7 results about "Surface acoustic wave sensor" patented technology

The application belongs to the technical field of electrical sensors, and particularly relates to a preparation method of a surface acoustic wave sensor for improving the binding force of a gate electrode, comprising the following steps: cleaning a lithium niobate substrate, drying the lithium niobate substrate to obtain a pretreated lithium niobate substrate; spin-coating 3510T photoresist on the pretreated lithium niobate substrate, and then performing a pre-baking treatment at 100-120 DEG C; performing photoetching on the photoresist of the substrate after the pre-baking treatment, and then performing exposure and development treatment; performing post-baking treatment on the substrate after the development treatment at 120-140 DEG C; spin-coating photoresist on one side of the substrate after the post-baking treatment, and magnetron sputtering a platinum-gold layer; slowly heating the substrate after the magnetron sputtering treatment to 450-500 DEG C to perform heat treatment; removing the photoresist in the substrate after the heat treatment to form a platinum-gold gate electrode, and obtaining the surface acoustic wave sensor. The application reduces the cost and improves the stability of electrode material adhesion, and has a wide application prospect.

The application provides a surface acoustic wave sensor rapid query method and system. The method comprises: generating a query signal covering a preset query frequency band; sending the query signal to a surface acoustic wave sensor and receiving a primary echo output by the surface acoustic wave sensor after being excited by the linear frequency modulation query signal; performing time reversal processing on the primary echo to construct a secondary transmission signal; sending the secondary transmission signal to the surface acoustic wave sensor and receiving a secondary echo output by the surface acoustic wave sensor after being excited by the secondary transmission signal; and performing frequency domain processing on the secondary echo to obtain a resonance frequency estimation value of the surface acoustic wave sensor. The application effectively solves the technical problems of frequency mismatch, echo weakening and the need for multi-frequency point repeated scanning when the resonance frequency is unknown or drifts in the prior art, realizes wideband rapid query, and still maintains full-band effective coverage under the condition of uncertain resonance frequency.

This application discloses a method and system for monitoring the temperature of power cables based on surface acoustic wave (SAW) sensors, belonging to the field of power detection. This application is applicable to power cables with dynamic loads, by simultaneously acquiring frequency drift data and real-time current waveform data from a SAW sensor array along the power cable. The frequency drift data is converted into multiple temperature points and subjected to spatial interpolation and differentiation to obtain measured temperature gradient information. Harmonic component information is extracted from the current waveform and input into a deep neural network to predict theoretical temperature gradient information. Kalman filtering is used to iteratively fuse the predicted temperature gradient information with the measured temperature gradient information to generate an optimized target temperature gradient. Finally, based on this target temperature gradient and starting from a known temperature point, the complete temperature distribution data of the power cable is reconstructed through integral calculation, enabling comprehensive and accurate temperature monitoring of the power cable.

The application discloses a passive temperature detection device and a preparation method thereof. The device comprises an insulating substrate, a functional layer, a flexible piezoelectric layer and a surface acoustic wave sensor. The insulating substrate comprises a fixed part and a deformation layer, the deformation layer is suspended and fixed at one end of the fixed part. The functional layer is at least partially located on the deformation layer. The flexible piezoelectric layer is arranged on the functional layer and at least partially located in the overlapping area of the deformation layer and the functional layer. The thermal expansion coefficients of the deformation layer, the functional layer and the flexible piezoelectric layer increase in sequence. The surface acoustic wave sensor is arranged on the flexible piezoelectric layer, and the surface acoustic wave sensor comprises an interdigital transducer electrode, which is at least partially located in the overlapping area of the deformation layer, the functional layer and the flexible piezoelectric layer. The application can amplify the differential deformation effect and improve the temperature detection sensitivity.

The present application belongs to the technical field of data processing, and particularly relates to a medicament quantitative injection optimization method for a liquid-phase oxidation desulfurization system, comprising the following steps: step 1, installing an acoustic surface wave sensor array composed of multiple Love wave sensors in a bypass detection cavity of a desulfurization liquid circulation pipeline, matching each candidate independent component with a pre-established waveform feature template library to determine a medicament component label, and obtaining each medicament concentration component signal; step 2, sampling each medicament concentration component signal and a synchronously collected desulfurization efficiency time sequence in a sliding time window, and updating channel division as the sliding time window moves forward; and step 3, configuring one control intelligent agent for each medicament injection pipeline, so that the adjustment margin obtained by a leading channel is greater than that of a subordinate channel. The present application realizes synchronous online perception and cross-response decoupling of multiple medicament component concentrations.

This invention relates to a high-precision indirect measurement method and system for internal temperature based on the fusion of surface acoustic wave signal analysis and machine learning. The method includes: acquiring temperature-sensitive acoustic response parameters of a surface acoustic wave sensor in real time; synchronously acquiring ambient humidity parameters; performing an affine transformation on the temperature-sensitive acoustic response parameters using a linear relationship pre-calibrated at multiple known temperature points to obtain a pre-corrected response value; constructing a feature vector from the pre-corrected response value and the ambient humidity parameter, and inputting it into a pre-trained fusion prediction model to obtain a preliminary internal temperature estimate, wherein the fusion prediction model is constructed by weighted fusion of a multilayer perceptron neural network model and a Kriging interpolation model; performing time-series smoothing on the continuously acquired preliminary internal temperature estimates, and performing global regression analysis based on the smoothed sequence and reference temperature data to calculate and apply global correction coefficients to obtain the internal temperature output value.