Jing Lin

Jing Lin
Beihang University (BUAA) | BUAA · School of Reliability and Systems Engineering

PhD

About

264
Publications
140,986
Reads
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17,456
Citations
Citations since 2016
180 Research Items
15292 Citations
201620172018201920202021202205001,0001,5002,0002,5003,000
201620172018201920202021202205001,0001,5002,0002,5003,000
201620172018201920202021202205001,0001,5002,0002,5003,000
201620172018201920202021202205001,0001,5002,0002,5003,000
Additional affiliations
January 2009 - present
Xi'an Jiaotong University
Position
  • Professor
September 2003 - December 2008
Chinese Academy of Sciences
Position
  • Researcher

Publications

Publications (264)
Article
For the modeling of Lamb wave propagation, the accuracy of some two-dimensional (2D) plate theories like the first order shear deformation theory (FSDT) may decline at a high frequency, since their displacement fields cannot match those complicated Lamb wave structures. To address this issue, this paper proposes an improved 2D thin plate theory whi...
Article
Many nondestructive testing (NDT) and structural health monitoring (SHM) systems utilize Lamb wave transducer arrays for identification and localization of scattering wave sources. A large number of transducers are usually required during array signal processing and source localization, which increases hardware cost and reduces system reliability....
Article
Deep learning-based fault diagnosis methods have to be trained by a large amount of labeled data for accurate diagnosis results. However, in real-case industrial scenarios, the data available is limited since the difficulty of obtaining fault samples. In addition, the monitoring data always come from various working conditions. As a result, data sc...
Article
Adhesive lap joints between composite and metal plates have been widely used in industrial fields including the automotive industry, marine manufacturing and aerospace engineering. Low quality of operation, harsh environment, adhesive aging and other disadvantages may lead to disbonding. To assess the disbond contour at an adhesive interface, this...
Article
Full-text available
Composite materials are progressively employed in many safety-critical structural applications due to their superior properties. Structural health monitoring techniques based on Lamb waves have been utilized to assess the damages of composite structures. Recently, deep learning algorithms are adopted for damage detection and localization. Identifyi...
Article
Adhesively bonded joints between metallic plates and composite laminates are frequently used in various fields including aviation, automobile industry, and marine manufacturing. The edge of adhesive layer is exposed to pollutants in the air, which implies that the joints are inclined to suffer debonding defects along the adhesive bond line. To eval...
Article
Full-text available
Structural health monitoring of long-span bridge has received increasing attention in recent years. In order to achieve accurate monitoring, the integrity of data collection should be guaranteed. Unfortunately, these data inevitably contain a variety of types of anomalies due to sensor faults, harsh environments, and other issues. Identifying anoma...
Article
Existing quantification models using Lamb waves are generally data-driven models, and the model choice can have a significant impact on the quantification results and the probability of detection (POD). This study develops a general method of model averaging and probability of detection estimation for Lamb wave detection. By treating each of the da...
Article
The vibration signals of variable speed rotating machines are non-stationary. Time-frequency analysis (TFA) can effectively analyze non-stationary signals in time-frequency (TF) plane and polynomial chirplet transform (PCT) is one of widely adopted TFA methods. In PCT, a vital step is to approximate the instantaneous frequency (IF) of signals throu...
Article
Rolling bearing is an indispensable part in rotary machinery, and its fault diagnosis and life prediction have been a hot issue in the field of research and engineering. With the development of fault diagnosis technology, researchers pay a growing attention to skidding which is easy to cause incipient bearing failure. Due to the complex structure a...
Article
Full-text available
In this article, a new decomposition theory, feature mode decomposition (FMD), is tailored to the feature extraction of machinery fault. The proposed FMD is essentially for the purpose of decomposing the different modes by the designed adaptive finite impulse response (FIR) filters. Benefitted from the superiority of correlated kurtosis, FMD takes...
Article
Lamb wave minimum variance imaging is a promising method for visual damage identification and localization with a sparse transducer array. Imaging performance of minimum variance is highly dependent on the design accuracy of look-direction to describe amplitude relationship of array reflection signals. Look-direction is the combination of a directi...
Article
Driven by industrial big data and intelligent manufacturing, deep learning approaches have flourished and yielded impressive achievements in the community of machine fault diagnosis. Nevertheless, current diagnosis models trained on a specific dataset seldom work well on other datasets due to the domain discrepancy. Recently, adversarial domain ada...
