by the self-sensing displacement estimation algorithm, as shown in the following formula: ;

[0125] in, The transfer function of the magnetic bearing displacement control system considering the delay of the self-sensing displacement estimation algorithm is: is the Smith delay compensation transfer function for the delay of the self-sensing displacement estimation algorithm, The transfer function of the magnetic bearing displacement control system for Smith delay compensation of the magnetic bearing displacement control is: for The output variable, for The input variables are , where s is the Laplace variable; With delay ,Right now , is the transfer function of the actual magnetic bearing displacement control system, is the delay of the self-sensing displacement estimation algorithm of the magnetic bearing displacement control system; in order to offset the system delay factor, the compensation transfer function used is However, it is not easy to obtain the transfer function of the actual magnetic bearing displacement control system. Therefore, the system transfer function can only be estimated based on the response of the magnetic bearing displacement control system. ,in and In order to estimate the system parameters of the actual magnetic bearing displacement control system; at the same time, in order to eliminate the delay effect, it is necessary to perform PI control on the error between the estimated system transfer function and the actual system transfer function, that is, ,in is the proportional link coefficient, is the integration link coefficient;

[0126] Step S6: adopting the integral sliding film variable structure control algorithm to resist the parameter perturbation and external interference of the magnetic bearing displacement control system, and improving the robustness of the magnetic bearing self-sensing displacement estimation algorithm, such as Fig.11 As shown;

[0127] Considering that the self-sensing displacement estimation algorithm of the magnetic bearing is difficult to cope with changes in the external environment, it is necessary to adopt a control law switching method for resisting parameter perturbations and external interferences of the magnetic bearing displacement control system to improve the robustness of the magnetic bearing displacement control system. The control law switching method for resisting parameter perturbations and external interferences of the magnetic bearing displacement control system adopts sliding film variable structure control to continuously switch the control law so that the system state slides along the sliding surface. The specific design process is shown below.

[0128] Step S61: simplifying the calculation formula between ripple current and rotor displacement;

[0129] The control law switching method for resisting control system parameter perturbations and external interference has a switching function and a control function design derived from a calculation formula between ripple current and rotor displacement. Specifically, the switching function and the control law are designed based on the calculation formula between ripple current and rotor displacement.

[0130] According to the calculation formula between ripple current and rotor displacement in step S2, since the equivalent electromagnet resistance R is small, it is ignored. The calculation formula between ripple current and rotor displacement is simplified to ;Then the calculation formula between ripple current and rotor displacement can be obtained as: ;

[0131] Step S62: designing a switching function of an integral sliding film variable structure control system of a magnetic bearing displacement control system;

[0132] The reference position of the rotor of the magnetic bearing displacement control system is set to , select the position of the magnetic bearing rotor and the rate of change of position As the state variable of the magnetic bearing displacement control system, the rotor displacement error of the magnetic bearing displacement control system is , that is, the error between the expected displacement and the actual position of the magnetic bearing rotor. The error change rate is obtained by derivation: , that is, the error between the rotor displacement change rate and the expected rotor displacement change rate; and then design the switching function of the integral sliding film variable structure control system , as shown in the following formula: , where c is the proportional term coefficient greater than 0, is an integral term coefficient greater than 0; the integral structure can retain the error in the derivative and enhance the robustness of the magnetic bearing displacement control system.

[0133] Step S63: Design a control law for an integral sliding film variable structure control system suitable for a magnetic bearing displacement control system ;

[0134] Since the input of the magnetic bearing displacement control system is the ripple current of the switching power amplifier , so the control law of the magnetic bearing displacement control system is ;

[0135] When selecting the control law, it is necessary to consider the approaching motion of the sliding mode motion. The control law of the integral sliding mode variable structure control system is designed by the exponential approaching law, which is shown in the following formula: ,in, For the switch function The exponential reaching law of is the coefficient of the uniform convergence law greater than 0, is the symbolic function, is the switching function term coefficient greater than 0;

[0136] Derivative of the switching function: ;

[0137] Also because ,therefore ;

[0138] because , Substituting into the above formula, we can get: ;

[0139] In addition , so the calculation formula between ripple current and rotor displacement is: ;

[0140] Displace the rotor Substitute the calculation formula into , and take , then the control law of the integral sliding film variable structure control of the magnetic bearing displacement control system is obtained , as shown in the following formula: .

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope defined by the claims of the present invention.

