A motion control method for anti-interference linear motor module

Abstract

The present invention discloses an anti-interference linear motor module motion control method, which relates to the field of linear motor module control technology. The method monitors and analyzes the displacement error, acceleration fluctuation value, motor load force, motor working current I, motor real-time voltage value U, drag force and guide rail friction parameters of the motor module during operation in real time, as well as the interference of external environmental factors (such as airflow velocity, airflow pressure, deposition thickness and electrostatic effect coefficient). The present invention can comprehensively evaluate the motion state of the motor module, thereby effectively reducing the deviation of the motion trajectory and significantly improving the motion stability of the motor module. By collecting external environmental interference parameters (airflow interference, deposition thickness, environmental vibration, etc.) and combining neural network technology to establish an interference model, the motion control strategy of the motor module can be dynamically adjusted to compensate for different types of interference factors in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of linear motor module control, and in particular to an anti-interference linear motor module motion control method. Background Art

[0002] As a high-precision motion control device, linear motor modules have been widely used in modern industrial manufacturing, semiconductor processing, automated production lines and other fields. Their operating accuracy and stability directly affect the working performance and production efficiency of the entire system. However, when operating in a complex environment, the motion control performance of linear motor modules is often affected by a variety of external interferences, including air flow fluctuations, micro-matter deposition, electrostatic effects, environmental vibrations, temperature and humidity gradients, and light source fluctuations. These interferences will not only cause the motion trajectory of the motor module to deviate from expectations, but may also affect the service life and safety of the system.

[0003] In high-speed operation scenarios, changes in the surrounding airflow will cause random disturbances to the movement of the motor module, resulting in increased displacement errors. Especially for open environments or clean rooms that require frequent ventilation, airflow disturbances are more significant. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an anti-interference linear motor module motion control method to solve the problems mentioned in the background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an anti-interference linear motor module motion control method, comprising the following steps:

[0006] Step 1: Real-time monitoring of the displacement error and acceleration changes of the linear motor module during operation to collect displacement error ΔX, acceleration fluctuation value Δα, motor load force F z , motor working current I, motor real-time voltage value U, drag force F drag And the guide rail friction F c , generating a first data set;

[0007] Step 2: Collect airflow disturbance parameters in the external environment, including airflow velocity V w , air flow pressure P w , deposition thickness D s , electrostatic effect coefficient S e And the vibration frequency spectrum value V f , generating a second data set;

[0008] Step 3: After establishing and training the motor interference model using neural network technology, the first data group and the second data group are analyzed and calculated to obtain the motion stability index Sn and the environmental interference coefficient Ii, and the motion stability index Sn and the environmental interference coefficient Ii are associated to generate and evaluate the anti-interference compensation coefficient Cdc to generate a preliminary motion optimization control strategy;

[0009] Step 4: After implementing the preliminary motion optimization control strategy, collect the characterization environment-related data of the linear motor module to obtain the average temperature gradient ΔT f , average humidity gradient ΔH f , total motor expansion ΔL total And the comprehensive amplitude of light source fluctuation Φ l After generating the third data group, the motor characterization interference sensitivity coefficient Ch is constructed, and the motor characterization interference sensitivity coefficient Ch is evaluated to obtain the motion abnormality risk assessment result; according to the motion abnormality risk assessment result, the preliminary motion optimization control strategy is corrected to optimize the dynamic performance of the linear motor module.

[0010] Preferably, step one comprises:

[0011] S11. Set the target mark point on the motion path of the load platform of the linear motor module and use the laser displacement sensor to measure the actual position X of the module. actual and the expected position X target , the displacement error ΔX is calculated by the following formula:

[0012] ΔX=|X actual -X target |;

[0013] Among them, the output signal of the laser displacement sensor is transmitted to the control system in real time, and the sampling frequency is 1000Hz;

[0014] S12. Install a three-axis acceleration sensor on the load platform of the linear motor module and record the acceleration values ​​α in the x-axis, y-axis and z-axis directions. x , α u , α z , the acceleration fluctuation value Δα is calculated by the following formula:

[0015]

[0016] In the formula, and Respectively represent the reference average acceleration thresholds in the x-axis, y-axis and z-axis directions;

[0017] S13. Install a force sensor at the driving end of the linear motor module and collect the electrical signal V output by the force sensor. f, and calculate the motor load force F by the following formula z :

[0018] F z =k f *v f ;

[0019] In the formula, k f It represents the force-to-electricity conversion coefficient of the force sensor, which is obtained through the force sensor calibration;

[0020] S14, using Hall current sensor to collect output current signal V i The motor operating current I is calculated using the following formula:

[0021] I=k i *V i ;

[0022] In the formula, k i is the current conversion coefficient of the Hall current sensor; and a voltage sensor is used to collect the real-time voltage value U of the motor.

[0023] Preferably, step one further comprises:

[0024] S15. Collect the output torque T, drive efficiency η, and drive equivalent radius r of the linear motor module, and calculate the drag force F using the following formula drag :

[0025]

[0026] S16, according to the drag force F drag and the motor load force F obtained in S13 z , the guide rail friction force F is calculated by the following formula c :

[0027] F c =F drag -F z ;

[0028] Where, the guide rail friction force F c It indicates the friction force of the linear motor module's guide rail during movement, which is the main resistance in the equilibrium state;

[0029] S17, the displacement error ΔX, acceleration fluctuation value Δα, and motor load force F obtained in S11-S16 are z , motor working current I, motor real-time voltage value U, drag force F drag And the guide rail friction F c After cleaning, calibration and dimensionless processing, the first data set is generated by aggregation.

[0030] Preferably, step 2 includes:

[0031] S21. Arrange a multi-point wind speed measurement device in the operating environment of the linear motor module and use an ultrasonic wind speed sensor to collect the airflow velocity V w and the airflow direction angle θ w , air velocity V w Calculated by signal delay method:

[0032]

[0033] Where d is the propagation distance of the ultrasonic signal of the ultrasonic wind speed sensor, Δ t is the propagation time difference of the airflow to the ultrasonic signal; the airflow direction angle θ w It is obtained based on the triangular coordinate components of the ultrasonic wind speed sensor;

[0034] S22, using pressure sensor to measure the static pressure P in the operating environment static , calculate the air flow pressure P using the following formula w :

[0035] P w =P static +P dynamic ;

[0036] Where P dynamic represents the dynamic pressure and is calculated by the following formula:

[0037]

[0038] Where ρ represents the air density, V w is the air flow velocity obtained in S21;

[0039] S23, measuring the thickness D of tiny material deposits in the operating environment through surface deposition sensors s , deposition thickness D s Measured by laser reflection distance inside the surface deposition sensor:

[0040]

[0041] Where λ is the laser wavelength and θ is the reflection angle;

[0042] S24. Use charge sensor and electrostatic voltage measuring device to measure the electrostatic charge Q and electrostatic voltage value U in the operating environment static , calculate the electrostatic effect coefficient S by the following formula e :

[0043]

[0044] S25, collecting vibration signals in the operating environment through the environmental vibration sensor, and recording the vibration frequency spectrum value V f , vibration frequency spectrum value V f Extracted from the time domain signal by Fast Fourier Transform FFT;

[0045] S26, the air flow velocity V obtained in S21-S25 w , air flow pressure P w , deposition thickness D s , electrostatic effect coefficient S e And the vibration frequency spectrum value V f After data cleaning, denoising, calibration and dimensionless processing, the data are summarized to generate the second data set.

