A control method for pulse width modulation of ultrasonic motor

Abstract

The present invention relates to a control method for pulse width modulation of an ultrasonic motor, which generates a corresponding PWM signal by receiving target parameters set by a user, including a target frequency, a desired output torque, and an operating speed, wherein the signal includes duty cycle and frequency parameters. Operation feedback data, including actual frequency, phase offset, and ambient temperature, are collected in real time by a sensor connected to the motor, and the duty cycle and frequency parameters of the PWM signal are dynamically adjusted based on the feedback data to ensure that the motor maintains efficient and stable performance under changing operating conditions. The method also records feedback data and adjustment records during motor operation for subsequent fault diagnosis and control optimization, thereby improving system reliability and maintenance efficiency. The present invention provides a real-time, adaptive ultrasonic motor control method, which is suitable for application scenarios with high requirements for precise performance and dynamic response, and has wide practicality, especially in high-precision driving and complex environmental 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, due to their compact structure, fast response, and high-precision control, are widely used in optical equipment, precision instruments, and medical devices. Currently, pulse-width modulation (PWM) technology is the primary method for controlling ultrasonic motors. This technology drives and regulates the motor by adjusting the duty cycle and frequency of the signal. Existing technologies typically rely on fixed parameter settings and simple feedback adjustments to maintain motor performance, with sensors collecting operating data to assist in control.

[0003] However, existing technologies are limited in their ability to handle complex operating conditions and dynamically changing environments. Fixed parameter settings struggle to adapt to real-time operational demands, and feedback regulation is slow to respond, leading to reduced motor performance. Furthermore, operational data collection and recording are often independent of the control system, lacking comprehensive fault diagnosis and optimization capabilities, limiting 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:

[0007] receiving target parameters of the ultrasonic motor set by a user, wherein the target parameters include a target frequency, a desired output torque, and an operating speed;

[0008] 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;

[0009] Collecting operational feedback data of the ultrasonic motor from a sensor connected to the ultrasonic motor, wherein the operational feedback data includes an actual frequency, a phase offset, and an ambient temperature of the ultrasonic motor;

[0010] Dynamically adjusting the duty cycle and frequency of the pulse width modulation signal according to the real-time feedback data;

[0011] Record the operation feedback data and dynamic adjustment records collected during the operation of the ultrasonic motor for subsequent fault diagnosis and control optimization.

[0012] Furthermore, the control method of pulse width modulation of the ultrasonic motor further includes:

[0013] 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;

[0014] Based on the received operating constraints, the target parameters set by the user are checked to determine whether they exceed the operating constraints;

[0015] If it is detected that the target parameters exceed the limit conditions, a modification prompt will be sent to the user or the target parameters will be automatically adjusted according to preset rules to make them comply with the limit conditions and meet the safe operation requirements of the motor.

[0016] Furthermore, the control method of pulse width modulation of the ultrasonic motor further includes:

[0017] The real-time feedback data collected by sensors 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 operating stability.

[0018] 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.

[0019] Furthermore, the control method of pulse width modulation of the ultrasonic motor further includes:

[0020] While recording the ultrasonic motor's operational feedback data and dynamic adjustment records, the recorded data is encrypted and synchronously uploaded to a remote storage server;

[0021] Establish a real-time data analysis model on the remote server to automatically classify the uploaded data and detect abnormal trends;

[0022] 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.

[0023] Furthermore, the control method of pulse width modulation of the ultrasonic motor further includes:

[0024] Periodically collect historical operating data from sensors, including frequency, phase offset, and ambient temperature, and store the collected data as a time series record;

[0025] Based on the stored time series records, trend analysis methods are used to calculate the long-term trend of key parameters;

[0026] Based on 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.

[0027] Furthermore, the receiving of target parameters of the ultrasonic motor set by the user includes:

[0028] Check whether the target frequency, expected output torque and operating speed entered by the user are within the operating range of the motor;

[0029] 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.

[0030] Furthermore, the recording of the operation feedback data and dynamic adjustment records collected during the operation of the ultrasonic motor includes:

[0031] 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;

[0032] Extracting key indicators most relevant to fault diagnosis and operation optimization from the collected data, the key indicators including frequency drift trend and phase offset accumulation value;

[0033] Perform statistical analysis on stored key data and exception 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.

[0034] Furthermore, generating a corresponding pulse width modulation signal according to the target parameter includes:

[0035] 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. The frequency parameters are determined according to the following formula:

[0036] According to the following formula (1), the output frequency of the pulse width modulation signal is calculated:

[0037] ;

[0038] 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;

[0039] According to the following formula (2), the duty cycle of the pulse width modulation signal is calculated:

[0040] ;

[0041] 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 offset; is the phase offset correction factor;

[0042] After the frequency parameters and duty cycle are generated, they are optimized using dynamic constraints, which include frequency constraints and duty cycle constraints. The frequency constraint uses the following formula (3):

[0043] ;

[0044] in, and are the upper and lower limits of the resonant frequency range of the ultrasonic motor respectively;

[0045] The duty cycle constraint adopts the following (4):

[0046] ;

[0047] in, and are the minimum and maximum allowed duty cycles, respectively.

[0048] Furthermore, dynamically adjusting the duty cycle and frequency of the pulse width modulation signal according to the real-time feedback data includes:

[0049] Based on the target output power, actual output power, and phase offset in real-time feedback data, an improved nonlinear proportional-integral-differential control algorithm is used to dynamically adjust the duty cycle of the pulse width modulation signal. Specifically, the algorithm includes:

[0050] According to the following formula (5), calculate the current error frequency :

[0051] ;

[0052] in, is the target output power, set by the user; The actual output power collected by the sensor;

[0053] Use the following formula (6) to calculate the duty cycle adjustment value :

[0054] ;

[0055] 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 offset; is the current time; 、 and is the nonlinear adjustment factor;

[0056] According to the following formula (7), calculate the duty cycle adjustment value :

[0057] ;

[0058] in, is the temperature sensitivity coefficient; is the reference temperature; is the current temperature;

[0059] Update the duty cycle of the pulse width modulation signal according to the following formula (8):

[0060] ;

[0061] in, is the updated duty cycle; is the current duty cycle.

