Resonant frequency adjusting method and system

Abstract

The invention discloses a resonant frequency adjusting method and system. The surface acoustic wave filtering device with temperature compensation and the method are characterized in that a temperature sensitive layer of the surface acoustic wave filtering device carries out temperature sensing and signal acquisition; the signal preprocessing circuit is used for amplifying and filtering the acquired signal and inputting the signal into the temperature-frequency algorithm chip; calculating required compensation parameters by an algorithm model based on a neural network in the temperature-frequency algorithm chip; the compensation parameters are output to a variable capacitor, and the resonant frequency of the surface acoustic wave filtering device is adjusted; the resonant frequency of the surface acoustic wave filtering device is dynamically adjusted, so that closed-loop control of temperature compensation is realized; according to the invention, the temperature compensation control of the surface acoustic wave filtering device is realized, and the surface acoustic wave filter can keep stable resonant frequency in different temperature environments.

Description

Technical Field

[0001] The present invention relates to temperature compensation technology, and in particular, to a method and system for adjusting the resonant frequency. Background Art

[0002] Surface Acoustic Wave (SAW) filters are widely used in wireless communication, radar systems, Radio Frequency Identification (RFID), and satellite navigation due to their advantages such as small size, low power consumption, and stable performance. However, since the center frequency of the SAW filter is sensitive to temperature changes, temperature fluctuations may cause frequency drift of the filter, affecting the signal processing accuracy and communication quality of the system. Especially in application scenarios with high-precision and high-stability requirements, such as 5G communication, satellite communication, and industrial control systems, the frequency offset problem caused by temperature is particularly prominent.

[0003] To address the above problems, the present invention proposes a SAW filtering device and method with temperature compensation function, which realizes adaptive compensation for temperature changes by optimizing the structural design of the SAW filter, using specific material combinations, integrating temperature compensation mechanisms, etc. The technical solution of the present invention can effectively reduce the influence of temperature changes on the filter performance without increasing additional power consumption and system complexity, improve the frequency stability of the filter, and thus meet the requirements of modern wireless communication and precision electronic systems for high-reliability and high-stability filters. Summary of the Invention

[0004] The present invention provides a method for adjusting the resonant frequency, including: S110. The temperature-sensitive layer of the SAW filtering device performs temperature sensing and signal acquisition; S120. The signal preprocessing circuit amplifies and filters the collected signal and inputs it into the temperature-frequency algorithm chip; S130. The algorithm model based on neural network inside the temperature-frequency algorithm chip calculates the required compensation parameters; S140. Output the compensation parameters to the variable capacitor to adjust the resonant frequency of the SAW filtering device; S150. Through dynamically adjusting the resonant frequency of the SAW filtering device, realize the closed-loop control of temperature compensation.

[0005] In the method for adjusting the resonant frequency as described above, the method for the temperature-sensitive layer of the SAW filtering device to perform temperature sensing and signal acquisition specifically includes the following sub-steps: Set the temperature-sensitive layer; The temperature-sensitive layer performs real-time temperature monitoring and captures electrical signals; Collect and transmit the captured electrical signals.

[0006] A method and system for adjusting the resonance frequency as described above, wherein the signal preprocessing circuit amplifies and filters the temperature signal. First, it performs low-noise amplification through a preamplifier to amplify the signal to a level range suitable for subsequent processing, and then passes it through a band-pass filter to remove high-frequency and low-frequency noise in the signal, only retaining the effective signal frequency band related to temperature changes to obtain a more stable temperature signal.

[0007] A method for adjusting the resonance frequency as described above, wherein the preprocessed temperature signal is input into a temperature-frequency compensation algorithm chip. The neural network algorithm model inside the temperature-frequency compensation algorithm chip receives this temperature signal as input, and the neurons in the model perform layer-by-layer calculations on the input signal according to the trained weights. After the calculation by the neural network model, the temperature-frequency compensation algorithm chip outputs the required compensation parameters.