[0046] Preferably, step three includes:

[0047] S31, using a convolutional neural network to construct an initial model of the convolutional neural network, and using the first data group and the second data group to train and test the initial model of the convolutional neural network, and using the trained initial model of the convolutional neural network as a motor interference model, and using the intermediate layer output of the first data group and the second data group as a feature vector to identify feature information, and using the acquired feature information to train and test the motor interference model, and using the trained motor interference model as data operation prediction;

[0048] S32, extracting the displacement error ΔX, the acceleration fluctuation value Δα, and the motor load force F in the first data group z , motor working current I, motor real-time voltage value U, drag force F drag And the guide rail friction F c , after dimensionless processing, the motion stability index Sn is calculated by the following formula:

[0049]

[0050] Where a1, a2, a3, a4, a5 and a6 represent weight coefficients respectively;

[0051] S33, extracting the air flow velocity V in the second data group w , air flow pressure P w , deposition thickness D s , electrostatic effect coefficient S e And the vibration frequency spectrum value V f , after dimensionless processing, the environmental interference coefficient Ii is calculated by the following formula:

[0052] Ii=a7*V w +a8*P w +a9*D s +a 10 *Se +a 11 *V f ;

[0053] In the formula, a7, a8, a9, a 10 and a 11 They represent weight coefficients respectively.

[0054] Preferably, step three further includes: S34, calculating the motion stability index Sn and the environmental interference coefficient Ii by the following correlation formula to obtain the anti-interference compensation coefficient Cdc:

[0055]

[0056] In the formula, δ and β represent the weight coefficients of the environmental interference coefficient Ii and the motion stability index Sn respectively;

[0057] S35, preset an anti-interference threshold, and compare and evaluate the anti-interference compensation coefficient Cdc with the anti-interference threshold to obtain a first evaluation result, including:

[0058] If the anti-interference compensation coefficient Cdc> the anti-interference threshold, it means that the motion performance of the linear motor module is qualified, and a first qualified instruction is generated;

[0059] If the anti-interference threshold value*50%≤anti-interference compensation coefficient Cdc≤anti-interference threshold value, it means that the motion performance of the linear motor module is unqualified, and a first warning instruction is generated;

[0060] If the anti-interference compensation coefficient Cdc is less than the anti-interference threshold value*50%, it indicates that the motion performance of the linear motor module is unqualified, and a second warning instruction is generated.

[0061] Preferably, step three further includes: S36, generating a preliminary motion optimization control strategy according to the first evaluation result, including:

[0062] Generating a first operation instruction according to the first qualified instruction includes: maintaining the current motion control parameters of the linear motor module without additional intervention;

[0063] Generate a first control instruction according to the first warning instruction, including: limiting the motor load to 80-90% of the rated load of the motor, limiting the maximum speed of the motor to 90%-95% of the rated speed, and when the motor starts, temporarily setting the current to 110% of the rated current to overcome the inertial load, and gradually adjusting to 80% of the rated current after 5-10 minutes after starting;

[0064] A second control instruction is generated based on the second warning instruction, including: limiting the motor load to 70%-79% of the motor rated load, limiting the maximum speed of the motor to 80%-89% of the rated speed, and when the motor starts, the current is temporarily set to 120% of the rated current to overcome the inertial load, and gradually adjusted to 70% of the rated current after 11-20 minutes after starting.

[0065] Preferably, step four includes:

[0066] S41. After implementing the preliminary motion optimization control strategy, thermocouples or digital temperature sensors are arranged in the working environment of the linear motor module to measure the ambient temperature at different positions, ensuring that at least one temperature sensor is arranged in each corner of the working area of ​​the module. By collecting the temperature values ​​at each point, the temperature value T of the i-th sampling point is obtained. i , where i = 1, 2, ..., N, N represents the total number of sampling points;

[0067] Calculate the temperature difference of the total number of sampling points and calculate the average temperature gradient ΔT using the following formula f :

[0068]

[0069] Where, T ref,i represents the initial reference temperature value of the i-th sampling point, and the sampling frequency of the temperature sensor is set to 500 Hz;

[0070] S42. Arrange capacitive humidity sensors or thin film humidity sensors in the working environment of the linear motor module to measure the ambient humidity at different locations, ensuring that at least one humidity sensor is arranged in each corner of the working area of ​​the module, and obtain the humidity value H of the i-th sampling point by collecting the humidity values ​​at each point. i , where i = 1, 2, ..., N, N represents the total number of sampling points;

[0071] Calculate the humidity value difference of the total number of sampling points and calculate the average humidity gradient ΔH by the following formula f :

[0072]

[0073] In the formula, H ref,i represents the initial reference humidity value of the i-th sampling point, and the sampling frequency of the humidity sensor is set to 500 Hz;

[0074] S43. Based on the materials actually used in the linear motor module, including aluminum alloy, steel, carbon fiber composite material and glass fiber reinforced plastic GFRP, the material expansion caused by temperature is measured and the total motor expansion ΔL is calculated using the following formula total :

[0075]

[0076] Wherein, M represents the total number of types of materials contained in the linear motor module, for example: the shell and frame of the linear motor module are made of aluminum alloy, the motor core, stator and rotor of the linear motor module are made of steel, the load platform or slider of the linear motor module is made of carbon fiber composite material, and the supporting components and isolation electrical components of the linear motor module are made of glass fiber reinforced plastic.

[0077] L 0,k represents the initial volume of the kth material, am k Indicates the coefficient of thermal expansion, including:

[0078] When the linear motor module is made of aluminum alloy, k =23×10 -6 ℃ -1 ;

[0079] When the linear motor module is made of steel, am k =12×10 -6 ℃ -1 ;

[0080] When the linear motor module is made of carbon fiber composite material, am k =2.5×10 -6 ℃ -1 ;

[0081] When the linear motor module is made of glass fiber reinforced plastic GFRP, am k =10×10 -6 ℃ -1 ;

[0082] S44, use photoelectric sensor to record the light intensity signal value R in real time t , and calculate the fluctuation amplitude of the light intensity signal over time ΔR t :

[0083] ΔR t =max(R t )-min(R t );

[0084] In the formula, R t Indicates the light intensity signal value within time t, in lux;

[0085] And the light intensity signal value R t Perform fast Fourier transform FFT to obtain the frequency domain component F(f), and calculate the frequency domain fluctuation amplitude Φ based on the frequency domain component F(f) f :

[0086]

[0087] Where F(f) is the light intensity signal value R t The complex form in the frequency domain is used to represent the amplitude and phase of the frequency component. |F(f)| means taking the modulus of F(f) to obtain the amplitude corresponding to the frequency f. high and f low is the upper and lower limits of the frequency band, in Hz, in the frequency range f high to f low In the calculation, the spectrum amplitude |F(f)| is accumulated to calculate the total energy and obtain the frequency domain fluctuation amplitude Φ f ; df represents a small change in frequency;

[0088] The light intensity signal fluctuates over time ΔR t and the frequency domain fluctuation amplitude Φ f After dimensionless processing, the comprehensive amplitude of light source fluctuation Φ is calculated by the following formula: l :

[0089] Φ1=ΔR t *w1+Φ1*w2;

[0090] Where w1 and w2 represent the fluctuation amplitude of light intensity signal over time ΔR t and the frequency domain fluctuation amplitude Φ f The weight of , and w1+w2=1;

[0091] S45, the average temperature gradient ΔT obtained from S41-S44 f , average humidity gradient ΔH f , total motor expansion ΔL total And the comprehensive amplitude of light source fluctuation Φ l After cleaning, calibration and dimensionless processing, the third data set is generated by aggregation.