[0062] Furthermore, collecting the operation feedback data of the ultrasonic motor from the sensor connected to the ultrasonic motor includes:

[0063] Collect current ambient temperature And the actual frequency , and perform frequency correction according to the following formula (9):

[0064] ;

[0065] in, is the frequency after temperature correction; is the linear temperature correction coefficient; is the nonlinear temperature correction coefficient;

[0066] The corrected frequency As the corrected frequency data, it is used to adjust the pulse width modulation signal.

[0067] The beneficial effects of the technical solution provided by this application include:

[0068] (1) By dynamically adjusting the duty cycle and frequency parameters of the pulse width modulation signal based on operational feedback data, the ultrasonic motor can adapt to complex and changing operating conditions in real time, ensuring that it always maintains efficient and stable operating performance in 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, meeting the requirements of application scenarios with high-precision control requirements, such as optical equipment and precision instruments. (3) Recording operational 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) By comprehensively processing multi-dimensional data such as actual frequency, phase offset, and ambient temperature, this method can effectively coordinate multiple control objectives, optimize motor operating efficiency, and reduce unnecessary energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] 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

[0070] The following description sets forth many specific details to facilitate a thorough 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 scope of the present application. Therefore, the present application is not limited to the specific implementations disclosed below.

[0071] 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 this application. Figure 1 A first embodiment of the present application provides a method for controlling pulse width modulation of an ultrasonic motor, which is described in detail.

[0072] 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 an operating speed.

[0073] Step S101 is the foundation of this method, receiving the user's set target parameters for the ultrasonic motor, including the target frequency, desired output torque, and operating speed. This defines the motor's operating objectives and provides a basis for subsequent control. This step can be implemented in a variety of ways, as detailed below.

[0074] 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 the target frequency, the expected output torque, and the operating speed, and can be expanded to other specific parameters according to the application scenario, such as the temperature range or the maximum allowable energy consumption. 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.

[0075] 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 safe 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 motor overheating, the system can recommend a safe frequency value close to the resonant frequency.

[0076] After verification, the system adapts and optimizes the target parameters based on operating conditions. For example, at high ambient temperatures, the target frequency may need to be slightly reduced to protect motor components; at lower loads, the system may recommend adjusting the desired output torque to improve energy efficiency. This optimization can be achieved through built-in algorithms, such as a dynamic parameter adjustment rule base based on environmental data or a simple logical conditional judgment module.

[0077] After completing the above process, the target parameters are confirmed and stored in the system's operating parameter database, serving as a direct reference for generating the pulse width modulation signal in subsequent steps. The system also saves a record of the parameter settings, including timestamps and specific parameter values, in the background for subsequent debugging or fault tracing.

[0078] Furthermore, to enhance user experience and system intelligence, step S101 can also include user preference learning. For example, after multiple parameter settings, the system can record the user's parameter usage habits and provide intelligent recommendations during the next setting. For example, if a user frequently sets similar torque values ​​within a specific load range, the system can prioritize related parameters, reducing the complexity of user input.

[0079] In summary, step S101 receives user-set parameters from multiple input methods and combines them with functions such as validity verification, parameter adaptation optimization, and intelligent recommendation to ensure the rationality, safety, and accuracy of the target parameters, laying a solid foundation for the subsequent generation of pulse width modulation signals and efficient control of motor operation.

[0080] Furthermore, the receiving of target parameters of the ultrasonic motor set by the user includes:

[0081] Check whether the target frequency, expected output torque and operating speed entered by the user are within the operating range of the motor;

[0082] 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.

[0083] This embodiment provides a functional module for enhancing parameter input validation and logic relationship checking in ultrasonic motor control methods. Its purpose is to ensure that the target parameters set by the user are technically and logically reasonable and to provide optimization suggestions based on system analysis. This approach can effectively reduce the negative impact of unreasonable parameters on motor operation while improving the safety and intelligence of the entire control system.

[0084] 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 must be verified to be within the resonant frequency range of the motor, which is the basis for efficient motor operation. 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 be consistent with the dynamic capabilities and mechanical limits of the motor. Especially in high-frequency switching scenarios, excessively high speeds may cause mechanical failures or signal synchronization problems.

[0085] 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. A higher operating speed may require a lower target frequency to maintain stability. In addition, an increase in the expected output torque may require a corresponding adjustment of the operating speed to avoid excessive energy distribution or heat accumulation. By verifying these logical relationships, the system can identify potential contradictions in the parameter combination. For example, the combination of high frequency, high torque and high-speed operation may exceed the motor design capability.

[0086] 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 the 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 select according to specific needs.

[0087] To enhance the user experience, the system can introduce intelligent recommendation capabilities, automatically optimizing and adjusting recommendations by learning from the user's parameter input habits. For example, if the system detects that a user frequently selects a target frequency close to a certain frequency range, it can prioritize frequencies within that range as initial recommendations. Similarly, the system can adjust the thresholds of pre-set rules based on historical data and actual operating results. For example, if analysis reveals that stable operation can be achieved even when the user's input frequency is close to the limit, the permissible range for that frequency can be appropriately relaxed.

[0088] Furthermore, to enhance the persuasiveness of adjustment recommendations, the system can provide accompanying simulation or forecast results. For example, when recommending a frequency reduction, a dynamic simulation can demonstrate the resulting change in vibration performance, or predict the output power and efficiency of the modified parameter combination under current load conditions. This visualization not only helps users better understand the necessity of adjustments but also strengthens their trust in the system's recommendations.

[0089] By combining these steps, this method not only effectively ensures motor operational safety but also significantly improves system adaptability and user experience through logic relationship checking and intelligent suggestion functions. This method is particularly suitable for ultrasonic motor control in complex operating conditions, such as in precision machining, medical equipment drives, or industrial automation scenarios, providing higher control accuracy and reliability.

[0090] Step S102: generating 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.

[0091] The purpose of step S102 is to generate a pulse-width modulated (PWM) signal for driving the ultrasonic motor based on the received target parameters. Key signal parameters include duty cycle and frequency. This step is the core of the entire control method and directly affects the motor's operating performance and adaptability. Step S102 is described in detail below.

[0092] 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.

