A surface acoustic wave sensor device design method and application system

Abstract

The present invention provides a surface acoustic wave sensor device design method and application system. It belongs to the field of environmental detection and solves the problem of high cost of empirical trial and error and poor design effect when designing SAW devices. Among them, the technical solution of the surface acoustic wave sensor device design method is to include the following steps: S1. Given multi-physical field coupling parameters. S2. Bring the coupling parameters into GOAL to obtain the parameters of each module of the port network, and connect the parameters of each module to form a complete structural model. S3. Distributed global search extracts important feature points in the structural model as optimization targets, and defines the Assmt function to select solutions that meet the optimization targets. S4. Perform opportunity decision based on the evaluation value, and record the optimal result after the global search as the final output parameter. The beneficial effects of the present invention are: improving the design effect of the SAW sensor device and saving the design cost of the SAW sensor device.

Description

Technical Field

[0001] The invention belongs to the field of environmental detection, and in particular relates to a surface acoustic wave sensor device design method and an application system. Background Art

[0002] Surface acoustic wave (SAW) sensors have become a hot topic of research due to their unique advantages, such as wireless and no need for external power supply. SAW sensors use acoustic waves to transmit signals on the surface of piezoelectric materials to detect physical quantities such as temperature. They usually use interdigital transducers (IDTs) to excite and detect surface acoustic waves. Delay line and resonator structures are two basic forms. Among them, resonator-type SAW sensors are widely used in wireless detection due to their high Q value. Temperature changes affect the propagation speed of SAW in piezoelectric materials, thereby changing the resonant frequency of the sensor. If the sensor and the supporting antenna system cannot maintain frequency synchronization, signal transmission failure may occur. Therefore, the design of SAW sensors requires fine-tuning to ensure stable performance over the entire operating temperature range. Traditional design methods rely on empirical formulas and trial and error methods, which are not only inefficient but also difficult to ensure optimal design.

[0003] With the development of microelectronics technology and materials science, the design of SAW sensors has begun to introduce finite element analysis (FEM) and boundary element method (BEM). These numerical analysis methods can accurately simulate the electromagnetic characteristics and mechanical behavior of SAW devices, thereby guiding the design of sensors. However, although the FEM / BEM method has high accuracy, the computational cost is expensive, especially when performing multi-parameter optimization, which requires a lot of computing resources and time. Summary of the invention

[0004] In order to solve the above problems, the present invention provides a surface acoustic wave sensor device design method based on multi-physical field coupling and distributed global search. The complete structural model of the port device network is obtained according to the GOAL function, and the Assmt function is introduced to evaluate the optimal solution that meets the conditions, so as to make an opportunistic decision and finally obtain the design result of the surface acoustic wave sensor device. The method has the advantages of accuracy, convenience and economy, and has a strong application value for the design of surface acoustic wave sensor devices.

[0005] In order to achieve the above-mentioned invention object, the technical solution adopted by the present invention is specifically: a surface acoustic wave sensor device design method based on multi-physical field coupling and distributed global search, comprising the following steps:

[0006] S1. Given the multi-physics field coupling parameters, the information set of the finger , where is the number of stripes , overlapping aperture , refers to the stripe arrangement period , film thickness , and the reflector information set , where the reflection grating period is , number of reflection grating pairs , summarizing each group of SAW device structure information into the same column vector solution ,in .

[0007] S2. Substitute the coupling parameters into the target equation to obtain the parameters of each module of the port network, and connect the parameters of each module to form a complete structural model.

[0008] S3. Distributed global search extracts important feature points in the structural model as optimization targets, and defines an evaluation function to select solutions that meet the optimization targets.

[0009] S4. Make an opportunity decision based on the evaluation value and record the optimal result after the global search as the final output parameter.

[0010] Furthermore, the S2 comprises the following steps:

[0011] S21. First, substitute the coupling parameter solution into the relation

[0012] = (1)

[0013] in for Linear fitting parameters, is a set of penetration depth parameters, is a set of SAW reflection parameters. The sampling frequency is defined as f(q), is the device center frequency, and q is the number of sampling points.

