Method and apparatus for determining device performance curve, and electronic device

Abstract

This application discloses a method, apparatus, and electronic device for determining a device performance curve, relating to the field of electronic equipment technology. The method includes: acquiring the power input range and voltage input range of an ultrasonic transducer; determining an initial performance curve of the ultrasonic transducer based on the power input range and voltage input range; acquiring N expected power values ​​set for the ultrasonic transducer, wherein the expected power values ​​all fall within the power input range, and N is an integer greater than or equal to 1; and iteratively updating the initial performance curve based on the target power actually received by the ultrasonic transducer when each expected power value is expected to be received, to obtain the target performance curve of the ultrasonic transducer. This application solves the technical problem in the prior art where the performance evaluation of ultrasonic transducers is often poor due to reliance on a uniform performance curve described at the time of manufacture, which fails to determine the actual performance curve of the ultrasonic transducer in a timely manner.

Description

Technical Field

[0001] This application relates to the fields of equipment testing and electronic equipment technology, and more specifically, to a method, apparatus, and electronic equipment for determining equipment performance curves. Background Technology

[0002] In traditional equipment manufacturing, the performance curves of ultrasonic transducers are often standardized and fixed by the equipment manufacturer after design or manufacturing. However, due to differences in equipment manufacturing processes and design variations (such as the type of piezoelectric material, component thickness, and radius of curvature), different transducers from the same batch or with different designs may require different drive voltages when receiving the same electrical power. Therefore, it is necessary to establish the most accurate performance curve possible for each ultrasonic transducer. However, there is currently no technology that can readily test the performance curves of ultrasonic transducers, making it impossible to determine the actual performance curve of each ultrasonic transducer in a timely manner, thus affecting the accuracy of ultrasonic transducer performance evaluation. Summary of the Invention

[0003] Some embodiments of this application provide a method, apparatus, and electronic device for determining device performance curves, in order to at least solve the technical problem in the prior art that the performance evaluation of ultrasonic transducers is poor because it usually relies on a uniform performance curve described at the time of manufacture of the ultrasonic transducer and cannot determine the actual performance curve of the ultrasonic transducer in a timely manner.

[0004] In some embodiments, a method for determining a device performance curve is provided, comprising: acquiring the power input range and voltage input range of an ultrasonic transducer; determining an initial performance curve of the ultrasonic transducer based on the power input range and voltage input range; acquiring N expected power values ​​set for the ultrasonic transducer, wherein the expected power values ​​are all located within the power input range, and N is an integer greater than or equal to 1; iteratively updating the initial performance curve based on the target power actually received by the ultrasonic transducer when it is expected to receive each expected power value, to obtain a target performance curve of the ultrasonic transducer.

[0005] In some embodiments, a device for determining a device performance curve is also provided, comprising: a first acquisition unit for acquiring an electrical power input range and a voltage input range of an ultrasonic transducer; a first determination unit for determining an initial performance curve of the ultrasonic transducer based on the electrical power input range and the voltage input range; a second acquisition unit for acquiring N expected electrical powers set for the ultrasonic transducer, wherein the expected electrical powers are all located within the electrical power input range, and N is an integer greater than 1; and a second determination unit for iteratively updating the initial performance curve based on the target electrical power actually received by the ultrasonic transducer when it is expected to receive each expected electrical power, to obtain a target performance curve of the ultrasonic transducer.

[0006] In some embodiments, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer-readable storage medium, wherein when the computer program is executed, the device in which the computer-readable storage medium is located performs the above-described method for determining the device performance curve.

[0007] In some embodiments, an electronic device is also provided, including one or more processors and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors perform the method for determining the device performance curve described above.

[0008] In some embodiments, a computer program product is also provided, including a computer program or instructions, which, when executed by a processor, implement the method for determining the device performance curve described above. Attached Figure Description

[0009] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0010] Figure 1 This is a flowchart of a method for determining device performance curves according to some embodiments of this application;

[0011] Figure 2 This is a flowchart of the detection process for the power response characteristics of a transducer, provided according to some embodiments of this application.

[0012] Figure 3 This is a flowchart of the fitting coefficient update based on some embodiments of this application;

[0013] Figure 4 This is a flowchart illustrating the dynamic updating of the target performance curve according to some embodiments of this application;

[0014] Figure 5 This is a schematic diagram of a device for determining device performance curves according to some embodiments of this application. Detailed Implementation

[0015] It should be understood that the examples and illustrations in this application are for illustrative purposes, and deviations and variations can be constructed and deployed based on the teachings of this application without departing from the scope of this application. Before detailing at least one embodiment of this application, it should be understood that this application is not necessarily limited to the detailed configuration and arrangement of the components and / or methods set forth in the following description and / or illustrated in the drawings and / or embodiments. This application can have other embodiments or can be practiced or implemented in different ways.

[0016] Unless otherwise defined, all technical and / or scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. While similar or equivalent methods and materials to those described in this application may be used to practice or test embodiments of this application, exemplary methods and / or materials are described below. In the event of any conflict, the specification (including definitions) of this application shall prevail. Furthermore, these materials, methods, and embodiments are illustrative only and are not intended to impose necessary limitations.

[0017] It should be noted that the information collected in this application (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) are information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of this data all comply with relevant laws, regulations, and standards, necessary confidentiality measures have been taken, and they do not violate public order and good morals. Corresponding access points are provided for users to choose to authorize or refuse. For example, interfaces are set up between this system and relevant users or organizations, providing users with corresponding access points to choose to agree to or refuse automated decision-making results; if the user chooses to refuse, the process proceeds to the expert decision-making stage.

[0018] Figure 1 This is a flowchart of a method for determining device performance curves according to some embodiments of this application, such as... Figure 1 As shown, the method includes the following steps:

[0019] Step S101: Obtain the power input range and voltage input range of the ultrasonic transducer.

[0020] For example, an ultrasonic transducer can be used for ultrasonic ablation or ultrasonic imaging. Furthermore, an ultrasonic transducer can be any device that converts input electrical energy into another form of output energy (such as mechanical, acoustic, thermal, or optical energy). The input-output characteristics of this device may drift due to differences in manufacturing processes, design, aging, or environmental changes, thus requiring real-time calibration.

[0021] In some implementations, when the ultrasonic transducer is connected to the ultrasonic ablation host, the host automatically reads the key parameters preset at the factory from the internal storage chip or identifier, thereby obtaining the safe operating voltage range (e.g., 10V to 80V) and power range (e.g., 5W to 50W) of the ultrasonic transducer. This range constitutes a hard safety boundary for all subsequent operations, ensuring that any predicted drive voltage will not exceed the limits of the ultrasonic transducer, thus helping to avoid the risk of transducer damage due to improper voltage settings in traditional step-by-step scanning.

[0022] For example, if a user has specific power requirements (such as specifying that the ultrasound transducer should only operate between 20W and 40W during patient treatment), the intersection of this requirement range and the safe range can be used to form the "electrical power input range".

[0023] For example, in an optional ultrasound transducer performance testing system, the system mainly includes an ultrasound ablation host and an ultrasound transducer connected thereto. During operation, the ultrasound ablation host outputs a voltage signal of a specific frequency to the ultrasound transducer, which then converts the received electrical power into ultrasound power output for treatment, such as for ultrasound ablation of renal artery tissue. It should be noted that the ultrasound transducer is a receiver of electrical power, not an output; its core function is to convert the input electrical power into acoustic power.

[0024] For example, due to differences in transducer manufacturing processes and design variations (such as the type of piezoelectric material, component thickness, radius of curvature, etc.), the response characteristics between received electrical power and driving voltage may vary between different transducers from the same batch and those with different designs. Therefore, it is necessary to dynamically adjust the input voltage signal based on the actual electrical power received by the transducer to ensure the stability of output performance.

[0025] The basic working principle of an ultrasonic transducer can be summarized as follows: by applying a driving voltage of different amplitudes at a specific frequency, the transducer generates a corresponding level of input electrical power, thereby outputting ultrasonic power of corresponding intensity. Under ideal conditions, assuming the transducer's electroacoustic conversion efficiency remains constant, and that this efficiency value has been rigorously tested and recorded in its internal memory chip before the transducer leaves the factory, it can be directly read and used. Under this premise, there is a fixed proportional relationship between the transducer's input electrical power and output acoustic power; that is, by adjusting the driving voltage to change the input electrical power, the output acoustic power can be controlled proportionally.

[0026] Based on the above principles, the core strategy of ultrasonic transducer performance testing technology is to use the voltage scanning method. Using this method, the system can obtain the electrical power response characteristic curves of the transducer under different driving voltages through the ultrasonic ablation host; and since the electroacoustic conversion efficiency is known, this electrical power curve can be indirectly converted into an acoustic power response characteristic curve, both of which are collectively referred to as power response characteristic curves in this application.