[0093] Secondly, the generation of signal parameters needs to consider the system's operational stability and dynamic responsiveness. To improve the adaptability of duty cycle and frequency parameters, the system can perform a comprehensive analysis based on the target parameters and the motor's historical operating data. For example, if historical data indicates significant frequency fluctuations under high-load conditions, the system can appropriately reduce the frequency adjustment range of the PWM signal to avoid vibration instability caused by rapid frequency changes. Furthermore, if the target operating speed is within a relatively low range, the system can appropriately increase the duty cycle to enhance the efficiency of output power transfer.

[0094] While generating PWM signals, the system also verifies signal quality. For example, the built-in signal verification module simulates the generated PWM signal to confirm whether it meets the motor's operating characteristics and target requirements. If signal parameters deviate or mismatch with target parameters, the system can readjust the calculation rules to correct the frequency or duty cycle deviation to ensure signal output quality.

[0095] The generated PWM signal must be implemented using a digital signal processor (DSP) or microcontroller (MCU). The system generates a continuous square wave signal based on frequency parameters and adjusts the high-level duration of the square wave signal using a duty cycle control module. To avoid signal distortion caused by hardware switching delays, the system can utilize high-precision timers and high-speed digital control circuits to achieve real-time PWM signal output. For motor control scenarios requiring multi-channel output, the system can further synchronize the PWM signals of multiple channels to ensure phase consistency between the signals.

[0096] Furthermore, to enhance the system's intelligence and adaptability, the generated PWM signal can dynamically incorporate environmental adjustment logic. For example, in high-temperature environments, the system can automatically adjust the PWM signal's duty cycle to reduce the motor's power output and protect its lifespan. If the target frequency is detected approaching the critical value of the motor's resonant frequency, the system can appropriately increase the frequency stability weight of the PWM signal to ensure signal continuity and stability.

[0097] Finally, 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 historical signal generation data, the system can continuously adjust the calculation model to improve the accuracy and applicability of signal generation.

[0098] Step S102 illustrates how to generate a high-quality PWM signal based on target parameters and optimize it according to operating conditions, thereby achieving efficient drive of the ultrasonic motor. This step not only ensures the proper operation of the motor but also, through intelligent signal generation and dynamic adaptability, provides a stable and reliable control solution for ultrasonic motors in complex operating environments.

[0099] Furthermore, generating a corresponding pulse width modulation signal according to the target parameter includes:

[0100] 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. The frequency parameters are determined according to the following formula:

[0101] According to the following formula (1), the output frequency of the pulse width modulation signal is calculated:

[0102] ;

[0103] 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;

[0104] According to the following formula (2), the duty cycle of the pulse width modulation signal is calculated:

[0105] ;

[0106] 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 offset; is the phase offset correction factor;

[0107] After the frequency parameters and duty cycle are generated, they are optimized using dynamic constraints, which include frequency constraints and duty cycle constraints. The frequency constraint uses the following formula (3):

[0108] ;

[0109] in, and are the upper and lower limits of the resonant frequency range of the ultrasonic motor respectively;

[0110] The duty cycle constraint adopts the following (4):

[0111] ;

[0112] in, and are the minimum and maximum allowed duty cycles, respectively.

[0113] In formula (1), the first term It is the target frequency set by the user, usually determined by the operating requirements. The range is set within a safe range above and below the resonant frequency based on the resonant characteristics of the motor.

[0114] Item 2 Represents the frequency correction term based on ambient temperature changes. The reference temperature of the motor is usually the optimal operating temperature when the motor is designed, such as 25°C or room temperature; Is the current real-time temperature. 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.

[0115] 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. 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 synchronous adjustment requirements of medium loads.

[0116] 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.

[0117] The duty cycle is calculated based on formula (2), where The target power is calculated based on the user's desired output torque and speed, and is 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 offset Obtained through sensor 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.

[0118] 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 to ensure that the frequency is within the stable operating range of the motor.

[0119] 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% .

[0120] Step S103: collecting operational feedback data of the ultrasonic motor from a sensor connected to the ultrasonic motor, wherein the operational feedback data includes an actual frequency, a phase offset, and an ambient temperature of the ultrasonic motor.

[0121] Step S103 is a key step in achieving closed-loop control. By collecting real-time feedback data related to the ultrasonic motor's operation, 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 motor's current operating status and environmental conditions, and are of great importance for control. Step S103 is explained in detail below.

[0122] 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 placed 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 placed in key locations on the motor housing or around the motor to obtain the real-time ambient temperature when the motor is running.

[0123] During the data collection process, the system needs to set a reasonable sampling frequency and time interval to ensure timely and accurate data collection. The sampling frequency should be determined based on the motor's operating characteristics, ensuring it can capture high-frequency changes while avoiding data redundancy and processing delays caused by excessively high sampling frequencies. For example, when collecting vibration frequency and phase offset, the sampling frequency should be greater than twice the signal frequency to meet the requirements of the sampling theorem. However, for slower-changing ambient temperature, the sampling frequency can be relatively low to conserve system resources.

[0124] The collected data is transmitted via a data bus to the control module for real-time processing. During transmission, the data needs to be encoded and compressed to reduce data transmission delays while ensuring data integrity and interference resistance. To improve the system's interference resistance, differential signal transmission or noise suppression can be implemented using filters. Furthermore, for critical data such as phase offset, a redundant sampling strategy can be implemented—collecting multiple sets of data at different time points and averaging them—to further improve data reliability.

[0125] After data is transmitted to the control module, the system needs to perform preliminary processing and storage on the collected feedback data. This 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 these abnormal data points can be removed or marked. 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 smoothing can produce a more realistic average phase offset value.

[0126] After processing, the collected feedback data is used to update the system's control parameters, such as adjusting the PWM signal's duty cycle and frequency in real time to ensure stable motor operation. Furthermore, this feedback data is stored in the system's operation log for subsequent fault diagnosis and performance optimization. To enhance data utility, key data can be labeled and categorized, such as by marking the fluctuation range for frequency data, the maximum deviation point for phase offset data, and the time periods of rapid change for temperature data.

[0127] Step S103 not only enables comprehensive monitoring of the ultrasonic motor's operating status but also provides crucial support for the subsequent dynamic adjustment of the control strategy through efficient data processing and reliable storage. This step not only ensures the motor's efficient and reliable operation but also significantly enhances the system's robustness and intelligence through real-time detection and processing of abnormal conditions.