Article
Full-text available
Lamb wave-based damage identification and localization methods hold the potential for nondestructive evaluation and structural health monitoring. Dispersive and multimodal characteristics lead to complicated Lamb wave signals that are challenging to be analyzed. Deep learning architectures could identify damage-related features effectively. Convolu...
Article
This paper proposes an improved double-dictionary K-singular value decomposition (IDDK-SVD) algorithm for the compound fault diagnosis of rolling element bearings under complex industrial environments. In the framework, a double-dictionary is first designed for respectively identifying and distinguishing compound-fault features. In addition, an ato...
Article
A thorough understanding of the scattering mechanism of Lamb waves at discontinuities is of interest for quantitative evaluation of structural properties and mode control. This study extends the generalized scattering matrix method to investigate the interaction of straight crested Lamb waves with multiple cascaded rectangular notches. Based on the...
Article
Orthotropic steel bridge decks and steel box girders are key structures of long-span bridges. Fatigue cracks often occur in these structures due to coupled factors of initial material flaws and dynamic vehicle loads, which drives the need for automating crack identification for bridge condition monitoring. With the use of unmanned aerial vehicle (U...
Article
The scattered fields of Lamb waves resulting from damage have been extensively studied because they carry rich structural information that allow us to identify and evaluate damage. This paper investigates the interaction of the fundamental symmetric Lamb mode (S0) near the first Lamé point with opening cracks of various heights under the plane stra...
Article
Fault diagnosis is of significance for ensuring the safe and reliable operation of machinery equipment. Due to the heavy noise and interference, it is difficult to detect the fault directly from the measured signal. Hence, signal processing techniques that can achieve feature extraction, signal denoising, and fault identification are the most commo...
Article
Signature extraction of fault impacts is a significant task for rolling bearing diagnosis. A series of blind source and target deconvolution methods respectively represented by minimum entropy deconvolution (MED) and maximum correlated kurtosis deconvolution (MCKD) are proposed to enhance the fault impulses from the complex interference components....
Article
To meet industrial demand, plenty of research works have been dedicated to monitoring the health status of planetary gearboxes. For the same purpose, a new path is explored in this work based on rotating encoder signal (RES) by considering arbitrary speed condition. In this framework, generalized demodulated (GD) is applied on second-order derivati...
Article
The core of structural health monitoring is to provide a real-time monitoring, inspection, and damage detection of structures. As one of the most promising technology to structural health monitoring, the Lamb wave method has attracted interest because it is sensitive to small-scale damage with a long detection range. However, in many real-world str...
Article
The key idea behind demodulation analysis for bearing diagnosis is to determine the fault-induced frequency band and directly detect the potential bearing fault characteristic frequency (FCF) in the demodulated spectrum. Till now, most demodulation methods are based on the optimal selection of only one informative frequency band. However, the unwan...
Article
To realize fault identification of unlabeled data and improve model generalization capability, domain adaptation has been increasingly applied to intelligent fault diagnosis of machinery. Nevertheless, traditional domain adaptation diagnosis models generally constrain different domains to have the same label space, which is not always hold in compl...
Article
Full-text available
Behind the brilliance of the deep diagnosis models, the issue of distribution discrepancy between source training data and target test data is being gradually concerned for catering to more practical and urgent diagnostic requirements. Consequently, advanced domain adaptation algorithms have been introduced to the field of fault diagnosis to addres...
Article
Maximum second-order cyclostationarity blind deconvolution (CYCBD) outperforms other deconvolution methods in retrieving the weak periodic impulses related to bearing incipient faults. However, the main challenge in the practical application of CYCBD is how to set several key parameters appropriately, the uppermost of which is the targeted cyclic f...
Article
Lamb wave spectral methods are one candidate to characterize invisible damages in composite structures. Unfortunately, multiple reflections resulting from geometric boundaries could distort the Lamb wave spectrum, which may cover the important signatures concerning structural integrity. To eliminate spectral interference, a cepstrum based filtering...
Article
Full-text available
Ultrasonic phased array (UPA) provides a powerful tool for nondestructive testing (NDT) of carbon fiber-reinforced plastic (CFRP). By the aid of full matrix capture (FMC) technique, the optimum resolution of anisotropic CFRP inspection could be achieved by the total focusing method (TFM). The directional dependence of ultrasonic velocity is one of...
