CN111481842A - A wearable ultrasonic therapeutic apparatus based on dynamic matching - Google Patents

Abstract

The invention discloses a wearable ultrasonic therapeutic apparatus based on dynamic matching, which comprises a main control unit, a signal generation module, a power amplifier, an impedance matching module, an ultrasonic transducer, an automatic frequency tracking module and a power supply module, wherein the main control unit is used for controlling the power amplifier to output power; the main control unit is respectively connected with the signal generation module, the frequency automatic tracking module and the power supply module, the power supply module is further connected with the shaping filter circuit and the power amplifier, the power amplifier is further connected with the impedance matching module, the impedance matching module is connected with the ultrasonic transducer, and the ultrasonic transducer is connected with the frequency automatic tracking module. According to the invention, the dynamic matching inductance is output, and the reactance angle of the reactor is adjusted in real time according to the size of the dynamic inductance, so that the voltage and the current at two ends of the transducer are changed, and the dynamic adjustment of the matching inductance is realized by adopting closed-loop control.

Description

A wearable ultrasonic therapeutic apparatus based on dynamic matching

technical field

The invention belongs to the technical field of ultrasonic therapy equipment, in particular to a wearable ultrasonic therapy instrument based on dynamic matching.

Background technique

Chronic soft tissue injury is a common disease and its etiology has not yet been determined. Science has shown that the use of ultrasound therapy has a positive therapeutic effect on the treatment of different types of chronic soft tissue injuries.

Ultrasonic technology is widely used in industrial production, such as electronic packaging industry, ultrasonic processing industry, etc. Generally, high-power ultrasound equipment must have a matching circuit, but most of the current matching circuits use static matching circuits, and the research is carried out under the condition that no load is added to the system. In fact, during the processing of the transducer, temperature changes, load changes and tool wear will affect the changes of the transducer parameters, which will inevitably lead to static matching imbalance, which will cause problems such as reactive power generation and vibration amplitude reduction. . Obviously, static matching is not suitable for long-term operation of high-power equipment.

The frequency tracking method of the conventional phase-locked loop technology is easy to lose lock, while the ordinary fuzzy control lacks the self-integral dynamic response ability, and cannot maintain an automatic processing function of real-time adjustment of parameters in the system, and the tracking speed is slow, which cannot guarantee the system dynamic. Effect.

Through the analysis of some of the existing ultrasonic physiotherapy devices, the main problems currently exist:

(1) The current matching circuit does not add any neural network algorithm, and the adjustment effect is poor, resulting in unstable output sound intensity. And most of them use static matching circuits, which are prone to static matching misalignment.

(2) The frequency tracking speed is slow and the dynamic response capability is weak. It is impossible to maintain an automatic processing function of adjusting parameters in real time in the system, and the dynamic effect of the system cannot be guaranteed. When the transduction system dynamically matches the switching inductance, the lock phenomenon is easily lost, and the overall performance of the dynamic matching circuit of the transduction system is low. The frequency tracking method of the conventional phase-locked loop technology is easy to lose lock, while the ordinary fuzzy control tracking speed is slow and the dynamic response capability is weak.

(3) Does not have wearable properties. Most of the therapeutic devices are bulky, duplicated in operation, complicated in charging, and have not been truly wearable.

SUMMARY OF THE INVENTION

In order to solve the technical problems existing in the above-mentioned prior art, the present invention provides a wearable ultrasonic therapeutic apparatus based on dynamic matching. The therapeutic apparatus of the present invention adopts intelligent algorithms to jointly realize the impedance dynamic matching of the ultrasonic therapeutic apparatus, improves the overall performance of the dynamic matching circuit of the transducer system, and generates efficient and stable output ultrasonic waves.