[0128] Furthermore, collecting the operation feedback data of the ultrasonic motor from the sensor connected to the ultrasonic motor includes:

[0129] Collect current ambient temperature And the actual frequency , and perform frequency correction according to the following formula (9):

[0130] ;

[0131] in, is the frequency after temperature correction; is the linear temperature correction coefficient; is the nonlinear temperature correction coefficient;

[0132] The corrected frequency As the corrected frequency data, it is used to adjust the pulse width modulation signal.

[0133] This embodiment provides a method for adjusting ultrasonic motor frequency based on temperature correction. By collecting current ambient temperature and actual frequency data and using an improved correction model, the frequency is dynamically adjusted, ensuring efficient and stable operation of the motor in variable temperature environments. This method combines linear and nonlinear temperature correction models to more comprehensively address the impact of complex temperature changes on frequency.

[0134] During implementation, the system first collects the current ambient temperature and actual frequency from sensors connected to the ultrasonic motor. Ambient temperature is measured in real time using precision temperature sensors, typically installed in key locations on the motor, such as near the vibration unit or drive circuitry. This ensures that the temperature data accurately reflects the motor's actual operating environment. The actual frequency, acquired through a vibration sensor or signal detection module, directly reflects the motor's current vibration state.

[0135] The collected data will be input into the temperature correction model and the corrected frequency will be calculated according to Formula 9.

[0136] 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 This is the optimal 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.

[0137] 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 This value reflects the weight of nonlinear effects, and its value needs to be fitted based on experimental data. For example, under extreme high or low temperature conditions, nonlinear effects may be more significant than linear effects. An initial reference value of 0.0005 can be set and optimized based on the actual usage environment. The introduction of a sine function reflects the periodic effects of temperature deviations and is particularly suitable for scenarios with slowly fluctuating temperatures.

[0138] After the correction is completed, the This temperature-compensated frequency data more accurately reflects the motor's vibration characteristics under current temperature conditions. This corrected frequency not only eliminates direct errors caused by temperature changes but also enhances adaptability to extreme environments through a combination of linear and nonlinear methods.

[0139] Finally, the corrected frequency It is used as an input parameter to further adjust the pulse width modulation signal and 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 driving efficiency and operating stability.

[0140] This frequency adjustment method, based on a combination of linear and nonlinear correction models, significantly enhances the motor's performance stability in variable temperature environments, while also providing technical support for reliable operation under extreme operating conditions. By rationally selecting correction coefficients and dynamically optimizing the correction formula, this method can adapt to different motor types and operating scenarios.

[0141] Step S104: dynamically adjusting the duty cycle and frequency of the pulse width modulation signal according to the real-time feedback data.

[0142] The core of step S104 is to dynamically adjust the duty cycle and frequency of the pulse-width modulation (PWM) signal based on real-time feedback data to ensure that the ultrasonic motor maintains optimal performance under changing operating conditions. Implementing this step requires multi-level processing logic and precise algorithm design, which are described in detail below.

[0143] After the real-time feedback data reaches the control module, it first needs to be parsed and classified. Feedback data typically includes actual frequency, phase offset, and ambient temperature. Each type of data has a different impact on the operation of the motor, and the adjustment logic needs to be designed for each of these data. 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 re-match. Phase offset reflects the synchronization of the 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.

[0144] After the analysis is complete, the system calculates the required adjustment based on the results. The adjustment logic must 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 must consider the changing trend of the phase offset to ensure that the frequency adjustment does not introduce new instabilities. Duty cycle adjustments are typically based on output power requirements and motor load conditions. For example, if the load increases, the system can appropriately increase the duty cycle to increase output power, while dynamically evaluating changes in ambient temperature to ensure that adjustments do not cause motor overheating.

[0145] A dynamic response mechanism needs to be incorporated into the adjustment logic to adapt to varying operating conditions and data fluctuations. When feedback data changes slowly, adjustments can be made incrementally to avoid the impact of frequent switching on motor performance. However, when data changes significantly, such as unusually large fluctuations in phase offset, the system needs to respond quickly, significantly adjusting the duty cycle or frequency parameters to quickly stabilize motor operation. Furthermore, to improve the accuracy of adjustments, historical data and operational models can be combined. For example, by analyzing frequency and phase offset trends over a period of time, future trends can be predicted and adjustments can be made in advance.

[0146] Implementation of dynamic adjustment requires hardware support. PWM signal generation and adjustment are typically performed by a digital signal processor (DSP) or microcontroller (MCU). During signal generation, the system must adjust the high and low time periods of the output signal in real time to change the duty cycle and update the signal period based on the adjusted frequency parameters. At the hardware level, high-resolution timers and hardware interrupt mechanisms can be used to ensure accurate signal switching and avoid signal distortion caused by delays or jitter during the adjustment process.

[0147] To enhance the adaptability of the adjustment strategy, the system can also incorporate environmental adaptation logic. For example, if the system detects a continuous increase in ambient temperature, it can dynamically reduce the frequency and duty cycle of the PWM signal, thereby reducing the motor's power output and extending its lifespan. For specific scenarios, such as high-precision positioning or operation under complex load conditions, the system can automatically adjust the PWM signal parameters based on task requirements through a preset mode switching function to meet the needs of different application scenarios.

[0148] After the adjustment is complete, the results need to be fed back into the system's operation log in real time and serve as reference data for the next round of adjustments. For example, the frequency, duty cycle, and phase offset values ​​before and after the adjustment should be recorded, and the triggering conditions for the adjustment should be marked. These records are not only used for operational optimization but also serve as diagnostic data when faults occur.

[0149] Step S104 not only dynamically adjusts the PWM signal parameters but also ensures accuracy and reliability through multi-level data processing, dynamic response mechanisms, and hardware collaboration. Furthermore, by expanding environmental adaptation logic and incorporating historical data, this step can better cope with complex operating conditions, enhancing the system's robustness and intelligence.