[0008] A method for adjusting the resonance frequency as described above, wherein the method of outputting the compensation parameters to a variable capacitor and adjusting the resonance frequency of the surface acoustic wave filtering device specifically includes the following sub-steps: Generate a corresponding control voltage signal according to the calculated compensation parameters; Adjust the resonance frequency of the surface acoustic wave filtering device according to the control voltage signal.

[0009] The present invention also provides a system for adjusting the resonance frequency, including: Temperature sensing and signal acquisition module: The temperature-sensitive layer of the surface acoustic wave filtering device performs temperature sensing and signal acquisition; Signal preprocessing circuit module: The signal preprocessing circuit amplifies and filters the acquired signal and inputs it into the temperature-frequency algorithm chip; Temperature-frequency algorithm chip module: The algorithm model based on neural network inside the temperature-frequency algorithm chip calculates the required compensation parameters; Resonance frequency adjustment module: Output the compensation parameters to a variable capacitor to adjust the resonance frequency of the surface acoustic wave filtering device; Closed-loop control module: Realize the closed-loop control of temperature compensation by dynamically adjusting the resonance frequency of the surface acoustic wave filtering device.

[0010] A system for adjusting the resonance frequency as described above, wherein the method of the temperature-sensitive layer of the surface acoustic wave filtering device performing temperature sensing and signal acquisition specifically includes the following sub-steps: Set the temperature-sensitive layer; The temperature-sensitive layer performs real-time temperature monitoring and captures electrical signals; Collect and transmit the captured electrical signals.

[0011] A resonant frequency adjustment system as described above, wherein the signal preprocessing circuit amplifies and filters the temperature signal. First, it performs low-noise amplification through a preamplifier to amplify the signal to a level range suitable for subsequent processing, and then passes it through a band-pass filter to remove high-frequency and low-frequency noise in the signal, only retaining the effective signal frequency band related to temperature changes to obtain a more stable temperature signal.

[0012] A resonant frequency adjustment system as described above, wherein the preprocessed temperature signal is input into a temperature-frequency compensation algorithm chip. The neural network algorithm model inside the temperature-frequency compensation algorithm chip receives this temperature signal as input, and the neurons in the model perform layer-by-layer calculations on the input signal according to the trained weights. After the calculation by the neural network model, the temperature-frequency compensation algorithm chip outputs the required compensation parameters.

[0013] A resonant frequency adjustment system as described above, wherein the method of outputting the compensation parameters to a variable capacitor to adjust the resonant frequency of the surface acoustic wave filtering device specifically includes the following sub-steps: Generate a corresponding control voltage signal according to the calculated compensation parameters; Adjust the resonant frequency of the surface acoustic wave filtering device according to the control voltage signal.

[0014] The beneficial effects achieved by the present invention are as follows: It realizes the temperature compensation control of the surface acoustic wave filtering device, ensuring that the surface acoustic wave filter can maintain a stable resonant frequency in different temperature environments. Description of the Drawings

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to these drawings.

[0016] Figure 1 It is a flow chart of a method and system for adjusting the resonant frequency provided in Embodiment 1 of the present application; Figure 2 It is a schematic diagram of a resonant frequency adjustment system provided in Embodiment 2 of the present application; Detailed Embodiments

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some but not all of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0018] Example 1

[0019] As Figure 1 shown, Example 1 of the present application provides a method for adjusting the resonant frequency, including: Step S110: The temperature-sensitive layer of the surface acoustic wave filtering device performs temperature sensing and signal acquisition; The method for the temperature-sensitive layer of the surface acoustic wave filtering device to perform temperature sensing and signal acquisition specifically includes the following sub-steps: Step S111: Set the temperature-sensitive layer; Cover a temperature-sensitive layer composed of polyvinylidene fluoride (PVDF) and carbon nanotubes (CNT) on the surface of the surface acoustic wave filtering device body. PVDF has piezoelectricity and pyroelectricity, can sense temperature changes and generate corresponding electrical signal changes. The carbon nanotubes are uniformly dispersed in PVDF. On the one hand, it enhances the mechanical properties of PVDF, and on the other hand, it improves its electrical conductivity, enabling the electrical signal changes caused by temperature changes to be transmitted more quickly and effectively. The thickness of the temperature-sensitive layer is precisely controlled and set to 500 nanometers to ensure high sensitivity to temperature changes and minimal interference to surface acoustic wave propagation.