Claims

1. A micron-level magnetic bearing displacement sensing detection method, characterized in that: The invention comprises a DSP processor, an eddy current sensor driving and detecting system and an eddy current sensor signal conditioning system; the eddy current sensor driving and detecting system is used to drive the eddy current sensor and detect the displacement signal of the rotor under test; the eddy current sensor signal conditioning system processes the rotor displacement signal detected by the eddy current sensor driving and detecting system and inputs it into the DSP processor; the invention specifically comprises the following steps: Step S1: Use the micron-level magnetic bearing displacement sensing detection system to collect the displacement data of the magnetic bearing rotor at the current time k ; Step S2: determining the relationship between the ripple current output by the switching power amplifier in the magnetic bearing and the rotor displacement; First, the electromagnet coil in the magnetic bearing is equivalent to resistance and inductance. The equivalent inductance is used to describe the circuit parameters of the induced electromotive force effect caused by the change of coil current in the coil or in another coil. The induced electromotive force induced by the equivalent inductance is the same as the ripple current of the switching power amplifier. Related, the total output current of the switching power amplifier is , ,in is the effective output DC amount in the total current, is the ripple current output by the switching power amplifier, so the voltage applied to the magnetic bearing coil is , is the equivalent resistance, is the equivalent inductance, is an imaginary unit; the equivalent inductance is: , represents the magnetic permeability in vacuum, Indicates the number of turns of the electromagnet coil in the magnetic bearing, Represents the cross-sectional area of ​​the core in the electromagnet coil in the magnetic bearing; the ripple current is obtained from this With rotor displacement The calculation formula between is as follows: ,in, is the switching angular frequency of the switching power amplifier; Step S3: Establishing a magnetic bearing self-sensing displacement estimation algorithm; Step S31: The DSP processor collects the total current of the discrete output of the switching power amplifier. ; Step S32: Discretize the total current Conduct preliminary processing; Step S33: Designing a biorthogonal spline wavelet function based on a multi-resolution filter bank to extract the discrete total current output by the switching power amplifier High frequency ripple current in ; Step S34: Analyze the ripple current containing displacement information , take the absolute value, and then enter the low-pass filter to filter out the high-frequency components, thereby obtaining the required rotor displacement signal; Step S35: Ripple current With rotor displacement The calculation formula between the two demodulates the rotor displacement data; Step S4: using a magnetic bearing self-sensing displacement estimation algorithm to estimate rotor displacement data, and fusing it with the rotor displacement data collected by a micron-level displacement detection system to obtain fused and corrected rotor displacement data; Step S5: using the Smith delay compensation algorithm to compensate for the delay caused by the self-sensing displacement estimation algorithm; Step S6: adopting the integral sliding film variable structure control algorithm to resist the parameter perturbation and external interference of the magnetic bearing displacement control system, so as to improve the robustness of the magnetic bearing self-sensing displacement estimation algorithm.

2. A micron-level magnetic bearing displacement sensing detection method according to claim 1, characterized in that: The eddy current sensor driving and detection system comprises a driving circuit, a detection circuit and a first bias and amplification circuit of the eddy current sensor; the output end of the driving circuit is connected to the eddy current sensor coil, and is used to generate an alternating signal to drive the eddy current sensor coil to generate an alternating magnetic field, so that eddy currents are induced on the rotor to form an eddy current effect; The detection circuit is used to extract the peak value of the AC signal output by the coil of the eddy current sensor and convert the AC signal into a DC signal; the output end of the detection circuit is connected to the first bias and amplification circuit; The first bias and amplifier circuit is used to convert the DC signal output by the detection circuit into a DC voltage proportional to the measured rotor displacement after bias and amplification processing. The output end of the first bias and amplifier circuit is connected to the eddy current sensor signal conditioning system.

3. A micron-level magnetic bearing displacement sensing detection method according to claim 2, characterized in that: The driving circuit is composed of a power supply VCC1, a voltage regulating circuit and a capacitor three-point oscillation circuit, wherein the power supply VCC1 is the input of the voltage regulating circuit, and the power supply VCC1 also supplies power to the eddy current sensor probe; the voltage regulating circuit provides voltage to the base of the capacitor three-point oscillation circuit; the capacitor three-point oscillation circuit amplifies the oscillation signal using the transistor T1, thereby generating a high-frequency stable oscillation signal to provide an excitation signal to the eddy current sensor probe to generate an eddy current phenomenon, and the output of the oscillation circuit is superimposed on the output of the voltage regulating circuit, thereby realizing the driving of the eddy current sensor; The capacitor three-point oscillation circuit is composed of an eddy current sensor probe equivalent inductance L1 and two capacitors C1 and C2 connected in series to form a resonant cavity. In addition, the emitter of the transistor T1 is connected to the connection between the capacitor C1 and the inductor L1, the collector of the transistor is connected to the connection between the capacitors C1 and C2, and the base of the transistor T1 is connected to the output end of the voltage regulation circuit.

