Control method for pulse width modulation of ultrasonic motor

Abstract

The invention relates to a control method for pulse width modulation of an ultrasonic motor, which comprises the following steps: receiving target parameters set by a user, including target frequency, expected output torque and running speed, and generating a corresponding PWM (Pulse Width Modulation) signal which comprises a duty ratio and a frequency parameter; operation feedback data including actual frequency, phase deviation and environment temperature are collected in real time through a sensor connected with the motor, and the duty ratio and frequency parameters of PWM signals are dynamically adjusted based on the feedback data so as to ensure that the motor keeps efficient and stable performance under changing operation conditions. The method also records feedback data and adjustment records during the operation of the motor for subsequent fault diagnosis and control optimization, thereby improving the reliability and maintenance efficiency of the system. The invention provides a real-time and self-adaptive ultrasonic motor control method, which is suitable for application scenes with high requirements on accurate performance and dynamic response, and particularly has wide practicability under high-precision driving and complex environment conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of ultrasonic motor control, and in particular to a control method for pulse width modulation of an ultrasonic motor. Background Art

[0002] Ultrasonic motors are widely used in optical equipment, precision instruments, medical equipment and other fields due to their compact structure, fast response speed and high-precision control. At present, pulse width modulation (PWM) technology is the main method to control the operation of ultrasonic motors. The motor is driven and regulated by adjusting the duty cycle and frequency of the signal. The existing technology usually relies on fixed parameter settings and simple feedback adjustments to maintain motor performance, and collects operating data through sensors to assist control.

[0003] However, existing technologies are insufficient in dealing with complex operating conditions and dynamically changing environments. Fixed parameter settings are difficult to adapt to real-time operating requirements, and the feedback adjustment response speed is insufficient, resulting in reduced motor performance. In addition, the collection and recording of operating data is usually independent of the control system, lacking comprehensive fault diagnosis and optimization functions, which limits the long-term stability and efficiency of ultrasonic motors.

[0004] In order to solve the above problems, the present invention provides a new ultrasonic motor control method. Summary of the invention

[0005] The present application provides a control method for pulse width modulation of an ultrasonic motor to improve the regulation accuracy of the ultrasonic motor.

[0006] The present application provides a control method for pulse width modulation of an ultrasonic motor, comprising: receiving target parameters of the ultrasonic motor set by a user, wherein the target parameters include a target frequency, a desired output torque, and a running speed; According to the target parameter, a corresponding pulse width modulation signal is generated, wherein the pulse width modulation signal includes a duty cycle and a frequency parameter; Collecting operation feedback data of the ultrasonic motor from a sensor connected to the ultrasonic motor, wherein the operation feedback data includes an actual frequency, a phase shift, and an ambient temperature of the ultrasonic motor; Dynamically adjusting the duty cycle and frequency of the pulse width modulation signal according to the real-time feedback data; Record the operation feedback data and dynamic adjustment records collected during the operation of the ultrasonic motor for subsequent fault diagnosis and control optimization.

[0007] Furthermore, the control method of pulse width modulation of the ultrasonic motor further includes: Receive operating constraints related to user-set target parameters, including the maximum allowable frequency, maximum torque range, and safe speed limit of the ultrasonic motor; Based on the received operating constraints, the target parameters set by the user are checked to determine whether they exceed the operating constraints; If it is detected that the target parameter exceeds the limit condition, a modification prompt is sent to the user or the target parameter is automatically adjusted according to preset rules to make it meet the limit condition and satisfy the safe operation requirements of the motor.

[0008] Furthermore, the control method of pulse width modulation of the ultrasonic motor further includes: According to the real-time feedback data collected by the sensor, the data is grouped and processed by data category. The actual frequency data is used to adjust the frequency of the pulse width modulation signal, the phase offset data is used to optimize the duty cycle, and the ambient temperature data is used to evaluate the overall operation stability; When the real-time feedback data indicates that the change range of a certain category of data exceeds a preset threshold, a dynamic response mechanism is triggered, which includes increasing the sampling frequency of the category of data or adjusting relevant control parameters.

[0009] Furthermore, the control method of pulse width modulation of the ultrasonic motor further includes: While recording the ultrasonic motor operation feedback data and dynamic adjustment records, the recorded data is encrypted and synchronously uploaded to the remote storage server; Establish a real-time data analysis model on the remote server to automatically classify the uploaded data and detect abnormal trends; Based on the detection results, real-time operation status reports and optimization suggestions are provided to users, and early warning information is issued when possible failure trends are found.

[0010] Furthermore, the control method of pulse width modulation of the ultrasonic motor further includes: Periodically collect historical operating data from sensors, including frequency, phase offset, and ambient temperature, and store the collected data as a time series record; Based on the stored time series records, trend analysis methods are used to calculate the long-term trend of key parameters; According to the trend analysis results, the initial parameter configuration of the pulse width modulation signal is dynamically adjusted to adapt to long-term changes in operating conditions and ensure continuous and stable operation of the motor.

[0011] Furthermore, the receiving of the target parameters of the ultrasonic motor set by the user includes: Check whether the target frequency, expected output torque and operating speed entered by the user are in compliance with the operating range of the motor; According to the preset parameter correlation rules, verify whether the target parameters conform to the logical relationship. If a conflict is found, generate adjustment suggestions and notify the user.

[0012] Furthermore, the recording of the operation feedback data and dynamic adjustment records collected during the operation of the ultrasonic motor includes: According to the data source and type, the operation feedback data and dynamic adjustment records are classified into frequency data, phase data and environmental data respectively, and abnormal data points are marked for subsequent analysis; Extracting key indicators most relevant to fault diagnosis and operation optimization from the collected data, wherein the key indicators include frequency drift trend and phase offset accumulation value; Perform statistical analysis on stored key data and abnormal records, generate trend reports and performance evaluation results, and store or synchronize the reports to a remote server for use by users and maintenance personnel.

[0013] Furthermore, generating a corresponding pulse width modulation signal according to the target parameter includes: Based on the target frequency, current ambient temperature, phase offset and historical motor operation data, the frequency parameters of the pulse width modulation signal are calculated, where the frequency parameters are determined according to the following formula: According to the following formula (1), the output frequency of the pulse width modulation signal is calculated: ; in, is the output frequency of the pulse width modulation signal; is the target frequency; is the reference temperature; is the current temperature; is the real-time phase offset; is the historical frequency offset data; Indicates the number of sampling points of historical data; The 0 in represents the start time of the current sampling period; Indicates the current time; and is the weighting factor; According to the following formula (2), the duty cycle of the pulse width modulation signal is calculated: ; in, is the duty cycle of the pulse width modulation signal; is the target power calculated based on the desired output torque and speed; is the rated power of the motor; is the real-time phase offset; is the maximum allowed phase shift; is the phase offset correction factor; After the frequency parameters and duty cycle are generated, they are optimized through dynamic constraints, which include frequency constraints and duty cycle constraints. The frequency constraint adopts the following formula (3): ; in, and are the upper and lower limits of the resonant frequency range of the ultrasonic motor respectively; The duty cycle constraint adopts the following (4): ; in, and are the minimum and maximum allowed duty cycles respectively.

[0014] Furthermore, dynamically adjusting the duty cycle and frequency of the pulse width modulation signal according to the real-time feedback data includes: Based on the target output power, actual output power and phase offset in the real-time feedback data, the duty cycle of the pulse width modulation signal is dynamically adjusted using an improved nonlinear proportional-integral-differential control algorithm, including: According to the following formula (5), calculate the current error frequency : ; in, is the target output power, set by the user; The actual output power collected by the sensor; Use the following formula (6) to calculate the duty cycle adjustment value: : ; in, is the proportional gain coefficient; is the integral gain coefficient; is the differential gain coefficient; is the real-time phase offset; is the maximum allowed phase shift; is the current time; , and is the nonlinear adjustment factor; According to the following formula (7), calculate the duty cycle adjustment value : ; in, is the temperature sensitivity coefficient; is the reference temperature; is the current temperature; Update the duty cycle of the pulse width modulation signal according to the following formula (8): ; in, is the updated duty cycle; is the current duty cycle.

[0015] Furthermore, the collecting of the operation feedback data of the ultrasonic motor from the sensor connected to the ultrasonic motor includes: Collect current ambient temperature And the actual frequency , and perform frequency correction according to the following formula (9): ; in, is the frequency after temperature correction; is the linear temperature correction coefficient; is the nonlinear temperature correction coefficient; The corrected frequency As the corrected frequency data, it is used to adjust the pulse width modulation signal.