Article
Blind deconvolution (BD) is a popular tool for vibration analysis, which has been extensively studied to extract useful information from contaminative signals for the diagnosis of rotating machinery. However, due to the disturbance of diverse interferences, good performance of conventional BD methods is usually hard to be guaranteed in some situati...
Article
Owing to carrying rich information about structure flaws, broadband Lamb waves are considered as a promising tool for non-destructive testing. However, since every Lamb wave mode has its own dispersion characteristics, the feature extraction among broadband multimodal Lamb wave is challenging. Time–frequency representation is significantly effectiv...
Article
Deconvolution methods have been proven to be effective tools to extract excitation sources from the noisy measured signal. However, its application is confined by the extraction of incomplete information. To tackle this problem, a new deconvolution method, named period-oriented multi-hierarchy deconvolution (POMHD) is proposed in this paper. Variou...
Article
Domain adaptation technologies have been extensively explored and successfully applied to machine fault diagnosis, aiming to address problems that target data are unlabeled and have a certain distribution bias with source data. Nonetheless, existing fault diagnosis methods mainly explore feature-level alignment strategies to reduce domain discrepan...
Article
The comprehensive assessment of crack angle, length and profile could provide an important reference for the non-destructive evaluation of plate-like structures. In this paper, we aim at fully exploiting information carried by reflections, so that details of the crack could be displayed as much as possible. Firstly, the Lamb wave reflections from a...
Article
Although deep networks based diagnostic methods have been increasingly studied and acquired certain achievements in recent years, most of them suppose that the training and test data share similar probability distribution. The data distribution discrepancy is common and inevitable in practical industry due to the change of working conditions, equip...
Article
Trailing pulses, which are Lamb waves generated at large frequency-thickness (fd) products, act like a list of longitudinal pulses with constant time interval. These longitudinal pulses with short wave length are a promising tool for detection of damage in thick plates. However, the waveform complexity of trailing pulses brings challenges. In this...
Article
Full wavefield processing techniques are promising for damage detection and imaging. However, the high measuring requirements in space are labor-consuming. To improve the imaging quality of wavefields with limited scanning points, 2D interpolation methods are investigated with simulating wavefields. To detect the defects, a damage index called firs...
Article
The paper presents a quantitative Lamb wave detection method for delamination characterization in composite laminates using local wavenumber features. In contrast to the conventional Fourier transform based methods, the improved sparse reconstruction method is efficient and able to evaluate the spatial wavenumbers of Lamb waves with limited measure...
Article
Sparse fault transient extraction is the primary step in rotating machine fault detection. In the present paper, periodical convolutional sparse representation (PCSR) is proposed for reliable separation of fault transients imbedded in raw vibration signals. Specifically, a sparse optimization problem of PCSR is constructed, in which periodical faul...
Article
At present the majority of the research works on machining chatter detection are based on energy level monitoring of certain chatter frequencies which are premised to be invariant. However, chatter frequencies are very complicated with multi-frequency/frequency band, time-variant characteristics and are also affected by many factors in the machinin...
Article
With the rapid development of manufacturing industry, machine fault diagnosis has become increasingly significant to ensure safe equipment operation and production. Consequently, multifarious approaches have been explored and developed in the past years, of which intelligent algorithms develop particularly rapidly. Convolutional neural network (CNN...
Chapter
This paper proposes a systematic framework for the fault detection and condition monitoring of planetary gearbox using internal encoder signal rather than traditional external vibration signal. In this work, the raw encoder signal is firstly converted into instantaneous angular speed signal through difference method. Then comb filtering is applied...
Chapter
Deep neural networks based intelligent diagnosis methods are able to learn powerful features for accurate fault classification, however they cannot always generalize well across changes in data distributions. To address this issue, a novel residual domain adaptation network is proposed for transfer diagnosis of machinery in this paper. In the propo...
Article
Due to the harsh operating condition and persistent heavy load, planetary gearboxes as the key transmission parts are prone to damage. With lower cost and better accessibility, the built-in encoder signal has been considered an alternative tool for health state monitoring of gearboxes in recent researches. However, how to extract the feature signat...
Article
Rolling bearing skidding can seriously affect the service life and aggravate the performance degradation process of rolling bearings. Once skidding occurs under variable speed and load, the movement of rolling elements relative to the inner and outer rings is no longer strictly pure rolling. As a result, the speed of rolling bearing cage becomes mo...
