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A multi-sensor relation model for recognizing and localizing faults of machines based on network analysis

《机械工程前沿（英文）》 2023年 第18卷 第2期 doi: 10.1007/s11465-022-0736-9

摘要： Recently, advanced sensing techniques ensure a large number of multivariate sensing data for intelligent fault diagnosis of machines. Given the advantage of obtaining accurate diagnosis results, multi-sensor fusion has long been studied in the fault diagnosis field. However, existing studies suffer from two weaknesses. First, the relations of multiple sensors are either neglected or calculated only to improve the diagnostic accuracy of fault types. Second, the localization for multi-source faults is seldom investigated, although locating the anomaly variable over multivariate sensing data for certain types of faults is desirable. This article attempts to overcome the above weaknesses by proposing a global method to recognize fault types and localize fault sources with the help of multi-sensor relations (MSRs). First, an MSR model is developed to learn MSRs automatically and further obtain fault recognition results. Second, centrality measures are employed to analyze the MSR graphs learned by the MSR model, and fault sources are therefore determined. The proposed method is demonstrated by experiments on an induction motor and a centrifugal pump. Results show the proposed method’s validity in diagnosing fault types and sources.

关键词： fault recognition     fault localization     multi-sensor relations     network analysis     graph neural network    

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Robotized machining of big work pieces: Localization of supporting heads

Wojciech SZYNKIEWICZ, Teresa ZIELIŃSKA, Włodzimierz KASPRZAK

《机械工程前沿（英文）》 2010年 第5卷 第4期   页码 357-369 doi: 10.1007/s11465-010-0103-0

摘要： A planner for a self adaptable and reconfigurable fixture system is proposed. The system is composed of mobile support agents that support thin sheet metal parts to minimize part dimensional deformation during drilling and milling operations. Compliant sheet metal parts are widely used in various manufacturing processes including automotive and aerospace industries. The main role of the planner is to generate an admissible plan of relocation of the mobile agents. It has to find the admissible locations for the supporting heads that provide continuous support in close proximity to the tool and trajectories of the mobile bases characterized by very high speeds during the relocation phases.

关键词： fixture     robot     milling     drilling    

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Optimal localization of complex surfaces in CAD-based inspection

XU Jinting, LIU Weijun, SUN Yuwen

《机械工程前沿（英文）》 2008年 第3卷 第4期   页码 426-433 doi: 10.1007/s11465-008-0068-4

摘要： Complex surface inspection requires the optimal localization of the measured surface related to the design surface so that the two surfaces can be compared in a common coordinate frame. This paper presents a new technique for solving the localization problem. The basic approach consists of two steps: 1) rough localization of the measured points to the design surface based on curvature features, which can produce a good initial estimate for the optimal localization; 2) fine localization based on the least-square principle so that the deviation between the measured surface and the design surface is minimized. To efficiently compute the closest points on the design surface of the measured points, a novel method is proposed. Since this approach does not involve an iterative process of solving non-linear equations for the closest points, it is more convenient and robust. The typical complex surface is used to test the developed algorithm. Analysis and comparison of experimental results demonstrate the validity and applicability of the algorithm.

关键词： deviation     comparison     non-linear     localization     inspection    

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Strain localization analyses of idealized sands in biaxial tests by distinct element method

Mingjing JIANG, Hehua ZHU, Xiumei LI,

《结构与土木工程前沿（英文）》 2010年 第4卷 第2期   页码 208-222 doi: 10.1007/s11709-010-0025-2

摘要： This paper presents a numerical investigation on the strain localization of an idealized sand in biaxial compression tests using the distinct element method (DEM). In addition to the dilatancy and material frictional angle, the principal stress field, and distributions of void ratio, particle velocity, and the averaged pure rotation rate (APR) in the DEM specimen are examined to illustrate the link between microscopic and macroscopic variables in the case of strain localization. The study shows that strain localization of the granular material in the tests proceeds with localizations of void ratio, strain and APR, and distortions of stress field and force chains. In addition, both thickness and inclination of the shear band change with the increasing of axial strain, with the former valued around 10–14 times of mean grain diameter and the later overall described by the Mohr-Coulomb theory.