4. A micron-level magnetic bearing displacement sensing detection method according to claim 2, characterized in that: The detection circuit is composed of a first detection diode D1, a capacitor C3, a resistor R1, a resistor R2, and a second detection diode D2. The anode of the first detection diode D1 is connected to the output end of the capacitor three-point oscillation circuit, and the cathode is connected to the capacitor C3 and one end of the resistor R1. The other end of the capacitor C3 is connected to the positive electrode of the power supply VCC1 in the drive circuit, the other end of the resistor R1 is connected to one end of the resistor R2, the other end of the resistor R2 is connected to the anode of the second detection diode D2, and the cathode of the second detection diode D2 is grounded; wherein, the power supply VCC1 in the drive circuit, the first detection diode D1 and the capacitor C3 constitute a charging circuit, and the resistor R1, the resistor R2 and the second detection diode D2 constitute a discharging circuit.

5. The micron-level magnetic bearing displacement sensing detection method according to claim 1 is characterized in that: The eddy current sensor signal conditioning system includes: a differential circuit, an adjustable bias power supply VCC2, a voltage follower circuit, a second bias and amplification circuit, a low-pass filter circuit and a limiting circuit; The differential circuit is used to remove the same nonlinear interference components in the output signals of the eddy current sensors installed at symmetrical positions on both sides of the stator of the magnetic bearing motor, and the output of the differential circuit is connected to the second bias and amplification circuit; The voltage follower circuit is used to isolate the influence of the adjustable bias power supply VCC2 of -7.5V~+7.5V on the signal conditioning system. The input of the voltage follower circuit is the bias voltage. The voltage follower circuit adjusts the magnitude of the bias voltage output by the adjustable bias power supply VCC2 through a sliding resistor. The output of the voltage follower circuit is connected to the second bias and amplification circuit. The second bias and amplifier circuit is used to superimpose the output of the voltage follower circuit and the output signal of the differential circuit to amplify them, and the output of the second bias and amplifier circuit is connected to the low-pass filter circuit; The low-pass filter circuit is used to filter out the high-frequency components of the output signal of the second bias and amplification circuit to avoid interference from high-frequency signals, and the output of the low-pass filter circuit is connected to the limiting circuit; The limiting circuit is used to limit the output of the low-pass filter circuit to between 3.3V and GND. The limiting circuit is connected to the ADC acquisition I / O port of the DSP processor.

6. A micron-level magnetic bearing displacement sensing detection method according to claim 1, characterized in that: The specific method of step S33 is: Step S331: Obtain the ripple current in the discrete domain after passing through the typical filter group based on the working principle of the typical filter group The total current of the switching amplifier output Relationship: ,in, , and , They are the analysis filter and reconstruction filter designed considering the anti-aliasing condition and the biorthogonal condition respectively; represents the ripple current in the discrete domain, represents the total output current of the switching amplifier in the discrete domain, z is a complex frequency domain variable in the discrete domain, and -z is used to examine the behavior of the filter at negative frequencies; Step S332: Construct the frequency domain expression of the quadratic spline function according to the requirements of symmetry and fidelity of extracting the high-frequency component of the ripple current of the magnetic bearing ; Step S333: Design two analysis filters considering anti-aliasing conditions and biorthogonal conditions , With reconstruction filter , ; By decomposition filter , With reconstruction filter , Obtain the biorthogonal spline wavelet function; Step S334: constructing a scaling function and a wavelet function based on a typical filter bank to output the total current of the discrete magnetic bearing switch power amplifier Perform wavelet decomposition; Step S335: Use a multi-resolution analysis filter bank to decompose, extract and reconstruct the total current data of the discrete magnetic bearing switch power amplifier output after wavelet decomposition to obtain a ripple current containing displacement information. .

7. A micron-level magnetic bearing displacement sensing detection method according to claim 6, characterized in that: The specific method of step S333 is: In order to eliminate Give The aliasing phenomenon caused by ; Introducing anti-aliasing conditions ; So the decomposition filter : ; Simplified: ; Perform discrete domain transformation to obtain: ; Designed according to anti-aliasing conditions , , , as shown in the following formula: , , ; By decomposition filter , With reconstruction filter , Get the biorthogonal spline wavelet function.