[0014] (2)

[0015] in is the IDT device length group, is the length group of the reflector device.

[0016] S22. Connect the IDT modules according to the coupling parameter solution. The IDT model can be composed of two acoustic physical fields and one electric physical field. =0 and = Assuming that the sound wave is from =0 propagates to = If the direction is positive, then = Spread to =0 is the negative direction of sound wave propagation, and two acoustic physics field formulas about the sound wave propagation direction are obtained, where the parameter subscript represents the propagation direction of SAW.

[0017] (3)

[0018] (4)

[0019] make have to

[0020] (5)

[0021] Will and Expressed as |c|, and using Euler's formula, the above formula can be simplified to

[0022] (6)

[0023] S23, among which is the dispersion relation, which can be obtained from and It is expressed as:

[0024] (7)

[0025] That is, the GOAL function of formula (6) can be used to represent the IDT model of the acoustic physical field at two locations. and represents the reflection coefficient and excitation efficiency. Then the structural solution is brought into the static capacitance , we can get a set of positive correlation equations , the unit period static capacitance group is used to calculate the GOAL function of the electric physics field IDT.

[0026] (8)

[0027] S24, then connect the left and right reflection gratings to the IDT model, and the left and right reflection grating coefficients can be expressed by the following formula:

[0028] (9)

[0029] in , connect it with the IDT model to form a complete structural model, and the device's admittance characteristic group is obtained according to the structural model:

[0030] (10)

[0031] Furthermore, the S3 comprises the following steps:

[0032] S31. Establish a device evaluation model based on distributed global search, optimize device performance indicators through the evaluation model, and obtain the device performance indicators from the admittance characteristic group. Set the maximum number of global searches to H, divide the important feature points according to the sampling frequency f(q), and divide the points corresponding to the sampling frequency f(q) into The value of , put important feature points into the feature set , the corresponding eigenvalue set is , a is used to divide the feature interval.

[0033] (11)

[0034] S32. Let the threshold value to be optimized be T, and the evaluation function be

[0035] (12)

[0036] Then record the feature value index in the feature set that is greater than the optimization threshold T, and assign the evaluation value of the index mapping to Otherwise, it is assigned to , thus the size of each eigenvalue evaluation value can be recorded to obtain a set of evaluation groups. Different optimization thresholds can be set according to different eigenvalue intervals to optimize the performance of the device.

[0037] Further, the S4 comprises the following steps:

[0038] S41, first perform distribution initialization and generate solutions in dynamic space , the type of information that the initial node needs to propagate is recorded as the dimension of the problem, and the initialization solution is based on the following formula:

[0039] ( ) (13)

[0040] The solution range is limited to ∈( , ), =(0, 1,…DP), DP is the number of problems to be solved.

[0041] S42, calculate the solution of the new individual propagation information in the node. Since there is positive feedback between nodes, individuals at different nodes will intelligently propagate information to nearby individuals, so that information can be propagated and updated between nodes. Based on this, the new solution can be generated as follows:

[0042] (14)

[0043] in The individuals that transmit information cannot be the same individual, and the node search range satisfy .

[0044] S43, perform opportunity selection according to the evaluation value sought, and select the solution with high evaluation as the reliable solution. The reliable solution has a high chance of being selected by the node for information dissemination. Therefore, the chance of each solution being selected is:

[0045] (15)

[0046] S44. After the opportunity decision, it is necessary to monitor the update degree of each solution and record the update times of each solution as Bas. Once the solution has not been updated after reaching the propagation threshold Limt, the original solution will be discarded and a new node individual will be selected to propagate the information.

[0047] (16)

[0048] in , loop according to the maximum global search times H, thereby finding the optimal solution, and finally recording the global optimal solution and the optimal eigenvalue, and the design parameters and device performance of the SAW sensor device after global search and optimization can be obtained.

[0049] The present application also provides a temperature detection transceiver system, including a transmitting path, a receiving path, a temperature acquisition module, a conversion switch, a microcontroller module, a transceiver antenna, a reader and a display module. The temperature acquisition module includes a resonant surface acoustic wave sensor and an antenna designed using the above-mentioned design method.

