Detection of Defects in Elevator Wire Ropes and Pipes Using Ultrasonic Guided Waves and Signal Processing


Student thesis: Doctoral Thesis

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Awarding Institution
Award date22 Jan 2018


Elevator wire ropes and pipes are an important part of the infrastructure in big cities. Their continuous operation is of significant importance for the economy of the city. Such infrastructures are prone to the different type of damages including rust, corrosion, and rupture. Undermining such issues may result in a catastrophic disaster that cost huge economic loss. For the case of elevator wire ropes and pipes carrying gas into residential buildings, any failure can endanger human lives. In order to avoid any disastrous incident, the integrity of such structures must be monitored and checked.

Among many developed nondestructive testing techniques, Visual Inspection and Magnetic Flux Leakage (MFL) can be used for inspecting wire ropes. However, the visual inspection highly depends on an operator’s eyes and therefore its reliability can be questioned. Meanwhile, hidden defects such as breakage in the internal wire are not detectable by naked eyes. MFL, on the other hand, has been used for detecting defects even if they are hidden inside the wire ropes. Nonetheless, MFL based inspection is point by point which means the sensor must move along the wire rope to cover all its length. Point by point approach for inspection takes a lot of time and subsequently high labor cost. When it comes to inspecting pipes, this approach can take a massive amount of time because of the bigger length of the pipe lines. This can be seen as a drawback of current conventional techniques for pipe inspection. Ultrasonic Bulk Wave technology and Eddy Current based Techniques to inspect pipes are all based on point by point fashion. In addition, they cannot be used to inspect inaccessible areas of pipe lines such as the parts covered by concrete walls.

Ultrasonic Guided Wave (UGW) is an effective method for performing health monitoring of plate like structures and detecting defects. It does not follow the point by point fashion and can monitor a structure such as wire ropes and pipes from a single point. In addition to long distance testing potential, the whole cross-section of the structure can be covered and any internal defects can be detected. In spite of the abovementioned advantages for guided wave based inspection, there are some challenges that need to be addressed. In practice, UGW signals are dispersive and contain multiple modes and noise. In the presence of overlapped wave-packets/modes and noise together with dispersion occurred in propagating wave signals, extracting meaningful features from these defects that are embedded in the signals is a challenging task. Handling such challenge requires advanced signal processing techniques. The aim of this thesis is to develop effective signal processing techniques to deal with the complexity of UGW signals for nondestructive testing (NDT) purpose. To achieve this goal, advanced signal processing techniques were developed for guided wave based inspection method. Addressing three aforementioned problems that complicate signal interpretation hence affect the accuracy in defect’s features extraction, the signal processing techniques can help to separate the overlapped modes, minimize noise and reduce the effect caused by dispersion.

For wire ropes inspection with polymer cores, extensive experiments were conducted to reveal guided wave characteristics in such structures. Broken wires that can be created over time as a result of corrosive environment and fluctuating loads were simulated in the laboratory. It was found out that in the presence of noise if the defect is small, broken wires cannot be identified. In order to expose the defect indication, novel tailor made Tone-Burst Wavelet was designed and applied to the signal. Unlike the result from conventional Morlet Wavelet, the broken wires were exposed in Time-Frequency Representation of the defective signal.

For the dispersion and overlapped UGW modes, Finite Element Method (FEM) was used to predict the form of wave packets propagating along the inspected structure. The predicted waveforms have the maximum resemblance with real UGW signals. A sophisticated algorithm called Sparse and Dispersion Based Matching Pursuit (SDMP) is proposed to solve the problem. SDMP operates in two stages. In the first stage, the approximation improves by adding a single atom to the solution set at each loop. However, atom selection criterion of SDMP utilizes the time localization of UGW’s reflections that causes a portion of overlapped wave-packets to be composed mainly of a single echo. Afterward, those atoms with frequency inconsistency with the excitation signal are discarded. This increases the sparsity of the final representation. Meanwhile, leading to accurate approximation, as discarded atoms do not represent UGW’s wave reflections, it simplifies the signal interpretation for detecting defects. To verify the effectiveness of SDMP for damage detection, results obtained from numerical simulations and experiments on steel pipes are presented in this thesis.

For the real application of detecting natural corrosion in pipes that are passing through concrete walls from the external wall to an internal unit of a residential building, another technique was proposed. The method called Smooth Empirical Mode Decomposition (SEMD) proved to effectively separate any overlapped GUW signal. It is based on the use of conventional Empirical Mode Decomposition (EMD).Wavelet transform was adopted in the sifting stage to improve the final outcome in SEMD. However, the process of selecting a proper mother wavelet that suits best for decomposing the overlapped signal plays an important role. Since in UGW inspection, the incident waves are well known and are usually tone-burst signals, a complex tone-burst signal was tailored to be used as the mother wavelet. During the sifting stage, wavelet de-noising was applied to eliminate unwanted frequency components from each Intrinsic Mode Function (IMF). The results show that SEMD can extract fault features even when the signal is highly contaminated. In the experiments conducted for inspecting corrosion occurred in the portion of the pipe that was covered by a concrete wall, this technique proved that it had successfully determined the location and severity of defects. It not only could separate the reflected UGW signals that were entering and exiting the concrete wall section from the temporal waveform of the reflected UGW, but also could reveal the natural corrosion with complex geometry that was hidden and located inside the concrete wall section of the inspected pipes.