[0027] Because ultrasonic transducers are highly sensitive to voltage input, excessively high drive voltages can cause the input power to exceed their rated capacity, resulting in performance degradation or even permanent damage. Furthermore, different transducers require different drive voltages to achieve the same output acoustic power range, further increasing the risk of equipment damage when directly driving the transducer with a fixed voltage. To address this, this application introduces an intelligent prediction algorithm to predict the next applied scanning voltage value in real time during the scanning process. This strategy helps prevent transducer damage due to excessive voltage and also facilitates more accurate scanning of each required acoustic power point, thereby improving the accuracy of output control.

[0028] Step S102: Determine the initial performance curve of the ultrasonic transducer based on the power input range and voltage input range.

[0029] For example, the minimum value of the voltage input range can be correlated with the minimum value of the power input range to form the starting coordinates of the initial performance curve; simultaneously, the maximum value of the voltage input range can be correlated with the maximum value of the power input range to form the ending coordinates of the initial performance curve. Based on these two sets of determined boundary points, a straight line connecting the starting and ending points can be automatically generated, and this straight line is defined as the initial performance curve. This method can quickly provide a basic reference for the zeroth iteration, making it suitable for application scenarios with high initialization speed requirements, and providing a relatively reliable linearized starting point for subsequent performance curve iterations.

[0030] For example, typical response patterns under similar operating conditions can be extracted by accessing historical performance databases of similar devices (devices similar to ultrasonic transducers). Then, based on the feature patterns obtained through statistical learning, and combined with the voltage input range and electrical power input range obtained in this study, a curve reflecting the common response trend of this type of device can be dynamically generated as an initial performance curve. The initial curve generated by this method may exhibit nonlinear characteristics, thus more closely resembling the actual situation of the device and helping to reduce the number of adjustments required for subsequent iterative optimization.

[0031] Step S103: Obtain N expected electrical powers set for the ultrasonic transducer, wherein the expected electrical powers are all located within the electrical power input range, and N is an integer greater than or equal to 1.

[0032] For example, the acquisition of the expected electrical power is guided by pre-set operational requirements. The ultrasonic ablation host can divide the electrical power input range into several target segments according to a plan or preset program. For instance, to achieve a smooth transition from low to high power, a uniformly increasing expected electrical power sequence can be generated, where each power value in the sequence lies within the electrical power input range, and the step size between adjacent values ​​remains constant. This gradually linearly increasing approach not only helps improve the controllability and safety of power output but also ensures that the performance curve establishment process uniformly covers the entire operating range of the ultrasonic transducer, providing more evenly distributed data points for curve fitting.

[0033] For example, the configuration of N expected electrical powers can be customized according to the actual application scenario. For instance, users or upper-level control programs can dynamically define the expected electrical power sequence based on a specific working path. This sequence does not need to change monotonically; it can present an inverted V-shaped waveform (increasing first, then decreasing), a repeating cyclic waveform, or other arbitrarily customized patterns. For example, to simulate periodic power modulation or test the response stability of the device during power abrupt changes, the sequence can include multiple stages such as rising, plateauing, and falling. This non-linear customization method allows the performance curve to not only reflect the static characteristics of the ultrasonic transducer but also detect the actual performance of the ultrasonic transducer under dynamic operating conditions, thereby helping to generate more robust and scenario-adaptive curve models.

[0034] Step S104: Based on the target electrical power actually received by the ultrasonic transducer when it is expected to receive each expected electrical power, the initial performance curve is iteratively updated to obtain the target performance curve of the ultrasonic transducer.

[0035] For example, the iterative update process can be represented as a real-time closed-loop optimization cycle. For instance, during the first update of the initial performance curve, the ultrasonic ablation host calculates the driving voltage corresponding to the first expected electrical power based on the current initial performance curve, and then the ultrasonic transducer operates based on this driving voltage. The ultrasonic ablation host can then acquire the actual target electrical power received by the ultrasonic transducer under this driving voltage, and incorporate this target electrical power and the first expected electrical power as a data pair into the dataset. Then, online estimation algorithms such as recursive least squares can be used to recalculate the fitting function corresponding to the initial performance curve, thereby generating an updated performance curve. Next, the ultrasonic ablation host calculates a new driving voltage for the next expected electrical power based on this updated performance curve, and repeats the process of acquiring target electrical power, forming new data pairs, and updating the performance curve. This cycle repeats, updating the performance curve each time a new data pair is obtained, so that the performance curve continuously approaches the true characteristics of the ultrasonic transducer as data accumulates (gradually acquiring the target electrical power corresponding to each expected electrical power, forming more data pairs), eventually converging into a more accurate target performance curve.

[0036] For example, instead of immediately updating the performance curve after obtaining each set of data pairs, a data accumulation threshold can be preset. For instance, in the early stages of iteration, the ultrasonic ablation host continuously drives the ultrasonic transducer to receive multiple (e.g., five) target electrical powers when multiple (e.g., five) expected electrical powers are expected, forming a batch (e.g., this batch includes 5 sets) of "expected electrical power - target electrical power" data pairs. When the number of accumulated data pairs reaches the threshold, this complete batch of datasets is called all at once, and a fitting algorithm (such as weighted least squares) is used to globally recalculate and optimize all parameters of the initial performance curve, thereby generating a new version of the performance curve. Subsequent iterations will continue to collect the next batch of data based on this new performance curve and perform batch optimization again. This "collect a batch of data pairs, optimize the performance curve once" approach helps reduce the overhead of frequent calculations and can utilize the correlation between data, which is beneficial for generating smoother and more reliable target performance curves.

[0037] In some embodiments, the method for determining the device performance curve proposed in this application dynamically acquires multiple expected electrical powers within the electrical power input range and voltage input range of the ultrasonic transducer, and iteratively updates the initial performance curve based on the actual received electrical power (i.e., target electrical power) when the device is expected to receive these expected electrical powers. This method can reflect the current performance state of the ultrasonic transducer in a timely manner, thus facilitating the achievement of the expected power output by adjusting control parameters (such as voltage) regardless of the performance level of the ultrasonic transducer. In other words, this application, by providing a performance curve determination mechanism, helps improve the timeliness and accuracy of updating the device performance curve. For example, for multiple ultrasonic transducers, using the technical solution of this application, a corresponding target performance curve can be determined for each ultrasonic transducer, thereby facilitating personalized performance management for each ultrasonic transducer. This helps solve the technical problem in the prior art that often relies on a uniform performance curve described at the time of manufacture of the ultrasonic transducer, and cannot determine the actual performance curve of the ultrasonic transducer in a timely manner, resulting in poor accuracy of ultrasonic transducer performance evaluation.

[0038] In some implementations, users can use the technical solutions provided in this application to test the performance curves of one or more ultrasonic transducers at any time. For example, after the ultrasonic transducer leaves the factory, the performance curve of the ultrasonic transducer can be obtained by using the technical solutions provided in this application. If, after the ultrasonic transducer has been used for a period of time, the user believes that the actual performance curve of the ultrasonic transducer may be inconsistent with the performance curve described when the equipment was shipped, the user can also use the technical solutions provided in this application to test the actual performance curve of the ultrasonic transducer.

[0039] In some embodiments, determining the initial performance curve of the ultrasonic transducer based on the power input range and the voltage input range includes: determining the maximum power and minimum power from the power input range, and determining the maximum voltage and minimum voltage from the voltage input range; and determining the initial performance curve of the ultrasonic transducer based on the maximum power, minimum power, maximum voltage, and minimum voltage.

[0040] For example, the ultrasonic ablation host can pair the minimum electrical power within the electrical power input range with the minimum voltage within the voltage input range to form the starting point in a two-dimensional coordinate system; simultaneously, it can pair the maximum electrical power with the maximum voltage to form the ending point. Based on these two sets of limit coordinate points determined by physical safety boundaries, a straight line connecting the starting and ending points is directly generated on the electrical power-voltage plane and defined as the initial performance curve. This straight line represents the maximum possible operating range of the device under an ideal linear model, providing an initial reference framework for subsequent iterative algorithms.

[0041] For example, normalization can be introduced based on the endpoint parameters to construct a more reasonable initial curve. For instance, the ultrasonic ablation unit first processes the input ranges of voltage and power into a normalized scale from 0 to 1, where the minimum value is 0 and the maximum value is 1. Based on the general physical characteristics of the device (e.g., the ultrasonic transducer may exhibit an approximately linear trend in the low-voltage region and a saturated nonlinear trend in the high-voltage region), the ultrasonic ablation unit presets a typical one-dimensional normalized response function. Then, using the actual minimum and maximum voltage and power values ​​as scaling parameters, the normalized function is inversely transformed to map back to the actual physical quantity coordinates, thereby generating an initial performance curve that may exhibit slight curvature. The initial curve generated by this method is likely to be closer to the actual response trend of most similar devices, thus helping to reduce the number of iterations and improve the convergence speed.