[0050] Furthermore, the surface acoustic wave temperature sensor includes two reflection gratings, a piezoelectric substrate, an interdigital transducer, and two transceiver antennas, and the two transceiver antennas are connected to two ends of the interdigital transducer electrodes.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] This method comprehensively considers global optimum and local optimum according to multi-physical field coupling and distributed global search methods. The distributed global search concept reduces the empirical trial and error cost and design complexity in the manual design of SAW devices. For the target optimization results, the present invention can provide a variety of reliable reference methods, providing more optimized performance and more choices in the actual design of devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0054] Figure 1 The present invention discloses an overall process of a surface acoustic wave sensor device design method based on multi-physical field coupling and distributed global search.

[0055] Figure 2 This is a processing framework diagram of a surface acoustic wave sensor device design method based on multi-physical field coupling and distributed global search according to the present invention.

[0056] Figure 3 The present invention is a design flow chart of a surface acoustic wave sensor device design method based on multi-physical field coupling and distributed global search.

[0057] Figure 4 This is a structural diagram of a temperature detection transceiver system according to a surface acoustic wave sensor device design method based on multi-physical field coupling and distributed global search and its application in the present invention.

[0058] Figure 5 The present invention is a schematic diagram of a resonant device structure of a surface acoustic wave sensor device design method based on multi-physical field coupling and distributed global search and its application.

[0059] Figure 6 The present invention is an application flow chart of a surface acoustic wave sensor device temperature measurement system based on multi-physical field coupling and distributed global search.

[0060] In the figure, 1, reflection grating; 2, piezoelectric substrate; 3, interdigital transducer; 4, reflection grating; 5, transceiver antenna; 6, transceiver antenna; DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. Of course, the specific embodiments described here are only used to explain the present invention and are not used to limit the present invention.

[0062] Example 1

[0063] See also Figures 1 to 3 This embodiment provides a surface acoustic wave sensor device design method based on multi-physical field coupling and distributed global search, comprising the following steps:

[0064] S1. Given multi-physics coupling parameters.

[0065] S2. Substitute the coupling parameters into the target equation to obtain the parameters of each module of the port network, and connect the parameters of each module to form a complete structural model.

[0066] S3. Distributed global search extracts important feature points in the structural model as optimization targets, and defines an evaluation function to select solutions that meet the optimization targets.

[0067] S4. Make an opportunity decision based on the evaluation value and record the optimal result after the global search as the final output parameter.

[0068] The step S1 comprises the following steps:

[0069] S11, given the multi-physics coupling parameters, the substrate used is 36° The propagation velocity of the substrate is V = 4111.8 m / s, and the center frequency of the designed resonant device is 660MHz. , where is the number of stripes , overlapping aperture , refers to the stripe arrangement period , film thickness , and the reflector information set , where the reflection grating period is , number of reflection grating pairs , summarizing each group of SAW device structure information into the same column vector solution ,in Let j = 10, which means to take 10 different solutions to solve the problem, and choose the index logarithm. With overlapping aperture As an optimized solution.

[0070] The step S2 comprises the following steps:

[0071] S21. First, substitute the coupling parameter solution into the relation

[0072] = (1)

[0073] in for Linear fitting parameters, is a set of penetration depth parameters, is a set of SAW reflection parameters. The sampling frequency is defined as f(q), is the device center frequency, and q is the number of sampling points.

[0074] (2)

[0075] in is the IDT device length group, is the length group of the reflector device.

[0076] S22. Connect the IDT modules according to the coupling parameter solution. The IDT model can be composed of two acoustic physical fields and one electric physical field. =0 and = Assuming that the sound wave is from =0 propagates to = If the direction is positive, then = Spread to =0 is the negative direction of sound wave propagation, and two acoustic physics field formulas about the sound wave propagation direction are obtained, where the parameter subscript represents the propagation direction of SAW.