关键词： idealized sand     strain localization     numerical analyses     distinct element method (DEM)    

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Three-dimensional finite difference analysis of shallow sprayed concrete tunnels crossing a reverse faultor a normal fault: A parametric study

Masoud RANJBARNIA, Milad ZAHERI, Daniel DIAS

《结构与土木工程前沿（英文）》 2020年 第14卷 第4期   页码 998-1011 doi: 10.1007/s11709-020-0621-8

摘要： Urban tunnels crossing faults are always at the risk of severe damages. In this paper, the effects of a reverse and a normal fault movement on a transversely crossing shallow shotcreted tunnel are investigated by 3D finite difference analysis. After verifying the accuracy of the numerical simulation predictions with the centrifuge physical model results, a parametric study is then conducted. That is, the effects of various parameters such as the sprayed concrete thickness, the geo-mechanical properties of soil, the tunnel depth, and the fault plane dip angle are studied on the displacements of the ground surface and the tunnel structure, and on the plastic strains of the soil mass around tunnel. The results of each case of reverse and normal faulting are independently discussed and then compared with each other. It is obtained that deeper tunnels show greater displacements for both types of faulting.

关键词： urban tunnel     sprayed concrete     reverse fault     normal fault     finite difference analysis    

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Basic research on machinery fault diagnostics: Past, present, and future trends

Xuefeng CHEN, Shibin WANG, Baijie QIAO, Qiang CHEN

《机械工程前沿（英文）》 2018年 第13卷 第2期   页码 264-291 doi: 10.1007/s11465-018-0472-3

摘要：

Machinery fault diagnosis has progressed over the past decades with the evolution of machineries in terms of complexity and scale. High-value machineries require condition monitoring and fault diagnosis to guarantee their designed functions and performance throughout their lifetime. Research on machinery Fault diagnostics has grown rapidly in recent years. This paper attempts to summarize and review the recent R&D trends in the basic research field of machinery fault diagnosis in terms of four main aspects: Fault mechanism, sensor technique and signal acquisition, signal processing, and intelligent diagnostics. The review discusses the special contributions of Chinese scholars to machinery fault diagnostics. On the basis of the review of basic theory of machinery fault diagnosis and its practical applications in engineering, the paper concludes with a brief discussion on the future trends and challenges in machinery fault diagnosis.

关键词： fault diagnosis     fault mechanism     feature extraction     signal processing     intelligent diagnostics    

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Lipin3 leads to hypertriglyceridemia and obesity by disrupting the expression and nucleocytoplasmic localization

《医学前沿（英文）》 doi: 10.1007/s11684-023-1003-0

摘要： Lipin proteins including Lipin 1–3 act as transcriptional co-activators and phosphatidic acid phosphohydrolase enzymes, which play crucial roles in lipid metabolism. However, little is known about the function of Lipin3 in triglyceride (TG) metabolism. Here, we identified a novel mutation (NM_001301860: p.1835A>T/p.D612V) of Lipin3 in a large family with hypertriglyceridemia (HTG) and obesity through whole-exome sequencing and Sanger sequencing. Functional studies revealed that the novel variant altered the half-life and stability of the Lipin3 protein. Hence, we generated Lipin3 heterozygous knockout (Lipin3-heKO) mice and cultured primary hepatocytes to explore the pathophysiological roles of Lipin3 in TG metabolism. We found that Lipin3-heKO mice exhibited obvious obesity, HTG, and non-alcoholic fatty liver disorder. Mechanistic study demonstrated that the haploinsufficiency of Lipin3 in primary hepatocytes may induce the overexpression and abnormal distribution of Lipin1 in cytosol and nucleoplasm. The increased expression of Lipin1 in cytosol may contribute to TG anabolism, and the decreased Lipin1 in nucleoplasm can reduce PGC1α, further leading to mitochondrial dysfunction and reduced TG catabolism. Our study suggested that Lipin3 was a novel disease-causing gene inducing obesity and HTG. We also established a relationship between Lipin3 and mitochondrial dysfunction.