[0042] In one optional embodiment, before iteratively updating the initial performance curve based on the target electrical power actually received by the ultrasonic transducer when it is expected to receive each expected electrical power, the voltage signal actually received by the ultrasonic transducer can be acquired during the operation when the ultrasonic transducer is expected to receive each expected electrical power; the voltage signal is sampled to obtain M voltage values ​​and M current values, wherein the M voltage values ​​and M current values ​​are in one-to-one correspondence, and M is an integer greater than or equal to 1; the sampled electrical power is calculated based on the one-to-one correspondence of the voltage values ​​and current values ​​to obtain M sampled electrical powers; and the target electrical power actually received by the ultrasonic transducer when it is expected to receive each expected electrical power is determined based on the M sampled electrical powers.

[0043] For example, the end condition for each voltage signal sampling includes a first condition or a second condition. The first condition includes: ending the current voltage signal sampling when the cumulative received power of the ultrasonic transducer is detected to be greater than or equal to a preset power threshold. The second condition includes: ending the current voltage signal sampling when the operating voltage of the ultrasonic transducer is detected to reach a preset end voltage.

[0044] Taking the example of an ultrasonic transducer outputting energy based on a single operating voltage each time, the current energy output of the ultrasonic transducer will immediately terminate when any of the following conditions are met, and the test process based on the current operating voltage will be considered complete: (1) the actual power received by the ultrasonic transducer reaches or exceeds the preset end power threshold; (2) the current operating voltage reaches or exceeds the preset end voltage threshold. If the power received by the transducer has not yet reached the end power and the operating voltage is still within the safe range, after accumulating a specified number of feedback power data, these data will be submitted to the control terminal for curve fitting processing.

[0045] For example, to obtain the target electrical power actually received by the ultrasonic transducer when it is expected to receive the expected electrical power, an electrical parameter acquisition operation can be performed synchronously during each energy reception of the expected electrical power by the ultrasonic transducer. For example, the voltage signal actually carried at the input terminal of the ultrasonic transducer can be captured in real time through its built-in sensing and data acquisition circuit; the analog voltage signal and the current signal connected in series in the loop are synchronously sampled at high speed and converted from analog to digital to obtain M sets of time-aligned instantaneous voltage and current values; then, the corresponding instantaneous voltage and instantaneous current of each set are multiplied to calculate M instantaneous electrical power sample values ​​in real time; to filter out measurement noise, switching interference and redundant signals, these discrete sampled electrical powers can be further digitally processed, for example, through moving average filtering or median filtering algorithms, to finally output a relatively stable and reliable electrical power value, which is determined as the target electrical power actually received by the ultrasonic transducer under the current driving conditions, and used as the core input data for subsequent curve iteration updates.

[0046] For example, consider an ultrasonic transducer: When the ultrasonic ablation host outputs a driving voltage of a specific frequency (e.g., 3MHz) and amplitude to the transducer based on the current fitted curve, expecting it to receive a certain expected electrical power (e.g., 30W), the monitoring circuit inside the host simultaneously samples the voltage across the piezoelectric ceramic of the transducer and the current flowing through it at high speed. By calculating and filtering the instantaneous voltage and current values ​​obtained over hundreds of sampling periods, the host can more accurately obtain the effective electrical power actually converted by the transducer under this driving condition (e.g., actually measured as 28.5W). This measured power value is the "target electrical power," and the deviation between this "target electrical power" and the expected value of 30W will be used to trigger and guide subsequent parameter corrections to the power-voltage fitting curve to complete iterative updates.

[0047] In one optional embodiment, determining the target electrical power actually received by the ultrasonic transducer when it is expected to receive each expected electrical power, based on M sampled electrical powers, includes: performing mathematical statistical processing on the M sampled electrical powers to obtain a reference electrical power; and performing filtering processing on the reference electrical power to obtain the target electrical power actually received by the ultrasonic transducer when it receives each expected electrical power.

[0048] For example, in order to extract a stable power value that represents the actual operating condition of the ultrasonic transducer from multiple instantaneous sampled electrical power values, the host can adopt a two-stage data processing strategy of first statistical analysis and then filtering: First, mathematical statistical processing is performed on the M sampled electrical power values ​​collected during each energy reception period of the ultrasonic transducer at the expected electrical power level. For example, its arithmetic mean, median, or truncated mean is calculated after removing obvious outliers (such as the maximum and minimum values ​​in the top 5%), thereby obtaining a preliminary "reference power value", which helps to eliminate random measurement errors and obtain a central trend estimate. Subsequently, considering the periodic interference or low-frequency drift that may exist during equipment operation, the reference power value can be further digitally filtered, for example, through a first-order low-pass filter or a Kalman filter, to smooth instantaneous fluctuations and suppress noise in specific frequency bands, and finally output a relatively stable and reliable "target power value".

[0049] In one alternative embodiment, the mathematical statistical processing includes any of the following processing operations:

[0050] The first processing operation is used to calculate the average value of M sampled electrical powers as the reference electrical power when M is greater than or equal to 2.

[0051] The second processing operation is used to calculate the median of the M sampled electrical powers as the reference electrical power when M is greater than 2.

[0052] The third processing operation is used to calculate the average value of the remaining M-2 sampled electrical powers after removing the maximum and minimum values ​​from the M sampled electrical powers when M is greater than 2.

[0053] For example, when the number of sampling points M is large enough (M≥2), the first processing operation can be performed, that is, directly calculating the arithmetic mean of all M sampled electrical powers as the reference electrical power. This method is relatively efficient and suitable for situations where the noise distribution is uniform. When the sampled data may contain asymmetric transient interference or outliers, the second processing operation can be used, that is, taking the median of the M sampled electrical powers as the reference electrical power. This method helps to suppress the interference of extreme outliers and improve the representativeness of the reference value. In more common engineering scenarios, in order to balance efficiency and robustness, the system can perform a third processing operation, that is, after removing one maximum and one minimum value from the M sampled values ​​(i.e. removing possible high-frequency glitches and transient drops), the average value of the remaining M-2 core sampled electrical powers is calculated. This method helps to improve the stability and reliability of the reference electrical power while preserving the main distribution characteristics of the data.

[0054] In one optional embodiment, the initial performance curve is iteratively updated based on the target electrical power actually received by the ultrasonic transducer when it is expected to receive each expected electrical power, to obtain the target performance curve of the ultrasonic transducer. This includes: determining the endpoint power from N expected electrical powers, wherein the endpoint power is the last expected electrical power set for the ultrasonic transducer; and iteratively updating the initial performance curve at least once based on the target electrical power actually received by the ultrasonic transducer when it is expected to receive each expected electrical power and the endpoint power, to obtain the target performance curve of the ultrasonic transducer, wherein the initial performance curve after each iteration update is used as the update object for the next iteration update.

[0055] In some embodiments, the endpoint power is set as the final target anchor point of the entire iterative process. The ultrasound ablation host sequentially drives and samples N expected electrical powers according to a preset order. After acquiring the actual power corresponding to each expected power point, the host can update the current performance curve using all acquired data points, including that point. For example, the update process can consider the extrapolation trend of the curve towards the endpoint power, which helps the updated curve not only fit the existing data, but also ensures that the extension of the updated curve conforms to physical constraints (such as monotonicity and curvature limitations) near the endpoint power. Through this iterative method of "point-by-point acquisition, global fitting, and endpoint guidance," the performance curve gradually evolves from the initial state as data points accumulate, and finally converges into a complete target performance curve that can accurately cover the entire process from the start point to the endpoint after traversing all expected electrical powers.

[0056] In some embodiments, a more flexible, endpoint-referenced intelligent iterative strategy can also be employed. After each iteration updates the performance curve, the voltage required to reach the endpoint power can be predicted using the new curve, and the reasonableness and safety of this prediction (e.g., whether it exceeds the safe voltage range) can be evaluated. If the predicted voltage is deemed unreliable, one or more intermediate expected power points may be dynamically inserted for testing before reaching the final endpoint to obtain richer measured data in the vicinity of the endpoint. Subsequently, the curve is updated again using all the measured information containing these new data points. This endpoint-oriented closed-loop process of "prediction-verification-interpolation-refitting" makes the iterative updates more targeted, ultimately contributing to higher confidence and accuracy of the target performance curve in the critical endpoint power region.

[0057] In one optional embodiment, each iteration update includes: obtaining the fitting function corresponding to the latest initial performance curve; obtaining the origin of the coordinate system and the predicted endpoint of the curve, wherein the coordinate values ​​of the predicted endpoint include: endpoint power and predicted endpoint voltage, the predicted endpoint voltage being obtained based on each target electrical power actually received by the ultrasonic transducer before this iteration update and the historical voltage corresponding to each target electrical power; updating the fitting function according to the origin of the coordinate system and the predicted endpoint of the curve; and obtaining the updated initial performance curve based on the updated fitting function.

