A surface acoustic wave ADM sensor device design method based on dynamic neighborhood screening set

Abstract

The present invention provides a surface acoustic wave ADM sensor device design method based on a dynamic neighborhood screening set, which belongs to the field of environmental monitoring and solves the problem of air-conditioning dust detection. The technical solution includes the following steps: S10, providing the target parameters of the surface acoustic wave ADM sensor device. S20, generating a finger arrangement structure based on the minimum absolute difference between the theoretical predicted area S1 and the actual calculated area S2. S30, generating a screening set, modifying Y based on the dynamic neighborhood, and generating a new structure. S40, comparing the simulation frequency response and the target frequency response, and outputting the surface acoustic wave ADM sensor device design result. The beneficial effects of the present invention are: a surface acoustic wave ADM sensor device based on a dynamic neighborhood screening set is simply and efficiently designed, and it is easy to generalize to other surface acoustic wave devices.

Description

Technical Field

[0001] The invention relates to the field of environmental monitoring, and in particular to a surface acoustic wave ADM sensor device design method based on a dynamic neighborhood screening set. Background Art

[0002] Nowadays, air conditioners have become one of the indispensable household appliances in modern society. They are widely used to adjust indoor temperature and humidity, provide people with a comfortable indoor environment, and improve the quality of life. However, after using the air conditioner for a long time, a lot of dust may accumulate in it, which not only reduces the efficiency of the air conditioning system, but also has a negative impact on the health of users.

[0003] Current air conditioning systems provide dust fullness reminders based on cumulative operating time, but do not clearly state the dust content in the air conditioner. A common way to determine the dust content of an air conditioner is to observe visible dust on the air filter or exhaust port, but this method is highly subjective and cannot provide accurate quantitative measurements. Currently, there is a lack of an efficient monitoring system to quantitatively measure dust levels in air conditioning systems and provide accurate monitoring results in a timely manner to ensure high-quality indoor air.

[0004] Therefore, the present invention provides a surface acoustic wave ADM sensor device design method based on a dynamic neighborhood screening set for an air-conditioning dust detection system to achieve efficient air-conditioning dust monitoring. Summary of the invention

[0005] The present invention provides a surface acoustic wave ADM sensor device design method based on a dynamic neighborhood screening set, according to the theoretical prediction area and the actual calculated area The minimum absolute difference of the finger arrangement structure is generated; by modifying the structure through screening sets and dynamic neighborhoods, comprehensively considering the global optimum and local optimum, comparing the simulation frequency response and the target frequency response, the design results of the surface acoustic wave ADM sensor device are given, which is used in the air-conditioning dust detection system to effectively realize the air-conditioning dust detection, showing the advantages of reliability, accuracy and real-time, and has strong application value.

[0006] In order to achieve the above-mentioned invention object, the technical solution adopted by the present invention is specifically as follows:

[0007] A surface acoustic wave ADM sensor device design method based on a dynamic neighborhood screening set comprises the following steps:

[0008] S10. Give the parameters of the surface acoustic wave ADM sensor device, the bar sequence , Information collection , , where S1 is the theoretical predicted area, S2 is the actual calculated area, △S is the absolute difference between S1 and S2, and the objective function is TF.

[0009] S20, generating a finger arrangement structure according to the minimum absolute difference between the theoretically predicted area S1 and the actually calculated area S2.

[0010] S30, generating a screening set, modifying Y based on the dynamic neighborhood, and generating a new structure.

[0011] S40, comparing the simulated frequency response and the target frequency response, and outputting the surface acoustic wave ADM sensor device design result.

[0012] Furthermore, the surface acoustic wave ADM sensor device design method based on dynamic neighborhood screening set is characterized in that step S20 comprises the following steps:

[0013] S21, solve the theoretical prediction area S1

[0014]

[0015] in , P is the envelope formula of TF.

[0016] S22, solve the actual calculated area S2

[0017]

[0018] in ,

[0019] ;

[0020] S23. Calculation The absolute difference between S1 and S2 is △S

[0021]

[0022] S24, arranging the fingers according to the minimum absolute difference between S1 and S2, i.e., min△S;

[0023]

[0024]

[0025]

[0026]

[0027] Furthermore, the surface acoustic wave ADM sensor device design method based on dynamic neighborhood screening set is characterized in that step S30 comprises the following steps:

[0028] S31. Generate a screening set OT.