[0150] Furthermore, dynamically adjusting the duty cycle and frequency of the pulse width modulation signal according to the real-time feedback data includes:

[0151] Based on the target output power, actual output power, and phase offset in real-time feedback data, an improved nonlinear proportional-integral-differential control algorithm is used to dynamically adjust the duty cycle of the pulse width modulation signal. Specifically, the algorithm includes:

[0152] According to the following formula (5), calculate the current error frequency :

[0153] ;

[0154] in, is the target output power, set by the user; The actual output power collected by the sensor;

[0155] Use the following formula (6) to calculate the duty cycle adjustment value :

[0156] ;

[0157] 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 offset; is the current time; 、 and is the nonlinear adjustment factor;

[0158] According to the following formula (7), calculate the duty cycle adjustment value :

[0159] ;

[0160] in, is the temperature sensitivity coefficient; is the reference temperature; is the current temperature;

[0161] Update the duty cycle of the pulse width modulation signal according to the following formula (8):

[0162] ;

[0163] in, is the updated duty cycle; is the current duty cycle.

[0164] 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 based on the current, voltage and load characteristics. The difference between the two represents the deviation between the actual operating state and the target state and is calculated using Equation 5. This error value forms the basis for subsequent control adjustments. By reflecting the magnitude and direction of the current operating state deviation, it determines the magnitude and trend of duty cycle adjustments.

[0165] Next, use formula (6) to calculate the duty cycle adjustment value This formula combines the three control terms of proportional, integral and differential, 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, and it can be increased appropriately for low inertia motors. Used to correct long-term errors, its reference value is usually small, such as 0.1, to avoid integral overshoot. Determines the system's sensitivity to the error change rate. Its reference value is set according to the target response time, for example, 0.05.

[0166] 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 offset 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 should be appropriately increased.

[0167] 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, and can be increased appropriately for high temperature sensitive scenes. The current temperature is the optimal operating temperature when the motor is designed, for example 25°C. The temperature compensation term uses an exponential decay function to reduce the adjustment range under large temperature differences, thus preventing excessive adjustment from affecting the stability of the motor operation.

[0168] 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.

[0169] This control method incorporates multiple factors, including real-time error, phase offset, and temperature, to create a dynamic, nonlinear adjustment mechanism. This approach is not only suitable for high-precision motor control, but also maintains stability and efficiency under complex operating conditions. By precisely setting and optimizing various coefficients, the system achieves a balance between high responsiveness and robustness.

[0170] Step S105: Recording the operation feedback data and dynamic adjustment records collected during the operation of the ultrasonic motor for subsequent fault diagnosis and control optimization.

[0171] Step S105 is a key part of this embodiment. It records the feedback data collected during the operation of the ultrasonic motor and the dynamic adjustments made, providing a reliable foundation for subsequent fault diagnosis and control optimization. This step not only involves data collection and storage, but also requires data classification, processing, and subsequent analysis and application. This step is described in detail below.

[0172] During motor operation, the system collects real-time feedback data including actual frequency, phase offset, and ambient temperature. PWM signal parameters generated during dynamic adjustment (such as duty cycle and frequency adjustment) also need to be recorded synchronously. The collected data is first transferred to a data storage module. To ensure data integrity, the system uses a real-time transmission protocol to avoid data loss due to transmission delays or interference. The system tags this data in real time, including recording timestamps, operating status, and related adjustment events. Timestamps ensure a clear chronological order for data recording, while operating status can be used to describe the overall operating status of the motor at the time the data is recorded, such as whether it is operating stably or undergoing a sudden load change.

[0173] To improve data recording efficiency and facilitate subsequent use, the system needs to categorize and store feedback data and dynamic adjustment records. For example, actual frequency data and frequency adjustment records can be grouped together, phase offset data and duty cycle adjustment records can be grouped together, and ambient temperature data can be stored separately. This categorized storage method facilitates rapid subsequent data retrieval and targeted analysis. Furthermore, the system can flag critical data points, such as frequency or phase offset values ​​outside the normal range as abnormal data points, providing clues for fault diagnosis.

[0174] During 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 preprocess it using a sliding window averaging method, recording only the smoothed data to reduce storage requirements and remove noise. For temperature data, which changes more slowly, interval sampling can be used to record only key change points. Furthermore, the system can ignore duplicate or invalid adjustment records, such as those where frequency and duty cycle adjustments remain unchanged, to optimize storage resources.

[0175] Recorded data is not only stored locally but can also be uploaded to remote servers simultaneously, forming a distributed data storage architecture. This approach allows the system to more securely store operational records while facilitating remote diagnostics and large-scale data analysis. During upload, data is encrypted to ensure secure transmission. The system also regularly backs up important historical data to prevent data loss due to hardware failures.

[0176] In addition to recording and storing data, the system performs preliminary processing and analysis on the recorded data. For example, the system can calculate the long-term trend of frequency offset by comparing the actual frequency with the target frequency, or determine the stability of motor vibration by analyzing the amplitude of phase offset changes. Regarding ambient temperature, the system can analyze the frequency adjustment patterns under different temperature conditions, providing data support for subsequent control optimization. Based on these preliminary analysis results, the system can generate an operation report that includes frequency and phase stability analysis, the impact of ambient temperature on motor performance, and an evaluation of the effectiveness of the adjustment records.

[0177] These data records play a key role in subsequent fault diagnosis and control optimization. For example, when a motor fails, the source of the problem can be quickly located by reviewing the frequency and phase offset records. Abnormal frequency fluctuations accompanied by high phase offset may be related to distortion in the motor's drive signal. A rapid increase in ambient temperature may indicate a cooling system failure or motor overload. Similarly, analyzing dynamic adjustment records can reveal deficiencies in the control strategy, such as slow frequency adjustment response or insufficient duty cycle adjustment range, providing a basis for optimization algorithms.

[0178] Step S105 not only fully records operational data and adjustment history, but also enhances data practicality and system intelligence through classified storage, data compression, and preliminary analysis. This step provides crucial support for the long-term, stable operation of the motor and lays a solid foundation for optimizing control strategies and improving fault diagnosis efficiency.

[0179] Furthermore, the control method of pulse width modulation of the ultrasonic motor further includes:

[0180] 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;

[0181] Based on the received operating constraints, the target parameters set by the user are checked to determine whether they exceed the operating constraints;

[0182] If it is detected that the target parameters exceed the limit conditions, a modification prompt will be sent to the user or the target parameters will be automatically adjusted according to preset rules to make them comply with the limit conditions and meet the safe operation requirements of the motor.