[0058] In some embodiments, the current curve function fitted from historical data (i.e., the fitting function corresponding to the latest initial performance curve) is obtained. Based on all accumulated actual received power and the historical voltage corresponding to each actual received power, the predicted endpoint voltage is obtained, thus enabling the curve prediction endpoint. Based on the origin of the coordinate system and the curve prediction endpoint, newly added sub-function coefficients are obtained. These newly added sub-function coefficients are then used to update the fitting function, resulting in the updated initial performance curve. The initial performance curve updated in each iteration serves as the update object for the next iteration, facilitating continuous tracking and correction of the device's dynamic response.

[0059] For example, the ultrasonic ablation host can determine the coefficients to be added to the fitting function by introducing two mandatory constraint points: the origin of the coordinate system (e.g., the physical starting point corresponding to zero voltage and zero power) and the predicted endpoint of the curve, thereby obtaining an updated fitting function and generating the latest performance curve. The ultrasonic ablation host can calculate the predicted endpoint voltage based on the historical voltage and historical received electrical power data of the ultrasonic transducer—that is, each target electrical power and its corresponding voltage actually received before the current iteration update—using trend extrapolation or linear regression algorithms. The predicted endpoint voltage represents the theoretical estimate of the power reaching the endpoint. When updating the curve, the algorithm uses the updated fitting function as a basis and, through coordinate transformation or parameter adjustment, can make the new curve more accurately pass through the origin and the predicted endpoint. This method helps avoid curve drift or endpoint distortion that may occur from simply relying on data fitting, thus improving the physical rationality and target orientation of the updated curve at the two key positions of the starting and ending points.

[0060] For example, based on historical voltage and power data sequences, the changing trends of historical voltage and power can be analyzed (e.g., calculating the recent average slope), and this trend can be extrapolated to obtain the predicted endpoint voltage. In updating the performance curve by updating the coefficients of the fitted function, the system can construct a fusion model using the origin of the coordinate system, the predicted endpoint of the curve, and the latest fitted function. For instance, the latest fitted function can be used as the main component, but origin constraints and predicted endpoint constraints can be introduced as strong weighting conditions to solve for a new curve (that is, one that best fits the latest measured data trend represented by the fitted function, passes through the origin, and converges to the predicted endpoint in the endpoint region). This method, while respecting measured data, incorporates prior knowledge of the endpoints, thereby helping to improve the dynamic adaptability of the updated performance curve and the robustness of the overall structure.

[0061] In some embodiments, obtaining the updated initial performance curve based on the updated fitting function includes: determining the next operating voltage of the ultrasonic transducer based on the updated fitting function and the next expected electrical power; obtaining the target electrical power actually received by the ultrasonic transducer under the next operating voltage; and obtaining the updated initial performance curve based on the next expected electrical power, the target electrical power corresponding to the next expected electrical power, and the updated fitting function.

[0062] For example, after updating the fitting function, the driving voltage corresponding to the next expected power point can be determined by inversion calculation using the latest fitting function. Subsequently, the ultrasonic transducer is controlled to operate under this driving voltage, and the voltage signal sampling and processing procedure is also performed to obtain the target power actually received by the ultrasonic transducer under this driving voltage. Based on the relationship between the next expected power and the corresponding target power, it is determined whether the coefficients in the updated fitting function need to be updated, which is beneficial to obtaining the optimal performance curve.

[0063] In some embodiments, the initial performance curve after this update is obtained based on the next expected power, the target power corresponding to the next expected power, and the updated fitting function. This includes: when the next expected power and the target power corresponding to the next expected power are not equal, correcting the known coefficients in the updated fitting function according to each target power actually received by the ultrasonic transducer before completing this iteration update and the corresponding expected power. The curve corresponding to the fitting function after coefficient correction is the initial performance curve after this update.

[0064] For example, after updating the fitted function, the driving voltage corresponding to the next expected power point can be determined by inversion calculation using the latest fitted function. Subsequently, the ultrasonic transducer is controlled to operate under this driving voltage, and the voltage signal sampling and processing process is also performed to obtain the target power actually received by the ultrasonic transducer under this driving voltage. Once the new data pair is obtained, the host computer will include the data pair into the dataset. If the next expected power and its corresponding target power are not equal, the coefficients in the updated fitted function are recalculated using optimization algorithms such as the least squares method to correct the known coefficients in the updated fitted function, thus completing this iteration update and entering the next round of the "function update-comparison-coefficient correction" cycle.

[0065] For example, if the expected power in the next iteration is equal to the actual target power received, the curve corresponding to the updated fitting function is determined as the initial performance curve after this iteration update.

[0066] In some embodiments, based on the actual target electrical power and the corresponding expected electrical power received by the ultrasonic transducer before completing the current iteration update, the known coefficients in the fitting function are corrected to obtain the corrected fitting function. This includes: calculating the difference between each target electrical power and the corresponding expected electrical power to obtain the power error; calculating the square of each power error and summing the squares of each power error to obtain the total error value; and correcting the known coefficients in the fitting function based on the total error value to obtain the corrected fitting function.

[0067] For example, the process of correcting the known coefficients in the fitted function can employ the least squares optimization principle: The ultrasonic ablation host first calculates the difference between each expected electrical power (command value) and its corresponding measured target electrical power (feedback value) for all historical data points collected within the current iteration cycle. This difference represents the power error reflecting the current curve fitting accuracy. Then, each power error is squared to eliminate the mutual cancellation of positive and negative errors. All squared results are then summed to obtain a total error value that quantifies the overall fitting deviation of the current curve. Finally, minimizing this total error value is the core optimization objective. This is achieved by solving the normal equation system or using numerical optimization algorithms such as gradient descent to refine the fitted function (e.g., a polynomial equation (y = ...)). + x + The known coefficients of each term in (+ ……)) are (e.g.) , , The fitting function is iteratively corrected using coefficients (equal to zero) so that it can better fit the overall distribution trend of all collected data points, thereby generating a corrected fitting function with smaller total prediction deviation and higher accuracy, providing a more reliable mathematical model for voltage prediction in the next stage.

[0068] For example, a sequential closed-loop iterative method can be used to update the performance curve. In some embodiments, the iterative process of the performance curve is a closed-loop loop that proceeds sequentially according to a expected sequence. For instance, after completing one iteration and obtaining a new initial performance curve, it is first determined whether the preset iteration termination condition is met (e.g., whether all expected power points have been scanned). If not, based on the fitting coefficients corresponding to this optimized performance curve, coefficients are added to the fitting function according to the origin of the coordinate system and the predicted endpoint of the curve to obtain the fitting coefficients after this iteration update; and the driving voltage value corresponding to the next expected power is determined by function inverse calculation using the fitting coefficients and the next expected power. Subsequently, the ultrasonic transducer is controlled to operate stably under this driving voltage value, and a complete sampling and data processing flow is executed to obtain the target power actually output by the ultrasonic transducer under this driving voltage value. Once a new measured data pair is obtained (i.e., the latest determined driving voltage value and the corresponding target electric power), this data pair is added to the historical dataset, and the currently determined target electric power is compared with the corresponding expected electric power. If the expected electric power is not equal to the target electric power, the least squares method is used to determine the coefficient error of the fitted function after this update based on all collected target electric powers and the expected electric power corresponding to each target electric power. The coefficient error is then used to correct the coefficients of the updated fitted function, and the curve corresponding to the fitted function with corrected coefficients is determined as the initial performance curve obtained in this iteration, completing this iteration update. If the expected electric power is equal to the target electric power, the curve corresponding to the updated fitted function is determined as the initial performance curve obtained in this iteration update. This initial performance curve, obtained in this iteration update, is used as input to trigger the next round of iteration update. This process repeats continuously, with each iteration advancing based on the optimization results of the previous step, allowing the performance curve to gradually approach the true characteristics of the ultrasonic transducer in a dynamic evolution.

[0069] For example, an adaptive jump-based intelligent iteration method can also be used to iteratively update the performance curve. Some embodiments incorporate intelligent judgment and path optimization strategies during the iteration process. For instance, when an iteration update is completed but the termination condition has not been met, the host does not mechanically determine the next expected power point according to a preset order. Instead, it evaluates the rate of change or curvature characteristics of the curve within the remaining unmeasured power range based on the latest performance curve. If it is determined that the current curve has sufficient confidence in a certain power range, it may choose to skip some intermediate points within that range and select a more distant, representative power value as the next test point (jump target point). Based on the current curve, the predicted voltage required for the jump target point is calculated, and the ultrasonic transducer is driven to operate at the predicted voltage and collect the actual electrical power. If the measured electrical power matches the predicted value, it proves that the jump is reasonable and can accelerate convergence; if there is a large deviation, it will be dynamically adjusted in subsequent iterations, or even backtracked to insert intermediate points. This strategy helps improve iteration efficiency while maintaining accuracy, and is more suitable for application scenarios that require rapid coverage of a wide power range.