[0092] Preferably, step 4 further comprises:

[0093] S46, extracting the average temperature gradient ΔT in the third data group f , average humidity gradient ΔH f , total motor expansion ΔL total And the comprehensive amplitude of light source fluctuation Φ l , after dimensionless processing, the motor characterization interference sensitivity coefficient Ch is calculated by the following formula:

[0094] Ch=a 12 *ΔT f +a 13 *ΔH f +a 14 *ΔL total +a15 *φ1;

[0095] In the formula, a 12 、a 13 、a 14 and a 15 Respectively represent weight coefficients;

[0096] S47, preset a sensitivity threshold, and compare the motor characterization interference sensitivity coefficient Ch with the sensitivity threshold to obtain a motion abnormality risk assessment result, including:

[0097] If the motor characterization interference sensitivity coefficient Ch ≥ the sensitivity threshold, it means that after the preliminary motion optimization control strategy, the motor performance has abnormal behavior after adjustment, and a correction instruction is generated;

[0098] If the motor characterization interference sensitivity coefficient Ch is less than the sensitivity threshold, the preliminary motion optimization control strategy indicates that the motor performance does not have abnormal behavior after adjustment.

[0099] Preferably, the correction instruction includes:

[0100] The first control instruction is modified, including: limiting the motor load to 75-85% of the rated load of the motor, limiting the maximum speed of the motor to 85%-90% of the rated speed, and when the motor starts, the current is temporarily set to 115% of the rated current to overcome the inertial load, and gradually adjusted to 75% of the rated current after 7-12 minutes after starting;

[0101] The second control instruction is modified, including: limiting the motor load to 60%-70% of the motor rated load, limiting the maximum speed of the motor to 75%-84% of the rated speed, and when the motor starts, the current is temporarily set to 125% of the rated current to overcome the inertial load, and gradually adjusted to 65% of the rated current after 15-25 minutes after starting;

[0102] If the motor characterization interference sensitivity coefficient Ch is still ≥ the sensitivity threshold, an environmental control instruction is generated, including: cleaning the sediment outside the motor module, adding an electrostatic shielding device and a vibration isolation device, and installing a wind pressure regulating valve to adjust the airflow pressure.

[0103] The present invention provides an anti-interference linear motor module motion control method, which has the following beneficial effects:

[0104] (1) This anti-interference linear motor module motion control method can significantly reduce the impact of external interference factors such as air flow fluctuations, temperature and humidity changes, environmental vibrations, etc. on the motion trajectory of the linear motor module by real-time monitoring and identification of these factors, thereby improving the accuracy and stability of motion control and ensuring that the system can operate efficiently in complex environments.

[0105] (2) This anti-interference linear motor module motion control method, through the early warning and control strategy for interference factors, the system can adjust the working parameters of the motor in time to avoid equipment damage caused by overload, abnormal movement or adverse environmental conditions, thereby effectively extending the service life of the motor module and related systems and reducing maintenance costs.

[0106] (3) This anti-interference linear motor module motion control method monitors and analyzes the motor's interference sensitivity coefficient in real time, promptly discovers potential risks during system operation, generates correction or environmental control instructions in advance, avoids system failures or safety accidents caused by abnormal motor performance, and ensures the safety of industrial production.

[0107] (4) This anti-interference linear motor module motion control method combines the changes in the external environment and the motor state, and the system can automatically adjust the operating parameters, such as load, speed, current, etc., thereby enhancing the adaptive ability of the linear motor module. Especially in application scenarios with high speed and high precision requirements, it can effectively cope with the challenges brought by environmental changes and ensure the efficient and stable operation of the production process. BRIEF DESCRIPTION OF THE DRAWINGS

[0108] Figure 1 The figure is a schematic diagram of the steps of an anti-interference linear motor module motion control method of the present invention. DETAILED DESCRIPTION

[0109] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0110] Example 1

[0111] See also Figure 1 The present invention provides an anti-interference linear motor module motion control method, comprising the following steps:

[0112] Step 1: Real-time monitoring of the displacement error and acceleration changes of the linear motor module during operation to collect displacement error ΔX, acceleration fluctuation value Δα, motor load force F z , motor working current I, motor real-time voltage value U, drag force F drag And the guide rail friction F c , generating a first data set;

[0113] Step 2: Collect airflow disturbance parameters in the external environment, including airflow velocity V w , air flow pressure Pw , deposition thickness D s , electrostatic effect coefficient S e And the vibration frequency spectrum value V f , generating a second data set;

[0114] Step 3: After establishing and training the motor interference model using neural network technology, the first data group and the second data group are analyzed and calculated to obtain the motion stability index Sn and the environmental interference coefficient Ii, and the motion stability index Sn and the environmental interference coefficient Ii are associated to generate and evaluate the anti-interference compensation coefficient Cdc to generate a preliminary motion optimization control strategy;

[0115] Step 4: After implementing the preliminary motion optimization control strategy, collect the characterization environment-related data of the linear motor module to obtain the average temperature gradient ΔT f , average humidity gradient ΔH f , total motor expansion ΔL total And the comprehensive amplitude of light source fluctuation Φ l After generating the third data group, the motor characterization interference sensitivity coefficient Ch is constructed, and the motor characterization interference sensitivity coefficient Ch is evaluated to obtain the motion abnormality risk assessment result; according to the motion abnormality risk assessment result, the preliminary motion optimization control strategy is corrected to optimize the dynamic performance of the linear motor module.

[0116] In this embodiment, the displacement error ΔX, acceleration fluctuation value Δα, and motor load force F of the motor module during operation are monitored and analyzed in real time. z , motor working current I, motor real-time voltage value U, drag force F drag And the guide rail friction F c Multiple parameters, as well as external environmental factors (such as air velocity V w , air flow pressure P w , deposition thickness D s and electrostatic effect coefficient S e ), the present invention can comprehensively evaluate the motion state of the motor module, thereby effectively reducing the deviation of the motion trajectory and significantly improving the motion stability of the motor module.

[0117] By collecting external environmental interference parameters (airflow interference, deposition thickness, environmental vibration, etc.) and combining neural network technology to establish an interference model, the motion control strategy of the motor module can be dynamically adjusted to compensate for different types of interference factors in real time. This targeted control method effectively reduces the impact of external interference on the motion performance of the motor module and enhances its adaptability in complex environments. By evaluating the risk of motion abnormality in real time, the present invention can timely identify potential sources of interference and abnormal behavior, avoiding system failures or performance degradation caused by interference or unstable factors. The correction of the preliminary motion optimization control strategy further reduces the operating risk of the system in a complex environment and improves the safety and reliability of the equipment. Under high-speed operation and harsh environments, the motor module can maintain high-precision motion control, significantly reduce the error or loss caused by interference, and improve the production efficiency of the overall system. The stability and reliability of the system are enhanced, which not only extends the service life of the equipment, but also reduces the frequency of maintenance and adjustment, thereby saving costs.

[0118] The present invention further optimizes the motion control strategy by constructing the motor characterization interference sensitivity coefficient Ch and evaluating it based on actual operation data. Different from the traditional fixed control method, the invention innovatively adopts a dynamic adjustment mechanism to continuously optimize the control parameters during the movement of the motor module, thereby improving the dynamic response performance and long-term stability of the system.

[0119] Example 2

[0120] This embodiment is explained in Example 1. Specifically, step 1 includes:

[0121] S11. Set the target mark point on the motion path of the load platform of the linear motor module and use the laser displacement sensor to measure the actual position X of the module. actual and the expected position X target , the displacement error ΔX is calculated by the following formula:

[0122] ΔX=|X actual -X target |;

[0123] Among them, the output signal of the laser displacement sensor is transmitted to the control system in real time with a sampling frequency of 1000Hz; the laser displacement sensor has high precision and can effectively capture the position changes of the motor module during movement in real time, thereby providing accurate feedback data for subsequent control strategies and improving the system's motion accuracy and stability.