[0077] (3)

[0078] (4)

[0079] make have to

[0080] (5)

[0081] Will and Expressed as |c|, and using Euler's formula, the above formula can be simplified to

[0082] (6)

[0083] in is the dispersion relation, which can be obtained from and It is expressed as:

[0084] (7)

[0085] That is, the GOAL function of formula (6) can be used to represent the IDT model of the acoustic physical field at two locations. and represents the reflection coefficient and excitation efficiency. Then the structural solution is brought into the static capacitance , we can get a set of positive correlation equations , the unit period static capacitance group is used to calculate the GOAL function of the electric physics field IDT.

[0086] (8)

[0087] S23, then connect the left and right reflection gratings to the IDT model, and the left and right reflection grating coefficients can be expressed by the following formula:

[0088] (9)

[0089] in , connect it with the IDT model to form a complete structural model, and the device's admittance characteristic group is obtained according to the structural model:

[0090] (10)

[0091] The step S3 comprises the following steps:

[0092] S31. Establish a device evaluation model based on distributed global search, optimize device performance indicators through the evaluation model, and obtain the device performance indicators from the admittance characteristic group. Set the maximum number of global searches to 500, divide the important feature points according to the sampling frequency f(q), the number of sampling points q is 200, and the center frequency is 660MHz, the sampling frequency f(q) corresponds to The value of , put important feature points into the feature set , the corresponding eigenvalue set is , assuming that The nearby points are taken as optimization targets, and the number of points is j.

[0093] (11)

[0094] The available feature points and feature value sets are shown in Table 1.

[0095]

[0096] S32, let the threshold value that the eigenvalue seeks to optimize be T, here we take The eigenvalue is evaluated and the evaluation function is changed to:

[0097] (12)

[0098] Then record the index of the eigenvalue in the eigenvalue set that is greater than the optimization threshold T, and assign the evaluation value of the index mapping to Otherwise, it is assigned to , thus the size of each eigenvalue evaluation value can be recorded to obtain a set of evaluation groups. Different optimization thresholds can be set according to different eigenvalue intervals to optimize the performance of the device.

[0099] The step S4 comprises the following steps:

[0100] S41, first perform distribution initialization and generate solutions in dynamic space , the type of information that the initial node needs to propagate is recorded as the dimension of the problem, and the initialization solution is based on the following formula:

[0101] ( ) (13)

[0102] The solution range is limited to ∈( , ), =(0, 1,…DP), DP is the number of problems to be solved. The solutions generated for NF and AP are shown in Table 2.

[0103]

[0104] S42. Calculate the solution of the information propagation of the new individual in the node. Since there is positive feedback between the nodes, different individuals of the node will intelligently propagate information to nearby individuals, so that the information can be propagated and updated between the nodes. Based on this, the generation method of the new solution is:

[0105] (14)

[0106] in The individuals that transmit information cannot be the same individual, and the node search range satisfy .

[0107] S43. Perform a chance decision based on the evaluation value obtained by formula (12), and select the solution with a high evaluation value as a reliable solution. A reliable solution has a high chance of being selected by a node for information dissemination. Thus, the chance of each solution being selected is:

[0108] (15)

[0109] S44. After the opportunity decision, it is necessary to monitor the update degree of each solution and record the update times of each solution as Bas. Let Limt=10. Once the solution has not been updated after reaching the propagation threshold Limt, the original solution will be discarded and a new node individual will be selected to propagate the information.

[0110]

[0111] in , loop according to the maximum number of global searches to find the optimal solution, and finally record the global optimal solution and the optimal eigenvalue to obtain the design parameters and device performance of the SAW sensor device after intelligent search and optimization.

[0112] like Figure 4 The temperature detection system structure shown is composed of a surface acoustic wave single-ended resonator device designed by the present invention and connected with an antenna to form a SAW temperature sensor for remote temperature measurement.