The present invention is achieved through the following technical solutions:

A wearable ultrasonic therapeutic apparatus based on dynamic matching, comprising a main control unit, a signal generation module, a power amplifier, an impedance matching module, an ultrasonic transducer, an automatic frequency tracking module and a power supply module; The signal generating module, the frequency automatic tracking module and the power supply module are connected, the power supply module is also connected with the shaping filter circuit and the power amplifier, the power amplifier is also connected with the impedance matching module, and the impedance matching module is connected with the ultrasonic transducer, The ultrasonic transducer is connected with the frequency automatic tracking module;

The main control unit is used to control the signal generator to generate the DDS signal, the power amplification module is used to amplify the DDS signal to generate an enabling signal of the ultrasonic transducer, and the impedance matching module is used to dynamically adjust the ultrasonic transducer. The matching inductance; the automatic frequency tracking module enables the output frequency of the ultrasonic transducer to track the input frequency of the transducer in real time;

The power supply module supplies power to the main control unit, the signal generating module and the power amplifying module.

Aiming at the problem that the current matching circuit is prone to static matching misalignment, the impedance matching module dynamically adjusts the matching inductance of the ultrasonic transducer; at the same time, the invention solves the phenomenon that the ultrasonic system is easy to lose lock when the inductance is dynamically matched and switches, and improves the transduction system. Dynamically match the overall performance of the circuit to generate efficient and stable output ultrasonic waves.

The impedance matching module of the present invention outputs the dynamic matching inductance through the BP neural network, and adjusts the reactance angle of the reactor in real time according to the size of the dynamic inductance, thereby changing the magnitude of the voltage and current at both ends of the transducer, and adopts closed-loop control to realize the matching inductance dynamic adjustment. Preferably, the impedance matching module of the present invention includes a data detection module, a data preprocessing module and a BP neural network module, the input parameters of the ultrasonic transducer are collected through the data detection module, and the data preprocessing module performs the input parameters and output parameters. After processing the training sample data, the BP neural network module inputs the training sample data into the BP neural network for training, and uses the trained neural network to output the matching inductance in real time to realize the dynamic adjustment of the matching inductance.

Preferably, the input parameters of the present invention are five variables that cause changes in the internal parameters of the transducer, including transducer temperature, ultrasonic frequency, voltage value at both ends of the transducer, current value at both ends of the transducer, and depth of the transducer. The depth of the water tank, the output parameter is the matching inductance value.

Preferably, the BP neural network module of the present invention is configured to perform the following steps:

S1, the BP neural network learns and trains multiple sample data, and adjusts the weights of the network to achieve the minimum error, thereby obtaining a trained BP neural network;

S2, using the BP neural network trained in step S1 to output the matching inductance, which is used to adjust the reactance angle of the reactor in real time, thereby changing the magnitude of the voltage and current at both ends of the transducer;

In S3, the dynamic adjustment of the matching inductance can be realized by repeating the execution of S2.

The frequency automatic tracking module of the invention adopts the automatic frequency tracking technology based on the fuzzy neural network, so that the output frequency of the ultrasonic transducer can track its input frequency in real time, the frequency tracking speed of the system is improved, and the working frequency of the ultrasonic therapeutic apparatus is improved. Preferably, the frequency automatic tracking module of the present invention includes a voltage and current acquisition module, a phase detector and a Fuzzy neural network controller, and the voltage and current acquisition module is used for real-time acquisition of voltage and current signals at both ends of the transducer and transmission of the signals to A phase detector, the phase detector obtains the phase difference and the rate of change of the phase difference according to the voltage and current signals, and inputs them into the Fuzzy neural network controller to adjust the phase difference to realize automatic frequency tracking.

Preferably, the Fuzzy neural network controller of the present invention is configured to perform the following steps:

S11, the phase difference and the rate of change of the phase difference are used as the input of the fuzzy neural network, the adjusted phase difference is used as the output of the fuzzy neural network, and the input and output are mapped by the neural network algorithm;

S12, determine the fuzzification, membership function and fuzzy rules, and obtain the Fuzzy neural network model;

S13, using multiple data samples to train the Fuzzy neural network model to obtain a trained Fuzzy neural network model;

S14, input the phase difference obtained in real time and the rate of change of the phase difference into the trained Fuzzy neural network model to output the size of the adjusted phase difference;

S15 , changing the current at both ends of the transducer, and repeating step S14 until the phase difference is zero, so that the signal output frequency is gradually consistent with the input frequency, and automatic frequency tracking is realized.