[0183] This embodiment provides a new functional module in the ultrasonic motor pulse width modulation control method: a mechanism that verifies and adjusts user-set target parameters based on operating constraints to ensure motor operation within a safe range. By receiving operating constraints related to the target parameters and verifying and dynamically adjusting the user-entered parameters, this method significantly improves system safety and reliability.

[0184] First, operating constraints can be received through a variety of methods, including a built-in database, external input, or dynamic calculation. 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 typically provided by the motor manufacturer and set to a safe range based on experimental verification results. Furthermore, operating constraints can be dynamically generated based on environmental factors, such as appropriately reducing the maximum allowable frequency or torque range in high-temperature environments. These constraints are received by the system through a parameter loading module and compared with the target parameters entered by the user.

[0185] 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. 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 narrowing of the frequency range to avoid overload operation.

[0186] If the inspection results indicate that the target parameters exceed the limit conditions, the system needs to take corrective measures in a timely manner. First, the system can send a prompt message to the user, notifying the user of unreasonable parameter settings through the display interface or remote communication, and recommending 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 seriously exceed the safety range, the system can automatically adjust the parameters according to 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.

[0187] During automatic parameter adjustment, the system needs to dynamically optimize adjustment rules to ensure that the output parameter combination meets actual needs while also ensuring safety. For example, when both the target frequency and torque exceed their limits, the system may prioritize frequency adjustment, as frequency changes have a greater impact on motor stability. Conversely, under light load conditions, the system may prioritize torque reduction to extend motor life. To achieve this dynamic optimization, the system can automatically determine adjustment priorities based on the operating environment and parameter dependencies using a built-in logical decision tree or a simple weighted algorithm.

[0188] Furthermore, all operational constraints, inspection results, and adjustment records should be stored in real time by the system for subsequent operational analysis and control optimization. For example, by analyzing multiple parameter adjustment records, the system can gradually refine the logic for setting constraints. For example, if a user frequently sets parameters close to the maximum frequency, the system can consider appropriately increasing the maximum allowable frequency or optimizing its range. The recorded data can also provide a traceable basis in the event of an operational anomaly, helping to quickly locate the source of the problem.

[0189] This method not only effectively ensures the safe operation of ultrasonic motors, but also enhances the system's intelligence and adaptability by checking and automatically adjusting user-input parameters. This functional module can be widely used in ultrasonic motor applications requiring high reliability and precise control, such as precision instrument drives, medical equipment, and high-performance industrial equipment, providing more stable and secure motor operation in complex applications.

[0190] Furthermore, the control method of pulse width modulation of the ultrasonic motor further includes:

[0191] The real-time feedback data collected by sensors 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 operating stability.

[0192] 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.

[0193] This embodiment proposes a group processing and dynamic response mechanism based on real-time sensor feedback data, aiming to enhance the flexibility and accuracy of the ultrasonic motor control method while improving the system's adaptability to complex operating conditions.

[0194] The method first relies on real-time feedback data collected by sensors, including actual frequency, phase offset, and ambient temperature. To utilize 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's operating frequency and the target frequency. This data is directly related to the motor's vibration efficiency and performance, so it needs to be processed separately and used to adjust the frequency parameters of the pulse width modulation signal. Phase offset data reflects the synchronization between the drive signal and the actual vibration of the motor. Its abnormality may lead to degraded motor performance or unstable vibration, so this data is assigned to the category used to optimize the duty cycle. Ambient temperature data provides information on the environmental conditions in which the motor operates. High temperature may affect the motor's operating stability and even cause failures, so this data is used to evaluate the overall operating status and adjust the system's safety strategy.

[0195] After grouping, the system analyzes each data category independently. For example, for actual frequency data, the system can calculate the deviation between the target and actual frequencies in real time to determine whether the PWM signal's frequency parameters need to be adjusted. For phase offset data, the system can analyze its changing trends to determine whether the duty cycle needs to be adjusted to improve the synchronization between the signal and the motor's vibration. Ambient temperature data is typically processed primarily for risk assessment, for example, detecting potential overheating issues by measuring the increase in consecutive data points.

[0196] During the analysis of grouped data, if the change in a certain category of data exceeds a preset threshold, the system will trigger a dynamic response mechanism. The core of this mechanism is to quickly respond 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 and motor vibration to ensure operational synchronization. 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.

[0197] In a dynamic response mechanism, increasing the sampling frequency requires a coordinated effort between hardware and software. At the hardware level, the system can utilize a high-precision timer to increase the sampling frequency by shortening the sampling period. At the software level, data collection and transmission priorities must be adjusted accordingly to ensure that the additional high-frequency data does not cause processing delays or resource conflicts. Furthermore, when adjusting control parameters, the system must dynamically calculate the adjustment range and employ smoothing algorithms to avoid sudden fluctuations during the adjustment process. For example, when increasing the duty cycle to improve phase synchronization, a gradual increase can be employed to ensure a smooth adjustment process.

[0198] To enhance the adaptability and intelligence of this approach, the system can also optimize dynamic response mechanisms by integrating historical data. For example, by analyzing historical fluctuations in frequency data, the system can more accurately set trigger thresholds for frequency adjustments. Similarly, by analyzing historical trends in temperature data, the system can use predictive models to proactively identify potential risks, further enhancing the proactive nature of responses.

[0199] This approach processes real-time feedback data by grouping it into categories, enabling more targeted control adjustments while effectively addressing rapidly changing operating conditions through a dynamic response mechanism. This not only significantly improves the control accuracy and adaptability of ultrasonic motors, but also provides technical support for their safe and reliable operation in complex application scenarios.

[0200] Furthermore, the control method of pulse width modulation of the ultrasonic motor further includes:

[0201] While recording the ultrasonic motor's operational feedback data and dynamic adjustment records, the recorded data is encrypted and synchronously uploaded to a remote storage server;

[0202] Establish a real-time data analysis model on the remote server to automatically classify the uploaded data and detect abnormal trends;

[0203] 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.