[0016] The beneficial effects of the technical solution provided by this application include: (1) By dynamically adjusting the duty cycle and frequency parameters of the pulse width modulation signal according to the operation feedback data, the ultrasonic motor can adapt to complex and changeable operating conditions in real time, ensuring that it always maintains efficient and stable operating performance under various environments. (2) By receiving the target parameters set by the user and adjusting them in combination with the feedback data, this method can accurately control the frequency and output characteristics of the motor to meet the application scenarios with high requirements for high-precision control, such as optical equipment and precision instruments. (3) Recording the operation feedback data and dynamic adjustment records facilitates subsequent fault diagnosis and control strategy optimization, improving the maintenance efficiency and long-term reliability of the system. (4) Through the comprehensive processing of multi-dimensional data such as actual frequency, phase offset and ambient temperature, this method can effectively coordinate multiple control objectives, optimize the motor operation efficiency and reduce unnecessary energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart of a control method for pulse width modulation of an ultrasonic motor provided in the first embodiment of the present application. DETAILED DESCRIPTION

[0018] Many specific details are described in the following description to facilitate a full understanding of the present application. However, the present application can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of the present application, so the present application is not limited by the specific implementation disclosed below.

[0019] The first embodiment of the present application provides a control method for pulse width modulation of an ultrasonic motor. Figure 1 , which is a schematic diagram of the first embodiment of the present application. Figure 1 A first embodiment of the present application provides a method for controlling pulse width modulation of an ultrasonic motor for detailed description.

[0020] Step S101: receiving target parameters of an ultrasonic motor set by a user, wherein the target parameters include a target frequency, a desired output torque, and a running speed.

[0021] Step S101 is the basic part of the method, which is used to receive the target parameters of the ultrasonic motor set by the user, including the target frequency, the expected output torque and the operating speed, so as to define the operating target of the motor and provide a basis for the subsequent control process. This step can be achieved in a variety of ways, which are described in detail below.

[0022] First, the user's target parameter settings are received through the input device. The input device can be a physical keyboard, a touch screen, or a remote control system (such as instructions received through a wireless communication module). The system interface should provide intuitive parameter setting options, such as through a slider, a numeric input box, or a preset option list, allowing the user to enter the target parameters in a variety of ways. These parameters include but are not limited to target frequency, expected output torque, and operating speed, and can be expanded to other specific parameters such as temperature range or maximum allowable energy consumption according to the application scenario. The target frequency determines the operating base frequency of the ultrasonic motor, the expected output torque is related to the load capacity of the motor, and the operating speed directly affects the final effect of the motor drive.

[0023] Secondly, the system verifies the validity of the target parameters entered by the user. The system should include a built-in parameter range database to verify whether the target parameters are within the safe operating range of the motor. For example, the target frequency needs to be verified to be within the allowable deviation range of the motor's resonant frequency, whether the expected output torque is less than the rated torque of the motor, and whether the operating speed is within the mechanical limit range. If the input parameters do not meet the safety range, the system should immediately prompt the user and recommend reasonable parameter adjustments. For example, when the frequency set by the user is too high and may cause the motor to overheat, the system can recommend a safe frequency value close to the resonant frequency.

[0024] After verification, the system will adapt and optimize the target parameters according to the operating conditions. For example, under high ambient temperature, the target frequency may need to be slightly reduced to protect the motor components; under lower load conditions, the system may recommend adjusting the expected output torque to improve energy efficiency. This optimization can be achieved through built-in algorithms, such as a parameter dynamic adjustment rule base based on environmental data or a simple logical condition judgment module.

[0025] After completing the above process, the target parameters are confirmed and stored in the system's operating parameter database as a direct reference for generating pulse width modulation signals in subsequent steps. At the same time, the system can save a record of this parameter setting in the background, including timestamps and specific parameter values, for subsequent debugging or fault tracing.

[0026] In addition, to enhance user experience and system intelligence, step S101 may also include a user preference learning function. For example, after multiple parameter settings, the system may record the user's parameter usage habits and provide intelligent recommendations during the next setting. For example, if the user often sets similar torque values ​​within a specific load range, the system may prioritize the relevant parameters to reduce the complexity of user input.

[0027] In summary, step S101 receives user-set parameters from a variety of input methods, combines validity verification, parameter adaptation optimization, and intelligent recommendation functions to ensure the rationality, safety, and accuracy of target parameters, laying a solid foundation for the subsequent generation of pulse width modulation signals and efficient control of motor operation.

[0028] Furthermore, the receiving of the target parameters of the ultrasonic motor set by the user includes: Check whether the target frequency, expected output torque and operating speed entered by the user are in compliance with the operating range of the motor; According to the preset parameter correlation rules, verify whether the target parameters conform to the logical relationship. If a conflict is found, generate adjustment suggestions and notify the user.

[0029] This embodiment provides a functional module for enhancing parameter input verification and logical relationship checking in an ultrasonic motor control method, the purpose of which is to ensure that the target parameters set by the user are technically and logically reasonable, and to provide the user with optimization suggestions based on system analysis. This method can effectively reduce the negative impact of unreasonable parameters on motor operation, while improving the safety and intelligence level of the entire control system.

[0030] When receiving the target parameters set by the user, the system first needs to check whether the target frequency, expected output torque and operating speed are within the operating range of the motor. The target frequency needs to be verified to be within the resonant frequency range of the motor, which is the basis for efficient operation of the motor. If the input frequency is too high or too low, it may cause unstable motor vibration or reduced output efficiency. Similarly, the expected output torque needs to match the rated torque range of the motor to avoid mechanical or thermal damage due to overload. The operating speed needs to meet the dynamic capabilities and mechanical limits of the motor, especially in high-frequency switching scenarios, where excessive speed may cause mechanical failures or signal synchronization problems.

[0031] After the parameter range check is completed, the system needs to further verify the logical consistency between the target parameters according to the preset parameter correlation rules. These rules are usually determined by the motor operating characteristics and control algorithms. For example, the relationship between the target frequency and the operating speed may be limited by specific physical laws or design parameters. Higher operating speeds may require a reduction in the target frequency to maintain stability. In addition, an increase in the expected output torque may require a corresponding adjustment in the operating speed to avoid excessive energy distribution or heat accumulation. By verifying these logical relationships, the system can identify potential contradictions in parameter combinations. For example, the combination of high frequency, high torque and high-speed operation may exceed the motor design capabilities.

[0032] If it is found that the target parameters entered by the user have logical conflicts or are out of range, the system will immediately generate adjustment suggestions and notify the user. These suggestions can be presented to the user in various forms such as display interface, sound prompts or remote messaging. For example, when the target frequency exceeds the allowable range, the system may suggest that the user select a value closer to the resonant frequency and explain its optimization effect on motor performance. Similarly, when the operating speed conflicts with the output torque, the system may provide a variety of adjustment options, such as reducing the speed to match the torque or reducing the torque to maintain the speed, allowing the user to choose according to specific needs.

[0033] To improve the user experience, the system can introduce an intelligent recommendation function to automatically optimize and adjust the suggestions by learning the user's parameter input habits. For example, when the system detects that the user often selects a target frequency close to a certain frequency range, it can prioritize the frequency value within this range as the initial suggestion. Similarly, the system can adjust the threshold of the preset rules based on historical data and actual operation results. For example, if the system finds that the user input frequency can still run stably when it is close to the limit range through analysis, the allowable range of the frequency can be appropriately relaxed.

[0034] In addition, to enhance the persuasiveness of adjustment recommendations, the system can be accompanied by simulation or prediction results. For example, when recommending users to reduce the frequency, dynamic simulation can be used to show the change in vibration performance after adjustment, or to predict the output power and efficiency of the modified parameter combination under the current load conditions. This visual approach not only helps users better understand the necessity of adjustment, but also enhances their trust in the system's recommendations.

[0035] Through the comprehensive implementation of the above steps, this method not only effectively ensures the operational safety of the motor, but also significantly improves the system's adaptability and user experience through logical relationship checking and intelligent suggestion functions. This method is particularly suitable for ultrasonic motor control under complex working conditions, such as in precision machining, medical equipment drive or industrial automation scenarios, and can provide higher control accuracy and reliability.

[0036] Step S102: Generate a corresponding pulse width modulation signal according to the target parameter, wherein the pulse width modulation signal includes a duty cycle and a frequency parameter.

[0037] The purpose of step S102 is to generate a pulse width modulation (PWM) signal for driving the ultrasonic motor according to the received target parameters, wherein the key parameters of the signal include duty cycle and frequency. This step is the core of the entire control method and directly affects the operating performance and adaptability of the motor. Step S102 is described in detail below.

[0038] First, according to the target parameters received in step S101, including the target frequency, expected output torque and operating speed, the system needs to calculate the signal parameters. The target frequency directly determines the base frequency of the PWM signal, which is the core condition for the motor to achieve resonant operation. In order to match the characteristics of the ultrasonic motor, the generated frequency parameters need to be optimized according to the resonant characteristic curve of the motor. For example, the system can refer to the rated frequency range of the motor and fine-tune the target frequency through the built-in adjustment rules to make the actual frequency close to the resonant frequency of the motor. In addition, the expected output torque and the operating speed jointly affect the duty cycle of the PWM signal. The system needs to calculate the duty cycle of the signal based on these parameters to ensure that the output power meets the motor load requirements.