[0070] In one optional embodiment, obtaining the curve prediction endpoint includes: taking the target electrical power actually received by the ultrasonic transducer last time before the current iteration update as the first power; obtaining the power difference between the endpoint power and the first power; determining the target coefficient based on the historical voltage change trend and the target electrical power change trend; determining the prediction endpoint voltage based on the target coefficient, the power difference, and the actual voltage used by the ultrasonic transducer when receiving the first power; and generating the curve prediction endpoint using the prediction endpoint voltage and the endpoint power as coordinate values.

[0071] For example, the average ratio of voltage increment to power increment can be calculated by analyzing several historical data points most recent to the current time, and this ratio can be used as a target coefficient (i.e., an approximate dynamic impedance or gain). Then, the difference between the endpoint power and the first power is calculated, and this power difference is multiplied by the target coefficient to obtain an estimated required voltage increment. Adding this voltage increment to the actual voltage used to generate the first power yields the predicted endpoint voltage. This method, based on the assumption of local linearity, helps to quickly respond to recent changes in device characteristics, thereby facilitating the generation of a curve predicting the endpoint that closely follows the current trend, guiding the performance curve to update in a more reasonable direction.

[0072] For example, the host computer can also maintain a dynamically sliding historical data window. A univariate linear regression analysis is performed on the voltage and power sequences within this window, using the slope of the regression line as the target coefficient. This coefficient reflects the average impact rate of voltage on power within the current operating range. After obtaining the power difference, the host computer uses this regression coefficient to calculate the predicted voltage increment and synthesizes it with the actual voltage corresponding to the first power to form the predicted endpoint voltage. This method smooths out noise in historical data through regression fitting, and the sliding window mechanism adaptively tracks changes in device characteristics over time (such as efficiency changes due to temperature rise). This helps to ensure that the determined prediction endpoint is not only based on the current state but also incorporates recent trends, thus facilitating more accurate global updates of the performance curve.

[0073] In some embodiments, the target coefficient is determined based on the changing trends of historical voltage and target power. The method for determining the device performance curve further includes: obtaining each pair of adjacent historical voltages actually received by the ultrasonic transducer and the corresponding historical received power based on the changing trends of historical voltage and target power; calculating a slope value based on each pair of adjacent historical voltages actually received by the ultrasonic transducer and the corresponding target power; summing all the calculated slope values ​​to obtain a slope summary value; and determining the target coefficient based on the slope summary value and the number of historical voltages of the ultrasonic transducer.

[0074] For example, the host computer can first traverse the stored, time-ordered pairs of historical voltage and target power data (i.e., outputting historical voltages to the ultrasonic transducer to anticipate the target power actually received during each expected power period). For each pair of adjacent data points, based on their voltage difference and corresponding power difference, an instantaneous local slope value is calculated. This value characterizes the instantaneous rate of change of voltage versus power of the ultrasonic transducer near a specific operating point. Subsequently, all calculated local slope values ​​are algebraically summed to obtain a slope summary value. Finally, the slope summary value is divided by the number of historical data point pairs used for calculation (i.e., the number of historical voltages minus one) to calculate the arithmetic mean. This arithmetic mean is determined as the final target coefficient. The target coefficient reflects the overall average trend of the voltage-power response characteristics of the ultrasonic transducer within the explored operating range. This is beneficial for providing a relatively robust and statistically significant scaling factor for extrapolating from the current point to the endpoint power, thereby helping to improve the rationality and accuracy of the predicted endpoint voltage calculation.

[0075] For example, Figure 2 This is a flowchart illustrating the detection process of the electrical power response characteristics of an ultrasonic transducer, which is considered as an optional ultrasonic transducer. Figure 2As shown, it includes the following steps:

[0076] Step 1: Determine the working range and step parameters.

[0077] For example, before the first energy output of the ultrasonic transducer, the basic boundary conditions for this test need to be defined, including: setting the target power range (i.e., the power input range) consisting of the starting and ending electrical power, and the corresponding safe voltage range (i.e., the voltage input range) consisting of the starting and ending voltages. Simultaneously, the power step size is set.

[0078] Step 2: Initialize the default power response formula.

[0079] For example, the power response curve is essentially a mathematical formula used to fit and describe the mapping relationship between the driving voltage and the measured electrical power. In this mathematical formula (i.e., the power-voltage fitting curve), y represents the electrical power and x represents the driving voltage. In the initial stage, since there is no measured data, the host uses the linear formula y = + x (corresponding to the initial performance curve) is used for initial estimation. As the number of scans increases and the amount of data accumulates, the fitting formula will gradually increase in order, evolving into y = + x + + ... + This form helps to more accurately characterize nonlinear properties.

[0080] For example, before receiving electrical power for the first time, an initial scan voltage (also known as an initial drive voltage) needs to be determined. The generation of the initial scan voltage relies on a series of default parameters preset based on practical experience (i.e., coefficients in the initial fitting formula). and These parameters provide a reliable starting point for initiating the energy output process and initially characterizing the power response features.

[0081] Step 3: Generate a single-point scanning voltage (i.e., a new driving voltage) based on the algorithm.

[0082] In the initial stage, the system uses preset default parameters. and The initial electrical power and the current power-voltage fitting curve are used to calculate and generate the first single-point scan voltage. Default parameters are used. and It is calculated based on the power range and voltage range determined in step 1 (e.g., through the minimum and maximum endpoints).

[0083] First, obtain the actual electrical power measured during this scan; if the actual electrical power and the corresponding expected electrical power are not equal, use the least squares method, based on all actual received electrical power and the expected electrical power corresponding to each actual received electrical power, to fit the current fitting function (e.g., f(x) = ...). + x + + ... + The coefficients in the formula are corrected; then, the fitting formula is dynamically updated based on the corrected fitting parameters (e.g., f(x) = ...). + x + + ... + ), complete the current iteration.

[0084] For each subsequent scan, a dynamic update strategy is used to generate the scan voltage: during a new iteration, the curve direction (i.e., an) is first determined by combining the origin of the coordinate system (0, 0) and the predicted endpoint (i.e., (endpoint power, predicted endpoint voltage)), thereby obtaining the updated fitting function (e.g., f(x) = ... + x + + ... + + The previous fitted function was f(x) = + x + + ... + The formula for predicting the endpoint voltage is: K (corresponding to the target coefficient mentioned above). (Endpoint power - last actual received target electrical power) + last actual input voltage, where the endpoint power is the last expected electrical power set for the ultrasonic transducer; finally, substitute the expected electrical power value for the next time into the updated fitting formula, and calculate the required scanning voltage for the next time in reverse.

[0085] Where K= ; = .

[0086] Through the above mechanism, the accuracy of the generated scanning voltage is continuously optimized as the collected data accumulates. After each scan, the system compares the expected power with the actual received target power. If a discrepancy exists, all previously scanned voltage-power data pairs are retrieved and the coefficients are recalculated. The more points scanned, the higher the accuracy of the fitting coefficients, and the more precise the subsequent voltage prediction.

[0087] Step 4: Drive the transducer at a fixed frequency and scanning voltage.

[0088] For each scan, the transducer outputs energy according to a pre-set fixed operating frequency and the scan voltage calculated in step 3. During energy output, the input voltage and current signals of the transducer are continuously sampled at preset time intervals to obtain a preset number of instantaneous voltage and current values. Each set of instantaneous voltage and current is multiplied to obtain a preset number of instantaneous sampled power values. To eliminate the influence of noise and instantaneous interference, the maximum and minimum values ​​of the sampled power values ​​are removed, and the arithmetic mean of the remaining values ​​is calculated. This average value is the actual power received in this scan. Once a sufficient number of valid feedback power data points have been accumulated, the energy output process automatically terminates.

[0089] Step 5: Collect the actual received target power and determine whether the actual received target power is equal to its corresponding expected power. If the actual received target power is not equal to its corresponding expected power, update the coefficients in the current fitting formula.

[0090] Optionally, during the operation of the transducer scanning algorithm, an update process for the fitting coefficients is triggered whenever new feedback power data is acquired, such as... Figure 3 As shown, the process includes the following three steps:

[0091] Data filtering: First, the acquired real-time power data undergoes digital filtering. Due to electromagnetic interference, sampling noise, and signal fluctuations in the measurement environment, the raw data may contain transient spikes or abnormal jumps. Through filtering, the system can remove these noise and interference components, extracting a more accurate and stable power value, providing a data foundation for subsequent coefficient calculations.