The present invention simplifies the volume of the instrument by arranging a power supply module to provide voltages with different requirements for different modules in the whole instrument. Preferably, the power supply module of the present invention adopts a 12V rechargeable polymer lithium battery pack, and the polymer lithium battery pack raises the 12V voltage to 48V through the boost boosting module, and directly supplies power to the power amplifier module; The 12V voltage is converted into 5V to supply power for the signal generation module; then the 5V voltage is converted into 3.3V through the voltage regulator chip to supply power to the main control unit.

Preferably, the signal generating module of the present invention includes a DDS signal generator, a shaping filter circuit and a driving circuit; the DDS signal generator is connected to the main control unit through a serial bus, and the main control unit generates a 2MHz square wave, and the driving circuit converts the DDS The 2MHz square wave generated by the signal generator is divided into a 1MHz square wave, which is then shaped by the shaping filter circuit and sent to the power amplifier module.

The present invention is also provided with a safety protection device for protecting the safety of personnel and equipment. Preferably, the present invention also includes a temperature control module, which uses a thermistor to collect the temperature at both ends of the ultrasonic transducer in real time. When the temperature exceeds a set safety threshold, the power is automatically controlled to ensure the safety of the user.

Preferably, the present invention further includes an overcurrent and overvoltage protection module and a human-computer interaction module, and both the human-computer interaction module and the overcurrent and overvoltage protection module are connected to the main control unit, and the human-computer interaction module is used for ultrasonic intensity Adjust and display the current ultrasonic intensity in gear, the over-current and over-voltage protection module is used for output over-voltage protection and over-current protection.

The present invention has the following advantages and beneficial effects:

1. The present invention introduces a BP neural network controller to realize the dynamic adjustment of the matching inductance. The invention outputs the dynamic matching inductance through the BP neural network controller, and adjusts the reactance angle of the reactor in real time according to the size of the dynamic inductance, thereby changing the magnitude of the voltage and current at both ends of the transducer, and adopts closed-loop control to realize the dynamic adjustment of the matching inductance. . Ordinary impedance matching does not add any neural network algorithm, and the adjustment effect is poor, resulting in unstable output sound intensity. And most of them use static matching circuits, which are prone to static matching misalignment.

2. The present invention proposes an automatic frequency tracking technology based on a fuzzy neural network, which enables the output frequency of the ultrasonic power supply to track the input frequency of the transducer in real time. The fuzzy neural network is added to the frequency tracking module, which makes the dynamic matching high accuracy and the frequency automatic tracking speed fast. It solves the phenomenon that the transduction system is easy to lose lock when the inductance is dynamically matched and switches, and improves the overall performance of the dynamic matching circuit of the transduction system. . It solves the pain points of slow tracking speed, weak dynamic response ability and easy lock loss of phase-locked loop technology in ordinary fuzzy control.

3. The ultrasonic therapeutic apparatus of the present invention is of a wearable design, which further simplifies the volume of the ultrasonic therapeutic apparatus by reducing the complex human-computer interaction interface and using battery power and wireless charging.

Description of drawings

The accompanying drawings described herein are used to provide further understanding of the embodiments of the present invention, and constitute a part of the present application, and do not constitute limitations to the embodiments of the present invention. In the attached image:

FIG. 1 is a structural block diagram of the ultrasonic therapeutic apparatus of the present invention.

FIG. 2 is a schematic block diagram of the principle of the impedance matching module of the present invention.

FIG. 3 is a schematic block diagram of the principle of the automatic frequency tracking module of the present invention.

