Dynamic properties such as natural frequencies and mode shapes are directly affected by damage in structures. In this paper, changes in natural frequencies and mode shapes were used as the input to various objective functions for damage detection. Objective functions related to natural frequencies, mode shapes, modal flexibility and modal strain energy have been used, and their performances hav...

Premature combustion that affects outputs, thermal efficiencies and lifetimes of internal combustion engine is called “knock effect”. However knock signal detection based on acoustic sensor is a challenging task due to existing of noise in the same frequency spectrum. Experimental results revealed that vibration signals, generated from knock, has certain frequencies related to vibration resonan...

We design an instrument with a novel embedded adaptive stochastic resonance (SR) algorithm that consists of a SR module and a digital zero crossing detection module for on-line weak signal detection in digital signal processing applications. The two modules are responsible for noise filtering and adaptive parameter configuration, respectively. The on-line weak signal detection can be stably ach...

The task of signal detection and separation is a central theme in a wide variety of fields. Many techniques exist to improve the capability of detecting or enhancement a weak target signal corrupted by the additive Gaussian noise or the background noise generated by an unknown nonlinear dynamical mechanism. Due to its simplicity in implementation and efficiency in computation, noise reduction b...

This paper provides statistical analysis for efficient detection of signal components when missing data samples are present. This analysis is important for both the areas of Lstatistics and compressive sensing. In both cases, few samples are available due to either noisy sample elimination or random undersampling signal strategies. The analysis enables the determination of the sufficient number...

On the basis of nonlinear dynamical modeling we investigate a chaos-based detector, which allows the extraction of signal frequencies in noisy chaotic interference.The detection scheme is tested by using both computer-generated chaotic data and real-life Lorenz-Sten£o (LS) chaotic circuit data respectively. The performance analysis demonstrates that signals hidden beneath the chaotic ambient no...