[0092] Calculate the fitting coefficients: The filtered feedback power data is substituted into the solution formula for calculation. In some embodiments, the least squares method is used as the core fitting algorithm, and the mathematical expression of its error function is as shown in formula (1):

[0093] E= (1)

[0094] in, This represents the actual electrical power value collected during the i-th scan. This indicates the corresponding drive voltage value. This is the currently used fitting function. The fitting function is in the form of a polynomial, as shown in formula (2):

[0095] = + x + + ... + (2)

[0096] For example, by minimizing the error function E, a new set of fitting coefficients is calculated by solving the normal equations. Substituting these new fitting coefficients into the fitting function yields the updated fitting curve, which more accurately reflects the overall distribution trend of all measured data points up to this point.

[0097] In some implementations, the target electrical power measured during the current scan is obtained; if the target electrical power and the corresponding expected electrical power are not equal, the least squares method is used, based on all received target electrical powers and the expected electrical power corresponding to each target electrical power, to fit the current fitting function (e.g., f(x) = ...). + x + +... + The coefficients in the formula are corrected; then, the fitting formula is dynamically updated based on the corrected fitting parameters (e.g., f(x) = ...). + x + + ... + ).

[0098] Through the closed-loop process of "acquisition-filtering-fitting-prediction" described above, the fitting coefficients can be continuously optimized as the amount of data increases, making the fitting curves increasingly approximate the actual power response characteristics of the transducer, thereby improving the accuracy of subsequent voltage prediction.

[0099] Step 6: Determine if the actual electrical power has reached the endpoint power. If the endpoint power has not been reached, repeat steps 3 to 5 until the ultrasonic transducer has completed the performance test based on the endpoint power.

[0100] In some embodiments, after obtaining the target performance curve of the ultrasonic transducer, a target plan can be obtained, wherein the target plan includes at least one planned received electrical power set for the ultrasonic transducer; during the implementation of the target plan using the ultrasonic transducer, the actual electrical power received by the ultrasonic transducer when it is expected to receive each planned received electrical power is collected; each time it is detected that the actual received electrical power of the ultrasonic transducer is inconsistent with the corresponding planned received electrical power, the coefficients in the fitting function corresponding to the target performance curve are updated based on all the electrical power actually received by the ultrasonic transducer and the corresponding planned received electrical power, and the target performance curve is updated based on the updated fitting function.

[0101] For example, the execution of the target plan is also a dynamic maintenance process of the target performance curve. Taking ultrasonic ablation of a target object (e.g., a biomimetic device) using an ultrasonic transducer as an example, the ultrasonic ablation process includes multiple planned received electrical powers (e.g., 30W, 35W, 40W). The driving voltage corresponding to each planned received electrical power is calculated based on the established target performance curve. While the ultrasonic transducer is running based on the driving voltage corresponding to each planned received power, the actual received electrical power can be continuously collected, and the actual received electrical power can be compared with the corresponding planned received electrical power in real time. Once the deviation between the actual value and the planned value is detected to exceed the preset tolerance range, the "planned received electrical power - actual received electrical power" data at that moment is immediately included in the historical dataset, and an online learning algorithm is used to quickly correct the coefficients in the fitting function corresponding to the target performance curve. This point-by-point real-time correction mechanism helps the performance curve to continuously self-calibrate, and even if the transducer experiences characteristic drift due to temperature rise or aging, the ultrasonic ablation host can respond immediately.

[0102] For example, a periodic batch update strategy can also be used to minimize frequent adjustments caused by fluctuations in a single measurement. For instance, during the execution of the target plan, the ultrasound ablation unit can continuously collect the actual received power corresponding to each planned received power, but does not immediately trigger an update every time a deviation is detected. Instead, the ultrasound ablation unit can set a fixed time window or data accumulation threshold (e.g., every 10 planned power measurements). At the end of a cycle, all accumulated "planned received power - actual received power" deviation data pairs within that cycle are summarized. Subsequently, using this batch of data, a weighted least squares method is used to perform a global optimization update of the target performance curve, where the weight of recent data can be set higher to reflect the latest state of the equipment. This method helps filter out transient noise and random interference, making the performance curve update process smoother and more robust. While maintaining the accuracy of the performance curve, it helps avoid system oscillations that may be caused by frequent fine-tuning, making it more suitable for treatment scenarios with high requirements for output stability.

[0103] For example, when a discrepancy is detected between the actual received power and the planned received power of the ultrasonic transducer, a comprehensive update based on global historical data is triggered. Instead of making isolated corrections based solely on the current single deviation data, the ultrasonic ablation host retrieves all accumulated "planned received power - actual received power" data pairs since the establishment of the target performance curve (or since the last global update), forming a complete dataset containing historical operating trajectories. Subsequently, a global optimization algorithm (such as global least squares) is used to recalculate the fitting of this complete dataset, systematically correcting all coefficients in the fitting function corresponding to the target performance curve. Finally, an updated fitting function is generated based on this newly calculated set of coefficients, and the target performance curve is reconstructed based on this. This "one-time trigger, global recalculation" update strategy helps ensure that each correction fully considers all response information of the ultrasonic transducer throughout its entire operating cycle, enabling the updated curve to reflect the latest deviation characteristics while maintaining overall consistency with historical data. This is beneficial for maintaining stable and accurate performance prediction capabilities during the long-term operation of the ultrasonic transducer.

[0104] In some embodiments, when the actual electrical power received by the ultrasonic transducer is found to be inconsistent with the corresponding planned electrical power, the coefficients in the fitting function corresponding to the target performance curve are updated based on all the electrical power actually received by the ultrasonic transducer and the corresponding planned electrical power. This includes: calculating the difference between the actual electrical power received by the ultrasonic transducer and the corresponding expected electrical power each time to obtain a power error; calculating the square of each power error, and summing the squares of each power error to obtain a total error value; and updating the coefficients in the fitting function based on the total error value.

[0105] For example, during the process of establishing the target performance curve and executing the target plan, it is still necessary to continuously maintain and dynamically update the target performance curve, such as... Figure 4 As shown, it includes the following steps:

[0106] Data filtering: During the treatment with ultrasound energy, the actual electrical power data received by the transducer is continuously collected, and this electrical power data is digitally filtered. By eliminating noise and interference, a more accurate and stable electrical power value is obtained, providing a reliable data foundation for subsequent curve updates.

[0107] Calculate and weightedly fuse fitting coefficients: Substitute the filtered power data into the coefficient calculation formula to calculate a set of fitting coefficients based on the latest measured data. Unlike the initial setup phase, in the therapeutic application phase, these new coefficients are not directly used to replace the original coefficients. Instead, the new coefficients are weighted and fused with the coefficients obtained through the coefficient calculation formula during the establishment of the target fitting curve. The weight of recent data can be appropriately increased to reflect the current latest state of the transducer; that is, the weight of data determined more recently is greater than the weight of data determined earlier.

[0108] Correcting existing fitted curves: The newly calculated weighted and fused fitting coefficients are added to the existing fitted curve algorithm, replacing or correcting the coefficients of the original curve. This dynamic correction mechanism can compensate for performance drift phenomena such as aging and temperature rise caused by long-term operation of the transducer.

[0109] According to another aspect of the embodiments of this application, a device for determining a device performance curve is also provided, such as... Figure 5 As shown, the device includes: a first acquisition unit 501, used to acquire the power input range and voltage input range of the ultrasonic transducer; a first determination unit 502, used to determine the initial performance curve of the ultrasonic transducer based on the power input range and voltage input range; a second acquisition unit 503, used to acquire N expected power values ​​set for the ultrasonic transducer, where the expected power values ​​are all located within the power input range and N is an integer greater than 1; and a second determination unit 504, used to iteratively update the initial performance curve based on the target power actually received by the ultrasonic transducer when it is expected to receive each expected power value, to obtain the target performance curve of the ultrasonic transducer.

[0110] Optionally, the first determining unit 502 includes: a first determining subunit, used to determine the maximum and minimum electric power from the electric power input range, and the maximum and minimum voltage from the voltage input range; and a second determining subunit, used to determine the initial performance curve of the ultrasonic transducer based on the maximum electric power, minimum electric power, maximum voltage, and minimum voltage.

[0111] Optionally, the device for determining the device performance curve further includes: a third acquisition unit, used to acquire the voltage signal actually received by the ultrasonic transducer during operation when the ultrasonic transducer is expected to receive each expected electrical power; a sampling unit, used to sample the voltage signal to obtain M voltage values ​​and M current values, wherein the M voltage values ​​and M current values ​​correspond one-to-one, and M is an integer greater than or equal to 1; a calculation unit, used to calculate the sampled electrical power based on the one-to-one correspondence of the voltage values ​​and current values ​​to obtain M sampled electrical powers; and a third determination unit, used to determine the target electrical power actually received by the ultrasonic transducer when it is expected to receive each expected electrical power based on the M sampled electrical powers.

[0112] Optionally, the third determining unit includes: a mathematical statistics subunit, used to perform mathematical statistics processing on the M sampled electrical powers to obtain a reference electrical power; and a filtering subunit, used to perform filtering processing on the reference electrical power to obtain the target electrical power actually received by the ultrasonic transducer when receiving each expected electrical power.