Article
Deep neural networks have been widely studied in the field of mechanical fault diagnosis with the rapidity of intelligent manufacturing and industrial big data, however, attractive performance gains usually come from a premise that source training data and target test data have the same distribution. Unfortunately, this assumption is generally unte...
Article
Envelope demodulation based on vibration data is widely used for the fault detection of rolling element bearing, which yet largely relies on the high signal to noise ratio of signal. In practical scenarios, because of the existence of various interfering components, it is necessary to estimate the fault-sensitive frequency band for feature enhancem...
Article
The accurate information of Lamb wave packets, such as amplitude, time of flight, and waveform, are essential for damage detection and evaluation. Due to the dispersive, multimodal, and attenuative characteristics of Lamb waves propagating in viscoelastic media, the desired mode component is difficult to be extracted from response signals. To addre...
Article
Lamb wave techniques have been widely used for structural health monitoring (SHM) and nondestructive testing (NDT). To deal with dispersive and multimodal problems of Lamb wave signals, many signal processing methods have been developed. A spatially distributed array of piezoelectric transducers is generally adopted for both transmission and recept...
Article
Full-text available
Error separation (ES) techniques can eliminate the systematic error caused by the rotary table, and thus, overcome the accuracy limit of state-of-the-art roundness instruments. However, up to now, no rigorous and effective approaches are available for evaluating the measurement uncertainty in ES techniques. To achieve the highest precision of ES te...
Article
This paper presents a baseline-free damage detection method which leverages the multipath reflected Lamb waves for structural prognosis. From the viewpoint of ray tracing, the reflection of a propagating wave at a free edge is considered as a virtual transducer sitting at the mirrored location of the actual one, injecting excitation into the struct...
Preprint
Full-text available
With the rapid development of manufacturing industry, machine fault diagnosis has become increasingly significant to ensure safe equipment operation and production. Consequently, multifarious approaches have been explored and developed in the past years, of which intelligent algorithms develop particularly rapidly. Convolutional neural network, as...
Article
Full-text available
This article presents a multipath Lamb wave imaging method that leverages the extra reflections present in the recorded ultrasonic waveforms for structural prognosis. Under the ray acoustic approximation, an edge behaves like a mirror, which changes the propagation path of a wave and provides more views of the damage than can be obtained from direc...
Article
The data distribution shift is inevitable in practical fault diagnosis due to internal and outside changes of equipment. These obstacles will lead to performance degrade or even failure of diagnostic models. In light of these problems, a novel unsupervised intelligent diagnostic framework named Adversarial Adaptation network based on Classifier Dis...
Article
Full-text available
Grinding burn monitoring is of great importance to guarantee the surface integrity of the workpiece. Existing methods monitor overall signal variation. However, the signals produced by metal burn are always weak. Therefore, the detection rate of grinding burn still needs to be improved. The paper presents a novel grinding burn detection method basi...
Article
Deep networks based mechanical intelligent diagnosis has been recently attracting considerable attentions with the development of Industry 4.0. Unfortunately, a more practical diagnostic scenario, i.e. unsupervised partial transfer diagnosis (UPTD), has not yet been well addressed. In view of this, a novel unsupervised intelligent diagnosis framewo...
Article
Intelligent Mechatronic Systems (IMS), such as intelligent vehicles/robots/transportation systems, are generally complex due to the integrations of artificial intelligence and multidisciplinary features taken from mechanical engineering, electrical engineering, and control engineering. This integrated complexity leads to challenges in reliability m...
Article
Due to severe working condition, unexpected failures in wind turbine gearbox become rather frequent and may lead to long downtime or even catastrophic casualties. However, traditional diagnosis techniques based on vibration, acoustic emission etc. still face some problems when they are used for failure identification of wind turbine gearbox. Encode...
Article
This paper proposes a transient feature extraction algorithm of encoder signal for the condition assessment of planetary gearboxes under variable speed condition. In the proposed method, local polynomial fitting and sparsity based algorithm (LSA) is first constructed to extract time domain transient features from raw encoder signal and then order t...
Article
Full-text available
Encoder signal as the built-in information is always used for the speed and motion control. Meanwhile, it has remarkable superiority in the fault diagnosis of gearbox compared with the popular vibration signal. Traditional decomposition method, such as EMD, gradually loses competitiveness with the increase of the complexity of the encoder signal. T...