Detailed ways

Hereinafter, the terms "comprising" or "may include" as may be used in various embodiments of the present invention indicate the presence of an invented function, operation or element and do not limit the identity of one or more functions, operations or elements Increase. Furthermore, as used in various embodiments of the present invention, the terms "comprising", "having" and their cognates are only intended to mean a particular feature, number, step, operation, element, component or combination of the foregoing, and should not be construed as first excluding the presence of or adding one or more other features, numbers, steps, operations, elements, components or combinations of the foregoing or the possibility of a combination of the foregoing.

In various embodiments of the invention, the expression "or" or "at least one of A or/and B" includes any and all combinations of the words listed at the same time. For example, the expressions "A or B" or "at least one of A or/and B" may include A, may include B, or may include both A and B.

Expressions (such as "first", "second", etc.) used in the various embodiments of the present invention may modify various constituent elements in the various embodiments, but may not limit the corresponding constituent elements. For example, the above expressions do not limit the order and/or importance of the elements described. The above expressions are only used for the purpose of distinguishing one element from other elements. For example, the first user device and the second user device indicate different user devices, although both are user devices. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of various embodiments of the present invention.

It should be noted that if a constituent element is described as being "connected" to another constituent element, the first constituent element may be directly connected to the second constituent element, and the "connection" between the first constituent element and the second constituent element may be "The third component. On the contrary, when one constituent element is "directly connected" to another constituent element, it can be understood that the third constituent element does not exist between the first constituent element and the second constituent element.

The terminology used in the various embodiments of the present invention is for the purpose of describing particular embodiments only and is not intended to limit the various embodiments of the present invention. As used herein, the singular is intended to include the plural as well, unless the context clearly dictates otherwise. Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which various embodiments of this invention belong. The terms (such as those defined in commonly used dictionaries) will be interpreted as having the same meaning as the contextual meaning in the relevant technical field and will not be interpreted as having an idealized or overly formal meaning, unless explicitly defined in the various embodiments of the present invention.

In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and the accompanying drawings. as a limitation of the present invention.

Example 1

This embodiment proposes a wearable ultrasonic therapeutic apparatus based on dynamic matching. The ultrasonic therapeutic apparatus of this embodiment adopts the combination of two intelligent neural network algorithms to jointly realize the dynamic matching of the ultrasonic therapeutic apparatus. The dynamic matching inductance is output by the BP neural network controller, and the reactance angle of the reactor is adjusted in real time according to the size of the dynamic inductance, thereby changing the magnitude of the voltage and current at both ends of the transducer. The closed-loop control is used to realize the dynamic adjustment of the matching inductance. The automatic frequency tracking technology based on Fuzzy neural network is adopted to solve the problem that the transducer system is easy to lose lock when the inductance is dynamically matched and switched, and the overall performance of the dynamic matching circuit of the transducer system is improved. Make the output frequency of the ultrasonic power supply track the input frequency of the transducer in real time.

As shown in FIG. 1 , as shown in FIG. 1 , a wearable ultrasonic therapeutic apparatus based on dynamic matching mainly includes a power supply module 1 , a signal generation module 2 , a power amplification module 3 , an impedance matching module 4 , and an ultrasonic transducer 5 , Frequency automatic tracking module 6 , main control unit 7 , temperature control module 8 , overcurrent and overvoltage protection module 9 , human-computer interaction module 10 . The power supply module 1 includes: a wireless charging module 11 , a 12V battery pack 12 , a 12V voltage regulator 13 , a boost voltage booster 14 , a voltage regulator chip LM7805 15 , and a voltage regulator chip AMS1117 16 . The signal generating module 2 includes: a DDS signal generator 21 , a driving circuit 22 , and a shaping filter circuit 23 . The temperature control module 8 includes: a temperature sampling module 81 and an over-temperature protection module 82 .