[0039] Secondly, the generation of signal parameters needs to consider the stability and dynamic response capability of the system operation. In order to improve the adaptability of duty cycle and frequency parameters, the system can perform a comprehensive analysis based on the target parameters and the historical operation data of the motor. For example, if the historical data shows that the frequency fluctuates greatly under high-load operation conditions, the system can appropriately reduce the frequency adjustment range of the PWM signal to avoid vibration instability caused by too fast frequency changes. At the same time, if the target operating speed is within a lower range, the system can appropriately increase the duty cycle to enhance the transmission efficiency of the output power.

[0040] While generating the PWM signal, the system also needs to verify the signal quality. For example, the generated PWM signal is simulated through the built-in signal verification module to confirm whether it meets the motor's operating characteristics and target requirements. If it is found that the signal parameters deviate or do not match the target parameters, the system can readjust the calculation rules to correct the deviation of the frequency or duty cycle to ensure the output quality of the signal.

[0041] The generated PWM signal needs to be implemented by a digital signal processor (DSP) or a microcontroller (MCU). The system can generate a continuous square wave signal according to the frequency parameters, and adjust the high level time of the square wave signal through the duty cycle control module. In order to avoid signal distortion caused by hardware switching delay, the system can use high-precision timers and high-speed digital control circuits to achieve real-time output of PWM signals. For motor control scenarios with multi-channel output requirements, the system can further synchronize the PWM signals of multiple channels to ensure phase consistency between signals.

[0042] In addition, in order to improve the intelligence and adaptability of the system, the generated PWM signal can also dynamically integrate the adjustment logic of environmental factors. For example, in a high temperature environment, the system can automatically adjust the duty cycle of the PWM signal to reduce the power output of the motor to protect the operating life of the motor. If it is detected that the target frequency is close to the critical value of the motor's resonant frequency, the system can appropriately increase the frequency stability weight of the PWM signal to ensure the continuity and stability of the signal.

[0043] Finally, in order to enhance the traceability and optimization capabilities of signal generation, the system needs to record the key parameters of the generated PWM signal and the core data of the calculation process. These records can be used for subsequent optimization analysis and parameter adjustment. For example, by analyzing the historical data of signal generation, the system can continuously adjust the calculation model to improve the accuracy and applicability of signal generation.

[0044] Step S102 illustrates how to generate high-quality PWM signals according to target parameters and optimize them in combination with operating conditions to achieve efficient driving of the ultrasonic motor. This step not only ensures the normal operation of the motor, but also provides a stable and reliable control solution for the ultrasonic motor in complex operating environments through intelligent signal generation and dynamic adaptability.

[0045] Furthermore, generating a corresponding pulse width modulation signal according to the target parameter includes: Based on the target frequency, current ambient temperature, phase offset and historical motor operation data, the frequency parameters of the pulse width modulation signal are calculated, where the frequency parameters are determined according to the following formula: According to the following formula (1), the output frequency of the pulse width modulation signal is calculated: ; in, is the output frequency of the pulse width modulation signal; is the target frequency; is the reference temperature; is the current temperature; is the real-time phase offset; is the historical frequency offset data; Indicates the number of sampling points of historical data; The 0 in represents the start time of the current sampling period; Indicates the current time; and is the weighting factor;

[0046] According to the following formula (2), the duty cycle of the pulse width modulation signal is calculated: ; in, is the duty cycle of the pulse width modulation signal; is the target power calculated based on the desired output torque and speed; is the rated power of the motor; is the real-time phase offset; is the maximum allowed phase shift; is the phase offset correction factor; After the frequency parameters and duty cycle are generated, they are optimized through dynamic constraints, which include frequency constraints and duty cycle constraints. The frequency constraint adopts the following formula (3): ; in, and are the upper and lower limits of the resonant frequency range of the ultrasonic motor respectively; The duty cycle constraint adopts the following (4): ; in, and are the minimum and maximum allowed duty cycles respectively.

[0047] In formula (1), the first term It is the target frequency set by the user, usually determined by the operating requirements, and the range is set within a safe range above and below the resonant frequency based on the resonant characteristics of the motor.

[0048] Item 2 Represents the frequency correction term based on ambient temperature changes. Among them, is the reference temperature of the motor, usually the optimal operating temperature when the motor is designed, such as 25°C or room temperature; Is the real-time temperature currently collected. Correction coefficient Obtained by experimental calibration, it reflects the sensitivity of temperature to frequency deviation. For example, for some motors, The initial value can be set to 0.05 Hz / °C and dynamically adjusted according to the accuracy requirements during actual operation.

[0049] Item 3 Reflects the cumulative effect of real-time phase offset. Phase offset It is the signal deviation measured by the sensor in real time, and its integral value represents the accumulated deviation over a period of time. The lower limit of the integral is the start time of the current sampling period, and the upper limit is the current time. , so the integral can dynamically reflect the synchronization problem in the recent time. The initial value of can be set through simulation, for example, 0.1 Hz·s, which is suitable for the synchronization adjustment requirements of medium loads.

[0050] Item 4 is a correction term based on historical frequency data, It is Historical frequency offset values, Indicates the number of sampling points of historical data, such as the data of the last 10 cycles. Reflects the weight of historical data on the current frequency adjustment. For example, the initial value can be set to 0.02 Hz, which is suitable for compensation of slowly changing conditions.

[0051] The duty cycle is calculated based on formula (2), where It is the target power calculated based on the user's desired output torque and speed, obtained using a motor efficiency model or empirical formula; is the rated power of the motor, usually provided by the manufacturer, for example 100 W. Real-time phase offset and the maximum allowed phase shift Obtained through sensors and motor design parameters. Correction factor Used to adjust the effect of phase offset on duty cycle. The initial value can be set to 0.1, which is suitable for synchronization adjustment in a medium range.

[0052] After the frequency parameters and duty cycle are calculated, they need to be optimized through dynamic constraints. The frequency constraint is implemented based on formula (3), where and are the lower and upper limits of the motor's resonant frequency range, usually determined experimentally, e.g. = 38 kHz, = 42 kHz, ensuring that the frequency is within the stable operating range of the motor.

[0053] The duty cycle constraint is implemented based on formula (4), where and are the minimum and maximum duty cycles allowed, the range depends on the drive circuit and load characteristics, e.g. = 20% , = 80% .

[0054] Step S103: collecting operation feedback data of the ultrasonic motor from a sensor connected to the ultrasonic motor, wherein the operation feedback data includes an actual frequency, a phase shift, and an ambient temperature of the ultrasonic motor.

[0055] Step S103 is a key link in realizing closed-loop control. By collecting feedback data related to the operation of the ultrasonic motor in real time, it provides an accurate basis for the subsequent dynamic adjustment of the pulse width modulation signal. The collected feedback data includes actual frequency, phase offset and ambient temperature. These data reflect the current operating state of the motor and the environmental conditions in which it is located, and have important control significance. Step S103 is described in detail below.

[0056] First, multiple types of sensors connected to the ultrasonic motor need to be deployed in appropriate locations to ensure the accuracy and real-time nature of the feedback data. The sensor used to collect the actual frequency is generally a vibration sensor or a high-speed signal analysis module, which needs to be arranged close to the motor drive end or output end to capture the actual vibration frequency of the motor. The acquisition of phase offset usually relies on the phase detection module inside the motor or an external high-precision sensor, and its installation position needs to be able to monitor the synchronization relationship between the drive signal and the actual vibration of the motor to calculate the phase difference between the two. The ambient temperature is collected using temperature sensors, which need to be arranged in key locations around the motor housing or motor to obtain the real-time ambient temperature when the motor is running.

[0057] During the acquisition process, the system needs to set a reasonable sampling frequency and time interval to ensure the timeliness and accuracy of the collected data. The sampling frequency should be determined according to the motor operating characteristics, which should be able to capture high-frequency changes while avoiding data redundancy and processing delays caused by excessively high sampling frequencies. For example, for the acquisition of vibration frequency and phase offset, the sampling frequency should be higher than twice the signal frequency to meet the requirements of the sampling theorem, while the ambient temperature changes slowly, and its sampling frequency can be relatively low to save system resources.

[0058] The collected data will be transmitted to the control module through the data bus for real-time processing. During the transmission process, the data needs to be encoded and compressed to reduce the delay of data transmission while ensuring the integrity and anti-interference ability of the data. In order to improve the anti-interference ability of the system, the system can use differential signal transmission or use filters to suppress noise. In addition, for key data, such as phase offset, a redundant sampling strategy can be introduced, that is, multiple sets of data are collected at different time points for average processing to further improve the reliability of the data.