关键词： Lipin3     Lipin1     hypertriglyceridemia     obesity     mitochondrial dysfunction    

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Machine learning for fault diagnosis of high-speed train traction systems: A review

《工程管理前沿（英文）》 doi: 10.1007/s42524-023-0256-2

摘要： High-speed trains (HSTs) have the advantages of comfort, efficiency, and convenience and have gradually become the mainstream means of transportation. As the operating scale of HSTs continues to increase, ensuring their safety and reliability has become more imperative. As the core component of HST, the reliability of the traction system has a substantially influence on the train. During the long-term operation of HSTs, the core components of the traction system will inevitably experience different degrees of performance degradation and cause various failures, thus threatening the running safety of the train. Therefore, performing fault monitoring and diagnosis on the traction system of the HST is necessary. In recent years, machine learning has been widely used in various pattern recognition tasks and has demonstrated an excellent performance in traction system fault diagnosis. Machine learning has made considerably advancements in traction system fault diagnosis; however, a comprehensive systematic review is still lacking in this field. This paper primarily aims to review the research and application of machine learning in the field of traction system fault diagnosis and assumes the future development blueprint. First, the structure and function of the HST traction system are briefly introduced. Then, the research and application of machine learning in traction system fault diagnosis are comprehensively and systematically reviewed. Finally, the challenges for accurate fault diagnosis under actual operating conditions are revealed, and the future research trends of machine learning in traction systems are discussed.

关键词： high-speed train     traction systems     machine learning     fault diagnosis    

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Acoustic fault signal extraction via the line-defect phononic crystals

《机械工程前沿（英文）》 2022年 第17卷 第1期   页码 10-10 doi: 10.1007/s11465-021-0666-y

摘要： Rotating machine fault signal extraction becomes increasingly important in practical engineering applications. However, fault signals with low signal-to-noise ratios (SNRs) are difficult to extract, especially at the early stage of fault diagnosis. In this paper, 2D line-defect phononic crystals (PCs) consisting of periodic acrylic tubes with slit are proposed for weak signal detection. The defect band, namely, the formed resonance band of line-defect PCs enables the incident acoustic wave at the resonance frequency to be trapped and enhanced at the resonance cavity. The noise can be filtered by the band gap. As a result, fault signals with high SNRs can be obtained for fault feature extraction. The effectiveness of weak harmonic and periodic impulse signal detection via line-defect PCs are investigated in numerical and experimental studies. All the numerical and experimental results indicate that line-defect PCs can be well used for extracting weak harmonic and periodic impulse signals. This work will provide potential for extracting weak signals in many practical engineering applications.

关键词： phononic crystals     line-defect     fault signal extraction     acoustic enhancement    

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Iterative HOEO fusion strategy: a promising tool for enhancing bearing fault feature

《机械工程前沿（英文）》 2023年 第18卷 第1期 doi: 10.1007/s11465-022-0725-z

摘要： As parameter independent yet simple techniques, the energy operator (EO) and its variants have received considerable attention in the field of bearing fault feature detection. However, the performances of these improved EO techniques are subjected to the limited number of EOs, and they cannot reflect the non-linearity of the machinery dynamic systems and affect the noise reduction. As a result, the fault-related transients strengthened by these improved EO techniques are still subject to contamination of strong noises. To address these issues, this paper presents a novel EO fusion strategy for enhancing the bearing fault feature nonlinearly and effectively. Specifically, the proposed strategy is conducted through the following three steps. First, a multi-dimensional information matrix (MDIM) is constructed by performing the higher order energy operator (HOEO) on the analysis signal iteratively. MDIM is regarded as the fusion source of the proposed strategy with the properties of improving the signal-to-interference ratio and suppressing the noise in the low-frequency region. Second, an enhanced manifold learning algorithm is performed on the normalized MDIM to extract the intrinsic manifolds correlated with the fault-related impulses. Third, the intrinsic manifolds are weighted to recover the fault-related transients. Simulation studies and experimental verifications confirm that the proposed strategy is more effective for enhancing the bearing fault feature than the existing methods, including HOEOs, the weighting HOEO fusion, the fast Kurtogram, and the empirical mode decomposition.