The functions of each module are as follows:

Power supply module 1, the power supply module has three voltage systems: power amplifier module power supply (12V), signal generator power supply (5V), main control unit (3.3V). The 12V rechargeable lithium battery boosts the 12V voltage to 48V through the boost boost module, and directly supplies power to the power amplifier module; considering that the voltage drop from 12V to 3.3V is too large. The signal generation circuit converts the 12V voltage into 5V through the linear voltage regulator chip LM7805 for power supply; uses the voltage regulator chip AMS1117 to convert the 5V voltage into 3.3V to supply power to the main control unit. The AMS1117 is a 3.3V forward low dropout regulator with low cost and simple circuit design. The charging part uses the QI standard wireless charging module to wirelessly charge the entire ultrasonic therapy device. The battery uses a 12.6V 1800mAh rechargeable polymer lithium battery pack. The polymer lithium battery pack is only 45 cubic centimeters in size, which further simplifies the volume of the physical therapy device.

Signal generation module 2, the signal generation module includes a DDS signal generator, a shaping filter circuit and a drive circuit. The AD9833 chip is connected to the main control unit through the serial bus, and the pins of the main control unit are configured as the SPI bus mode to cooperate with the AD9833 for data transmission. The main control unit adopts the low-power STM32L151 main controller, the AD9833 chip generates a 2MHz square wave through the low-power STM32L151 main controller, and the driving circuit uses a D flip-flop to divide the frequency of the 2MHz square wave generated by the DDS signal generator to become The more stable 1MHz square wave is then shaped by the shaping filter circuit. The concave piezoelectric ceramic sheet outputs an adaptive and adjustable ultrasonic wave with a frequency of 1MHz and an intensity of 0W/ ^cm2 to 1W/ ^cm2 .

The power amplification module 3, the power amplification module, is used for DDS signal amplification, and drives the DDS generator to generate a signal that can drive the ultrasonic transducer. DDS adopts AD9833 chip, DDS has the advantages of low cost, low power consumption, high resolution and fast conversion time. Since the output excitation signal strength of AD9833 is not enough to drive the ultrasonic transducer, it is necessary to amplify the excitation signal. After the ultrasonic excitation signal is processed by the logic chip 74HC74D for frequency division and filtering, it is sent to the gate driver chip UCC27525 for subsequent amplification. The amplified ultrasonic driving voltage signal can reach 40V, which can directly drive the ultrasonic transducer to work. The main control unit generates a PWM wave to control the enable terminal of the gate driver, so as to realize the indirect control of the ultrasonic output power.

The impedance matching module 4 is used to realize the dynamic adjustment of the matching inductance. For conventional static circuit matching, the frequency of the transducer is prone to drift. The impedance matching module 4 adopts a BP neural network module with a neural network intelligent algorithm to realize dynamic adjustment of the matching inductance.

As shown in Figure 2, the impedance matching module is mainly composed of five modules: data detection module, data preprocessing, BP neural network training, BP neural network prediction and BP neural network controller. The ultrasonic transducer first collects the input parameters through the data detection module, preprocesses the parameters, mainly normalized processing, and then trains the neural network, adjusts the weights of the network continuously, predicts the inductance value, and then passes the BP neural network. The controller outputs the dynamic matching inductance, and adjusts the reactance angle of the reactor in real time according to the size of the dynamic inductance, thereby changing the magnitude of the voltage and current at both ends of the transducer, and so on, to realize the dynamic adjustment of the matching inductance.

The intelligence of the BP neural network module is to adjust the weights of the network in real time, so that any input can get the desired output. The training method is to train a neural network for each group of data samples, and perform layer-by-layer computation from the first layer of the network to the output layer.

The specific steps of the BP neural network module are as follows:

S1: Obtain the input parameters of the neural network through the data detection module. Since the size of the matching inductance is related to the internal parameters of the ultrasonic transducer, five main variables that lead to the change of the internal parameters of the transducer are used as input parameters, namely the temperature of the transducer, the frequency of the ultrasonic wave, and the voltage across the transducer. value, the current value at both ends of the transducer and the depth of the concave piezoelectric ceramic sheet into the water tank, and the output parameter is the dynamic inductance value. The input parameters are represented by x ₁ , x ₂ ,...,x ₅ , and the dynamic inductance value is represented by y, so there is a formula y=f(x ₁ ,x ₂ ,...,x ₅ ).

