A feasibility study on elbow erosion monitoring using active sensing approach and fractional Fourier transform

Abstract

Elbow erosion monitoring is of great significance to the safety of pipeline systems and maintenance personnel. This paper proposes a new elbow erosion monitoring method, which combines the PZT (lead zirconate titanate) enabled active sensing with the fractional Fourier transform (FrRT), and takes the fractional-order energy peak of the stress wave signal as the damage index. Three 90°-elbows and three 90°-elbow assemblies were used in the experimental studies. Under different erosion degrees, the mass reduction of the three separate elbows was measured by high-precision electronic scale and the residual thickness of the three elbow assemblies was detected by ultrasonic thickness gauge. Two pieces of PZT patches were respectively used to excite and receive the signals in the active sensing. FrFT was used to distinguish the linear sweep signal components of stress wave signals from the energy of other interference or noise signals, and the fractional-order energy peak was used as the damage index. The results show that there is a one-to-one relationship between mass of erosion loss and damage index. Compared with the traditional time domain signal energy method, the new method has the advantage of eliminating the saturation phenomenon. The proposed method and damage index proposed in this paper will be a promising tool for real-time monitoring of elbow erosion.

A New Method for Erosion Prediction of 90° Elbow Based on Non-Axisymmetric Ultrasonic-Guided Wave and the PSO–LSSVM Algorithm

“…Therefore, we used a handheld grinder to make oval-shaped pits to simulate the actual erosion area during the experiment. The depth of grinding is roughly the same each time, and the average value of multiple measurements of the central area of the bottom of the erosion pit is measured with an ultrasonic thickness gauge [ 42 ].…”

“…The artificially simulated erosion area and the PZT pasting position are shown in Figure 5 . The PZT specifications and materials used in the test are the same, and the properties of the PZT material are shown in Table 1 [ 42 ].…”

“…After Almeida [ 38 ] pointed out that FrFT can be understood as the rotation of the time–frequency plane, and Ozaktas [ 39 ] proposed a discrete algorithm with a calculation amount equivalent to FFT, more scholars have begun applying FrFT to the signal processing field [ 40 , 41 ]. The p -order fractional Fourier transform of a one-dimensional signal is defined as follows [ 42 ]: where is the kernel function, and its expression is where is the rotation angle, p is the order of the FrFT, and δ is the impulse function. Equation (2) shows that the FrFT kernel is essentially a set of LFM signals whose modulation frequency is cot α .…”

“…After Almeida [38] pointed out that FrFT can be understood as the rotation of the time-frequency plane, and Ozaktas [39] proposed a discrete algorithm with a calculation amount equivalent to FFT, more scholars have begun applying FrFT to the signal processing field [40,41]. The p-order fractional Fourier transform of a one-dimensional signal is defined as follows [42]:…”

A pipeline corrosion detecting method using percussion and residual neural network

“…However, during their operation, pipelines face many different challenges due to internal and external environmental factors. Especially during long-term services, the inner wall is at risk due to corrosion or erosion [2][3][4]. In long-term use, the inner wall of the pipeline is damaged causing pipeline leakage and other problems, resulting in serious environmental pollution, huge economic losses and may even * Author to whom any correspondence should be addressed.…”