[0020] Step S112: The temperature-sensitive layer performs real-time temperature monitoring and captures electrical signals; After the surface acoustic wave filtering device is started, the temperature-sensitive layer continuously senses the temperature changes around the surface acoustic wave filter body. Due to the pyroelectric characteristics of PVDF, a small change in temperature will cause a corresponding charge change, thus forming an electrical signal. Specifically, the formula is used: represents the formed electrical signal, where, represents the pyroelectric voltage generated by PVDF, represents the pyroelectric coefficient, represents the temperature change rate.

[0021] Step S113: Collect and transmit the captured electrical signals; The electrical signals generated by the temperature-sensitive layer are quickly conducted to the signal preprocessing circuit through the internal carbon nanotube network. Carbon nanotubes are a tubular nanostructure composed of carbon atoms, with high electrical conductivity, high thermal conductivity, and high mechanical strength. In the surface acoustic wave filtering device, the carbon nanotubes connect the PVDF sensing layer and the signal preprocessing circuit in a network form, forming an efficient signal transmission path. The signal preprocessing circuit is composed of multiple high-performance operational amplifiers and precision resistors and capacitors, and this circuit receives the weak electrical signals from the temperature-sensitive layer.

[0022] Step S120: The signal preprocessing circuit amplifies and filters the collected signals and inputs them into the temperature-frequency algorithm chip; The temperature-frequency algorithm chip integrates a temperature-frequency mapping model based on neural network algorithm inside. This model is trained with a large amount of experimental data, which covers the frequency offset of the surface acoustic wave filter at different temperatures and the output electrical signals of the corresponding temperature-sensitive layer. During actual operation, the temperature-frequency algorithm chip quickly calculates the parameter values required for adjusting the frequency of the surface acoustic wave filter according to the received preprocessed temperature signal.

[0023] Since the temperature signal is weak, the signal preprocessing circuit needs to amplify and filter it to obtain a more stable temperature signal. First, it is low-noise amplified by a preamplifier to amplify the signal to a level range suitable for subsequent processing. Then, through a band-pass filter, the high-frequency and low-frequency noises in the signal are removed, and only the effective signal frequency band related to temperature change is retained. The operational amplifier selects a model with extremely low offset voltage and high common-mode rejection ratio to ensure the accuracy of signal processing. Specifically, the formula: is used for amplification and filtering processing, where represents the amplified signal, represents the signal amplification gain, represents the noise component removed by filtering.

[0024] Step S130: The algorithm model based on neural network inside the temperature-frequency algorithm chip calculates the required compensation parameters; The preprocessed temperature signal is input into the temperature-frequency compensation algorithm chip. The neural network algorithm model inside the temperature-frequency compensation algorithm chip receives this temperature signal as input, and the neurons in the model perform layer-by-layer calculations on the input signal according to the weights obtained through training. This neural network model has multiple hidden layers, and each hidden layer contains multiple neurons. The weights obtained through a large amount of experimental data training can accurately map the relationship between the temperature signal and the frequency offset of the surface acoustic wave filter.