S2: Data preprocessing. In order to reduce the absolute error, data preprocessing is performed before the normalization process, and the input and output data of the network are restricted between (0, 1) or the interval (-1, 1) through transformation.

S3: Normalization of sample data.

a. When the input and output samples are in the [0,1] interval, the formula for normalization is

Among them, X _i represents the input or output data, X _max represents the maximum value of the sample, and X _min represents the minimum value of the sample

b. When the input and output samples are in the interval [-1,1], the formula for normalization is

where X _mid represents the median value of the sample.

S4: Training of BP neural network. The training purpose of BP neural network is to fix the weights of the network. Cross-input a large number of samples of different categories, through a large amount of learning from multiple sample data, continuously adjust the weights to reduce the error, and adjust the weights of the network to minimize the error, thereby fixing the weights of the network.

S5: The prediction of the neural network, the purpose is to predict the matching inductance value through the BP neural network. After BP neural network training, the weights of the network have been determined. Test whether the trained sample data has good generalization ability. If the error of the training sample is small, but the error of the test sample is large, indicating that the generalization ability is relatively poor, then proceed to the first step until the neural network obtains a good generalization ability. prediction effect.

The frequency automatic tracking module 6 improves the frequency tracking speed of the system through the Fuzzy neural network module, solves the loss of lock phenomenon when the transducer system is dynamically matched to switch the inductance and locks the phase, and improves the overall performance of the dynamic matching circuit of the transducer system. The automatic frequency tracking speed can reach 0.12ms, which improves the frequency tracking speed of the system and improves the working efficiency of the ultrasonic therapeutic apparatus. Because the frequency tracking method of the conventional phase-locked loop technology is easy to lose lock, and the frequency of the ordinary fuzzy control lacks the self-integrated dynamic response ability, it cannot maintain an automatic processing function of real-time adjustment parameters in the system, and the tracking speed is slow, which cannot be guaranteed. System dynamic effects.

In order to solve the above pain points, an automatic frequency tracking technology based on Fuzzy neural network is proposed. The automatic frequency tracking technology based on Fuzzy neural network is based on some problems existing in Fuzzy controller and phase locked loop technology. The intelligent frequency tracking technology is introduced into the fuzzy control by neural network algorithm.

As shown in Figure 3, the automatic frequency tracking module mainly includes: voltage and current acquisition, phase detector, and fuzzy neural network controller. The specific working steps are as follows

(1) The voltage and current signals at both ends of the transducer are collected in real time by the phase detector, and the phase difference e and the change rate Δe of the phase difference are obtained.

(2) Input the phase difference e and the change rate Δe of the phase difference into the Fuzzy neural network controller. The specific working steps of the Fuzzy neural network controller are as follows:

S1: Determine the input and output signals of the Fuzzy neural network controller. The change rate Δe of the phase difference e is taken as the input of the fuzzy neural network controller. The adjusted phase difference E is used as the output, and then the neural network algorithm is used to map the input and output.

S2: Fuzzification and determination of membership functions. The input and output variables of the controller are fuzzified, and the MATLAB fuzzy control toolbox and neural network algorithm are used to jointly adjust the input and output parameters, which is simple, convenient and easy to operate. The membership function adopts a Gaussian fuzzification function.

S3: Formulation of fuzzy rules. In the MATLAB Fuzzy Toolbox, formulate fuzzy rules.

S4: Training of Fuzzy Neural Network Controller. The Fuzzy neural network controller has a tutor-style self-learning ability. It adopts a four-layer structure of input layer, middle layer, reasoning layer and output layer. The training method is to train the neural network for each data sample, starting from the first layer of the network. Layer calculation, up to the output layer, adjust the magnitude of the phase difference and change the current at both ends of the transducer through a large amount of learning from multiple sample data.