[0204] This embodiment provides an enhanced data management and analysis method that, through a combination of real-time recording, encrypted transmission, remote analysis, and user feedback, enables comprehensive monitoring and optimization of ultrasonic motor operating conditions. This approach not only enhances the system's intelligence but also significantly improves the safety and reliability of motor operation through anomaly detection and early warning capabilities.

[0205] During ultrasonic motor operation, the system records 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. To ensure data security during transmission, these records are encrypted before local storage. The encryption algorithm can use symmetric or asymmetric encryption, such as those based on AES or RSA, with the appropriate encryption strength selected based on the system's computing resources. After encryption, the data is synchronously uploaded to a remote storage server via a secure transmission protocol (such as TLS or HTTPS) to prevent interception or tampering during network transmission.

[0206] On the remote server side, the uploaded data is first received and stored. The server automatically categorizes and stores the data, assigning it to different database tables or storage areas based on data type (such as frequency, phase, and temperature) for subsequent analysis and retrieval. Furthermore, the server performs integrity checks on the data, such as by verifying cryptographic signatures or calculating hash values, to ensure that the data has not been tampered with during transmission.

[0207] To more efficiently utilize uploaded data, a real-time data analysis model was established on the remote server. This model uses rule-based classification or machine learning algorithms, such as KNN classification or decision tree models, to automatically classify and identify patterns in uploaded data. The classified data is further used to detect abnormal trends. For example, a sliding window is used to analyze the fluctuation range of frequency data to detect whether it continues to exceed the preset threshold; or a time series analysis of phase offset data is used to identify periodic anomalies. For ambient temperature data, historical data and current trends can be combined to determine whether there is an overtemperature risk. The flexibility of the analysis model allows for dynamic adjustment of detection parameters based on different application scenarios. For example, more stringent detection standards can be used to address frequency fluctuations and phase synchronization issues under high-load conditions.

[0208] Based on the analysis results, the system generates a real-time operating status report, including an assessment of the current operating status, trend analysis of key parameters, and a brief description of any anomaly detection. This report is presented in graphical form, such as time series graphs of frequency and phase, and temperature trend charts, for quick user understanding. Furthermore, the system provides optimization recommendations based on the analysis results. For example, in the case of excessive frequency fluctuations, the system recommends adjusting the target frequency or repairing the drive circuit. In the case of high temperature risks, the system recommends reducing the operating load or optimizing the cooling solution.

[0209] When the system detects a potential fault trend, such as abnormal fluctuations in both frequency and phase data, or a temperature rise exceeding a dangerous level, it issues an early warning. This warning can be communicated to the user through various means, including a pop-up prompt on the local control interface, a notification to the user's device (such as an SMS or app push message), or a detailed warning report via email. This warning should include a detailed description of the abnormality, an analysis of the possible causes, and emergency response recommendations, allowing the user to quickly take action to prevent the fault from escalating.

[0210] This approach seamlessly combines local recording with remote analysis, ensuring data security through encrypted transmission and distributed storage. It also leverages the powerful computing power of remote servers to provide real-time operational status analysis and intelligent optimization recommendations. This design not only enhances the system's adaptability to complex operating environments but also provides users with efficient monitoring and decision-making support tools, further enhancing the reliability and intelligence of ultrasonic motors in industrial applications.

[0211] Furthermore, the control method of pulse width modulation of the ultrasonic motor further includes:

[0212] Periodically collect historical operating data from sensors, including frequency, phase offset, and ambient temperature, and store the collected data as a time series record;

[0213] Based on the stored time series records, trend analysis methods are used to calculate the long-term trend of key parameters;

[0214] Based on 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.

[0215] This embodiment proposes an ultrasonic motor control method that regularly collects sensor data, analyzes historical trends, and dynamically adjusts control parameters. Its purpose is to adapt to changes in conditions during long-term motor operation, optimize control performance, ensure stable operation of the motor, and extend its life.

[0216] During motor operation, the system regularly collects operating data from sensors. This data includes frequency, phase offset, and ambient temperature, reflecting the motor's vibration status, synchronization performance, and operating environment, respectively. This data must be collected at a set time interval, such as once per minute, or the sampling frequency can be dynamically adjusted based on operating conditions. The system needs to ensure the accuracy and completeness of the data during collection, which can be achieved through high-precision frequency sensors, phase detection modules, and temperature sensors that are resistant to high-temperature environments. Furthermore, during the collection process, possible noise data or outliers must be removed in real time, such as by using a sliding window filter to remove short-term fluctuations, to ensure the reliability of the recorded data.

[0217] Collected data is stored as time series records. This storage method preserves the chronological order and trajectory of data changes, providing a foundation for subsequent trend analysis. Data storage requires an efficient structure, such as using key-value pairs to store timestamps and corresponding data, or adopting a columnar storage model to facilitate batch analysis. For long-running data, the system can implement a rolling storage mechanism, which regularly cleans up old data to save storage space and archives and backs up key historical data.

[0218] Based on stored time series records, the system regularly uses trend analysis methods to calculate the long-term variation trends of key parameters. For example, the time series of actual frequency can reveal the long-term variation 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 has decreased over time; and 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 variation 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.

[0219] Through trend analysis, the system can identify potential changes in the motor's operating state and predict 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 prediction shows that the ambient temperature may continue to rise in the future, the system can reduce the output power or adjust the cooling strategy in advance to avoid the risk of overheating.

[0220] Based on trend analysis results, the system dynamically adjusts the initial PWM signal parameter configuration to better adapt to long-term changes in operating conditions. This adjustment is typically achieved by modifying the control algorithm's default settings or optimizing its adjustment range. For example, if analysis indicates that the motor load is gradually increasing, the system can increase the default duty cycle to ensure that the output power meets demand. If ambient temperature forecasts indicate that high temperatures will persist for an extended period, the system can incorporate a temperature compensation factor into the frequency adjustment range, dynamically reducing the signal frequency to reduce heat generation.

[0221] This approach integrates trend analysis into the control system, enabling adaptive adjustments to long-term changes through regular data collection and analysis. It not only improves motor operational stability but also significantly extends motor life by dynamically optimizing control parameters. This approach is applicable to ultrasonic motor operation under a variety of complex operating conditions, particularly those with frequent load changes or complex operating environments, significantly enhancing the system's robustness and intelligence.