[0025] After the calculation by the neural network model, the temperature-frequency compensation algorithm chip outputs the required compensation parameters. The compensation parameters are closely related to the temperature change and the frequency offset characteristics of the surface acoustic wave filter. When the temperature rises or falls, the model calculates the frequency at which the resonant frequency of the surface acoustic wave filter needs to be lowered or raised. The temperature-frequency compensation algorithm chip outputs the corresponding control parameters to achieve this frequency adjustment. Specifically, the formula: is used to calculate the compensation parameters, represents the compensation parameter, L represents the number of layers of the neural network, represents the number of neurons in the th layer, represents the input temperature signal, represents the bias, Represents an activation function.

[0026] Step S140: Output the compensation parameter to the variable capacitor to adjust the resonant frequency of the surface acoustic wave filtering device. The method of outputting the compensation parameter to the variable capacitor to adjust the resonant frequency of the surface acoustic wave filtering device specifically includes the following sub-steps: Step S141: Generate a corresponding control voltage signal according to the calculated compensation parameter. Generate a corresponding control voltage signal according to the calculated compensation parameter. This control voltage signal is transmitted to the frequency fine-tuning actuator, which consists of multiple microelectromechanical system (MEMS) variable capacitors. These MEMS variable capacitors are connected to the resonant circuit of the surface acoustic wave filter, and the MEMS variable capacitors work based on the electrostatic drive principle. When the control voltage output by the temperature-frequency compensation algorithm chip is applied to the MEMS variable capacitor, its capacitance value will change precisely. Since the resonant frequency of the resonant circuit is closely related to the capacitance value, by adjusting the capacitance value of the MEMS variable capacitor, the frequency of the surface acoustic wave filter can be finely tuned, thereby compensating for the frequency shift caused by temperature changes. Specifically, use the formula: Calculate the control voltage signal, where Represents the control voltage signal, Represents the control gain coefficient, which is used to adjust the amplitude of the compensation signal, Represents the compensation parameter, Represents the offset compensation term to ensure that the output signal matches the operating range of the MEMS variable capacitor.

[0027] Step S142: Adjust the resonant frequency of the surface acoustic wave filtering device according to the control voltage signal. Transmit the calculated control voltage signal to the frequency fine-tuning actuator. The MEMS component adjusts its own capacitance value according to the control voltage, and then adjusts the resonant frequency of the surface acoustic wave filtering device. Specifically, use the formula: Calculate the resonant frequency, where Represents the resonant frequency, Represents the value of the variable capacitor, Represents the initial capacitance, Represents the voltage regulation coefficient, Represents the control voltage signal, L and Represents the equivalent inductance and inherent capacitance of the filter.

[0028] Step S150: Achieve closed-loop control of temperature compensation by dynamically adjusting the resonant frequency of the surface acoustic wave filtering device. By dynamically adjusting the resonant frequency of the surface acoustic wave filtering device, a closed-loop control for temperature compensation is achieved. The temperature-frequency compensation algorithm chip continuously collects the temperature signals of the temperature-sensitive layer, calculates the frequency compensation parameters, and dynamically adjusts the capacitance value of the MEMS to form a closed-loop compensation control system, enabling the surface acoustic wave filtering device to always be stable at the target resonant frequency. Specifically, the formula is used: represents the closed-loop control for temperature compensation, where represents the real-time resonant frequency, represents the target resonant frequency, represents the frequency tolerance.

[0029] Embodiment 2 As Figure 2 shown, Embodiment 2 of the present application provides an adjustment system for the resonant frequency, including: Temperature sensing and signal acquisition module 21: The temperature-sensitive layer of the surface acoustic wave filtering device performs temperature sensing and signal acquisition; The method for the temperature-sensitive layer of the surface acoustic wave filtering device to perform temperature sensing and signal acquisition specifically includes the following sub-steps: Setting module: Set the temperature-sensitive layer; Cover a temperature-sensitive layer composed of polyvinylidene fluoride (PVDF) and carbon nanotubes (CNT) on the surface of the surface acoustic wave filtering device body. PVDF has piezoelectricity and pyroelectricity, can sense temperature changes and generate corresponding electrical signal changes. The carbon nanotubes are uniformly dispersed in PVDF. On the one hand, it enhances the mechanical properties of PVDF, and on the other hand, it improves its electrical conductivity, enabling the electrical signal changes caused by temperature changes to be transmitted more quickly and effectively. The thickness of the temperature-sensitive layer is precisely controlled and set to 500 nanometers to ensure high sensitivity to temperature changes and minimal interference to surface acoustic wave propagation.