S5: Tuning of Fuzzy Neural Network Controllers. After the fuzzy rule training, the first derivative of the phase difference and the rate of change of the phase difference is used as the input of data preprocessing, and the trained Fuzzy neural network controller is used to adjust the size of the phase difference and change the value of the phase difference at both ends of the transducer. The current circulates like this until the phase difference is zero, so that the output frequency of the signal is gradually consistent with the input frequency, and the frequency is automatically tracked.

(3) Build a Simulink simulation model based on Fuzzy neural network controller through MATLAB fuzzy toolbox and Simulink simulation platform. Experiments show that the automatic frequency tracking speed of the automatic tracking module with Fuzzy neural network controller can reach 0.12ms, which improves the frequency tracking speed of the system and improves the working efficiency of the ultrasonic therapeutic apparatus.

Main control unit 7, the main control unit uses a low-power STM32L151 microprocessor to detect the voltage of the sampling resistor through the ADC, programmatically controls the ultrasonic output intensity and the current working state of the display device through the PID algorithm, and determines the output ultrasonic intensity by scanning the keys. The current gear is displayed by the LED light.

The temperature control module 8 adopts the thermistor to collect the temperature at both ends of the ultrasonic transducer in real time. When the temperature exceeds the set safety threshold, the power is automatically cut off to ensure the safety of the user.

The overvoltage and overcurrent protection module 9 uses a DC/DC power supply module URA2405ZP to supply power to the op amp, with an input voltage of 12V and an output voltage of ±5V. It has input undervoltage protection, output overvoltage protection, and output overcurrent protection.

Human-computer interaction module 8, the human-computer interaction module reduces the size of the ultrasonic therapeutic apparatus by simplifying functions. The human-computer interaction module only has buttons and LEDs. The output ultrasonic intensity is adjusted through the buttons, and the current gear is displayed through the LED lights.

As will be appreciated by those skilled in the art, the embodiments of the present application may be provided as a method, a system, or a computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It will be understood that each flow and/or block in the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing device to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing device produce Means for implementing the functions specified in a flow or flow of a flowchart and/or a block or blocks of a block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture comprising instruction means, the instructions The apparatus implements the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

These computer program instructions can also be loaded on a computer or other programmable data processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process such that The instructions provide steps for implementing the functions specified in the flow or blocks of the flowcharts and/or the block or blocks of the block diagrams.

The specific embodiments described above further describe the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above descriptions are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims (10)