关键词： higher order energy operator     fault diagnosis     manifold learning     rolling element bearing     information fusion    

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Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical fault

《机械工程前沿（英文）》 2021年 第16卷 第4期   页码 814-828 doi: 10.1007/s11465-021-0650-6

摘要： The fault diagnosis of bearings is crucial in ensuring the reliability of rotating machinery. Deep neural networks have provided unprecedented opportunities to condition monitoring from a new perspective due to the powerful ability in learning fault-related knowledge. However, the inexplicability and low generalization ability of fault diagnosis models still bar them from the application. To address this issue, this paper explores a decision-tree-structured neural network, that is, the deep convolutional tree-inspired network (DCTN), for the hierarchical fault diagnosis of bearings. The proposed model effectively integrates the advantages of convolutional neural network (CNN) and decision tree methods by rebuilding the output decision layer of CNN according to the hierarchical structural characteristics of the decision tree, which is by no means a simple combination of the two models. The proposed DCTN model has unique advantages in 1) the hierarchical structure that can support more accuracy and comprehensive fault diagnosis, 2) the better interpretability of the model output with hierarchical decision making, and 3) more powerful generalization capabilities for the samples across fault severities. The multiclass fault diagnosis case and cross-severity fault diagnosis case are executed on a multicondition aeronautical bearing test rig. Experimental results can fully demonstrate the feasibility and superiority of the proposed method.

关键词： bearing     cross-severity fault diagnosis     hierarchical fault diagnosis     convolutional neural network     decision tree    

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A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

《机械工程前沿（英文）》 2022年 第17卷 第2期 doi: 10.1007/s11465-022-0673-7

摘要： Convolutional neural network (CNN) has achieved remarkable applications in fault diagnosis. However, the tuning aiming at obtaining the well-trained CNN model is mainly manual search. Tuning requires considerable experiences on the knowledge on CNN training and fault diagnosis, and is always time consuming and labor intensive, making the automatic hyper parameter optimization (HPO) of CNN models essential. To solve this problem, this paper proposes a novel automatic CNN (ACNN) for fault diagnosis, which can automatically tune its three key hyper parameters, namely, learning rate, batch size, and L2-regulation. First, a new deep reinforcement learning (DRL) is developed, and it constructs an agent aiming at controlling these three hyper parameters along with the training of CNN models online. Second, a new structure of DRL is designed by combining deep deterministic policy gradient and long short-term memory, which takes the training loss of CNN models as its input and can output the adjustment on these three hyper parameters. Third, a new training method for ACNN is designed to enhance its stability. Two famous bearing datasets are selected to evaluate the performance of ACNN. It is compared with four commonly used HPO methods, namely, random search, Bayesian optimization, tree Parzen estimator, and sequential model-based algorithm configuration. ACNN is also compared with other published machine learning (ML) and deep learning (DL) methods. The results show that ACNN outperforms these HPO and ML/DL methods, validating its potential in fault diagnosis.

关键词： deep reinforcement learning     hyper parameter optimization     convolutional neural network     fault diagnosis    

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Gear fault diagnosis using gear meshing stiffness identified by gearbox housing vibration signals

《机械工程前沿（英文）》 2022年 第17卷 第4期 doi: 10.1007/s11465-022-0713-3

摘要： Gearbox fault diagnosis based on vibration sensing has drawn much attention for a long time. For highly integrated complicated mechanical systems, the intercoupling of structure transfer paths results in a great reduction or even change of signal characteristics during the process of original vibration transmission. Therefore, using gearbox housing vibration signal to identify gear meshing excitation signal is of great significance to eliminate the influence of structure transfer paths, but accompanied by huge scientific challenges. This paper establishes an analytical mathematical description of the whole transfer process from gear meshing excitation to housing vibration. The gear meshing stiffness (GMS) identification approach is proposed by using housing vibration signals for two stages of inversion based on the mathematical description. Specifically, the linear system equations of transfer path analysis are first inverted to identify the bearing dynamic forces. Then the dynamic differential equations are inverted to identify the GMS. Numerical simulation and experimental results demonstrate the proposed method can realize gear fault diagnosis better than the original housing vibration signal and has the potential to be generalized to other speeds and loads. Some interesting properties are discovered in the identified GMS spectra, and the results also validate the rationality of using meshing stiffness to describe the actual gear meshing process. The identified GMS has a clear physical meaning and is thus very useful for fault diagnosis of the complicated equipment.