[0059] After the data is transmitted to the control module, the system needs to perform preliminary processing and storage on the collected feedback data. Preliminary processing includes abnormal data detection and data smoothing. Abnormal data detection can identify abnormal data points caused by sudden noise or sensor failure by setting reasonable upper and lower limits or deviation ranges, and remove or mark these abnormal data points. Data smoothing can use sliding window averaging or low-pass filtering to remove high-frequency noise and obtain more stable feedback data. For example, phase offset data may be affected by instantaneous fluctuations, and a more realistic average phase offset value can be obtained through smoothing.

[0060] The collected feedback data will be used to update the control parameters of the system after processing, such as adjusting the duty cycle and frequency of the PWM signal in real time to ensure the stable operation of the motor. In addition, these feedback data will be stored in the system's operation log for subsequent fault diagnosis and performance optimization. In order to improve the practicality of the data, key data can be marked and classified, such as marking the fluctuation range for frequency data, marking the maximum deviation point for phase offset data, and marking the time period of rapid change for temperature data.

[0061] Step S103 not only realizes comprehensive monitoring of the operating status of the ultrasonic motor, but also provides important support for the dynamic adjustment of the subsequent control strategy through efficient data processing and reliable storage. This link not only ensures the efficiency and reliability of the motor operation, but also significantly enhances the robustness and intelligence level of the system through real-time detection and processing of abnormal conditions.

[0062] Furthermore, the collecting of the operation feedback data of the ultrasonic motor from the sensor connected to the ultrasonic motor includes: Collect current ambient temperature And the actual frequency , and perform frequency correction according to the following formula (9): ; in, is the frequency after temperature correction; is the linear temperature correction coefficient; is the nonlinear temperature correction coefficient; The corrected frequency As the corrected frequency data, it is used to adjust the pulse width modulation signal.

[0063] This embodiment provides an ultrasonic motor frequency adjustment method based on temperature correction, which collects the current ambient temperature and actual frequency data and uses an improved correction model to dynamically adjust the frequency, thereby ensuring that the motor can operate efficiently and stably in a variable temperature environment. This method combines linear and nonlinear temperature correction models to more comprehensively deal with the impact of complex temperature changes on frequency.

[0064] During the implementation process, the system first collects the current ambient temperature and actual frequency from the sensor connected to the ultrasonic motor. The ambient temperature is measured in real time by a precision temperature sensor, which is usually installed in a key position of the motor, such as near the vibration unit or drive circuit, to ensure that the temperature data can accurately reflect the actual working environment of the motor. The actual frequency is obtained through a vibration sensor or signal detection module, which directly reflects the current vibration state of the motor.

[0065] The collected data will be input into the temperature correction model and the corrected frequency will be calculated according to formula 9.

[0066] In the correction formula, the first correction term It is the linear correction part, which is used to describe the direct linear effect of temperature change on frequency. Linear correction coefficient Indicates the sensitivity of frequency to temperature changes. Its value is usually calibrated through experiments. For example, for some ultrasonic motors, a temperature increase of 1°C may cause a 0.1% frequency change. Based on this, The initial reference value is 0.001. Reference temperature It is the optimum operating temperature when the motor is designed, usually set to 25°C or other standard values ​​recommended by the motor manufacturer. is the current temperature.

[0067] The second amendment It is the nonlinear correction part, which is used to capture the complex nonlinear relationship of the temperature change on the frequency. Nonlinear correction coefficient It reflects the weight of nonlinear effects, and its value needs to be fitted according to experimental data. For example, under extreme conditions of high or low temperature, nonlinear effects may be more significant than linear effects. The initial reference value can be set to 0.0005 and optimized according to the actual use environment. The introduction of the sine function reflects the periodic effect of temperature deviation, which is especially suitable for dealing with scenarios with slow temperature fluctuations.

[0068] After the correction is completed, the obtained It is the frequency data after temperature compensation, which can more accurately reflect the vibration characteristics of the motor under the current temperature conditions. The corrected frequency can not only eliminate the direct error caused by temperature change, but also enhance the adaptability to extreme environments by combining linear and nonlinear methods.

[0069] Finally, the corrected frequency is used as an input parameter for further adjusting the pulse width modulation signal to optimize the motor's operating state in real time. Adjust the frequency parameters of the PWM signal to make it closer to the resonant frequency of the motor, thereby improving the driving efficiency and operating stability.

[0070] This frequency adjustment method based on a combination of linear and nonlinear correction models significantly enhances the performance stability of the motor in a variable temperature environment, while providing technical support for reliable operation under extreme working conditions. By reasonably selecting the correction coefficient and dynamically optimizing the correction formula, this method can adapt to different motor types and working scenarios.

[0071] Step S104: dynamically adjusting the duty cycle and frequency of the pulse width modulation signal according to the real-time feedback data.

[0072] The core of step S104 is to dynamically adjust the duty cycle and frequency of the pulse width modulation (PWM) signal according to the real-time feedback data to ensure that the ultrasonic motor maintains optimal performance under changing operating conditions. The implementation of this step requires multi-level processing logic and precise algorithm design, which is described in detail below.

[0073] After the real-time feedback data reaches the control module, it is first necessary to perform data parsing and classification. Feedback data usually includes actual frequency, phase offset and ambient temperature. Each data has different effects on the operation of the motor, and the adjustment logic needs to be designed for these data separately. The actual frequency is used to monitor whether the motor is close to the target operating frequency. If it deviates from the target frequency, the frequency parameters of the PWM signal need to be adjusted immediately to rematch. Phase offset reflects the synchronization of motor vibration. Its changes may lead to reduced efficiency or unstable vibration, so it needs to be compensated by adjusting the duty cycle. The ambient temperature determines the operating conditions of the motor. For example, high temperature may require reducing the output power to protect the motor.

[0074] After the analysis is completed, the system calculates the required adjustment amount based on the analysis results. The logic of the adjustment needs to take into account multiple factors. For example, when the actual frequency is low, the system can gradually increase the frequency of the PWM signal, but at the same time, it needs to consider the changing trend of the phase offset to ensure that the frequency adjustment does not introduce new instabilities. The duty cycle adjustment is usually based on the output power demand and the motor load status. For example, when the load increases, the system can appropriately increase the duty cycle to increase the output power, while dynamically evaluating the changes in the ambient temperature to ensure that the adjustment does not cause the motor to overheat.

[0075] A dynamic response mechanism needs to be introduced into the adjustment logic to adapt to different operating conditions and data change amplitudes. When the feedback data changes slowly, the adjustment can adopt a gradual strategy to avoid the impact of frequent switching on motor performance. When the data changes greatly, such as abnormal and drastic fluctuations in phase offset, the system needs to respond quickly and stabilize the motor operation quickly by significantly adjusting the duty cycle or frequency parameters. In addition, in order to improve the accuracy of the adjustment, historical data and operation models can be combined, such as analyzing the frequency and phase offset trends over a period of time, predicting future trends and making adjustments in advance.

[0076] The implementation of dynamic adjustment requires hardware support. The generation and adjustment of PWM signals are usually completed by a digital signal processor (DSP) or a microcontroller (MCU). During the signal generation process, the system needs to adjust the high and low time of the output signal in real time to change the duty cycle, and update the signal period according to the adjusted frequency parameters. At the hardware level, to ensure the accuracy of signal switching, high-resolution timers and hardware interrupt mechanisms can be used to avoid signal distortion caused by delays or jitter during the adjustment process.

[0077] In order to improve the adaptability of the adjustment strategy, the system can also introduce environmental adaptation logic. For example, when the ambient temperature is detected to continue to rise, the system can dynamically reduce the frequency and duty cycle of the PWM signal, reduce the power output of the motor, and extend the service life of the motor. For certain specific scenarios, such as high-precision positioning or operation under complex load conditions, the system can automatically adjust the PWM signal parameters according to the task requirements through the preset mode switching function to meet the needs of different application scenarios.

[0078] After the adjustment is completed, the adjustment results need to be fed back to the system's operation log in real time and used as reference data for the next round of adjustments. For example, record the frequency, duty cycle, and phase offset values ​​before and after the adjustment, and mark the trigger conditions for this adjustment. These records are not only used for operation optimization, but can also be used as a basis for diagnosis when a fault occurs.

[0079] Step S104 not only realizes the dynamic adjustment of PWM signal parameters, but also ensures the accuracy and reliability of the adjustment through multi-level data processing, dynamic response mechanism and hardware collaboration. At the same time, by expanding the environment adaptation logic and historical data reference, this step can better cope with complex operating conditions and enhance the robustness and intelligence level of the system.