[0124] S12. Install a three-axis acceleration sensor on the load platform of the linear motor module and record the acceleration values ​​α in the x-axis, y-axis and z-axis directions. x , α y , α z, the acceleration fluctuation value Δα is calculated by the following formula:

[0125]

[0126] In the formula, and They represent the reference average acceleration thresholds in the x-axis, y-axis, and z-axis directions, respectively; this helps to dynamically capture the vibration and motion instability of the system, identify disturbances and anomalies that may occur during motion, and accelerate feedback adjustments to reduce errors and improve the stability and responsiveness of the system.

[0127] S13. Install a force sensor at the driving end of the linear motor module and collect the electrical signal V output by the force sensor. f , and calculate the motor load force F by the following formula z :

[0128] F z =k f *V f ;

[0129] In the formula, k f It represents the force-to-electricity conversion coefficient of the force sensor, which is obtained through force sensor calibration. By obtaining the data of the motor load force, timely measures can be taken when the load is too large to prevent damage to the equipment and improve the durability and reliability of the system.

[0130] S14, using Hall current sensor to collect output current signal V i The motor operating current I is calculated using the following formula:

[0131] I=k i *V i ;

[0132] In the formula, k i is the current conversion coefficient of the Hall current sensor; and the voltage sensor is used to collect the real-time voltage value U of the motor. Accurate collection of current signals helps to diagnose abnormal conditions in motor operation (such as excessive or insufficient current), and provides real-time feedback for adjusting the control strategy, effectively improving the stability and energy saving of the system.

[0133] S15. Collect the output torque T, drive efficiency η, and drive equivalent radius r of the linear motor module, and calculate the drag force F using the following formula drag :

[0134]

[0135] S16, according to the drag force F drag and the motor load force F obtained in S13 z, the guide rail friction force F is calculated by the following formula c :

[0136] F c =F drag -F z ;

[0137] Where, the guide rail friction force F c The friction force of the linear motor module during the movement of the module guide is the main resistance in the equilibrium state; calculating the drag force helps to understand the interaction between the motor and the system, timely identify and reduce the motion error caused by insufficient drive or imbalance, thereby improving the drive efficiency and motion stability of the motor. Friction has a direct impact on the motion stability and power consumption of the motor. Real-time monitoring of friction can provide a reference for adjusting the motor output power and control strategy, ensuring efficient operation of the system and reducing unnecessary energy loss.

[0138] S17, the displacement error ΔX, acceleration fluctuation value Δα, and motor load force F obtained in S11-S16 are z , motor working current I, motor real-time voltage value U, drag force F drag And the guide rail friction F c After cleaning, calibration and dimensionless processing, the first data set is generated by aggregation.

[0139] Example 3

[0140] This embodiment is an explanation of the embodiment 1. Specifically, step 2 includes:

[0141] S21. Arrange a multi-point wind speed measurement device in the operating environment of the linear motor module and use an ultrasonic wind speed sensor to collect the airflow velocity V w and the airflow direction angle θ w , air velocity V w Calculated by signal delay method:

[0142]

[0143] Where d is the propagation distance of the ultrasonic signal of the ultrasonic wind speed sensor, Δ t is the propagation time difference of the airflow to the ultrasonic signal; the airflow direction angle θ w It is obtained based on the triangular coordinate components of the ultrasonic wind speed sensor; the airflow velocity is calculated using the signal delay method, which provides accurate flow velocity data, and the acquisition of the airflow direction angle further enhances the understanding of the airflow directionality, which helps the control system to more accurately respond to airflow interference, thereby optimizing the motion stability of the motor module.

[0144] S22, using pressure sensor to measure the static pressure P in the operating environmentstatic , calculate the air flow pressure P using the following formula w :

[0145] P w =P static +P dynamic ;

[0146] Where P dynamic represents the dynamic pressure and is calculated by the following formula:

[0147]

[0148] Where ρ represents the air density, V w The airflow velocity obtained in S21; using a pressure sensor to measure static pressure and calculate airflow pressure can accurately obtain the airflow pressure changes in the environment, which is crucial for evaluating the interference of airflow on the linear motor module. The dynamic pressure of the airflow reflects the possible impact of airflow changes on the system. Real-time monitoring of these changes helps to detect airflow disturbances in advance, so as to adjust the motor control strategy in time and reduce motion errors and system instability caused by airflow fluctuations.

[0149] S23, measuring the thickness D of tiny material deposits in the operating environment through surface deposition sensors s , deposition thickness D s Measured by laser reflection distance inside the surface deposition sensor:

[0150]

[0151] Where λ is the laser wavelength and θ is the reflection angle. The surface deposition sensor can monitor the deposition thickness of tiny substances in the operating environment in real time, which is very important for identifying potential deposition interference (such as dust or particulate matter). The deposition of these tiny substances will affect the surface friction, heat conduction and mechanical stability of the motor module. By timely detecting the deposition thickness, the motion error caused by material accumulation can be effectively avoided, thereby optimizing motion control and ensuring the stability and high precision of the motor module in long-term operation.

[0152] S24. Use charge sensor and electrostatic voltage measuring device to measure the electrostatic charge Q and electrostatic voltage value U in the operating environment static , calculate the electrostatic effect coefficient S by the following formula e :

[0153]

[0154] S25, collecting vibration signals in the operating environment through the environmental vibration sensor, and recording the vibration frequency spectrum value V f , vibration frequency spectrum value V fExtracted from the time domain signal through Fast Fourier Transform FFT; the impact of electrostatic effect on precision control systems cannot be ignored. By using charge sensors and electrostatic voltage measuring devices to monitor the amount of static charge and electrostatic voltage in the operating environment in real time, the intensity of the electrostatic effect can be quantified to prevent the reduction of motor control accuracy caused by static accumulation. The calculation of the electrostatic effect coefficient helps to accurately identify the impact of static electricity on motor movement and system performance, providing data support for the design of more efficient anti-static interference measures to avoid failures or damage caused by static electricity.

[0155] S26, the air flow velocity V obtained in S21-S25 w , air flow pressure P w , deposition thickness D s , electrostatic effect coefficient S e And the vibration frequency spectrum value V f After data cleaning, denoising, calibration and dimensionless processing, the data are summarized to generate the second data set.

[0156] In the present embodiment, environmental vibration has a great influence on the motion stability of the linear motor module, especially in a high-speed or high-precision operating environment. The vibration signal is collected by an environmental vibration sensor, and the vibration frequency spectrum value is extracted from the time domain signal by fast Fourier transform (FFT), so that the spectrum characteristics of the environmental vibration can be monitored in real time. By analyzing the vibration spectrum, the vibration source that may affect the motion trajectory of the motor module can be identified, and corresponding compensation measures can be taken to effectively reduce the impact of vibration on the motor motion accuracy. Steps S21 to S26 provide comprehensive environmental data support for the linear motor module through accurate monitoring and data processing of various environmental interference factors (airflow, pressure, deposition, static electricity, vibration, etc.). These data can help to identify and analyze the interference of the external environment to the system in real time, so as to realize effective interference compensation and optimization strategies in the control system, and improve the motion stability and accuracy of the system.

