Temperature Compensation of SAW Winding Tension Sensor Based on PSO-LSSVM Algorithm

Abstract

In this paper, a SAW winding tension sensor is designed and data fusion technology is used to improve its measurement accuracy. To design a high-measurement precision SAW winding tension sensor, the unbalanced split-electrode interdigital transducers (IDTs) were used to design the input IDTs and output IDTs, and the electrode-overlap envelope was adopted to design the input IDT. To improve the measurement accuracy of the sensor, the particle swarm optimization-least squares support vector machine (PSO-LSSVM) algorithm was used to compensate for the temperature error. After temperature compensation, the sensitivity temperature coefficient αs of the SAW winding tension sensor was decreased by an order of magnitude, thus significantly improving its measurement accuracy. Finally, the error with actually applied tension was calculated, the same in the LSSVM and PSO-LSSVM. By multiple comparisons of the same sample data set overall, as well as the local accuracy of the forecasted results, which is 5.95%, it is easy to confirm that the output error predicted by the PSO-LSSVM model is 0.50%, much smaller relative to the LSSVM’s 1.42%. As a result, a new way for performing data analysis of the SAW winding tension sensor is provided.

Grooving and Absorption on Substrates to Reduce the Bulk Acoustic Wave for Surface Acoustic Wave Micro-Force Sensors

“…In this paper, we proposed the electrode-overlap envelope to design the input IDT. We selected ST-X SiO 2 as the material of the piezoelectric substrate to reduce the influence of sound-electricity reclamation [18]. Two methods are given to reject sidelobes: one is arranging acoustic absorbers at both ends of the substrate, and another is grooving at the bottom of the piezoelectric substrate, which can reduce the influence of BAW.…”