[0080] Furthermore, dynamically adjusting the duty cycle and frequency of the pulse width modulation signal according to the real-time feedback data includes: Based on the target output power, actual output power and phase offset in the real-time feedback data, the duty cycle of the pulse width modulation signal is dynamically adjusted using an improved nonlinear proportional-integral-differential control algorithm, including: According to the following formula (5), calculate the current error frequency : ; in, is the target output power, set by the user; The actual output power collected by the sensor; Use the following formula (6) to calculate the duty cycle adjustment value: : ; in, is the proportional gain coefficient; is the integral gain coefficient; is the differential gain coefficient; is the real-time phase offset; is the maximum allowed phase shift; is the current time; , and is the nonlinear adjustment factor;

[0081] According to the following formula (7), calculate the duty cycle adjustment value : ; in, is the temperature sensitivity coefficient; is the reference temperature; is the current temperature; Update the duty cycle of the pulse width modulation signal according to the following formula (8): ; in, is the updated duty cycle; is the current duty cycle.

[0082] First, during the control process, the target output power It is the motor operation target set by the user according to actual needs, such as maintaining a stable torque or speed. Actual output power It is the power data collected by the sensor in real time and calculated from the current, voltage and load characteristics. Current error frequency is the difference between the two, indicating the deviation between the actual operating state and the target state, and is calculated using Formula 5. This error value is the basis for subsequent control adjustments, and determines the magnitude and trend of the duty cycle adjustment by reflecting the size and direction of the current operating state deviation.

[0083] Next, use formula (6) to calculate the duty cycle adjustment value This formula combines the three control terms of proportion, integration and differentiation, and introduces a nonlinear adjustment factor , and , to enhance the flexibility of control. Proportional gain coefficient It directly determines the response speed of the control system to the current error. It is usually adjusted through experiments or simulations. The initial reference value can be 1.0, which can be appropriately increased for low inertia motors. Used to correct long-term errors, the reference value is usually small, such as 0.1, to avoid integral overshoot. It determines the sensitivity of the system to the error change rate. Its reference value is set according to the target response time, for example, 0.05.

[0084] Nonlinear adjustment factor , and The design enhances the control stability of the algorithm under high error or large phase offset conditions. The reference value of can be set to 0.5 to limit the impact of large errors on the proportional term; The reference value of is 0.2, which suppresses the excessive influence of phase shift on the integral term; The reference value is 0.1, ensuring that the phase shift is close to When the weight of the differential term is appropriately increased.

[0085] Duty cycle adjustment value After the calculation is completed, it is necessary to perform temperature compensation according to formula (7). Among them, the temperature sensitivity coefficient Indicates the degree of influence of temperature change on duty cycle adjustment. The reference value can be set to 0.05, which can be appropriately increased for high temperature sensitive scenes. is the optimal operating temperature when the motor is designed, for example 25°C. Current temperature It is the ambient temperature measured in real time by the sensor. The temperature compensation term uses an exponential decay function to reduce the adjustment range under large temperature differences, avoiding excessive adjustment that affects the stability of the motor operation.

[0086] Finally, the duty cycle is updated by formula (8). is the current setting value of the PWM signal, and the updated duty cycle It will be directly applied to the signal generation module to drive the motor to run.

[0087] This control method builds a dynamic, nonlinear adjustment mechanism by incorporating multiple factors such as real-time error, phase offset and temperature into the calculation. It is not only suitable for high-precision motor control, but also able to maintain stability and efficiency under complex working conditions. By accurately setting and optimizing various coefficients, the system can achieve a balance between high responsiveness and robustness.

[0088] Step S105: Record the operation feedback data and dynamic adjustment records collected during the operation of the ultrasonic motor for subsequent fault diagnosis and control optimization.

[0089] Step S105 is the key part of this embodiment, which is responsible for recording the feedback data collected during the operation of the ultrasonic motor and the dynamic adjustment records, providing a reliable basis for subsequent fault diagnosis and control optimization. The implementation of this step not only involves data collection and storage, but also requires consideration of data classification, processing, and subsequent analysis and application. This step is described in detail below.

[0090] During the operation of the motor, the feedback data collected by the system in real time include actual frequency, phase offset and ambient temperature. At the same time, the PWM signal parameters (such as duty cycle and frequency adjustment amount) generated during the dynamic adjustment process also need to be recorded synchronously. The collected data is first transmitted to the data storage module. In order to ensure the integrity of the data, the system adopts a real-time transmission protocol to avoid data loss due to transmission delays or interference. For these data, the system needs to mark them in real time, including recording timestamps, operating status, and related adjustment events. The timestamp ensures that the time sequence of data recording is clear, and the operating status can be used to describe the overall operation of the motor when recording data, such as whether it is in a stable operation or a load mutation state.

[0091] In order to improve the efficiency of data recording and facilitate subsequent use, the system needs to classify and store feedback data and dynamic adjustment records. For example, the actual frequency data and frequency adjustment records are grouped together, the phase offset data and duty cycle adjustment records are grouped together, and the ambient temperature data is stored separately. This classified storage method facilitates the rapid retrieval and targeted analysis of subsequent data. In addition, the system can mark key data, such as marking frequency or phase offset values ​​that are out of the normal range as abnormal data points, to provide clues for fault diagnosis.

[0092] In the process of data recording, data compression and redundancy removal are important optimization steps. For high-frequency sampled data, such as actual frequency and phase offset, the system can use the sliding window averaging method for preprocessing and only record the smoothed data, thereby reducing the storage volume and removing noise. For temperature data, since the changes are relatively slow, interval sampling can be used to record only the key change points. In addition, for repeated or invalid adjustment records, such as when the frequency and duty cycle adjustment amounts have not changed, the system can choose to ignore them to optimize storage resources.

[0093] The recorded data not only needs to be stored locally, but can also be uploaded to a remote server synchronously to form a distributed data storage architecture. In this way, the system can save operation records more safely, while facilitating remote diagnosis and large-scale data analysis. During the upload process, the data needs to be encrypted to ensure transmission security. For important historical data, the system can also back up regularly to prevent data loss due to hardware failure.

[0094] In addition to recording and storage, the system needs to perform preliminary processing and analysis on the recorded data. For example, the long-term trend of frequency offset can be calculated by comparing the actual frequency with the target frequency, or the stability of motor vibration can be determined by analyzing the amplitude of phase offset change. For ambient temperature, the frequency adjustment rules under different temperature conditions can be analyzed to provide data support for subsequent control optimization. Based on these preliminary analysis results, the system can generate an operation report, including frequency and phase stability analysis, the impact of ambient temperature on motor performance, and effectiveness evaluation of adjustment records.

[0095] These data records play a core role in subsequent fault diagnosis and control optimization. For example, when a motor fails, the source of the problem can be quickly located by tracing back the frequency and phase offset records. If the frequency fluctuation is abnormal and accompanied by high phase offset, it may be related to the distortion of the motor's drive signal. A rapid increase in ambient temperature may indicate a cooling system failure or motor overload. Similarly, analyzing the dynamic adjustment records can also reveal deficiencies in the control strategy, such as slow frequency adjustment response or insufficient duty cycle adjustment range, providing a basis for the optimization algorithm.

[0096] Step S105 not only realizes the complete record of operation data and adjustment records, but also improves the practicality of data and the intelligence level of the system through classified storage, data compression and preliminary analysis. This step provides important support for the long-term and stable operation of the motor, and lays a solid foundation for optimizing control strategies and improving fault diagnosis efficiency.

[0097] Furthermore, the control method of pulse width modulation of the ultrasonic motor further includes: Receive operating constraints related to user-set target parameters, including the maximum allowable frequency, maximum torque range, and safe speed limit of the ultrasonic motor; Based on the received operating constraints, the target parameters set by the user are checked to determine whether they exceed the operating constraints; If it is detected that the target parameter exceeds the limit condition, a modification prompt is sent to the user or the target parameter is automatically adjusted according to preset rules to make it meet the limit condition and satisfy the safe operation requirements of the motor.

[0098] This embodiment provides a new functional module in the ultrasonic motor pulse width modulation control method, that is, a mechanism for checking and adjusting the user-set target parameters based on operating constraints to ensure that the motor operates within a safe range. The method significantly improves the safety and reliability of the system by receiving operating constraints related to the target parameters and verifying and dynamically adjusting the parameters input by the user.

[0099] First, the reception of operating constraints can be achieved through a variety of methods such as built-in databases, external inputs, or dynamic calculations. The system's built-in operating constraint database can store key parameters such as the motor's maximum allowable frequency, rated torque range, and safe speed. These parameters are usually provided by the motor manufacturer and set to a safe range based on experimental verification results. In addition, operating constraints can also be dynamically generated in combination with environmental factors, such as appropriately reducing the maximum allowable frequency or torque range in a high temperature environment. These constraints are received by the system through the parameter loading module and compared with the target parameters entered by the user.

