A Novel Method for Detection of Abrupt Signal Changes in Water Quality Sensors Onboard Autonomous Underwater Vehicles

Abstract

Autonomous underwater vehicles (AUV) are equipped with a variety of water quality sensors. In this paper, we apply wavelet analysis theory to signals acquired by the AUV and develop a tool for identifying such malfunctions. This paper proposes an abrupt signal change detection method based on wavelet transforms. By selecting a threshold for the high-frequency wavelet coefficients, we were able to detect the abrupt signal. Three evaluation criteria were used in this study to assess signal-to-noise quality. These were combined with experimental analysis, noise detection, and a denoising method which is appropriate for detecting abrupt signal changes.