Abstract
Due to the complexity of the interference operation environment of wire rope, the detection signals are usually weak and coupled in time-frequency domain, which makes the defect difficult to recognize, while the signal characterizations in phase space are also needed to be studied. Combining the nonlinear dynamic feature identification theories, phase space characteristics and chaotic features of wire rope defect detection signals are mainly investigated in this paper. First, principles of phase space reconstruction method for wire rope detection signals are presented by the chaotic dynamic indexes calculation of embedded dimension and delay time. Second, the change trends of the correlation dimension, approximate entropy and Lyapunov index of different phase space reconstructed wire rope defect detection signals are studied through the nonlinear simulation and analysis. Finally, a phase space reconstruction algorithm based on improved SVD is proposed, and the new algorithm is also compared with traditional signal processing methods. These results obtained by 6 groups of experiments were also evaluated and compared by the parameters of signal-to-noise ratio (SNR) and phase space trajectory chart, which manifests that the improved algorithm not only can increase the weak detection signal SNR to about 2.3dB of wire rope effectively, but also demonstrate the feasibility of the proposed methods in application.
Highlights
As one of the most frequently applied ferromagnetic objects in practical engineering, steel wire rope plays an important role in loading in various fields such as, elevator, coal mine and ocean platform
The blue curve is the original wire rope defect detection signal obtained under different working conditions with various noises and inx=199 x=199 terference of vibration, while the red curve is the corresponding wire rope defect detection signal processed by the improved algorithm. it can be observ1e000d0 10t00h0 at, the denoised signals processed by the improv.ed S
Combining the calculation principles of different chaos evaluation parameters such as the correlation dimension, approximate entropy and the maximum Lyapunov index, the simulations are conducted regarding to three typical wire rope defect detection signals, where the characterizations of different wire rope inspection signals in the phase space were revealed
Summary
As one of the most frequently applied ferromagnetic objects in practical engineering, steel wire rope plays an important role in loading in various fields such as, elevator, coal mine and ocean platform. In the perspective of the dynamic characteristics research for wire rope detection system, researchers studied the nonlinear dynamics of the transverse, longitudinal and coupled vibration without external periodic driving forces for the wire rope in the friction hoist system by designing related experiments They revealed the essence that the transverse vibration was a forced vibration while the longitudinal vibration was a complex random vibration state combining the time-frequency analysis for the vibration signals, and pointed out that the vibration amplitude and strength deviation depended on the linear trend of the driving force frequency and characterized the nonlinear multi-order natural frequency features [8]. Compared with traditional stochastic resonance system and methods, this proposed method has lower noise output after the second filtering, better bandpass filtering effect and anti-noise performance
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