[0029]

[0030] S32, based on dynamic neighborhood Make modifications to meet .

[0031]

[0032] in .

[0033] Furthermore, the surface acoustic wave ADM sensor device design method based on dynamic neighborhood screening set is characterized in that step S40 comprises the following steps:

[0034] S41, Calculate the simulation frequency response The relative bandwidth B is compared with the relative bandwidth B1 of the target frequency response to determine whether the error value △B of the relative bandwidth is within the allowable range.

[0035]

[0036] S42: Determine whether the out-of-band suppression OIPR is greater than the target suppression.

[0037]

[0038] The present application also provides an oscillator, including a surface acoustic wave ADM sensor device based on a dynamic neighborhood screening set and an operational amplifier designed by the above-mentioned design method, which is used in an air-conditioning dust measurement alarm system.

[0039] Furthermore, the oscillator includes a dust measurement input module, a dust measurement output module and a data processing module, wherein the dust measurement input module includes dust and surface acoustic wave ADM sensor devices; the dust measurement output module 5 includes Modules, cloud platforms and mobile applications.

[0040] The present application also provides an air-conditioning dust detection system, comprising an oscillator as described above.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] This method generates a finger arrangement structure based on the minimum absolute difference between the theoretical predicted area S1 and the actual calculated area S2; by modifying the structure through screening sets and dynamic neighborhoods, the global optimum and local optimum are comprehensively considered, which greatly reduces the complexity of the calculation. For the target frequency response, the present invention can provide a variety of different reliable reference schemes, providing more options for actual design. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 The present invention discloses an overall process of a surface acoustic wave (ADM) sensor device design method based on a dynamic neighborhood screening set.

[0044] Figure 2 The overall data processing framework diagram of a surface acoustic wave ADM sensor device design method based on a dynamic neighborhood screening set of the present invention.

[0045] Figure 3 The present invention is a design flow chart of a surface acoustic wave (ADM) sensor device design method based on a dynamic neighborhood screening set.

[0046] Figure 4 The present invention is a schematic diagram of a surface acoustic wave (ADM) sensor device design method based on a dynamic neighborhood screening set and an oscillator structure of an application system.

[0047] Figure 5 The present invention is a structural diagram of an air-conditioning dust detection system based on a surface acoustic wave (ADM) sensor device of a dynamic neighborhood screening set.

[0048] In the figure, 1. adsorption ball; 2. operational amplifier; 3. dust measurement input module; 4. data processing module; 5. dust measurement output module. DETAILED DESCRIPTION

[0049] In order to more clearly illustrate the specific technical scheme of the embodiment of the present invention, the present invention will be further described in conjunction with the implementation examples and the accompanying drawings. Obviously, the described implementation examples are part of the embodiments of the present invention, rather than all of the embodiments. In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail 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 intended to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. The implementation method of a surface acoustic wave ADM sensor device design method based on a dynamic neighborhood screening set of the present invention is as follows:

[0050] See also Figures 1 to 3As shown, the present invention provides a technical solution, which is a surface acoustic wave ADM sensor device design method based on a dynamic neighborhood screening set, comprising the following steps:

[0051] S10. Give the parameters of the surface acoustic wave ADM sensor device, including the substrate material used is ST-quartz, the parameters of this material include propagation speed , electromechanical coupling coefficient , center frequency , the objective function TF is the Morlet wavelet function, and the scale is 2 -2 ; Refers to the sequence , Information collection , , where S1 is the theoretical predicted area, S2 is the actual calculated area, and △S is the absolute difference between S1 and S2.

[0052] S20, generating a finger arrangement structure according to the minimum absolute difference between the theoretically predicted area S1 and the actually calculated area S2.

[0053] S30, generating a screening set, modifying Y based on the dynamic neighborhood, and generating a new structure.

[0054] S40, comparing the simulated frequency response and the target frequency response, and outputting the surface acoustic wave ADM sensor device design result.

