The Application of Multi-Wavelet Theory in Deformation Monitoring Data Processing
نویسندگان
چکیده
With wavelet technology used more widely in deformation analysis, the paper will talk multi-wavelet (the second generation wavelet) theory used for deformation monitoring data analysis. The paper studies signal adopting different preprocessing method, makes a study of the selection problem in optima multi-wavelet preprocessing method. The deformation monitoring signal is disposed using different multi-wavelet which adopts optima preprocessing method, and the paper makes a comparison to the conventional odd wavelet. The result confirms: multi-wavelet is more superiority than conventional wavelet, which decreases RMSE, advances SNR, obtains higher analytic precision, conforms the validity and practicability in physical problem, and offers a new road for deformation monitoring signal process. *Corresponding author. He Yong-hong. Current address: Department of Civil engineering and construction management, Hunan University of Science and Engineering,. Tel: 13212665220. Email address: [email protected].
منابع مشابه
Application of Wavelet Transform as a Signal Processing Method for Defect Detection using Lamb Waves: Experimental Verification
A Lamb wave-based crack detection method for aluminum plates health monitoring is developed in this paper. Piezoelectric disks are employed to actuate and capture the Lamb wave signals. The position of crack is assumed to be aligned with the sensor and actuator. Extraction of high quality experimental results of lamb wave propagation in a plate-like structure is considerably complicated due to...
متن کاملReconstruction of Data Gaps in Total-Ozone Records with a New Wavelet Technique
This study introduces a new technique to fill and reconstruct daily observational of Total Ozone records containing void data for some days based on the wavelet theory as a linear time-frequency transformation, which has been considered in various fields of science, especially in the earth and space physics and observational data processing related to the Earth and space sciences. The initial c...
متن کاملFeature Selection in Structural Health Monitoring Big Data Using a Meta-Heuristic Optimization Algorithm
This paper focuses on the processing of structural health monitoring (SHM) big data. Extracted features of a structure are reduced using an optimization algorithm to find a minimal subset of salient features by removing noisy, irrelevant and redundant data. The PSO-Harmony algorithm is introduced for feature selection to enhance the capability of the proposed method for processing the measure...
متن کاملAN INTELLIGENT FAULT DIAGNOSIS APPROACH FOR GEARS AND BEARINGS BASED ON WAVELET TRANSFORM AS A PREPROCESSOR AND ARTIFICIAL NEURAL NETWORKS
In this paper, a fault diagnosis system based on discrete wavelet transform (DWT) and artificial neural networks (ANNs) is designed to diagnose different types of fault in gears and bearings. DWT is an advanced signal-processing technique for fault detection and identification. Five features of wavelet transform RMS, crest factor, kurtosis, standard deviation and skewness of discrete wavelet co...
متن کاملEvaluation of Close-Range Photogrammetric Technique for Deformation Monitoring of Large-Scale Structures: A review
Close-range photogrammetry has been used in many applications in recent decades in various fields such as industry, cultural heritage, medicine and civil engineering. As an important tool for displacement measurement and deformation monitoring, close-range photogrammetry has generally been employed in industrial plants, quality control and accidents. Although close-range photogrammetric applica...
متن کامل