[0222] Furthermore, the recording of the operation feedback data and dynamic adjustment records collected during the operation of the ultrasonic motor includes:

[0223] 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;

[0224] Extracting key indicators most relevant to fault diagnosis and operation optimization from the collected data, the key indicators including frequency drift trend and phase offset accumulation value;

[0225] Perform statistical analysis on stored key data and exception 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.

[0226] This embodiment provides a comprehensive operational data management and analysis method. Through classified storage, key indicator extraction, and statistical analysis, it provides accurate data support for fault diagnosis and operational optimization. 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.

[0227] During ultrasonic motor operation, the system collects a large amount of feedback data and dynamic adjustment records through sensors. This data includes actual frequency, phase offset, ambient temperature, and the duty cycle and frequency adjustment of the pulse-width modulation signal. To facilitate subsequent analysis and optimization, this data needs to be categorized and stored according to source and type. The categorization logic can be based on the data's purpose and characteristics. For example, frequency data directly reflects the motor's vibration state and is relevant to frequency adjustment; phase data is used to monitor the synchronization between the drive signal and the motor's actual vibration; and environmental data reflects the impact of external conditions on motor performance. Categorized storage can adopt a distributed database structure, with each data type corresponding to a separate storage path to ensure efficient retrieval and processing.

[0228] While classifying and storing data, 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, an abnormality in frequency data may manifest as a sudden change in a short period of time or a long-term stable drift; an abnormality in phase data may manifest as a deviation from the normal synchronization range; an abnormality in environmental data may manifest as a sharp increase in temperature or significant fluctuations. To improve the accuracy of anomaly detection, the system can combine multi-dimensional data cross-validation. For example, when the frequency data is abnormal, the synchronization of the phase data is also checked to confirm the authenticity of the anomaly.

[0229] Extracting the most relevant key indicators for fault diagnosis and operational optimization from categorized and stored data is a core component of data management. These key indicators include, but are not limited to, frequency drift trends and accumulated phase offsets. Frequency drift trends, derived by analyzing the changing patterns of frequency data over a period of time, can reveal long-term offsets in the motor's resonant frequency. Accumulated phase offsets reflect the stability of the synchronization between the drive signal and vibration. High accumulated values ​​may indicate degraded synchronization performance or insufficient control accuracy. Other possible key indicators include the temperature rise rate, the number and amplitude of frequency adjustments, and so on. These indicators can be flexibly defined based on specific application scenarios.

[0230] The extracted key indicators and marked abnormal data points are further used for statistical analysis to generate trend reports and performance evaluation results. Trend reports can include time series graphs of frequency and phase changes, distribution diagrams of abnormal data, and other information, visually demonstrating the historical evolution of the motor's operating status. Performance evaluation results combine key indicators and historical data to quantify the motor's overall operating performance, such as output efficiency, synchronization score, and thermal stability index. These analysis results enable the system to provide precise decision support for users and maintenance personnel.

[0231] The generated reports and evaluation results are stored in a local database and synchronized to a remote server via encrypted transmission. This design not only ensures data security but also facilitates centralized management and distributed access. Data on the remote server can also be compared and analyzed with data from other devices to identify potential common issues or optimization opportunities. Furthermore, reports can be presented to users and maintenance personnel in a variety of ways, such as real-time display through a graphical interface, scheduled email reports, or push notifications via mobile applications, enhancing user visibility into device operating status.

[0232] 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.

[0233] A second embodiment of the present application provides an electronic device, comprising:

[0234] processor;

[0235] 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.

[0236] 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.

[0237] Although the present application is disclosed as above with the preferred embodiments, it is not intended to limit the present application. Any person skilled in the art 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 method for controlling 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 an operating speed; 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; Collecting operational feedback data of the ultrasonic motor from a sensor connected to the ultrasonic motor, wherein the operational feedback data includes an actual frequency, a phase offset, and an ambient temperature of the ultrasonic motor; Dynamically adjusting the duty cycle and frequency of the pulse width modulation signal according to the operation 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; The step of collecting the operational feedback data of the ultrasonic motor from a 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; is the reference temperature; The corrected frequency As the corrected frequency data, it is used to adjust the pulse width modulation signal.

2. The method for controlling pulse width modulation of an ultrasonic motor according to claim 1, wherein: 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 parameters exceed the limit conditions, a modification prompt will be sent to the user or the target parameters will be automatically adjusted according to preset rules to make them comply with the limit conditions and meet the safe operation requirements of the motor.

3. The method for controlling pulse width modulation of an ultrasonic motor according to claim 1, wherein: Also includes: The real-time feedback data collected by sensors 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 operating 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 method for controlling pulse width modulation of an ultrasonic motor according to claim 1, wherein: Also includes: While recording the ultrasonic motor's operational feedback data and dynamic adjustment records, the recorded data is encrypted and synchronously uploaded to a 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 for 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; Based on 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 method for controlling pulse width modulation of an ultrasonic motor according to claim 1, wherein: The receiving of 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 within 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 method for controlling pulse width modulation of an ultrasonic motor according to claim 1, wherein: 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, the key indicators including frequency drift trend and phase offset accumulation value; Perform statistical analysis on stored key data and exception 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 method for controlling pulse width modulation of an ultrasonic motor according to claim 1, wherein: Generating a corresponding pulse width modulation signal according to the target parameter includes: The output frequency of the pulse width modulation signal is calculated based on the target frequency, current ambient temperature, phase offset, and historical motor operation data. The output frequency is 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 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 operating speed; is the rated power of the motor; is the real-time phase offset; is the maximum allowed phase offset; is the phase offset correction factor; After the output frequency and duty cycle are generated, they are optimized using dynamic constraints, which include frequency constraints and duty cycle constraints. The frequency constraint uses 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 method for controlling pulse width modulation of an ultrasonic motor according to claim 1, wherein: The dynamically adjusting the duty cycle and frequency of the pulse width modulation signal according to the operation feedback data includes: Based on the target output power, actual output power, and phase offset in the operational feedback data, an improved nonlinear proportional-integral-differential control algorithm is used to dynamically adjust the duty cycle of the pulse width modulation signal. Specifically, the algorithm includes: 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 offset; 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.

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