[0030] Capture module: The temperature-sensitive layer performs real-time temperature monitoring and captures electrical signals; After the surface acoustic wave filtering device is started, the temperature-sensitive layer continuously senses the temperature changes around the surface acoustic wave filter body. Due to the pyroelectric property of PVDF, a slight change in temperature will cause a corresponding charge change, thus forming an electrical signal. Specifically, the formula is used: represents the formed electrical signal, where represents the pyroelectric voltage generated by PVDF, represents the pyroelectric coefficient, represents the temperature change rate.

[0031] Acquisition and transmission module: Acquire and transmit the captured electrical signals; The electrical signal generated by the temperature-sensitive layer is rapidly conducted through the internal carbon nanotube network to the signal preprocessing circuit. Carbon nanotubes are tubular nanostructures composed of carbon atoms, with high electrical conductivity, high thermal conductivity, and high mechanical strength. In the surface acoustic wave filtering device, the carbon nanotubes connect the PVDF sensing layer and the signal preprocessing circuit in a network form, forming an efficient signal transmission path. The signal preprocessing circuit is composed of multiple high-performance operational amplifiers, precision resistors, and capacitors, and this circuit receives the weak electrical signal from the temperature-sensitive layer.

[0032] Signal preprocessing circuit module 22: The signal preprocessing circuit amplifies and filters the collected signal and inputs it into the temperature-frequency algorithm chip; The temperature-frequency algorithm chip integrates a temperature-frequency mapping model based on the neural network algorithm inside. This model is trained with a large amount of experimental data, which covers the frequency offset of the surface acoustic wave filter at different temperatures and the corresponding output electrical signal of the temperature-sensitive layer. During actual operation, the temperature-frequency algorithm chip quickly calculates the parameter values required to adjust the frequency of the surface acoustic wave filter according to the received preprocessed temperature signal.

[0033] Since the temperature signal is weak, the signal preprocessing circuit needs to amplify and filter it to obtain a more stable temperature signal. First, it is low-noise amplified by a preamplifier to amplify the signal to a level range suitable for subsequent processing. Then, through a band-pass filter, the high-frequency and low-frequency noises in the signal are removed, and only the effective signal frequency band related to temperature changes is retained. The operational amplifier is selected with a model having an extremely low offset voltage and a high common-mode rejection ratio to ensure the accuracy of signal processing. Specifically, the formula: is used for amplification and filtering processing, where represents the amplified signal, represents the signal amplification gain, represents the noise component removed by filtering.

[0034] Temperature-frequency algorithm chip module 23: The algorithm model based on the neural network inside the temperature-frequency algorithm chip calculates the required compensation parameters; The preprocessed temperature signal is input into the temperature-frequency compensation algorithm chip. The neural network algorithm model inside the temperature-frequency compensation algorithm chip receives this temperature signal as input, and the neurons in the model perform layer-by-layer calculations on the input signal according to the weights obtained through training. This neural network model has multiple hidden layers, and each hidden layer contains multiple neurons. The weights obtained through a large amount of experimental data training can accurately map the relationship between the temperature signal and the frequency offset of the surface acoustic wave filter.