[0157] Example 4

[0158] This embodiment is an explanation of the embodiment 1. Specifically, step 3 includes:

[0159] S31, using a convolutional neural network to construct an initial model of the convolutional neural network, and using the first data group and the second data group to train and test the initial model of the convolutional neural network, and using the trained initial model of the convolutional neural network as a motor interference model, and using the intermediate layer output of the first data group and the second data group as a feature vector to identify feature information, and using the acquired feature information to train and test the motor interference model, and using the trained motor interference model as data operation prediction;

[0160] S32. Extract the displacement error ΔX, acceleration fluctuation value Δα, motor load force F in the first data set z , motor operating current I, real-time motor voltage value U, driving force F drag , and guide rail friction force F c . After dimensionless processing, calculate and obtain the motion stability index Sn through the following formula:

[0161]

[0162] In the formula, a1, a2, a3, a4, a5, and a6 respectively represent weight coefficients, where 0 < a1 < 1, 0 < a2 < 1, 0 < a3 < 1, 0 < a4 < 1, 0 < a5 < 1, 0 < a6 < 1, and a1 + a2 + a3 + a4 + a5 + a6 = 1. The control system can evaluate the motion status of the motor in real time according to the motion stability index Sn, so as to make timely adjustments and reduce the influence brought by motion instability.

[0163] S33. Extract the air flow velocity V, air flow pressure P, deposition thickness D, electrostatic effect coefficient S, and vibration frequency spectrum value V in the second data set w , air flow pressure P w , deposition thickness D s , electrostatic effect coefficient S e , and vibration frequency spectrum value V f . After dimensionless processing, calculate the environmental interference coefficient Ii through the following formula:

[0164] Ii = a7 * V w + a8 * P w + a9 * D s + a 10 * S e + a 11 * V f ;

[0165] In the formula, a7, a8, a9, a 10 , and a 11 respectively represent weight coefficients, where 0 < a7 < 1, 0 < a8 < 1, 0 < a9 < 1, 0 < a 10 < 1, 0 < a 11 < 1, and a7 + a8 + a9 + a 10 + a 11 = 1. The environmental interference coefficient Ii can reflect the influence of environmental factors on the performance of the motor module and identify the interference intensity under different environmental conditions. By monitoring and evaluating the environmental interference coefficient in real time, compensation measures can be taken in advance to avoid the negative impact of the external environment on the performance of the motor module.

[0166] S34. Calculate and obtain the anti-interference compensation coefficient Cdc by using the following correlation formula for the motion stability index Sn and the environmental interference coefficient Ii:

[0167]

[0168] In the formula, δ and β represent the weight coefficients of the environmental interference coefficient Ii and the motion stability index Sn, respectively, 0<δ<1, 0<β<1, and δ+β=1; the anti-interference compensation coefficient Cdc is calculated by combining the motion stability index Sn and the environmental interference coefficient Ii. This coefficient can comprehensively reflect the motion stability and anti-interference ability of the motor module in the current environment. By accurately calculating Cdc, it can ensure that the control system makes scientific intervention decisions, reduce the interference of external factors on the motor module, and improve motion accuracy and stability.

[0169] S35, preset an anti-interference threshold, and compare and evaluate the anti-interference compensation coefficient Cdc with the anti-interference threshold to obtain a first evaluation result, including:

[0170] If the anti-interference compensation coefficient Cdc> the anti-interference threshold, it means that the motion performance of the linear motor module is qualified, and a first qualified instruction is generated;

[0171] If the anti-interference threshold value*50%≤anti-interference compensation coefficient Cdc≤anti-interference threshold value, it means that the motion performance of the linear motor module is unqualified, and a first warning instruction is generated;

[0172] If the anti-interference compensation coefficient Cdc is less than the anti-interference threshold value*50%, it indicates that the motion performance of the linear motor module is unqualified, and a second warning instruction is generated.

[0173] S36: Generate a preliminary motion optimization control strategy based on the first evaluation result, including:

[0174] Generating a first operation instruction according to the first qualified instruction includes: maintaining the current motion control parameters of the linear motor module without additional intervention;

[0175] Generate a first control instruction according to the first warning instruction, including: limiting the motor load to 80-90% of the rated load of the motor, limiting the maximum speed of the motor to 90%-95% of the rated speed, and when the motor starts, temporarily setting the current to 110% of the rated current to overcome the inertial load, and gradually adjusting to 80% of the rated current after 5-10 minutes after starting;

[0176] A second control instruction is generated based on the second warning instruction, including: limiting the motor load to 70%-79% of the motor rated load, limiting the maximum speed of the motor to 80%-89% of the rated speed, and when the motor starts, the current is temporarily set to 120% of the rated current to overcome the inertial load, and gradually adjusted to 70% of the rated current after 11-20 minutes after starting.

[0177] In this embodiment, the first warning instruction generates the first control instruction: appropriately limiting the motor load and speed, and temporarily increasing the current at startup, which helps to overcome the inertial load, avoid equipment overload, and reduce losses.

[0178] The second warning instruction generates the second control instruction: by further limiting the motor load and speed and increasing the starting current, it helps the motor start smoothly under unstable conditions, avoids long-term overload operation, and extends the service life of the equipment.

[0179] The whole process combines convolutional neural networks for model training and prediction, and then calculates the motion stability index, environmental interference coefficient, and anti-interference compensation coefficient to finally generate an optimized control strategy that can effectively respond to different environmental interferences and improve the operating stability and anti-interference ability of the motor module. By dynamically adjusting the control parameters, refined control and interference compensation can be achieved, thereby optimizing the performance of the motor and ensuring that the system remains efficient and stable in complex and changing working environments.

[0180] Example 5

[0181] This embodiment is explained in Example 4. Specifically, step 4 includes:

[0182] S41. After implementing the preliminary motion optimization control strategy, thermocouples or digital temperature sensors are arranged in the working environment of the linear motor module to measure the ambient temperature at different positions, ensuring that at least one temperature sensor is arranged in each corner of the working area of ​​the module. By collecting the temperature values ​​at each point, the temperature value T of the i-th sampling point is obtained. i , where i = 1, 2, ..., N, N represents the total number of sampling points;

[0183] Calculate the temperature difference of the total number of sampling points and calculate the average temperature gradient ΔT using the following formula f :

[0184]

[0185] Where, T ref,i represents the initial reference temperature value of the i-th sampling point, and the sampling frequency of the temperature sensor is set to 500 Hz;

[0186] Multiple temperature sensors are placed in the working environment of the linear motor module to monitor the temperature changes at various locations in real time. By calculating the temperature difference between each sampling point and obtaining the average temperature gradient, the temperature distribution of the motor module under different environmental conditions can be accurately grasped. This is of great significance for evaluating the working state of the motor under different temperature conditions, predicting the thermal expansion effect, and optimizing the heat dissipation system. Real-time temperature monitoring can detect abnormal temperature fluctuations in time and avoid the negative impact of excessive temperature on motor performance and life.

[0187] S42. Arrange capacitive humidity sensors or thin film humidity sensors in the working environment of the linear motor module to measure the ambient humidity at different locations, ensuring that at least one humidity sensor is arranged in each corner of the working area of ​​the module, and obtain the humidity value H of the i-th sampling point by collecting the humidity values ​​at each point. i , where i = 1, 2, ..., N, N represents the total number of sampling points;

[0188] Calculate the humidity value difference of the total number of sampling points and calculate the average humidity gradient ΔH by the following formula f :

[0189]

[0190] In the formula, H ref,i represents the initial reference humidity value of the i-th sampling point, and the sampling frequency of the humidity sensor is set to 500 Hz;

[0191] By deploying humidity sensors, we can monitor the changes in humidity in the working environment. Humidity is an important factor affecting the stability of the motor system, especially in corrosive or humid environments. By calculating the difference in humidity values ​​and obtaining the average humidity gradient, we can fully evaluate the impact of humidity on the motor module. This can not only predict the damage to the motor electrical components caused by excessive humidity, but also provide data support for the design of the humidity control system to ensure the normal operation of the system in a high humidity environment.