[0055] As a surface acoustic wave ADM sensor device design method based on a dynamic neighborhood screening set provided by the present invention, step S20 includes the following steps:

[0056] S21, solve the theoretical prediction area S1

[0057] in .

[0058]

[0059] P is the formula of the envelope function of the Morlet wavelet function

[0060]

[0061] 2 of them k is the scale of the Morlet wavelet function, where k=-2.

[0062] S22, solve the actual calculated area S2

[0063]

[0064] in

[0065] ;

[0066] S23. Calculation The absolute difference between S1 and S2 is △S

[0067]

[0068] S24. Arrange the fingers according to the minimum absolute difference between S1 and S2, i.e., min△S.

[0069]

[0070]

[0071]

[0072]

[0073] As a surface acoustic wave ADM sensor device design method based on a dynamic neighborhood screening set provided by the present invention, step S30 includes the following steps:

[0074] S31. Generate a screening set OT.

[0075]

[0076] S32, based on dynamic neighborhood Make modifications to meet .

[0077]

[0078] in .

[0079] As a surface acoustic wave ADM sensor device design method based on a dynamic neighborhood screening set provided by the present invention, step S40 includes the following steps:

[0080] S41, Calculate the simulation frequency response The relative bandwidth B is compared with the relative bandwidth B1 of the target frequency response to determine whether the error value △B of the relative bandwidth is within the allowable range.

[0081]

[0082] S42: Determine whether the out-of-band suppression OIPR is greater than the target suppression.

[0083]

[0084] Specific embodiment 1 is shown in Table 1.

[0085]

[0086] Specific embodiment 2 is shown in Table 2.

[0087]

[0088] like Figure 4 , Figure 5 As shown, a surface acoustic wave ADM sensor device based on a dynamic neighborhood screening set and an operational amplifier 2 form an oscillator for an air-conditioning dust measurement alarm system, including a dust measurement input module 3, a dust measurement output module 5 and a data processing module 4.

[0089] The dust measurement input module 3 includes dust and surface acoustic wave (ADM) sensor devices; the gravity caused by the adsorption of dust on the oscillator generates pressure, and finally the sensitive film is deformed and generates a signal; the gravity caused by the different dust contents on the oscillator is different, so the pressure is different, so that the center frequency of the signal is different; the measured dust is divided into three levels, corresponding to the first level with low dust content, the second level with medium dust content, and the third level with high dust content; the oscillator is composed of a surface acoustic wave (ADM) sensor device and an operational amplifier 2; an adsorption ball 1 is composed of a material for adsorbing dust, and the black dot in the middle of the surface acoustic wave (ADM) sensor device is the bonding point between the adsorption ball 1 and the sensor substrate; since the system can measure the dust content by modifying the level according to the amount of dust content, the measurement accuracy and adaptive intelligence of the system are higher.

[0090] like Figure 4 The figure shows a schematic diagram of an oscillator, which is composed of a surface acoustic wave ADM sensor device and an operational amplifier 2. In the middle of the oscillator, there can be three to five adsorption balls 1 fixed with glue to absorb dust, using activated carbon material. Here, three adsorption balls 1 are used and they are at the same level. The function of the above structure is to absorb dust from the air outlet of the air conditioner, and the weight of the dust generates pressure on the substrate, thereby causing the center frequency of the oscillator to shift.

[0091] The operational amplifier 2 in the data processing module 4 amplifies the signal transmitted by the surface acoustic wave ADM sensor device to compensate for the loss in the signal acquisition process. The high-pass filter removes low-frequency noise and only retains high-frequency signals related to dust concentration. The microcontroller runs a data processing algorithm to convert the read signal into a dust concentration value.

[0092] The dust measurement output module 5 includes modules, cloud platforms and mobile applications; The module firmware is started by the microcontroller to achieve network connection and wireless data transmission, and communicate with the Internet through the wireless network protocol. The microcontroller transmits the processed data wirelessly to the cloud platform; the cloud platform is responsible for data storage and analysis, and can monitor the status of the equipment, analyze the trend of the increase and decrease of dust content, and give decision-making suggestions; the mobile application is used to obtain real-time data and display it to the user, so that the user can understand the current dust concentration, historical records, and receive alarms, so as to easily manage and monitor the air quality monitoring system.