8. A micron-level magnetic bearing displacement sensing detection method according to claim 7, characterized in that: The specific method of step S4 is: Step S41: initializing the displacement signal fusion correction parameters of the micron-level magnetic bearing displacement sensing detection system and the self-sensing displacement estimation based on the Kalman filter according to the mathematical model of the magnetic bearing self-sensing displacement estimation algorithm, the physical model of the magnetic bearing system and the sensor characteristics; Step S42: Establish a priori state estimate at time k : The rotor displacement state after fusion correction at the previous moment And the ripple current at the previous moment , get the prior state estimate of the rotor displacement at the current moment ; Step S43: Calculate the error covariance matrix of the rotor displacement prior state estimate at the current moment ; Step S44: Acquire displacement data collected by the micron-level displacement detection system And estimate the measurement error , integrated into the measurement vector ; Step S45: Calculate Kalman filter gain and fuse measurement vector With the prior state estimate , get the current fused magnetic bearing displacement data ; This achieves the fusion correction of the displacement data obtained by the eddy current sensor and the self-sensing displacement estimation value, and obtains the displacement data of the magnetic suspension bearing at the current moment; Step S46: Update time , update the posterior state estimate covariance matrix .

9. A micron-level magnetic bearing displacement sensing detection method according to claim 8, characterized in that: The step S5 uses the Smith delay compensation algorithm to compensate for the delay caused by the self-sensing displacement estimation algorithm, as shown in the following formula: ,in, The transfer function of the magnetic bearing displacement control system considering the delay of the self-sensing displacement estimation algorithm is: is the Smith delay compensation transfer function for the delay of the self-sensing displacement estimation algorithm, The transfer function of the magnetic bearing displacement control system for Smith delay compensation of the magnetic bearing displacement control is: for The output variable, for The input variables are: s is the Laplace variable; With delay ,Right now , is the transfer function of the actual magnetic bearing displacement control system, The delay of the self-sensing displacement estimation algorithm of the magnetic bearing displacement control system is calculated. To offset the system delay factor, the system transfer function is estimated according to the response of the magnetic bearing displacement control system, and the Smith delay compensation transfer function is designed accordingly. ,in and In order to estimate the system parameters of the actual magnetic bearing displacement control system; at the same time, in order to eliminate the delay effect, it is necessary to perform PI control on the error between the estimated system transfer function and the actual system transfer function, that is, ,in is the proportional link coefficient, is the integration link coefficient.

10. A micron-level magnetic bearing displacement sensing detection method according to claim 9, characterized in that: The specific method of step S6 is: Step S61: simplifying the calculation formula between ripple current and rotor displacement; According to the calculation formula between ripple current and rotor displacement in step S2, ignore The calculation formula between ripple current and rotor displacement is simplified to: ; The calculation formula between ripple current and rotor displacement is obtained as follows: ; Step S62: designing a switching function of an integral sliding film variable structure control system of a magnetic bearing displacement control system; The reference position of the rotor of the magnetic bearing displacement control system is set to , select the position of the magnetic bearing rotor and the rate of change of position As the state variable of the magnetic bearing displacement control system, the rotor displacement error of the magnetic bearing displacement control system is , that is, the error between the expected displacement and the actual position of the magnetic bearing rotor. The error change rate is obtained by derivation: , that is, the error between the rotor displacement change rate and the expected rotor displacement change rate; and then design the switching function of the integral sliding film variable structure control system , as shown in the following formula: , where c is the proportional term coefficient greater than 0, is the integral term coefficient greater than 0; Step S63: Design a control law for an integral sliding film variable structure control system suitable for a magnetic bearing displacement control system ; Since the input of the magnetic bearing displacement control system is the ripple current of the switching power amplifier , so the control law of the magnetic bearing displacement control system is ; The control law of the integral sliding mode variable structure control system is designed by the exponential reaching law. The exponential reaching law is shown in the following formula: ,in, For the switch function The exponential reaching law of is the coefficient of the uniform convergence law greater than 0, is the symbolic function, is the switching function term coefficient greater than 0; In addition , so the calculation formula between ripple current and rotor displacement is: ; Displace the rotor Substitute the calculation formula into , and take , then the control law of the integral sliding film variable structure control of the magnetic bearing displacement control system is obtained , as shown in the following formula: .

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