[0192] S43. Based on the materials actually used in the linear motor module, including aluminum alloy, steel, carbon fiber composite material and glass fiber reinforced plastic GFRP, the material expansion caused by temperature is measured and the total motor expansion ΔL is calculated using the following formula total :

[0193]

[0194] Where M represents the total number of materials contained in the linear motor module, L 0,k represents the initial volume of the kth material, am k Indicates the coefficient of thermal expansion, including:

[0195] When the linear motor module is made of aluminum alloy, k =23×10 -6 ℃ -1 ;

[0196] When the linear motor module is made of steel, am k =12×10 -6 ℃ -1 ;

[0197] When the linear motor module is made of carbon fiber composite material, am k =2.5×10 -6 ℃ -1 ;

[0198] When the linear motor module is made of glass fiber reinforced plastic GFRP, am k =10×10 -6 ℃ -1 ; By measuring the material expansion caused by temperature and calculating the total expansion of the motor module, the thermal expansion effect of the motor module material under different temperature conditions can be evaluated. This calculation can help determine the impact of temperature changes on the motor structure, especially the degree of expansion when using different materials such as aluminum alloy, steel, carbon fiber composite materials and glass fiber reinforced plastics. By accurately controlling the expansion of different materials, the design of the motor module can be optimized, the structural changes caused by expansion can be reduced, and the stable operation of the motor can be ensured. S44. Use a photoelectric sensor to record the light intensity signal value R in real time t , and calculate the fluctuation amplitude of the light intensity signal over time ΔR t :

[0199] ΔR t =max(R t )-min(R t );

[0200] In the formula, R t Indicates the light intensity signal value within time t, in lux;

[0201] And the light intensity signal value R t Perform fast Fourier transform FFT to obtain the frequency domain component F(f), and calculate the frequency domain fluctuation amplitude Φ based on the frequency domain component F(f) f :

[0202]

[0203] Where F(f) is the light intensity signal value R t The complex form in the frequency domain is used to represent the amplitude and phase of the frequency component. |F(f)| means taking the modulus of F(f) to obtain the amplitude corresponding to the frequency f. high and f low is the upper and lower limits of the frequency band, in Hz, in the frequency range f high to f low In the calculation, the spectrum amplitude |F(f)| is accumulated to calculate the total energy and obtain the frequency domain fluctuation amplitude Φ f ; df represents a small change in frequency;

[0204] The light intensity signal fluctuates over time ΔR t and the frequency domain fluctuation amplitude Φ fAfter dimensionless processing, the comprehensive amplitude of light source fluctuation Φ is calculated by the following formula: l :

[0205] Φ1=ΔR t *w1+Φ f *w2;

[0206] Where w1 and w2 represent the fluctuation amplitude of light intensity signal over time ΔR t and the frequency domain fluctuation amplitude Φ f The weight of w1+w2=1; the impact of light source fluctuations on the motor system is usually reflected in the perception of visual sensors or photoelectric sensors. By recording the light intensity signal in real time and calculating its fluctuation amplitude over time, we can understand the potential interference of changes in lighting conditions on the motor system. Using fast Fourier transform (FFT) to perform frequency domain analysis on the light intensity signal can identify and quantify periodic fluctuations in lighting changes and predict the frequency and amplitude of fluctuations that may interfere with the motor module. This analysis can provide a basis for the control and compensation of light source interference to ensure the stable operation of the system.

[0207] S45, the average temperature gradient ΔT obtained from S41-S44 f , average humidity gradient ΔH f , total motor expansion ΔL total And the comprehensive amplitude of light source fluctuation Φ l After cleaning, calibration and dimensionless processing, the third data set is generated by aggregation.

[0208] Example 6

[0209] This embodiment is explained in Embodiment 5. Specifically, step 4 also includes:

[0210] S46, extracting the average temperature gradient ΔT in the third data group f , average humidity gradient ΔH f , total motor expansion ΔL total And the comprehensive amplitude of light source fluctuation Φ l , after dimensionless processing, the motor characterization interference sensitivity coefficient Ch is calculated by the following formula:

[0211] Ch=a 12 *ΔT f +a 13 *ΔH f +a 14 *ΔL total +a 15 *Φ1;

[0212] In the formula, a 12 、a 13 、a 14 and a15 Represent weight coefficients, 0 12 <1,0 13 <1,0 14 <1,0 15 <1, and a 12 +a 13 +a 14 +a 15 =1;

[0213] S47, preset a sensitivity threshold, and compare the motor characterization interference sensitivity coefficient Ch with the sensitivity threshold to obtain a motion abnormality risk assessment result, including:

[0214] If the motor characterization interference sensitivity coefficient Ch ≥ the sensitivity threshold, it means that after the preliminary motion optimization control strategy, the motor performance has abnormal behavior after adjustment, and a correction instruction is generated;

[0215] If the motor characterization interference sensitivity coefficient Ch is less than the sensitivity threshold, the preliminary motion optimization control strategy indicates that the motor performance does not have abnormal behavior after adjustment.

[0216] The revised directives include:

[0217] The first control instruction is modified, including: limiting the motor load to 75-85% of the rated load of the motor, limiting the maximum speed of the motor to 85%-90% of the rated speed, and when the motor starts, the current is temporarily set to 115% of the rated current to overcome the inertial load, and gradually adjusted to 75% of the rated current after 7-12 minutes after starting;

[0218] The second control instruction is modified, including: limiting the motor load to 60%-70% of the motor rated load, limiting the maximum speed of the motor to 75%-84% of the rated speed, and when the motor starts, the current is temporarily set to 125% of the rated current to overcome the inertial load, and gradually adjusted to 65% of the rated current after 15-25 minutes after starting;

[0219] If the motor characterization interference sensitivity coefficient Ch is still ≥ the sensitivity threshold, an environmental control instruction is generated, including: cleaning the sediment outside the motor module, adding an electrostatic shielding device and a vibration isolation device, and installing a wind pressure regulating valve to adjust the airflow pressure.

[0220] ​​​​In this embodiment, this embodiment can monitor the operating status of the motor in real time and detect potential performance anomalies in a timely manner by calculating and evaluating the interference sensitivity coefficient of the motor. By generating correction instructions and adjusting the load, speed and current of the motor, the risk of damage to the motor due to overload or abnormal operation can be effectively reduced, and the working stability and service life of the motor can be improved. At the same time, when the correction instructions are invalid, the system further improves the working environment of the motor through environmental control instructions such as cleaning sediments, adding electrostatic shielding and vibration isolation devices, etc., to ensure that the motor is always in the best working state. This control strategy effectively improves the reliability and intelligence level of the motor system.

[0221] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0222] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula that is close to the actual value. The coefficients in the formula are set by technical personnel in this field according to actual conditions. The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited to this. Any technical personnel familiar with the technical field within the technical scope disclosed by the present invention, according to the technical solution and the inventive concept of the present invention, make equivalent replacement or change, which should be covered within the protection scope of the present invention.