[0035] After the calculation of the neural network model, the temperature-frequency compensation algorithm chip outputs the required compensation parameters. The compensation parameters are closely related to the temperature change and the frequency offset characteristics of the surface acoustic wave filter. When the temperature rises or falls, the model calculates the frequency at which the resonant frequency of the surface acoustic wave filter needs to be reduced or increased. The temperature-frequency compensation algorithm chip outputs the corresponding control parameters to achieve this frequency adjustment. Specifically, the formula is used: Calculate the compensation parameter, represents the compensation parameter, L represents the number of layers of the neural network, represents the number of neurons in the layer, represents the weight parameter, represents the input temperature signal, represents the bias,

[0036] Resonant frequency adjustment module 24: Output the compensation parameter to the variable capacitor to adjust the resonant frequency of the surface acoustic wave filtering device; The method of outputting the compensation parameter to the variable capacitor to adjust the resonant frequency of the surface acoustic wave filtering device specifically includes the following sub-steps: Control voltage signal module: Generate the corresponding control voltage signal according to the calculated compensation parameter; According to the calculated compensation parameter, generate the corresponding control voltage signal. This control voltage signal is transmitted to the frequency fine-tuning actuator. The frequency fine-tuning actuator consists of multiple microelectromechanical system (MEMS) variable capacitors. These MEMS variable capacitors are connected to the resonant circuit of the surface acoustic wave filter. The MEMS variable capacitors work based on the electrostatic drive principle. When the control voltage output by the temperature-frequency compensation algorithm chip is applied to the MEMS variable capacitor, its capacitance value will change precisely. Since the resonant frequency of the resonant circuit is closely related to the capacitance value, by adjusting the capacitance value of the MEMS variable capacitor, the fine-tuning of the frequency of the surface acoustic wave filter can be achieved, thereby compensating for the frequency offset caused by temperature changes. Specifically, the formula is used: Calculate the control voltage signal, where represents the control voltage signal, represents the control gain coefficient, which is used to adjust the amplitude of the compensation signal, represents the compensation parameter, represents the offset compensation term to ensure that the output signal matches the working range of the MEMS variable capacitor.

[0037] Resonant frequency adjustment module: Adjust the resonant frequency of the surface acoustic wave filtering device according to the control voltage signal; Transmit the calculated control voltage signal to the frequency fine-tuning actuator. The MEMS component adjusts its own capacitance value according to the control voltage, and then adjusts the resonant frequency of the surface acoustic wave filtering device. Specifically, the formula is used: Calculate the resonant frequency, where represents the resonant frequency, represents the value of the variable capacitance, represents the initial capacitance, represents the voltage regulation coefficient, represents the control voltage signal, L and represent the equivalent inductance and inherent capacitance of the filter.

[0038] Closed-loop control module 25: Realize the closed-loop control of temperature compensation by dynamically adjusting the resonant frequency of the surface acoustic wave filtering device; Realize the closed-loop control of temperature compensation by dynamically adjusting the resonant frequency of the surface acoustic wave filtering device. The temperature-frequency compensation algorithm chip continuously collects the temperature signal of the temperature-sensitive layer, calculates the frequency compensation parameter, and dynamically adjusts the capacitance value of the MEMS to form a closed-loop compensation control system, so that the surface acoustic wave filtering device is always stable at the target resonant frequency. Specifically, the formula is used: represents the closed-loop control of temperature compensation, where represents the real-time resonant frequency, represents the target resonant frequency, represents the frequency tolerance.

[0039] The specific embodiments described above further elaborate on the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made on the basis of the technical solution of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for adjusting a resonant frequency, characterized in that: include: S110, the temperature sensitive layer of the surface acoustic wave filter device performs temperature sensing and signal collection; S120, the signal preprocessing circuit amplifies and filters the collected signal, and inputs it into the temperature-frequency algorithm chip; S130, the temperature-frequency algorithm chip calculates the required compensation parameters based on the neural network algorithm model; S140, outputting the compensation parameter to the variable capacitor to adjust the resonant frequency of the surface acoustic wave filter device; S150, realizing closed-loop control of temperature compensation by dynamically adjusting the resonant frequency of the surface acoustic wave filter device.