[0113] Optionally, mathematical statistical processing includes any of the following processing operations:

[0114] The first processing operation is used to calculate the average value of M sampled electrical powers as the reference electrical power when M is greater than or equal to 2.

[0115] The second processing operation is used to calculate the median of the M sampled electrical powers as the reference electrical power when M is greater than 2.

[0116] The third processing operation is used to calculate the average value of the remaining M-2 sampled electrical powers after removing the maximum and minimum values ​​from the M sampled electrical powers when M is greater than 2.

[0117] Optionally, the second determining unit 504 includes: a third determining subunit, used to determine the endpoint power from N expected electrical powers, wherein the endpoint power is the last expected electrical power set for the ultrasonic transducer; and an iterative updating subunit, used to perform at least one iterative update on the initial performance curve based on the target electrical power actually received by the ultrasonic transducer when receiving each expected electrical power and the endpoint power, to obtain the target performance curve of the ultrasonic transducer, wherein the initial performance curve after each iterative update is used as the update object for the next iterative update.

[0118] Optionally, the iterative update subunit includes: a first processing module for obtaining the fitting function corresponding to the latest initial performance curve; a second processing module for obtaining the origin of the coordinate system and the predicted endpoint of the curve, wherein the coordinate values ​​of the predicted endpoint include: the endpoint power and the predicted endpoint voltage, the predicted endpoint voltage being obtained based on each target electrical power actually received by the ultrasonic transducer before this iterative update and the historical voltage corresponding to each target electrical power; updating the fitting function according to the origin of the coordinate system and the predicted endpoint of the curve; and obtaining the updated initial performance curve based on the updated fitting function.

[0119] Optionally, the device for determining the equipment performance curve further includes: a first updating unit, used to determine the next operating voltage of the ultrasonic transducer based on the updated fitting function and the next expected electrical power, and to obtain the target electrical power actually received by the ultrasonic transducer under the next operating voltage; and a second updating unit, used to obtain the updated initial performance curve based on the next expected electrical power, the target electrical power corresponding to the next expected electrical power, and the updated fitting function.

[0120] Optionally, the second update unit includes a second update subunit, which is used to obtain each target power and corresponding expected power actually received by the ultrasonic transducer before completing the current iteration update, when the next expected power and the target power corresponding to the next expected power are not equal; based on each target power and corresponding expected power actually received by the ultrasonic transducer before completing the current iteration update, the known coefficients in the updated fitting function are corrected, and the curve corresponding to the fitted function after coefficient correction is the initial performance curve after this update.

[0121] Optionally, the second processing module includes: a power difference determination submodule, used to take the target electrical power actually received by the ultrasonic transducer last time before the current iteration update as the first power; and obtain the power difference between the endpoint power and the first power; a target coefficient determination submodule, used to determine the target coefficient based on the historical voltage change trend and the target electrical power change trend; a predicted endpoint voltage determination submodule, used to determine the predicted endpoint voltage based on the target coefficient, the power difference, and the actual voltage used by the ultrasonic transducer when receiving the first power; and a curve predicted endpoint determination submodule, used to generate a curve predicted endpoint using the predicted endpoint voltage and the endpoint power as coordinate values.

[0122] Optionally, the target coefficient determination submodule includes: a first acquisition submodule, used to acquire, based on the changing trends of historical voltages and the changing trends of target power, each pair of adjacent historical voltages actually received by the ultrasonic transducer and the target power corresponding to those two historical voltages; a slope calculation submodule, used to calculate a slope value based on each pair of adjacent historical voltages actually received by the ultrasonic transducer and the target power corresponding to those two historical voltages respectively; a summary calculation submodule, used to sum all the calculated slope values ​​to obtain a slope summary value; and a target coefficient determination submodule, used to determine the target coefficient based on the slope summary value and the number of historical voltages of the ultrasonic transducer.

[0123] Optionally, the end condition for each sampling of the voltage signal includes a first condition or a second condition, wherein the first condition includes: ending the sampling of the current voltage signal when the cumulative received power of the ultrasonic transducer is detected to be greater than or equal to a preset power threshold; and the second condition includes: ending the sampling of the current voltage signal when the operating voltage of the ultrasonic transducer is detected to reach a preset end voltage.

[0124] Optionally, the device for determining the device performance curve further includes: a target plan acquisition unit, configured to acquire a target plan after obtaining the target performance curve of the ultrasonic transducer, wherein the target plan includes at least one planned received electrical power set for the ultrasonic transducer; an acquisition unit, configured to acquire the actual electrical power received by the ultrasonic transducer when it is expected to receive each planned received electrical power during the implementation of the target plan using the ultrasonic transducer; and a target update unit, configured to update the coefficients in the fitting function corresponding to the target performance curve based on all the electrical power actually received by the ultrasonic transducer and the planned received electrical power corresponding to each of the all electrical powers, and update the target performance curve based on the updated fitting function, whenever the actual electrical power received by the ultrasonic transducer is detected to be inconsistent with the corresponding planned received electrical power.

[0125] Optionally, the target update unit includes: a first calculation subunit, used to calculate the difference between the actual electrical power received by the ultrasonic transducer each time and the corresponding expected electrical power, to obtain the power error; a second calculation subunit, used to calculate the square of each power error, and then sum the squared results of each power error to obtain the total error value; and a third calculation subunit, used to update the coefficients in the fitting function according to the total error value.

[0126] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer-readable storage medium, wherein when the computer program is executed, the device in which the computer-readable storage medium is located performs the above-described method for determining the device performance curve.

[0127] According to another aspect of the embodiments of this application, an electronic device is also provided, including one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by one or more processors, the one or more processors cause the one or more processors to perform the above-described method for determining the device performance curve.

[0128] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program or instructions, which, when executed by a processor, implement the above-described method for determining the device performance curve.

[0129] It should be noted that the technical solutions formed by any of the above-described implementation methods (or embodiments) or any combination of implementation methods (or embodiments) are all within the scope of protection of this application.

[0130] Whenever a range of values ​​is indicated in this application, it refers to any of the listed values ​​(fractions and integers) that fall within the indicated range. The phrases “range between the first indicated value and the second indicated value” and “range from the first indicated value to the second indicated value” are used interchangeably in this application and refer to the values ​​indicated by the first and second indications, as well as all fractional and integer values ​​in between.

[0131] As used herein, when used in conjunction with numerical values ​​and / or ranges, the terms “about” and / or “approximately” generally refer to numerical values ​​and / or ranges that are close to the given value and / or range. In some cases, the terms “about” and “approximately” may mean within ±10% of the value. For example, in some cases, “about 100 [units]” may mean within ±10% of 100 (e.g., 90 to 110). The terms “about” and “approximately” are used interchangeably.

[0132] As used in this application, the singular forms “an,” “a,” and “the” include the plural forms unless the context clearly specifies otherwise. For example, the terms “a compound” or “at least one compound” can include a variety of compounds, including mixtures thereof.

[0133] The term "basically composed of" means that a composition, method, or structure may include additional ingredients, operations, and / or components, provided that these additional ingredients, operations, and / or components do not significantly alter the fundamental and novel properties of the claimed composition, method, or structure.

[0134] The implementation of the methods and / or systems of this application may include performing or fully performing selected tasks manually, automatically, or in a combination thereof. Furthermore, the actual instruments and equipment used in the implementation of the methods and / or systems of this application, using an operating system, may implement several selected tasks via hardware, software, firmware, or a combination thereof.

[0135] For example, the hardware used to perform the selected task according to embodiments of this application can be implemented in the form of a chip or circuit. As software, the selected task according to embodiments of this application can be implemented in the form of multiple software instructions executable by a computer using any suitable operating system. In exemplary embodiments of this application, one or more tasks of exemplary embodiments of the methods and / or systems according to this application are performed by a data processor, such as a computing platform for executing multiple instructions. Optionally, the data processor includes volatile memory for storing instructions and / or data and / or non-volatile memory for storing instructions and / or data, such as a magnetic hard disk and / or removable media. Optionally, a network connection is also provided. A display and / or user input devices such as a keyboard or mouse are also optionally provided.

[0136] It should be understood that certain features of this application described in the context of a single implementation for clarity can also be provided in combination in a single implementation. Conversely, multiple features of this application described in the context of a single implementation for brevity can also be provided individually or in any suitable sub-combination or, as appropriate, in any other described implementation of this application. Certain features described in the context of multiple implementations should not be considered essential features of those implementations unless the implementation does not function without these elements.

[0137] Although this application has been described in conjunction with its specific embodiments, it will be apparent to those skilled in the art that many alternatives, modifications, and variations are possible. Therefore, it is intended to include all such alternatives, modifications, and variations falling within the spirit and broad scope of the appended claims.