Article
This paper proposes a novel three-stage condition assessment scheme of rotating machinery using internal encoder data rather than traditional external vibration data. In this work, periodical group sparse derivatives (PGSD) based signal denoising method is proposed to suppress the background noise, which incorporates the periodical group sparse der...
Article
Full-text available
Time of flight and amplitude attenuation are commonly used features for corrosion detection in Lamb wave testing, but the sensitivity is limited by their individual application scenarios. The mode cutoff of Lamb waves is available and sensitive to determine and describe corrosion patches. In this paper, an approach is proposed by detecting envelope...
Article
The method based on Lamb wave shows great potential for structural health monitoring (SHM) and nondestructive testing (NDT). Damage index (DI) is a series of features extracted from Lamb wave signal that can be linked with damage, which can serve as an indicator to depict the damage. Conventional DIs including time-of-flight, amplitude change and s...
Article
K-singular value decomposition (K-SVD), as an extension of sparse coding, has attracted great attention for fault feature extraction of rolling element bearings (REBs) in recent years. However, the performance of original K-SVD algorithm is flawed since its atoms in the dictionary are invariably updated according to the principle component, which r...
Article
Since multicomponent modulation and complicated interference simultaneously exist in the vibration signals caused by the bearing compound fault, the fault feature becomes rather weak and is hard to be extracted. Therefore, the diagnosis of bearing compound fault is always considered as the bottle neck issue of machinery condition monitoring. The de...
Article
Misalignment is one of the commonly encountered faults that generate excessive rotor vibration. The diversity of its characteristic frequency brings great trouble for fault diagnosis. Especially when misalignment-induced vibration manifests it as only synchronous (1x) component, properly diagnosing this fault becomes more difficult, since other fau...
Article
Full-text available
Bearing faults are the main contributors to the failure of motors. Periodic harmonic components from the motor rotating and random impulses caused by the electromagnetic interference heavily trouble vibration-based resonance demodulation techniques. This paper presents a method that accurately identifies the optimal frequency band even with complic...
Article
In recent years, artificial intelligent techniques have been extensively explored in the field of health monitoring and fault diagnosis due to their powerful capabilities. In this paper, we propose a deep coupled dense convolutional network (CDCN) with complementary data to integrate information fusion, feature extraction and fault classification t...
Article
The application prospect of a permanently installed structural health monitoring (SHM) system for composite structural prognosis may be determined by the reliability, cost and the added weight of the system. In this paper, we aim at exploiting information encoded in multipath scattering Lamb wave signals, so that damage imaging could be achieved wi...
Article
Full-text available
With the rapid development of electronic technology, the use of portable and wearable electronics hasbeen widely. In order to eliminate the dependency of low-power electronic devices on batteries and the associated requirement of periodic replacement, researchers have begun investigating methods of generating energy from ambient sources. An airflow...
Article
Rolling element bearings (REBs) play an essential role in modern machinery and their condition monitoring is significant in predictive maintenance. Due to the harsh operating conditions, multi-fault may co-exist in one bearing and vibration signal always exhibits low signal-to-noise ratio (SNR), which causes difficulties in detecting fault. In the...
Article
Most Lamb wave methods utilize transducer array for damage detection and localization. Simultaneous excitation of multiple transmitters is a strategy for efficient data acquisition, in which matched filtering is generally applied for signal separation from different sources. However, the signal-to-noise ratio (SNR) and subsequent damage imaging per...
Article
Full-text available
In the era of big data, a huge amount of monitoring and manufacturing data are generated every hour. As these data are typically measured from different machines and under different working regimes, prior information and domain knowledge are highly required in order to properly analyze and utilize these data. In view of this limitation, a data-driv...
Article
Parameter-adaptive variational mode decomposition (VMD) has attenuated the dominant effect of prior parameters, especially the predefined mode number and balancing parameter, which heavily trouble the traditional VMD. However, parameter-adaptive VMD still encounters some problems when it is applied to the data from industry applications. On one han...
Article
Ultrasonic detection is one of the most commonly used methods in nondestructive testing. Trailing pulses that can be observed in plates and cylindrical rods are a list of longitudinal ultrasonic waves. However, the complexity of trailing pulses brings challenges for ultrasonic–based nondestructive testing. In this paper, a trailing pulses self-focu...