[0100] When checking the target parameters, the system needs to verify one by one whether the target frequency, expected output torque, and operating speed entered by the user meet the preset restrictions. The inspection logic can be implemented through simple threshold judgments, such as whether the target frequency is lower than the maximum allowable frequency, whether the expected torque is within the rated range, and whether the operating speed is lower than the safe speed limit. In order to improve the flexibility and accuracy of the inspection, the system can also combine the correlation between the restrictions for multi-dimensional verification. For example, a high target frequency may require a reduction in the operating speed to ensure motor stability, while a higher expected output torque may require a reduction in the frequency range to avoid overload operation.

[0101] If the inspection results show that the target parameters exceed the limit conditions, the system needs to take corrective measures in time. First, the system can send a prompt message to the user, inform the user of the unreasonable parameter settings through the display interface or remote communication, and suggest modification plans. The prompt message can intuitively explain the problem, such as the target frequency exceeds the safety range, and recommend appropriate frequency values ​​for the user to choose. If the user does not respond in time or the input parameters are seriously beyond the safety range, the system can automatically adjust the parameters according to the preset rules. For example, when the target frequency exceeds the maximum allowable value, the system can adjust the frequency to the highest value in the allowable range, and recalculate other parameters associated with it to ensure that the adjusted parameter combination conforms to the motor operation logic.

[0102] In the process of automatically adjusting parameters, the system needs to dynamically optimize the adjustment rules to ensure that the output parameter combination can meet actual needs and take safety into account. For example, when the target frequency and torque exceed the limit at the same time, the system can give priority to adjusting the frequency because the change in frequency has a greater impact on the stability of the motor. In the case of light load, the system may give priority to reducing the torque to extend the life of the motor. To achieve this dynamic optimization, the system can automatically determine the adjustment priority based on the operating environment and parameter correlation through a built-in logical decision tree or a simple weighted algorithm.

[0103] In addition, all operating restrictions, inspection results, and adjustment records should be saved by the system in real time for subsequent operation analysis and control optimization. For example, by analyzing multiple parameter adjustment records, the system can gradually improve the setting logic of the restriction conditions. For example, if it is found that the user frequently sets parameters close to the maximum frequency, the system can consider appropriately increasing the maximum allowable frequency or optimizing its use range. The recorded data can also provide a traceability basis when an operation abnormality occurs, which helps to quickly locate the source of the problem.

[0104] This method not only effectively ensures the safe operation of ultrasonic motors, but also enhances the intelligence and adaptability of the system by checking and automatically adjusting the user input parameters. This functional module can be widely used in ultrasonic motor scenarios that require high reliability and precise control, such as precision instrument drives, medical equipment, and high-performance industrial equipment, providing more stable and safer guarantees for motor operation in complex applications.

[0105] Furthermore, the control method of pulse width modulation of the ultrasonic motor further includes: According to the real-time feedback data collected by the sensor, the data is grouped and processed by data category. The actual frequency data is used to adjust the frequency of the pulse width modulation signal, the phase offset data is used to optimize the duty cycle, and the ambient temperature data is used to evaluate the overall operation stability; When the real-time feedback data indicates that the change range of a certain category of data exceeds a preset threshold, a dynamic response mechanism is triggered, which includes increasing the sampling frequency of the category of data or adjusting relevant control parameters.

[0106] This embodiment proposes a group processing and dynamic response mechanism based on real-time feedback data from sensors, aiming to enhance the flexibility and accuracy of the ultrasonic motor control method, while improving the system's adaptability to complex operating conditions.

[0107] The method first relies on real-time feedback data collected by sensors, including actual frequency, phase offset, and ambient temperature. In order to use this data more efficiently, the system groups and processes it by category. The main purpose of the actual frequency data is to monitor the deviation between the motor operating frequency and the target frequency. This data is directly related to the vibration efficiency and performance of the motor, so it needs to be processed separately and used to adjust the frequency parameters of the pulse width modulation signal. The phase offset data reflects the synchronization between the drive signal and the actual vibration of the motor. Its abnormality may cause the motor performance to deteriorate or the vibration to be unstable, so this data is assigned to the category for optimizing the duty cycle. The ambient temperature data provides information on the environmental conditions of the motor operation. High temperature may affect the operating stability of the motor and even cause failures, so this data is used to evaluate the overall operating status and adjust the system's safety strategy.

[0108] After the group processing is completed, the system will analyze each category of data independently. For example, for the actual frequency data, the system can calculate the deviation between the target frequency and the actual frequency in real time to determine whether the frequency parameters of the PWM signal need to be adjusted. For the phase offset data, the system can analyze its changing trend to determine whether it is necessary to improve the synchronization between the signal and the motor vibration by adjusting the duty cycle. The processing of ambient temperature data is usually based on risk assessment, such as detecting potential overheating problems by the increase in consecutive data points.

[0109] During the analysis of grouped data, if the change in a certain category of data exceeds the preset threshold, the system will trigger a dynamic response mechanism. The core of this mechanism is to respond quickly to sudden changes to avoid performance degradation or motor damage caused by control delays. For example, when the fluctuation of actual frequency data exceeds the allowable range, the system may prioritize increasing the sampling frequency of frequency data to capture more detailed frequency change characteristics, thereby achieving more accurate frequency adjustment. Similarly, if the phase offset data changes too quickly or the amplitude is too large, the system can dynamically adjust the duty cycle to re-match the drive signal with the motor vibration to ensure the synchronization of operation. When the increase in ambient temperature data exceeds the warning threshold, the dynamic response mechanism may reduce the frequency or duty cycle to reduce the motor power output, while increasing the sampling frequency of temperature data to continuously monitor environmental changes.

[0110] In the dynamic response mechanism, the increase in sampling frequency needs to be achieved through the collaboration of hardware and software. At the hardware level, the system can call a high-precision timer to increase the sampling frequency by shortening the sampling period. At the software level, the priority of data acquisition and transmission needs to be adjusted accordingly to ensure that the newly added high-frequency data does not cause processing delays or resource conflicts. In addition, when adjusting the control parameters, the system needs to dynamically calculate the adjustment amplitude and avoid sudden fluctuations during the adjustment process through a smoothing algorithm. For example, when increasing the duty cycle to improve phase synchronization, a gradual increase can be used to ensure a smooth adjustment process.

[0111] In order to improve the adaptability and intelligence of this method, the system can also optimize the dynamic response mechanism in combination with historical data. For example, by analyzing the historical fluctuation records of frequency data, the system can more accurately set the trigger threshold for frequency adjustment. Similarly, for the historical change trend of temperature data, the system can identify potential risks in advance through the prediction model, thereby further enhancing the initiative of the response.

[0112] This method achieves more targeted control adjustments by processing real-time feedback data by category grouping, while effectively responding to rapid changes in operating conditions through a dynamic response mechanism. This not only significantly improves the control accuracy and adaptability of ultrasonic motors, but also provides technical guarantees for the safe and reliable operation of motors in complex application scenarios.

[0113] Furthermore, the control method of pulse width modulation of the ultrasonic motor further includes: While recording the ultrasonic motor operation feedback data and dynamic adjustment records, the recorded data is encrypted and synchronously uploaded to the remote storage server; Establish a real-time data analysis model on the remote server to automatically classify the uploaded data and detect abnormal trends; Based on the detection results, real-time operation status reports and optimization suggestions are provided to users, and early warning information is issued when possible failure trends are found.

[0114] This embodiment provides an enhanced data management and analysis method, which realizes comprehensive monitoring and optimization of the operating status of the ultrasonic motor through the combination of real-time recording, encrypted transmission, remote analysis and user feedback mechanism. This method not only improves the intelligence level of the system, but also significantly improves the safety and reliability of the motor operation through abnormal detection and early warning functions.

[0115] During the operation of the ultrasonic motor, the system will record feedback data and dynamic adjustment records in real time. These data include actual frequency, phase offset, ambient temperature, and PWM signal parameters (such as duty cycle and frequency) at the corresponding time point. In order to ensure the security of data during transmission, these records will be encrypted before local storage. The encryption algorithm can use symmetric encryption or asymmetric encryption, such as encryption based on AES or RSA, and select the appropriate encryption strength based on the system computing resources. After encryption, the data is synchronously uploaded to the remote storage server through a secure transmission protocol (such as TLS or HTTPS) to prevent interception or tampering during network transmission.

[0116] On the remote server side, the uploaded data is first received and stored. The server automatically classifies and stores the data, and assigns it to different database tables or storage areas according to the data type (such as frequency data, phase data, and temperature data) for subsequent analysis and retrieval. In addition, the server side will perform integrity checks on the data, such as by verifying the encryption signature or calculating the hash value, to ensure that the data has not been tampered with during transmission.