关键词： gearbox fault diagnosis     meshing stiffness     identification     transfer path     signal processing    

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Finite element simulation for elastic dislocation of the North-Tehran fault: The effects of geologic

Pooya ZAKIAN; Hossein ASADI HAYEH

《结构与土木工程前沿（英文）》 2022年 第16卷 第4期   页码 533-549 doi: 10.1007/s11709-022-0802-8

摘要： The present study uses the finite element method for simulating the crustal deformation due to the dislocation of a segment of the North-Tehran fault located in the Karaj metropolis region. In this regard, a geological map of Karaj that includes the fault segment is utilized in order to create the geometry of finite element model. First, finite element analysis of homogeneous counterpart of the fault’s domain with two different sections was performed, and the results were compared to those of Okada’s analytical solutions. The fault was modeled with the existing heterogeneity of the domain having been considered. The influences of both uniform and non-uniform slip distributions were investigated. Furthermore, three levels of simplification for geometric creation of geological layers’ boundaries were defined in order to evaluate the effects of the geometric complexity of the geological layering on the displacement responses obtained with the finite element simulations. In addition to the assessment of slip distribution, layering complexity and heterogeneity, the results demonstrate both the capability and usefulness of the proposed models in the dislocation analysis for the Karaj segment of North-Tehran fault.

关键词： finite element method     fault dislocation     slip distribution     the North-Tehran fault     heterogeneity     geological layering    

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Centrifuge experiments for shallow tunnels at active reverse fault intersection

Mehdi SABAGH, Abbas GHALANDARZADEH

《结构与土木工程前沿（英文）》 2020年 第14卷 第3期   页码 731-745 doi: 10.1007/s11709-020-0614-7

摘要： Tunnels extend in large stretches with continuous lengths of up to hundreds of kilometers which are vulnerable to faulting in earthquake-prone areas. Assessing the interaction of soil and tunnel at an intersection with an active fault during an earthquake can be a beneficial guideline for tunnel design engineers. Here, a series of 4 centrifuge tests are planned and tested on continuous tunnels. Dip-slip surface faulting in reverse mechanism of 60-degree is modeled by a fault simulator box in a quasi-static manner. Failure mechanism, progression and locations of damages to the tunnels are assessed through a gradual increase in Permanent Ground Displacement (PGD). The ground surface deformations and strains, fault surface trace, fault scarp and the sinkhole caused by fault movement are observed here. These ground surface deformations are major threats to stability, safety and serviceability of the structures. According to the observations, the modeled tunnels are vulnerable to reverse fault rupture and but the functionality loss is not abrupt, and the tunnel will be able to tolerate some fault displacements. By monitoring the progress of damage states by increasing PGD, the fragility curves corresponding to each damage state were plotted and interpreted in related figures.

关键词： reverse fault rupture     continuous tunnel     geotechnical centrifuge     ground surface deformations     fragility curves    

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标题 作者 时间 类型 操作

A multi-sensor relation model for recognizing and localizing faults of machines based on network analysis

期刊论文

Robotized machining of big work pieces: Localization of supporting heads

Wojciech SZYNKIEWICZ, Teresa ZIELIŃSKA, Włodzimierz KASPRZAK

期刊论文

Optimal localization of complex surfaces in CAD-based inspection

XU Jinting, LIU Weijun, SUN Yuwen

期刊论文

Strain localization analyses of idealized sands in biaxial tests by distinct element method

Mingjing JIANG, Hehua ZHU, Xiumei LI,

期刊论文

Three-dimensional finite difference analysis of shallow sprayed concrete tunnels crossing a reverse faultor a normal fault: A parametric study

Masoud RANJBARNIA, Milad ZAHERI, Daniel DIAS

期刊论文

Basic research on machinery fault diagnostics: Past, present, and future trends

Xuefeng CHEN, Shibin WANG, Baijie QIAO, Qiang CHEN

期刊论文

Lipin3 leads to hypertriglyceridemia and obesity by disrupting the expression and nucleocytoplasmic localization

期刊论文

Machine learning for fault diagnosis of high-speed train traction systems: A review

期刊论文

Acoustic fault signal extraction via the line-defect phononic crystals

期刊论文

Iterative HOEO fusion strategy: a promising tool for enhancing bearing fault feature

期刊论文

Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical fault

期刊论文

A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

期刊论文

Gear fault diagnosis using gear meshing stiffness identified by gearbox housing vibration signals

期刊论文

Finite element simulation for elastic dislocation of the North-Tehran fault: The effects of geologic

Pooya ZAKIAN; Hossein ASADI HAYEH

期刊论文

Centrifuge experiments for shallow tunnels at active reverse fault intersection

Mehdi SABAGH, Abbas GHALANDARZADEH

期刊论文