Claims

1. A method for controlling motion of an anti-interference linear motor module, characterized in that: The following steps are involved: Step 1: Real-time monitoring of the displacement error and acceleration changes of the linear motor module during operation to collect displacement error ΔX, acceleration fluctuation value Δα, motor load force F z , motor working current I, motor real-time voltage value U, drag force F drag And the guide rail friction F c , generating a first data set; Step 2: Collect airflow disturbance parameters in the external environment, including airflow velocity V w , air flow pressure P w , deposition thickness D s , electrostatic effect coefficient S e And the vibration frequency spectrum value V f , generating a second data set; Step 3: After establishing and training the motor interference model using neural network technology, the first data group and the second data group are analyzed and calculated to obtain the motion stability index Sn and the environmental interference coefficient Ii, and the motion stability index Sn and the environmental interference coefficient Ii are associated to generate and evaluate the anti-interference compensation coefficient Cdc to generate a preliminary motion optimization control strategy; Step 4: After implementing the preliminary motion optimization control strategy, collect the characterization environment-related data of the linear motor module to obtain the average temperature gradient ΔT f , average humidity gradient ΔH f , total motor expansion ΔL total And the comprehensive amplitude of light source fluctuation Φ l After generating the third data group, the motor characterization interference sensitivity coefficient Ch is constructed, and the motor characterization interference sensitivity coefficient Ch is evaluated to obtain the motion abnormality risk assessment result; according to the motion abnormality risk assessment result, the preliminary motion optimization control strategy is corrected to optimize the dynamic performance of the linear motor module.

2. The anti-interference linear motor module motion control method according to claim 1, characterized in that: The step one comprises: S11. Set the target mark point on the motion path of the load platform of the linear motor module and use the laser displacement sensor to measure the actual position X of the module. actual and the expected position X target , the displacement error ΔX is calculated by the following formula: ΔX=|X actual -X target |; Among them, the output signal of the laser displacement sensor is transmitted to the control system in real time, and the sampling frequency is 1000Hz; S12. Install a three-axis acceleration sensor on the load platform of the linear motor module and record the acceleration values ​​α in the x-axis, y-axis and z-axis directions. x , α y , α z , the acceleration fluctuation value Δα is calculated by the following formula: In the formula, and Respectively represent the reference average acceleration thresholds in the x-axis, y-axis and z-axis directions; S13. Install a force sensor at the driving end of the linear motor module and collect the electrical signal V output by the force sensor. f , and calculate the motor load force F by the following formula z : F z =k f *V f ; In the formula, k f It represents the force-to-electricity conversion coefficient of the force sensor, which is obtained through the force sensor calibration; S14, using Hall current sensor to collect output current signal V i The motor operating current I is calculated using the following formula: I=k i *V i ; In the formula, k i is the current conversion coefficient of the Hall current sensor; and a voltage sensor is used to collect the real-time voltage value U of the motor.

3. The anti-interference linear motor module motion control method according to claim 2, characterized in that: The step one also includes: S15. Collect the output torque T, drive efficiency η, and drive equivalent radius r of the linear motor module, and calculate the drag force F using the following formula drag : S16, according to the drag force F drag and the motor load force F obtained in S13 z , the guide rail friction force F is calculated by the following formula c : F c =F drag -F z ; Where, the guide rail friction force F c It indicates the friction force of the linear motor module guide rail during the movement, which is the main resistance in the equilibrium state; S17, the displacement error ΔX, acceleration fluctuation value Δα, and motor load force F obtained in S11-S16 are z , motor working current I, motor real-time voltage value U, drag force F drag And the guide rail friction F c After cleaning, calibration and dimensionless processing, the first data set is generated by aggregation.

4. The anti-interference linear motor module motion control method according to claim 1, characterized in that: The second step comprises: S21. Arrange a multi-point wind speed measurement device in the operating environment of the linear motor module and use an ultrasonic wind speed sensor to collect the airflow velocity V w and the airflow direction angle θ w , air velocity V w Calculated by signal delay method: Where d is the propagation distance of the ultrasonic signal of the ultrasonic wind speed sensor, Δ t is the propagation time difference of the airflow to the ultrasonic signal; the airflow direction angle θ w It is obtained based on the triangular coordinate components of the ultrasonic wind speed sensor; S22, using pressure sensor to measure the static pressure P in the operating environment static , calculate the air flow pressure P using the following formula w : P w =P static +P dynamic ; Where P dynamic represents the dynamic pressure and is calculated by the following formula: Where ρ represents the air density, V w is the air flow velocity obtained in S21; S23, measuring the thickness D of tiny material deposits in the operating environment through surface deposition sensors s , deposition thickness D s Measured by laser reflection distance inside the surface deposition sensor: Where λ is the laser wavelength and θ is the reflection angle; S24. Use charge sensor and electrostatic voltage measuring device to measure the electrostatic charge Q and electrostatic voltage value U in the operating environment static , calculate the electrostatic effect coefficient S by the following formula e : S25, collecting vibration signals in the operating environment through the environmental vibration sensor, and recording the vibration frequency spectrum value V f , vibration frequency spectrum value V f Extracted from the time domain signal by Fast Fourier Transform FFT; S26, the air flow velocity V obtained in S21-S25 w , air flow pressure P w , deposition thickness D s , electrostatic effect coefficient S e And the vibration frequency spectrum value V f After data cleaning, denoising, calibration and dimensionless processing, the data are summarized to generate the second data set.

5. The anti-interference linear motor module motion control method according to claim 1, characterized in that: Step three includes: S31, using a convolutional neural network to construct an initial model of the convolutional neural network, and using the first data group and the second data group to train and test the initial model of the convolutional neural network, and using the trained initial model of the convolutional neural network as a motor interference model, and using the intermediate layer output of the first data group and the second data group as a feature vector to identify feature information, and using the acquired feature information to train and test the motor interference model, and using the trained motor interference model as data operation prediction; S32, extracting the displacement error ΔX, the acceleration fluctuation value Δα, and the motor load force F in the first data group z , motor working current I, motor real-time voltage value U, drag force F drag And the guide rail friction F c , after dimensionless processing, the motion stability index Sn is calculated by the following formula: Where a1, a2, a3, a4, a5 and a6 represent weight coefficients respectively; S33, extracting the air flow velocity V in the second data group w , air flow pressure P w , deposition thickness D s , electrostatic effect coefficient S e And the vibration frequency spectrum value V f , after dimensionless processing, the environmental interference coefficient Ii is calculated by the following formula: <h2 style=";text-align:left;direction:ltr">II=a7*V<h2 style=";text-align:left;direction:ltr"> w <h2 style=";text-align:left;direction:ltr"> +a8*P<h2 style=";text-align:left;direction:ltr"> w <h2 style=";text-align:left;direction:ltr"> +a9*D<h2 style=";text-align:left;direction:ltr"> s <h2 style=";text-align:left;direction:ltr"> +a<h2 style=";text-align:left;direction:ltr"> 10 <h2 style=";text-align:left;direction:ltr"> *S<h2 style=";text-align:left;direction:ltr"> e <h2 style=";text-align:left;direction:ltr"> +a<h2 style=";text-align:left;direction:ltr"> 11 <h2 style=";text-align:left;direction:ltr"> *V<h2 style=";text-align:left;direction:ltr"> f <h2 style=";text-align:left;direction:ltr"> ; In the formula, a7, a8, a9, a 10 and a 11 They represent weight coefficients respectively.