[0117] In order to use the uploaded data more efficiently, a real-time data analysis model is established on the remote server. The model uses rule-based classification algorithms or machine learning algorithms, such as KNN classification or decision tree models, to automatically classify and recognize patterns in the uploaded data. The classified data is further used for abnormal trend detection, such as analyzing the fluctuation range of frequency data through sliding windows to detect whether there is a phenomenon of continuously exceeding the preset threshold; or analyzing phase offset data through time series to identify whether there are periodic anomalies. For ambient temperature data, historical data and current trends can be combined to determine whether there is an over-temperature risk. The flexibility of the analysis model allows dynamic adjustment of detection parameters according to different application scenarios. For example, more stringent detection standards can be used for frequency fluctuations and phase synchronization problems under high load conditions.

[0118] Based on the analysis results, the system generates a real-time operating status report, including the evaluation results of the current operating status, trend analysis of key parameters, and a brief description of abnormal detection. The report is presented in graphical form, such as time series graphs of frequency and phase, trend graphs of temperature changes, etc., which is convenient for users to quickly understand. In addition, the system will provide optimization suggestions based on the analysis results. For example, in the case of excessive frequency fluctuations, it is recommended that users adjust the target frequency or repair the drive circuit; in the case of high temperature risks, it is recommended to reduce the operating load or optimize the heat dissipation solution.

[0119] When a possible fault trend is detected, such as abnormal fluctuations in frequency and phase data at the same time, or the temperature continues to rise to a dangerous range, the system will issue an early warning message. The warning can notify the user in a variety of ways, including pop-up prompts on the local control interface, sending notifications to user terminal devices (such as SMS or application push messages), or sending detailed warning reports via email. The warning information should include a specific description of the abnormality, possible cause analysis, and emergency response suggestions, so that users can take quick measures to prevent the fault from expanding.

[0120] This method realizes the seamless combination of local recording and remote analysis, ensures data security through encrypted transmission and distributed storage, and realizes real-time operation status analysis and intelligent optimization suggestions based on the powerful computing power of the remote server. This design not only enhances the system's adaptability to complex operating environments, but also provides users with efficient monitoring and decision support tools, further improving the reliability and intelligence level of ultrasonic motors in industrial applications.

[0121] Furthermore, the control method of pulse width modulation of the ultrasonic motor further includes: Periodically collect historical operating data from sensors, including frequency, phase offset, and ambient temperature, and store the collected data as a time series record; Based on the stored time series records, trend analysis methods are used to calculate the long-term trend of key parameters; According to the trend analysis results, the initial parameter configuration of the pulse width modulation signal is dynamically adjusted to adapt to long-term changes in operating conditions and ensure continuous and stable operation of the motor.

[0122] This embodiment proposes an ultrasonic motor control method by regularly collecting sensor data, analyzing historical trends and dynamically adjusting control parameters, with the aim of adapting to changes in conditions during long-term operation of the motor, optimizing control performance, and ensuring stable operation and extending the life of the motor.

[0123] During the operation of the motor, the system will regularly collect operating data from sensors. These data include frequency, phase offset and ambient temperature, which reflect the vibration state, synchronization performance and working environment of the motor respectively. The collection of these data needs to be based on a set time interval, such as collecting once a minute or dynamically adjusting the sampling frequency according to the operating conditions. The system needs to ensure the accuracy and integrity of the data during collection, which can be achieved through high-precision frequency sensors, phase detection modules and temperature sensors that can withstand high temperature environments. In addition, possible noise data or outliers need to be eliminated in real time during the collection process, such as using a sliding window filtering method to remove short-term fluctuations to ensure the reliability of the recorded data.

[0124] The collected data will be stored as time series records. This storage method can preserve the time order and change trajectory of the data, providing a basis for subsequent trend analysis. Data storage requires the design of an efficient structure, such as using key-value pairs to store timestamps and corresponding data, or using a columnar storage model to facilitate batch analysis. For long-running data, the system can set up a rolling storage mechanism, that is, regularly clean up old data to save storage space, and archive and back up key historical data.

[0125] Based on the stored time series records, the system will regularly use trend analysis methods to calculate the long-term change trends of key parameters. For example, the time series of actual frequency can reveal the long-term change pattern of the motor vibration frequency with load or environment; phase offset data can reflect whether the synchronization performance of the drive signal and the vibration state decreases over time; ambient temperature data can reveal the temperature rise trend of the working environment and its impact on the motor's operating performance. Analysis methods may include but are not limited to linear regression analysis, moving average method, Fourier transform or time series prediction models based on machine learning. For highly complex change patterns, such as multi-period fluctuations or nonlinear growth, autoregressive models (ARIMA) or long short-term memory networks (LSTM) can be used to achieve more accurate trend predictions.

[0126] Through trend analysis, the system can identify potential changes in the motor's operating state and estimate possible future operating conditions. For example, if the analysis shows that the frequency data gradually decreases over time, it may indicate that the motor's resonant frequency has shifted, and the frequency parameters of the PWM signal need to be adjusted to re-match the resonant conditions. Similarly, if the phase offset data shows that the synchronization performance has significantly decreased under certain conditions, the system can optimize the initial configuration of the duty cycle to improve synchronization. As for the ambient temperature data, if the forecast shows that the ambient temperature may continue to rise in the future, the system can reduce the output power in advance or adjust the cooling strategy to avoid the risk of overheating.

[0127] Based on the trend analysis results, the system dynamically adjusts the initial parameter configuration of the PWM signal to better adapt to long-term changing operating conditions. This adjustment is usually achieved by modifying the default value of the control algorithm or optimizing its adjustment range. For example, when the analysis shows that the load of the motor is gradually increasing, the system can increase the default value of the duty cycle to ensure that the output power meets the demand; when the ambient temperature forecast shows that the high temperature duration is prolonged, the system can add a temperature compensation factor within the frequency adjustment range to dynamically reduce the signal frequency to reduce heat.

[0128] This method integrates trend analysis into the control system and achieves adaptive adjustment to long-term changes through regular data collection and analysis. It not only improves the operating stability of the motor, but also significantly extends the service life of the motor by dynamically optimizing the control parameters. This method is suitable for the operation of ultrasonic motors under a variety of complex working conditions, especially in scenarios with frequent load changes or complex working environments, and can significantly enhance the robustness and intelligence of the system.

[0129] Furthermore, the recording of the operation feedback data and dynamic adjustment records collected during the operation of the ultrasonic motor includes: According to the data source and type, the operation feedback data and dynamic adjustment records are classified into frequency data, phase data and environmental data respectively, and abnormal data points are marked for subsequent analysis; Extracting key indicators most relevant to fault diagnosis and operation optimization from the collected data, wherein the key indicators include frequency drift trend and phase offset accumulation value; Perform statistical analysis on stored key data and abnormal records, generate trend reports and performance evaluation results, and store or synchronize the reports to a remote server for use by users and maintenance personnel.

[0130] This embodiment provides a comprehensive operation data management and analysis method, which provides accurate data support for fault diagnosis and operation optimization through classified storage, key indicator extraction and statistical analysis. This method not only improves data utilization efficiency, but also significantly enhances the intelligence and reliability of the system through trend analysis and performance evaluation.

[0131] During the operation of the ultrasonic motor, the system collects a large amount of feedback data and dynamic adjustment records through sensors. These data include actual frequency, phase offset, ambient temperature, and duty cycle and frequency adjustment of the pulse width modulation signal. In order to facilitate subsequent analysis and optimization, these data need to be classified and stored according to source and type. The classification logic can be based on the purpose and characteristics of the data. For example, frequency data directly reflects the vibration state of the motor and is related to frequency adjustment; phase data is used to monitor the synchronization between the drive signal and the actual vibration of the motor; and environmental data reflects the impact of external conditions on motor performance. Classification storage can adopt a distributed database structure, with each data type corresponding to a separate storage path to ensure the efficiency of retrieval and processing.

[0132] While classifying and storing, the system needs to mark abnormal data points for subsequent analysis. The identification of abnormal data points can be achieved by setting reasonable upper and lower limits, fluctuation ranges or dynamic thresholds. For example, the abnormality of frequency data may appear as a sudden change in a short period of time or a long-term stable drift; the abnormality of phase data may appear as a deviation from the normal synchronization range; the abnormality of environmental data may appear as a sharp increase or significant fluctuation in temperature. In order to improve the accuracy of anomaly detection, the system can combine multi-dimensional data cross-validation, such as checking the synchronization of phase data at the same time when the frequency data is abnormal to confirm the authenticity of the anomaly.

[0133] Extracting the most relevant key indicators for fault diagnosis and operation optimization from the classified and stored data is the core link of data management. These key indicators include but are not limited to frequency drift trend and phase shift accumulation value. The frequency drift trend is obtained by analyzing the changing pattern of frequency data over a period of time, which can reveal the long-term offset problem of the motor resonant frequency; the phase shift accumulation value reflects the stability of the synchronization between the drive signal and the vibration. A high accumulation value may indicate a decrease in synchronization performance or insufficient control accuracy. In addition, other possible key indicators include the temperature rise rate, the number and amplitude of frequency adjustments, etc. These indicators can be flexibly defined according to specific application scenarios.

