Fan Dongliang

Bio: Fan Dongliang is an academic researcher from Wuhan Institute of Technology. The author has contributed to research in topics: Ultrasonic sensor & Sequential probability ratio test. The author has an hindex of 2, co-authored 10 publications receiving 118 citations.

Finite Element Analysis Model on Ultrasonic Phased Array Technique for Material Defect Time of Flight Diffraction Detection

Abstract: In this study, the finite element method (FEM) for phased array technology in ultrasonic time of flight diffraction (TOFD) for the defect detection of two-dimensional (2-D) geometric materials was researched. The phased array technology generated the FEM model for the TOFD signal. We have established the finite element model by the FEM software ANSYS based on the ultrasonic mechanism about the defects and the phased array transducer. A plane strain elements have simulated the reflected signal of the defect. We can compare the error ratio between simulation and experiment by using the theoretical calculation value as the benchmark, and find the feasibility of the FEM detection.

Gearbox malfunction identification method based on sequential hypothesis test

Abstract: The present invention discloses a gearbox malfunction identification method based on the sequential hypothesis test. The method is that an identification system carries out an adaptive intelligent query to a propagation channel with available data. Firstly, an extracted vibration signal is pretreated with the wavelet packet analysis method. Secondly, a sequence of kurtosis values of the extractedvibration signal is taken as a test object of the sequential probability ratio test. Then effective identification for the mode and gear crack degradation under four states of the gearbox is performedaccording to the sequential probability ratio test algorithm. Finally the gearbox vibration signal is subjected to the three-layer sequential ratio test by combining the sequential probability ratiotest and the root mean square error algorithm. The invention solves the problems of slow identification speed, inaccurate target identification and low identification efficiency in malfunction detection and multi-malfunction identification.

Finite element numerical simulation analysis based on ultrasonic phased array

Abstract: In this paper, the ultrasonic phased array technology is used to detect the defects in the welded seam test specimens. Using pulse echo method to detect a specimen with defects and establishing the corresponding numerical model. At the same time, the finite element is used to simulate the propagation of ultrasonic waves in the defective test specimens, and figures of the sound pressure amplitude are obtained. Compared with the theoretical values, the experimental values and the simulated values show good agreement, and the errors are only - 1.37% and 4.11%, respectively. The results show that the ultrasonic phased array with finite element simulation is effective.

High-definition nonlinear detection method for minor defects of automobile welding seam

Abstract: The present invention discloses a high-definition nonlinear detection method for minor defects of automobile welding seam. A RAM-5000-SNAP system excite a high-energy single-frequency RF pulse signal,after the signal is attenuated and filtered, drives an ultrasonic transducer fixed at one end of a sample to be tested input into the sample a single-frequency ultrasonic wave. The input ultrasonic wave interacts with the sample to be tested during propagation process in the sample, causing the ultrasonic wave to be distorted, to generate an ultrasonic wave of high frequency components. An ultrasonic transducer fixed at the other end of the sample to be tested collects an ultrasonic signal passing through the sample, and then performs fast Fourier transform analysis to the acquired signal, toobtain a fundamental amplitude and a second harmonic amplitude. The method has higher time domain resolution and defect sensitivity, and can more accurately determine positions and sizes of minor defects inside the welding seam.

Double adaptive weights for stabilization of moth flame optimizer: Balance analysis, engineering cases, and medical diagnosis

Abstract: Moth flame optimization (MFO) is a swarm-based algorithm with mediocre performance and marginal originality proposed in recent years. It tried to simulate the fantasy navigation mode of moth lateral positioning. The basic MFO has no specific, deep strategies in different periods of the algorithm and a fragile evolutionary basis, which may lead to the problem of falling into local optimum and slow convergence trend. Therefore, this paper introduces a double adaptive weight mechanism into the MFO algorithm, termed as WEMFO, to boost the search capability of the basic MFO and provide a more efficient tool for optimization purposes. The proposed WEMFO adjusts the search strategy adaptively in different periods of the algorithm, making it more flexible between global search (diversification) and local search (intensification). The WEMFO algorithm is compared with some illustrious metaheuristic solvers and advanced metaheuristic methods developed in recent years on thirty benchmark functions. The experimental results expose that the developed WEMFO has apparent compensations in terms of convergence speed and solution accuracy. Moreover, this paper analyzes the diversity and balance of WEMFO and applies the algorithm to several engineering problems. The experimental results show that the WEMFO algorithm has good performance in engineering problems. Additionally, the proposed WEMFO was also applied to train Kernel Extreme Learning Machine (KELM), the resultant optimized WEMFO-KELM model was applied to six clinical disease classification problems. By comparing with MFO-KELM and other five classification models, the experimental results showed that the proposed algorithm had shown better performance in practical problems. An online guide for the algorithm in this research WEMFO and proposed classifier WEMFO-KELM will be publicly available at https://aliasgharheidari.com .

A computational framework for propagated waves in a sandwich doubly curved nanocomposite panel

Abstract: In the current report, characteristics of the propagated wave in a sandwich structure with a soft core and multi-hybrid nanocomposite (MHC) face sheets are investigated. The higher-order shear deformable theory (HSDT) is applied to formulate the stresses and strains. Rule of the mixture and modified Halpin–Tsai model are engaged to provide the effective material constant of the multi-hybrid nanocomposite face sheets of the sandwich panel. By employing Hamilton’s principle, the governing equations of the structure are derived. Via the compatibility rule, the bonding between the composite layers and a soft core is modeled. Afterward, a parametric study is carried out to investigate the effects of the CNTs' weight fraction, core to total thickness ratio, various FG face sheet patterns, small radius to total thickness ratio, and carbon fiber angel on the phase velocity of the FML panel. The results show that the sensitivity of the phase velocity of the FML panel to the $${W}_{\rm{CNT}}$$ and different FG face sheet patterns can decrease when we consider the core of the panel more much thicker. It is also observed that the effects of fiber angel and core to total thickness ratio on the phase velocity of the FML panel are hardly dependent on the wavenumber. The presented study outputs can be used in ultrasonic inspection techniques and structural health monitoring.