[0093] The microcontroller of this measurement system is STM32, which meets a wide range of application requirements with its high performance and low power consumption. STM32 is aimed at a diverse market with strict requirements on performance and energy efficiency. It not only provides a rich peripherals and flexible memory configuration, but also has easy-to-develop software support, ensuring that users can quickly realize the process from concept to market. The signal output by the high-pass filter can be digitally processed to meet the needs. The relationship between dust content and frequency is determined based on the detailed parameters of the surface acoustic wave ADM sensor device, and different dust levels correspond to different dust content ranges.

[0094] An air conditioner dust detection system based on a surface acoustic wave (ADM) sensor device design method of a dynamic neighborhood screening set includes the following steps: when the dust content is in the first gear, the surface acoustic wave sensor transmits a signal to an operational amplifier 2, and then to a microcontroller via a high-pass filter. At this time, the dust content has not reached the critical value of the minimum dust content in the second gear. The microcontroller controls the digital potentiometer to reduce the resistance value, so that the offset of the oscillator center frequency is within the range of 0.5MHz; when the dust content is in the second gear, the oscillator transmits a signal to the operational amplifier 2, and then to the microcontroller via a high-pass filter. At this time, the dust content has not reached the critical value of the minimum dust content in the third gear but is greater than the critical value of the minimum dust content in the second gear. The dust content is at the minimum critical value, and the microcontroller controls the digital potentiometer to increase the resistance value and the frequency of the digital potentiometer compared to the first gear, so that the offset of the oscillator center frequency is within the range of 1.0MHz; when the dust content is at the third gear, the oscillator is transmitted to the operational amplifier 2, and then to the microcontroller through the high-pass filter. At this time, the dust content is greater than the minimum critical value of the dust content in the third gear, and the microcontroller controls the digital potentiometer to increase the resistance value compared to the second gear, so that the offset of the oscillator center frequency is within the range of 1.5MHz; then the microcontroller converts the pressure caused by the dust weight according to the linear correspondence between pressure and frequency to obtain the dust content value, and The modules are uploaded to the cloud platform and finally sent to the mobile application after integration processing.

[0095] 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 ADM device design method based on a dynamic neighborhood screening set comprises the following steps: S10. Give the parameters of the surface acoustic wave device, the bar sequence , Information collection , ,in is the theoretical predicted area, is the actual calculated area, yes and The absolute difference, objective function TF; S20, area predicted based on theory and the actual calculated area The minimum absolute difference of the finger arrangement structure is generated; the step S20 comprises the following steps: S21. Solving the theoretical predicted area ; (1)； in, , is the center frequency, is the envelope formula of TF; S22. Solve the actual calculated area ; (2)； in, ; S23. Calculation Department and The absolute difference ; (3)； S24, according to and The minimum absolute difference is Arrange the finger strips; S30, generate a filter set, modify the finger sequence based on the dynamic neighborhood , generate new structures; S40, comparing the simulated frequency response and the target frequency response, and outputting the surface acoustic wave ADM device design result.

2. A surface acoustic wave ADM device design method based on dynamic neighborhood screening set according to claim 1, characterized in that: The step S40 includes the following steps: S41, Calculate the simulation frequency response The relative bandwidth , relative bandwidth to the target frequency response Compare and determine the relative bandwidth error value Is it within the permitted range? (4)； (5)； S42, determine out-of-band suppression Is it greater than the target inhibition? (6)； (7)； (8)。 3. An oscillator, characterized in that: It includes a surface acoustic wave ADM device and an operational amplifier based on a dynamic neighborhood screening set designed using the design method of claim 1, and is used in an air-conditioning dust detection system.

4. An oscillator according to claim 3, characterized in that: The oscillator includes a dust measurement input module, a dust measurement output module and a data processing module, wherein the dust measurement input module includes dust and surface acoustic wave ADM devices; the dust measurement output module includes a Wi-Fi module, a cloud platform and a mobile application.

5. An air conditioner dust detection system, characterized in that: An oscillator comprising the oscillator as claimed in claim 4.

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