Claims

1. A method for determining the performance curve of a device, characterized in that, include: Obtain the electrical power input range and voltage input range of the ultrasonic transducer; The initial performance curve of the ultrasonic transducer is determined based on the power input range and the voltage input range. Obtain N expected electrical powers set for the ultrasonic transducer, wherein the expected electrical powers are all located within the electrical power input range, and N is an integer greater than or equal to 1; The initial performance curve is iteratively updated based on the target electrical power actually received by the ultrasonic transducer when it is expected to receive each of the expected electrical powers, to obtain the target performance curve of the ultrasonic transducer.

2. The method for determining the equipment performance curve according to claim 1, characterized in that, The initial performance curve of the ultrasonic transducer is determined based on the power input range and the voltage input range, including: The maximum and minimum electrical power are determined from the electrical power input range, and the maximum and minimum voltage are determined from the voltage input range; The initial performance curve of the ultrasonic transducer is determined based on the maximum electric power, the minimum electric power, the maximum voltage, and the minimum voltage.

3. The method for determining the equipment performance curve according to claim 1, characterized in that, Before iteratively updating the initial performance curve based on the target electrical power actually received by the ultrasonic transducer when it is expected to receive each of the expected electrical powers, the method further includes: During operation in which the ultrasonic transducer is expected to receive each of the expected electrical powers, the voltage signal actually received by the ultrasonic transducer is acquired. The voltage signal is sampled to obtain M voltage values ​​and M current values, wherein the M voltage values ​​and the M current values ​​correspond one-to-one, and M is an integer greater than or equal to 1; The sampled electrical power is calculated based on the one-to-one corresponding voltage and current values, resulting in M ​​sampled electrical powers. Based on the M sampled electrical powers, determine the actual target electrical power received by the ultrasonic transducer when it is expected to receive each of the expected electrical powers.

4. The method for determining the equipment performance curve according to claim 3, characterized in that, Based on the M sampled electrical powers, determine the target electrical power actually received by the ultrasonic transducer when it is expected to receive each of the expected electrical powers, including: The reference power is obtained by performing mathematical statistical processing on the M sampled electrical powers; The reference electrical power is filtered to obtain the actual target electrical power received by the ultrasonic transducer when receiving each expected electrical power.

5. The method for determining the equipment performance curve according to claim 4, characterized in that, The mathematical statistical processing includes any one of the following processing operations: The first processing operation is used to calculate the average value of the M sampled electrical powers as the reference electrical power when M is greater than or equal to 2. The second processing operation is used to calculate the median of the M sampled electrical powers as the reference electrical power when M is greater than 2. The third processing operation is used to calculate the average value of the remaining M-2 sampled electrical powers after removing the maximum and minimum values ​​of the M sampled electrical powers when M is greater than 2.

6. The method for determining the equipment performance curve according to claim 1, characterized in that, Based on the target electrical power actually received by the ultrasonic transducer when it is expected to receive each of the expected electrical powers, the initial performance curve is iteratively updated to obtain the target performance curve of the ultrasonic transducer, including: Determine the endpoint power from N expected electrical powers, wherein the endpoint power is the last expected electrical power set for the ultrasonic transducer; Based on the target electrical power actually received by the ultrasonic transducer when it is expected to receive each of the expected electrical powers and the endpoint power, the initial performance curve is iterated and updated at least once to obtain the target performance curve of the ultrasonic transducer, wherein the initial performance curve after each iteration update is used as the update object for the next iteration update.

7. The method for determining the equipment performance curve according to claim 6, characterized in that, Each iteration update includes: Obtain the fitting function corresponding to the latest initial performance curve; Obtain the origin of the coordinate system and the predicted endpoint of the curve, wherein the coordinate values ​​of the predicted endpoint of the curve include: the endpoint power and the predicted endpoint voltage, and the predicted endpoint voltage is obtained based on the actual target electrical power received by the ultrasonic transducer before the current iteration update and the historical voltage corresponding to each target electrical power; The fitting function is updated based on the origin of the coordinate system and the predicted endpoint of the curve; Based on the updated fitting function, the updated initial performance curve is obtained.

8. The method for determining the equipment performance curve according to claim 7, characterized in that, Based on the updated fitting function, the updated initial performance curve is obtained, including: Based on the updated fitting function and the expected power for the next operation, the next operating voltage of the ultrasonic transducer is determined, and the target power actually received by the ultrasonic transducer under the next operating voltage is obtained. Based on the next expected power, the target power corresponding to the next expected power, and the updated fitting function, the updated initial performance curve is obtained.

9. The method according to claim 8, characterized in that, Based on the next expected power, the target power corresponding to the next expected power, and the updated fitting function, the updated initial performance curve is obtained, including: If the next expected power and the target power corresponding to the next expected power are not equal, obtain each target power and the corresponding expected power actually received by the ultrasonic transducer before completing the current iteration update. Based on the actual target electrical power and the corresponding expected electrical power received by the ultrasonic transducer before completing this iteration update, the known coefficients in the updated fitting function are corrected, and the curve corresponding to the fitted function after coefficient correction is the initial performance curve after this update.

10. The method for determining the equipment performance curve according to claim 7, characterized in that, To obtain the predicted endpoint of the curve, including: The target electrical power actually received by the ultrasonic transducer before the current iteration update is taken as the first power. Obtain the power difference between the endpoint power and the first power; The target coefficient is determined based on the historical voltage variation trend and the target power variation trend. The predicted endpoint voltage is determined based on the target coefficient, the power difference, and the actual voltage used by the ultrasonic transducer when receiving the first power. The predicted endpoint voltage and the endpoint power are used as coordinate values ​​to generate the predicted endpoint of the curve.

11. The method for determining the equipment performance curve according to claim 10, characterized in that, The target coefficient is determined based on the historical voltage variation trend and the target power variation trend, including: Based on the changing trends of the historical voltage and the changing trends of the target power, the actual two adjacent historical voltages received by the ultrasonic transducer and the target power corresponding to those two historical voltages are obtained. A slope value is calculated based on each pair of adjacent historical voltages actually received by the ultrasonic transducer and the target electrical power corresponding to those two historical voltages. Sum all the calculated slope values ​​to obtain a total slope value; The target coefficient is determined based on the sum of the slope values ​​and the number of historical voltages of the ultrasonic transducer.

12. The method for determining the equipment performance curve according to claim 3, characterized in that, The end condition for each sampling of the voltage signal includes a first condition or a second condition. The first condition includes ending the sampling of the voltage signal when the cumulative received power of the ultrasonic transducer is detected to be greater than or equal to a preset power threshold. The second condition includes ending the sampling of the voltage signal when the operating voltage of the ultrasonic transducer is detected to reach a preset end voltage.

13. The method for determining the equipment performance curve according to claim 1, characterized in that, After obtaining the target performance curve of the ultrasonic transducer, the method further includes: Obtain a target plan, wherein the target plan includes at least one planned received electrical power set for the ultrasonic transducer; During the implementation of the target plan using the ultrasonic transducer, the actual electrical power received by the ultrasonic transducer when it is expected to receive each of the planned electrical power is collected; In each instance where the actual electrical power received by the ultrasonic transducer is inconsistent with the corresponding planned electrical power, the coefficients in the fitting function corresponding to the target performance curve are updated based on all the electrical power actually received by the ultrasonic transducer and the planned electrical power corresponding to each of the all electrical powers, and the target performance curve is updated based on the updated fitting function.

14. The method for determining the equipment performance curve according to claim 13, characterized in that, Based on all the electrical power actually received by the ultrasonic transducer and the planned received electrical power corresponding to each of those electrical powers, the coefficients in the fitting function corresponding to the target performance curve are updated, including: The power error is obtained by calculating the difference between the actual electrical power received by the ultrasonic transducer each time and the corresponding expected electrical power. Calculate the square of each power error, and sum the squares of each power error to obtain the total error value; The coefficients in the fitted function are updated based on the total error value.

15. A device for determining the performance curve of an equipment, characterized in that, include: The first acquisition unit is used to acquire the power input range and voltage input range of the ultrasonic transducer; The first determining unit is used to determine the initial performance curve of the ultrasonic transducer based on the electric power input range and the voltage input range; The second acquisition unit is used to acquire N expected electrical powers set for the ultrasonic transducer, wherein the expected electrical powers are all located within the electrical power input range, and N is an integer greater than 1; The second determining unit is used to iteratively update the initial performance curve based on the target electrical power actually received by the ultrasonic transducer when it is expected to receive each of the expected electrical powers, so as to obtain the target performance curve of the ultrasonic transducer.

16. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein when the computer program is executed, the device in which the computer-readable storage medium is located performs the method for determining the device performance curve as described in any one of claims 1 to 14.

17. An electronic device, characterized in that, It includes one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to perform the method for determining the device performance curve as described in any one of claims 1 to 14.

18. A computer program product, characterized in that, It includes a computer program or instructions that, when executed by a processor, implement the method for determining the device performance curve as described in any one of claims 1 to 14.

Images