[0134] The extracted key indicators and marked abnormal data points will be further used for statistical analysis to generate trend reports and performance evaluation results. Trend reports can include time series change graphs of frequency and phase, distribution graphs of abnormal data, etc., which can intuitively show the historical evolution of the motor's operating status. The performance evaluation results combine key indicators and historical data to quantify the overall operating performance of the motor, such as output efficiency, synchronization score, and thermal stability index. Through these analysis results, the system can provide users and maintenance personnel with accurate decision support.

[0135] The reports and evaluation results generated by the analysis will be stored in the local database and synchronized to the remote server through encrypted transmission. This design not only ensures the security of the data, but also facilitates centralized management and distributed access. The data on the remote server can also be compared and analyzed with the data of other devices to discover potential common problems or optimization opportunities. In addition, the report can be presented to users and maintenance personnel in a variety of forms, such as real-time display through a graphical interface, regular generation of email reports, or push notifications through mobile terminal applications, to enhance users' control over the operating status of the equipment.

[0136] This method significantly improves data utilization efficiency and system diagnostic capabilities through classified storage, key indicator extraction and intelligent analysis, while providing users with efficient and convenient decision support tools.

[0137] A second embodiment of the present application provides an electronic device, the electronic device comprising: processor; The memory is used to store a program. When the program is read and executed by the processor, the program executes a control method for pulse width modulation of an ultrasonic motor provided in the first embodiment of the present application.

[0138] A third embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, a method for controlling pulse width modulation of an ultrasonic motor is provided.

[0139] Although the present application is disclosed as above in the form of a preferred embodiment, it is not intended to limit the present application. Any technical personnel in this field may make possible changes and modifications without departing from the spirit and scope of the present application. Therefore, the scope of protection of the present application shall be based on the scope defined by the claims of the present application.

Claims

1. A control method for pulse width modulation of an ultrasonic motor, characterized in that: include: receiving target parameters of the ultrasonic motor set by a user, wherein the target parameters include a target frequency, a desired output torque, and a running speed; According to the target parameter, a corresponding pulse width modulation signal is generated, wherein the pulse width modulation signal includes a duty cycle and a frequency parameter; Collecting operation feedback data of the ultrasonic motor from a sensor connected to the ultrasonic motor, wherein the operation feedback data includes an actual frequency, a phase shift, and an ambient temperature of the ultrasonic motor; Dynamically adjusting the duty cycle and frequency of the pulse width modulation signal according to the real-time feedback data; Record the operation feedback data and dynamic adjustment records collected during the operation of the ultrasonic motor for subsequent fault diagnosis and control optimization.

2. The control method of pulse width modulation of an ultrasonic motor according to claim 1, characterized in that: Also includes: Receive operating constraints related to user-set target parameters, including the maximum allowable frequency, maximum torque range, and safe speed limit of the ultrasonic motor; Based on the received operating constraints, the target parameters set by the user are checked to determine whether they exceed the operating constraints; If it is detected that the target parameter exceeds the limit condition, a modification prompt is sent to the user or the target parameter is automatically adjusted according to preset rules to make it meet the limit condition and satisfy the safe operation requirements of the motor.

3. The control method of pulse width modulation of an ultrasonic motor according to claim 1, characterized in that: Also includes: According to the real-time feedback data collected by the sensor, the data is grouped and processed by data category. The actual frequency data is used to adjust the frequency of the pulse width modulation signal, the phase offset data is used to optimize the duty cycle, and the ambient temperature data is used to evaluate the overall operation stability; When the real-time feedback data indicates that the change range of a certain category of data exceeds a preset threshold, a dynamic response mechanism is triggered, which includes increasing the sampling frequency of the category of data or adjusting relevant control parameters.

4. The control method of pulse width modulation of an ultrasonic motor according to claim 1, characterized in that: Also includes: While recording the ultrasonic motor operation feedback data and dynamic adjustment records, the recorded data is encrypted and synchronously uploaded to the remote storage server; Establish a real-time data analysis model on the remote server to automatically classify the uploaded data and detect abnormal trends; Based on the detection results, real-time operation status reports and optimization suggestions are provided to users, and early warning information is issued when possible failure trends are found.

5. The control method of pulse width modulation of an ultrasonic motor according to claim 1, characterized in that: Also includes: Periodically collect historical operating data from sensors, including frequency, phase offset, and ambient temperature, and store the collected data as a time series record; Based on the stored time series records, trend analysis methods are used to calculate the long-term trend of key parameters; According to the trend analysis results, the initial parameter configuration of the pulse width modulation signal is dynamically adjusted to adapt to long-term changes in operating conditions and ensure continuous and stable operation of the motor.

6. The control method of pulse width modulation of an ultrasonic motor according to claim 1, characterized in that: The receiving of target parameters of the ultrasonic motor set by the user comprises: Check whether the target frequency, expected output torque and operating speed entered by the user are in compliance with the operating range of the motor; According to the preset parameter correlation rules, verify whether the target parameters conform to the logical relationship. If a conflict is found, generate adjustment suggestions and notify the user.

7. The control method of pulse width modulation of an ultrasonic motor according to claim 1, characterized in that: The recording of the operation feedback data and dynamic adjustment records collected during the operation of the ultrasonic motor includes: According to the data source and type, the operation feedback data and dynamic adjustment records are classified into frequency data, phase data and environmental data respectively, and abnormal data points are marked for subsequent analysis; Extracting key indicators most relevant to fault diagnosis and operation optimization from the collected data, wherein the key indicators include frequency drift trend and phase offset accumulation value; Perform statistical analysis on stored key data and abnormal records, generate trend reports and performance evaluation results, and store or synchronize the reports to a remote server for use by users and maintenance personnel.

8. The control method of pulse width modulation of an ultrasonic motor according to claim 1, characterized in that: The step of generating a corresponding pulse width modulation signal according to the target parameter comprises: Based on the target frequency, current ambient temperature, phase offset and historical motor operation data, the frequency parameters of the pulse width modulation signal are calculated, where the frequency parameters are determined according to the following formula: According to the following formula (1), the output frequency of the pulse width modulation signal is calculated: ； in, is the output frequency of the pulse width modulation signal; is the target frequency; is the reference temperature; is the current temperature; is the real-time phase offset; is the historical frequency offset data; Indicates the number of sampling points of historical data; The 0 in represents the start time of the current sampling period; Indicates the current time; and is the weighting factor; According to the following formula (2), the duty cycle of the pulse width modulation signal is calculated: ； in, is the duty cycle of the pulse width modulation signal; is the target power calculated based on the desired output torque and speed; is the rated power of the motor; is the real-time phase offset; is the maximum allowed phase shift; is the phase offset correction factor; After the frequency parameters and duty cycle are generated, they are optimized through dynamic constraints, which include frequency constraints and duty cycle constraints. The frequency constraint adopts the following formula (3): ； in, and are the upper and lower limits of the resonant frequency range of the ultrasonic motor respectively; The duty cycle constraint adopts the following (4): ； in, and are the minimum and maximum allowed duty cycles respectively.

9. The control method of pulse width modulation of an ultrasonic motor according to claim 1, characterized in that: The step of dynamically adjusting the duty cycle and frequency of the pulse width modulation signal according to the real-time feedback data includes: Based on the target output power, actual output power and phase offset in the real-time feedback data, the duty cycle of the pulse width modulation signal is dynamically adjusted using an improved nonlinear proportional-integral-differential control algorithm, including: According to the following formula (5), calculate the current error frequency : ； in, is the target output power, set by the user; The actual output power collected by the sensor; Use the following formula (6) to calculate the duty cycle adjustment value: : ； in, is the proportional gain coefficient; is the integral gain coefficient; is the differential gain coefficient; is the real-time phase offset; is the maximum allowed phase shift; is the current time; , and is the nonlinear adjustment factor; According to the following formula (7), calculate the duty cycle adjustment value : ； in, is the temperature sensitivity coefficient; is the reference temperature; is the current temperature; Update the duty cycle of the pulse width modulation signal according to the following formula (8): ； in, is the updated duty cycle; is the current duty cycle.

10. The control method of pulse width modulation of an ultrasonic motor according to claim 1, characterized in that: The step of collecting the operation feedback data of the ultrasonic motor from the sensor connected to the ultrasonic motor includes: Collect current ambient temperature And the actual frequency , and perform frequency correction according to the following formula (9): ； in, is the frequency after temperature correction; is the linear temperature correction coefficient; is the nonlinear temperature correction coefficient; The corrected frequency As the corrected frequency data, it is used to adjust the pulse width modulation signal.

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