[0113] The structure of the temperature detection transceiver system includes a transmitting path, a receiving path, a temperature acquisition module, a switching switch, a microcontroller module, a transceiver antenna, a reader and a display module. The transmitting path includes a direct digital frequency synthesizer module, a phase-locked loop module, a switch, a bandpass filter, and a power amplifier; the receiving path includes a low-noise power amplifier, a bandpass filter, a mixer, and an analog-to-digital converter; the temperature acquisition module includes a resonant surface acoustic wave sensor and an antenna, the surface acoustic wave temperature sensor is installed in the test area and the initial temperature information is converted into an electrical signal by an interdigital transducer, and the transceiver antenna transmits the converted electrical signal to the reader for collection; the microcontroller module changes the switching switch to the receiving path, and transmits the received temperature value to the microcontroller for analysis as a reference temperature value for temperature change, and the microcontroller module adopts STM3 The single-chip microcomputer changes the conversion switch to the transmitting path and transmits an electrical signal to the direct digital frequency synthesizer to generate a periodic sinusoidal electrical signal, and the phase-locked loop module performs frequency multiplication; the microcontroller module controls the switch to be turned on and off to generate an intermittent sinusoidal signal, and the frequency multiplied signal is amplified by the power amplifier, and the bandpass filter and the power amplifier further filter and amplify the signal, and the reader antenna transmits the intermittent sinusoidal electrical signal to the temperature acquisition module, and the conversion switch is changed to the receiving path, and the sinusoidal electrical signal is converted into a surface acoustic wave through the interdigital transducer of the sensor, and is reflected back to the interdigital transducer through the reflection grating and is converted again into an electromagnetic echo signal and transmitted back to the reader. The electromagnetic echo signal is transmitted to a low-noise amplifier and a bandpass filter through a reader for signal amplification and filtering. The local oscillator signal and the echo signal are transmitted through a microcontroller connected to a mixer for difference frequency. The bandpass filter and the power amplifier filter and amplify the signal and then transmit it back to the microcontroller through an analog-to-digital converter. In the process of continuous emission of sinusoidal wave electrical signals, the velocity of the surface acoustic wave will change with the temperature of the piezoelectric substrate of the sensor, causing the frequency of the returned electromagnetic wave signal to change. Finally, the temperature change fed back by the microcontroller and the initial reference temperature are processed and output to the display module.

[0114] Further Figure 5 As shown, this embodiment uses a single-ended resonator type surface acoustic wave temperature sensor to collect the initial value of the temperature of the area to be measured. The surface acoustic wave temperature sensor includes a reflection grating 1, a piezoelectric substrate 2, an interdigital transducer 3, a reflection grating 4, a transceiver antenna 5, and a transceiver antenna 6. The transceiver antenna 5 and the transceiver antenna 6 are connected to both ends of the interdigital transducer electrodes.

[0115] Further Figure 6 This is an application flow chart of the surface acoustic wave device temperature measurement system based on multi-physical field coupling and distributed global search in this embodiment.

[0116] Through the above work process, the design method and application of surface acoustic wave devices based on multi-physics field coupling and distributed global search can achieve real-time, non-contact and high-precision temperature measurement. In different application scenarios, appropriate parameter adjustments and evaluation function modifications can be made as needed to meet specific temperature measurement requirements.

[0117] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A surface acoustic wave device design method based on multi-physical field coupling and distributed global search, comprising the following steps: S10, given the multi-physics field coupling parameters, for the finger information set , where is the number of stripes , overlapping aperture , refers to the stripe arrangement period , film thickness , and the reflector information set , where the reflection grating period is , number of reflection grating pairs , summarizing each group of SAW device structure information into the same column vector solution ,in , S20, bring the coupling parameters into the target equation to obtain the parameters of each module of the port network. The target equation of the acoustic physics field in the port network is: , the objective equation of the electric physics field is , the module is a single element in the structural model, connecting the parameters of each module to form a complete structural model, and using the structural model to find the admittance characteristic group, S30, distributed global search, extracting important feature points in the structural model as optimization targets, defining an evaluation function to select solutions that meet the optimization targets, S40, making an opportunity decision based on the evaluation value, and recording the optimal result after the global search as the final output parameter.