6. The anti-interference linear motor module motion control method according to claim 5, characterized in that: The step three also includes: S34, calculating the motion stability index Sn and the environmental interference coefficient Ii by the following correlation formula to obtain the anti-interference compensation coefficient Cdc: In the formula, δ and β represent the weight coefficients of the environmental interference coefficient Ii and the motion stability index Sn respectively; S35, preset an anti-interference threshold, and compare and evaluate the anti-interference compensation coefficient Cdc with the anti-interference threshold to obtain a first evaluation result, including: If the anti-interference compensation coefficient Cdc> the anti-interference threshold, it means that the motion performance of the linear motor module is qualified, and a first qualified instruction is generated; If the anti-interference threshold value*50%≤anti-interference compensation coefficient Cdc≤anti-interference threshold value, it means that the motion performance of the linear motor module is unqualified, and a first warning instruction is generated; If the anti-interference compensation coefficient Cdc is less than the anti-interference threshold value*50%, it indicates that the motion performance of the linear motor module is unqualified, and a second warning instruction is generated.

7. The anti-interference linear motor module motion control method according to claim 6, characterized in that: The step three also includes: S36, generating a preliminary motion optimization control strategy according to the first evaluation result, including: Generating a first operation instruction according to the first qualified instruction includes: maintaining the current motion control parameters of the linear motor module without additional intervention; Generate a first control instruction according to the first warning instruction, including: limiting the motor load to 80-90% of the rated load of the motor, limiting the maximum speed of the motor to 90%-95% of the rated speed, and when the motor starts, temporarily setting the current to 110% of the rated current to overcome the inertial load, and gradually adjusting to 80% of the rated current after 5-10 minutes after starting; A second control instruction is generated based on the second warning instruction, including: limiting the motor load to 70%-79% of the motor rated load, limiting the maximum speed of the motor to 80%-89% of the rated speed, and when the motor starts, the current is temporarily set to 120% of the rated current to overcome the inertial load, and gradually adjusted to 70% of the rated current after 11-20 minutes after starting.

8. The anti-interference linear motor module motion control method according to claim 1, characterized in that: Step 4 includes: S41. After implementing the preliminary motion optimization control strategy, thermocouples or digital temperature sensors are arranged in the working environment of the linear motor module to measure the ambient temperature at different positions, ensuring that at least one temperature sensor is arranged in each corner of the working area of ​​the module. By collecting the temperature values ​​at each point, the temperature value T of the i-th sampling point is obtained. i , where i = 1, 2, ..., N, N represents the total number of sampling points; Calculate the temperature difference of the total number of sampling points and calculate the average temperature gradient ΔT using the following formula f : Where, T ref,i represents the initial reference temperature value of the i-th sampling point, and the sampling frequency of the temperature sensor is set to 500 Hz; S42. Arrange capacitive humidity sensors or thin film humidity sensors in the working environment of the linear motor module to measure the ambient humidity at different locations, ensuring that at least one humidity sensor is arranged in each corner of the working area of ​​the module, and obtain the humidity value H of the i-th sampling point by collecting the humidity values ​​at each point. i , where i = 1, 2, ..., N, N represents the total number of sampling points; Calculate the humidity value difference of the total number of sampling points and calculate the average humidity gradient ΔH by the following formula f : In the formula, H ref,i represents the initial reference humidity value of the i-th sampling point, and the sampling frequency of the humidity sensor is set to 500 Hz; S43. Based on the materials actually used in the linear motor module, including aluminum alloy, steel, carbon fiber composite material and glass fiber reinforced plastic GFRP, the material expansion caused by temperature is measured and the total motor expansion ΔL is calculated using the following formula total : Where M represents the total number of materials contained in the linear motor module, L 0,k represents the initial volume of the kth material, am k Indicates the coefficient of thermal expansion, including: When the linear motor module is made of aluminum alloy, k =23×10 -6 ℃ -1 ; When the linear motor module is made of steel, am k =12×10 -6 ℃ -1 ; When the linear motor module is made of carbon fiber composite material, am k =2.5×10 -6 ℃ -1 ; When the linear motor module is made of glass fiber reinforced plastic GFRP, am k =10×10 -6 ℃ -1 ; S44, use photoelectric sensor to record the light intensity signal value R in real time t , and calculate the fluctuation amplitude of the light intensity signal over time ΔR t : ΔR t =max(R t )-min(R t ); In the formula, R t Indicates the light intensity signal value within time t, in lux; And the light intensity signal value R t Perform fast Fourier transform FFT to obtain the frequency domain component F(f), and calculate the frequency domain fluctuation amplitude Φ based on the frequency domain component F(f) f : Where F(f) is the light intensity signal value R t The complex form in the frequency domain is used to represent the amplitude and phase of the frequency component. |F(f)| means taking the modulus of F(f) to obtain the amplitude corresponding to the frequency f. high and f low is the upper and lower limits of the frequency band, in Hz, in the frequency range f high to f low In the calculation, the spectrum amplitude |F(f)| is accumulated to calculate the total energy and obtain the frequency domain fluctuation amplitude Φ f ; df represents a small change in frequency; The light intensity signal fluctuates over time ΔR t and the frequency domain fluctuation amplitude Φ f After dimensionless processing, the comprehensive amplitude of light source fluctuation Φ is calculated by the following formula: l : Φ1=ΔR t *w1+Φ f *w2; Where w1 and w2 represent the fluctuation amplitude of light intensity signal over time ΔR t and the frequency domain fluctuation amplitude Φ f The weight of , and w1+w2=1; S45, the average temperature gradient ΔT obtained from S41-S44 f , average humidity gradient ΔH f , total motor expansion ΔL total And the comprehensive amplitude of light source fluctuation Φ l After cleaning, calibration and dimensionless processing, the third data set is generated by aggregation.

9. The anti-interference linear motor module motion control method according to claim 8, characterized in that: Step 4 also includes: S46, extracting the average temperature gradient ΔT in the third data group f , average humidity gradient ΔH f , total motor expansion ΔL total And the comprehensive amplitude of light source fluctuation Φ l , after dimensionless processing, the motor characterization interference sensitivity coefficient Ch is calculated by the following formula: Ch=a 12 *ΔT f +a 13 *ΔH f +a 14 *ΔL total +a 15 *Φ1; In the formula, a 12 、a 13 、a 14 and a 15 Respectively represent weight coefficients; S47, preset a sensitivity threshold, and compare the motor characterization interference sensitivity coefficient Ch with the sensitivity threshold to obtain a motion abnormality risk assessment result, including: If the motor characterization interference sensitivity coefficient Ch ≥ the sensitivity threshold, it means that after the preliminary motion optimization control strategy, the motor performance has abnormal behavior after adjustment, and a correction instruction is generated; If the motor characterization interference sensitivity coefficient Ch is less than the sensitivity threshold, the preliminary motion optimization control strategy indicates that the motor performance does not have abnormal behavior after adjustment.

10. The anti-interference linear motor module motion control method according to claim 9, characterized in that: The correction instructions include: The first control instruction is modified, including: limiting the motor load to 75-85% of the rated load of the motor, limiting the maximum speed of the motor to 85%-90% of the rated speed, and when the motor starts, the current is temporarily set to 115% of the rated current to overcome the inertial load, and gradually adjusted to 75% of the rated current after 7-12 minutes after starting; The second control instruction is modified, including: limiting the motor load to 60%-70% of the motor rated load, limiting the maximum speed of the motor to 75%-84% of the rated speed, and when the motor starts, the current is temporarily set to 125% of the rated current to overcome the inertial load, and gradually adjusted to 65% of the rated current after 15-25 minutes after starting; If the motor characterization interference sensitivity coefficient Ch is still ≥ the sensitivity threshold, an environmental control instruction is generated, including: cleaning the sediment outside the motor module, adding an electrostatic shielding device and a vibration isolation device, and installing a wind pressure regulating valve to adjust the airflow pressure.

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