A novel redundant haar lifting wavelet analysis based fault detection and location technique for telephone transmission lines

The current morphological wavelet technologies utilize a fixed filter or a linear decomposition algorithm, which cannot cope with the sudden changes, such as impulses or edges in a signal effectively. This paper presents a novel signal processing scheme, adaptive morphological update lifting wavelet (AMULW), for rolling element bearing fault detection. In contrast with the widely used morphological wavelet, the filters in AMULW are no longer fixed. Instead, the AMULW adaptively uses a morphological dilation-erosion filter or an average filter as the update lifting filter to modify the approximation signal. Moreover, the nonlinear morphological filter is utilized to substitute the traditional linear filter in AMULW. The effectiveness of the proposed AMULW is evaluated using a simulated vibration signal and experimental vibration signals collected from a bearing test rig. Results show that the proposed method has a superior performance in extracting fault features of defective rolling element bearings.

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“…(19)- (21) accords with the requirement of Eq. (18). Therefore, the proposed AMULW fits the perfect reconstruction condition.…”

Section: Perfect Reconstructionmentioning

confidence: 75%

“…Some MWs have been established, such as morphological Haar wavelet [18]. The schematic of the proposed AMULW in one stage is illustrated in Figure 2.…”

Section: Morphological Waveletmentioning

confidence: 99%

Detection of Bearing Faults Using a Novel Adaptive Morphological Update Lifting Wavelet

Zuo

Feng

et al. 2017

Chin. J. Mech. Eng.

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“…Additionally, its flexibility (in terms of adaptability to the desired application) has contributed to making TDR an interesting solution for the most diverse applications, such as fault detection on electric wires [20,21]; qualitative and quantitative control of liquids [22][23][24]; moisture measurements of soil [25][26][27][28] and of porous materials in general [29]; dielectric characterizations of materials [30][31][32][33]; and structural analysis [34][35][36].…”

Section: Theoretical Backgroundmentioning

confidence: 99%