2. A surface acoustic wave device design method based on multi-physical field coupling and distributed global search according to claim 1, characterized in that: The step S20 comprises the following steps: S21. First, substitute the coupling parameter solution into the relation = (1)； in for Linear fitting parameters, is a set of penetration depth parameters, is a set of SAW reflection parameters, and the sampling frequency is defined as f(q). is the device center frequency, q is the number of sampling points, (2)； in is the length group of the IDT device, is the length group of the reflector device, S22, connect the IDT module according to the coupling parameter solution. The IDT module consists of two acoustic physical fields and one electric physical field. The two acoustic physical fields are respectively =0 and = Assuming that the sound wave is from =0 propagates to = If the direction is positive, then = Spread to =0 is the negative direction of sound wave propagation, that is, two acoustic physics field formulas about the direction of sound wave propagation are obtained, in which the parameter subscripts represent the propagation direction of SAW. (3)； (4)； make have to (5)； Will and Denote it by |c| and use Euler's formula to simplify the above formula to (6)； S23, among which is the dispersion relation, given by and It is expressed as: (7)； The target equation of formula (6) is To represent the module of the interdigital transducer with two acoustic physics fields, and Represent the reflection coefficient and excitation efficiency, and then bring the structural solution into the static capacitance , that is, a set of positive correlation equations , static capacitance group per unit period Target equations for calculating the electro-physics field of the interdigital transducer , (8)； S24, and then connect the left and right reflection gratings to the IDT module. The left and right reflection grating coefficients are expressed by the following formula: (9)； in , connect it with the IDT module to form a complete structural model, and the device's admittance characteristic group is obtained according to the structural model: (10)。 3. The surface acoustic wave device design method based on multi-physical field coupling and distributed global search according to claim 1 is characterized in that: The step S30 includes the following steps: S31. Establish a device evaluation model based on distributed global search, optimize device performance indicators through the evaluation model, and obtain the device performance indicators from the admittance characteristic group. curve, set the maximum number of global searches to H, according to the sampling frequency Divide the important feature points and set the sampling frequency The corresponding The value of , put important feature points into the feature set , the corresponding eigenvalue set is , a is used to divide the feature interval, (11)； S32, let the threshold value that the eigenvalue seeks to optimize be T, and let the evaluation function be: (12)； Then record the feature value index in the feature set that is greater than the optimization threshold T, and assign the evaluation value of the index mapping to Otherwise, it is assigned to , thereby recording the size of each eigenvalue evaluation value to obtain a group of evaluation value groups, and setting different optimization thresholds according to different eigenvalue intervals to optimize the performance of the device.

4. The surface acoustic wave device design method based on multi-physical field coupling and distributed global search according to claim 1 is characterized in that: The step S40 comprises the following steps: S41, first perform distribution initialization and generate solutions in dynamic space , the type of information that the initial node needs to propagate is recorded as the dimension of the problem , the initialization solution is as follows: ( ) (13)； The solution range is limited to ∈( , ), =(0, 1,…DP), DP is the number of problems to be solved, S42, calculate the solution of the new individual propagation information in the node. Due to the positive feedback between the nodes, different distributed nodes will intelligently propagate information to nearby nodes, so that the information can be propagated and updated between the nodes. Based on this, the new solution is generated as follows: (14)； in The node that transmits information cannot be the same node, and the node search range satisfy , S43, perform opportunity selection according to the evaluation value sought, and select the solution with a high evaluation value as a reliable solution. The reliable solution has a high chance of being selected by the node for information dissemination, so the chance of each solution being selected is: (15)； S44. After the opportunity decision, the update degree of each solution needs to be monitored, and the update number of each solution is recorded as Bas. Once the solution has not been updated after reaching the propagation threshold Limt, the original solution is Discard and select new node individuals to propagate information. (16); in , loop according to the maximum global search times H, thereby finding the optimal solution, and finally record the global optimal solution and the optimal eigenvalue, that is, the SAW device design parameters and device performance after intelligent search and optimization are obtained.

5. A temperature detection transceiver system, comprising a transmitting path, a receiving path, a temperature acquisition module, a conversion switch, a microcontroller module, a transceiver antenna, a reader and a display module, characterized in that: The temperature acquisition module includes a surface acoustic wave sensor device designed using the design method of claim 1.

6. A temperature detection transceiver system according to claim 5, characterized in that: The surface acoustic wave sensor device comprises two reflection gratings, a piezoelectric substrate, an interdigital transducer, and two transceiver antennas, wherein the two transceiver antennas are connected to two ends of the interdigital transducer electrodes.

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