2. A method for adjusting the resonant frequency as claimed in claim 1, characterized in that: The method for temperature sensing and signal acquisition of the temperature sensitive layer of the surface acoustic wave filter device specifically comprises the following sub-steps: Setting temperature sensitive layer; The temperature-sensitive layer performs real-time temperature monitoring and captures electrical signals; The captured electrical signals are collected and transmitted.

3. A method for adjusting the resonant frequency as claimed in claim 1, characterized in that: The signal preprocessing circuit amplifies and filters the temperature signal. It first performs low-noise amplification through a preamplifier to amplify the signal to a level range suitable for subsequent processing. Then it passes through a bandpass filter to remove high-frequency and low-frequency noise in the signal, retaining only the effective signal frequency band related to temperature changes to obtain a more stable temperature signal.

4. A method for adjusting the resonant frequency as claimed in claim 3, characterized in that: The preprocessed temperature signal is input into the temperature-frequency compensation algorithm chip. The neural network algorithm model inside the temperature-frequency compensation algorithm chip receives the temperature signal as input. The neurons in the model calculate the input signal layer by layer according to the trained weights. After calculation by the neural network model, the temperature-frequency compensation algorithm chip outputs the required compensation parameters.

5. A method for adjusting the resonant frequency as claimed in claim 1, characterized in that: The method of outputting the compensation parameter to the variable capacitor to adjust the resonant frequency of the surface acoustic wave filter device specifically comprises the following sub-steps: Generate a corresponding control voltage signal according to the calculated compensation parameter; The resonant frequency of the surface acoustic wave filter device is adjusted according to the control voltage signal.

6. A resonant frequency adjustment system, characterized in that: include: Temperature sensing and signal acquisition module: The temperature sensitive layer of the surface acoustic wave filter device performs temperature sensing and signal acquisition; Signal preprocessing circuit module: The signal preprocessing circuit amplifies and filters the collected signal and inputs it into the temperature-frequency algorithm chip; Temperature-frequency algorithm chip module: The neural network-based algorithm model inside the temperature-frequency algorithm chip calculates the required compensation parameters; Resonance frequency adjustment module: outputs the compensation parameters to the variable capacitor to adjust the resonant frequency of the surface acoustic wave filter device; Closed-loop control module: A closed-loop control of temperature compensation is achieved by dynamically adjusting the resonant frequency of the surface acoustic wave filter device.

7. A resonant frequency adjustment system as claimed in claim 6, characterized in that: The method for temperature sensing and signal acquisition of the temperature sensitive layer of the surface acoustic wave filter device specifically comprises the following sub-steps: Setting temperature sensitive layer; The temperature-sensitive layer performs real-time temperature monitoring and captures electrical signals; The captured electrical signals are collected and transmitted.

8. A resonant frequency adjustment system as claimed in claim 6, characterized in that: The signal preprocessing circuit amplifies and filters the temperature signal. It first performs low-noise amplification through a preamplifier to amplify the signal to a level range suitable for subsequent processing. Then it passes through a bandpass filter to remove high-frequency and low-frequency noise in the signal, retaining only the effective signal frequency band related to temperature changes to obtain a more stable temperature signal.

9. A resonant frequency adjustment system as claimed in claim 8, characterized in that: The preprocessed temperature signal is input into the temperature-frequency compensation algorithm chip. The neural network algorithm model inside the temperature-frequency compensation algorithm chip receives the temperature signal as input. The neurons in the model calculate the input signal layer by layer according to the trained weights. After calculation by the neural network model, the temperature-frequency compensation algorithm chip outputs the required compensation parameters.

10. A resonant frequency adjustment system as claimed in claim 6, characterized in that: The method of outputting the compensation parameter to the variable capacitor to adjust the resonant frequency of the surface acoustic wave filter device specifically comprises the following sub-steps: Generate a corresponding control voltage signal according to the calculated compensation parameter; The resonant frequency of the surface acoustic wave filter device is adjusted according to the control voltage signal.

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