1. a wearable ultrasonic therapeutic apparatus based on dynamic matching, is characterized in that, comprises main control unit, signal generation module, power amplifier, impedance matching module, ultrasonic transducer, frequency automatic tracking module and power supply module; The main control unit is respectively connected with the signal generation module, the frequency automatic tracking module and the power supply module, the power supply module is also connected with the shaping filter circuit and the power amplifier, the power amplifier is also connected with the impedance matching module, and the impedance matching module is connected with the The ultrasonic transducer is connected, and the ultrasonic transducer is connected with the frequency automatic tracking module; The main control unit is used to control the signal generator to generate the DDS signal, the power amplification module is used to amplify the DDS signal to generate an enabling signal of the ultrasonic transducer, and the impedance matching module is used to dynamically adjust the ultrasonic transducer. The matching inductance; the automatic frequency tracking module enables the output frequency of the ultrasonic transducer to track the input frequency of the transducer in real time; The power supply module supplies power to the main control unit, the signal generating module and the power amplifying module. 2. a kind of wearable ultrasonic therapeutic apparatus based on dynamic matching according to claim 1, is characterized in that, described impedance matching module comprises data detection module, data preprocessing module and BP neural network module, collects by data detection module The input parameters of the ultrasonic transducer, the data preprocessing module processes the input parameters and output parameters to obtain training sample data, the BP neural network module inputs the training sample data into the BP neural network for training, and uses the trained neural network. The network outputs the matching inductance in real time to realize the dynamic adjustment of the matching inductance. 3. a kind of wearable ultrasonic therapeutic apparatus based on dynamic matching according to claim 2, is characterized in that, described input parameter is five variables that cause the change of internal parameter of transducer, comprise transducer temperature, ultrasonic frequency , the voltage value at both ends of the transducer, the current value at both ends of the transducer, and the depth of the transducer deep into the water tank, and the output parameter is the matching inductance value. 4. a kind of wearable ultrasonic therapeutic apparatus based on dynamic matching according to claim 2, is characterized in that, described BP neural network module is configured to carry out the following steps: S1, the BP neural network learns and trains multiple sample data, and adjusts the weights of the network to achieve the minimum error, thereby obtaining a trained BP neural network; S2, using the BP neural network trained in step S1 to output the matching inductance, which is used to adjust the reactance angle of the reactor in real time, thereby changing the magnitude of the voltage and current at both ends of the transducer; In S3, the dynamic adjustment of the matching inductance can be realized by repeating the execution of S2. 5. A wearable ultrasonic therapeutic apparatus based on dynamic matching according to claim 1, wherein the automatic frequency tracking module comprises a voltage and current acquisition module, a phase detector and a Fuzzy neural network controller, and the voltage The current acquisition module is used to collect the voltage and current signals at both ends of the transducer in real time and transmit the signals to the phase detector. The phase detector obtains the phase difference and the rate of change of the phase difference according to the voltage and current signals and inputs them into the fuzzy nerve. The network controller performs phase difference adjustment to achieve automatic frequency tracking. 6. A wearable ultrasonic therapeutic apparatus based on dynamic matching according to claim 5, wherein the Fuzzy neural network controller is configured to perform the following steps: S11, the phase difference and the rate of change of the phase difference are used as the input of the fuzzy neural network, the adjusted phase difference is used as the output of the fuzzy neural network, and the input and output are mapped by the neural network algorithm; S12, determine the fuzzification, membership function and fuzzy rules, and obtain the Fuzzy neural network model; S13, using multiple data samples to train the Fuzzy neural network model to obtain a trained Fuzzy neural network model; S14, input the phase difference obtained in real time and the rate of change of the phase difference into the trained Fuzzy neural network model to output the size of the adjusted phase difference; S15 , changing the current at both ends of the transducer, and repeating step S14 until the phase difference is zero, so that the signal output frequency is gradually consistent with the input frequency, and automatic frequency tracking is realized. 7. The wearable ultrasonic therapeutic apparatus based on dynamic matching according to any one of claims 1-6, wherein the power supply module adopts a 12V rechargeable polymer lithium The voltage module raises the 12V voltage to 48V, and directly supplies power to the power amplifier module; the polymer lithium battery pack converts the 12V voltage to 5V through the linear voltage regulator chip to supply power for the signal generation module; then the voltage regulator chip converts the 5V voltage to 3.3V as Power supply to the main control unit. 8. A wearable ultrasonic therapeutic apparatus based on dynamic matching according to any one of claims 1-6, wherein the signal generating module comprises a DDS signal generator, a shaping filter circuit and a drive circuit; the The DDS signal generator is connected to the main control unit through the serial bus, and the main control unit generates a 2MHz square wave. The driving circuit divides the 2MHz square wave generated by the DDS signal generator into a 1MHz square wave, and then passes through the shaping filter circuit. After shaping, it is sent to the power amplifier module. 9. A wearable ultrasonic therapeutic apparatus based on dynamic matching according to any one of claims 1-6, characterized in that, further comprising a temperature control module, adopting a thermistor to collect the temperature at both ends of the ultrasonic transducer in real time, When the temperature exceeds the set safety threshold, the automatic control power-off ensures the safety of the user. 10. A wearable ultrasonic therapeutic apparatus based on dynamic matching according to any one of claims 1-6, characterized in that, further comprising an overcurrent and overvoltage protection module and a human-computer interaction module, and the human-computer interaction Both the module and the overcurrent and overvoltage protection module are connected to the main control unit. The human-computer interaction module is used to adjust the ultrasonic intensity and display the gear of the current ultrasonic intensity. The overcurrent and overvoltage protection module is used to output overvoltage. protection and overcurrent protection.

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