Search | Engineering

订阅投稿

首页工程期刊工程焦点工程成就工程前沿关于我们 English

资源类型

期刊论文 536

会议视频 23

年份

2023 69

2022 56

2021 54

2020 40

2019 29

2018 25

2017 17

2016 25

2015 19

2014 15

2013 14

2012 18

2011 24

2010 18

2009 16

2008 23

2007 31

2006 17

2005 7

2004 5

展开︾

关键词

机理 9

故障诊断 6

能源 4

卫星 3

故障 3

2021全球工程前沿 2

DX桩 2

Maradbcm算法 2

作用机制 2

创新 2

动力学 2

医学教育 2

原子力显微镜 2

双库协同机制 2

工程前沿 2

智能制造 2

木质素 2

机制 2

汶川地震 2

展开︾

检索范围：

排序：展示方式：

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

HTML PDF 收藏

煤矿开采动静载叠加诱发断层冲击地压机理 Article

蔡武, 窦林名, 司光耀, 胡亚伟

《工程（英文）》 2021年第7卷第5期页码 687-700 doi: 10.1016/j.eng.2020.03.017

摘要：

断层作为煤层采掘过程中普遍存在的一种地质构造，其独特不连续结构控制着煤岩的变形、破坏与力学性质，该结构与煤层采掘活动之间的相互作用是断层活化及其诱发冲击地压的关键。本文通过调研总结煤层采掘活动与断层赋存状态之间的概念模型，提出了采动应力主导和矿震动载主导两种断层活化类型的力学机制及其动静载叠加诱冲机理；其次，结合物理实验、数值模拟和现场微震监测结果验证了模型与机理的合理性；在此基础上，针对性地探讨了断层冲击地压监测与防治的方法和策略。研究结果表明，断层冲击地压是由断层煤柱高静载与断层活化动载叠加诱发，其中，断层煤柱高静载是断层与顶板结构双重作用导致，断层活化动载是由采动应力主导型局部解锁活化、等效劈裂破坏和矿震动载主导型超低摩擦效应组成。研究结果对于系统理解断层冲击地压机理、监测与防治具有重要指导意义。

关键词：冲击地压断层活化采动应力矿震动载应力断层煤柱

HTML PDF 收藏

连续生产线设备故障诊断专家系统的动态模糊推理机制的研究

谈理,刘谨,梅丽婷

《中国工程科学》 2005年第7卷第6期页码 57-60

摘要：

针对连续生产线设备故障诊断专家系统的研制，阐述了在建立模糊推理机过程中引入具有实时性的动态模糊关系的思想，并构造一个随无故障时间变化的动态隶属度函数来实现。

关键词：故障诊断专家系统模糊推理

HTML PDF 收藏

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

HTML PDF 收藏

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

HTML PDF 收藏

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

HTML PDF 收藏

大跨度混凝土连续梁桥的病害成因分析

林帆,王萍,肖开军,李伟

《中国工程科学》 2010年第12卷第4期页码 78-81

摘要：

自20世纪80年代以来，我国建成了大量大跨度预应力混凝土连续体系桥梁，取得了辉煌成就，但随着桥梁建设数量与使用年限的增加，该类桥梁在施工与运营期陆续出现一些具有共性的病害：跨中挠度过大、箱梁开裂与跨中合龙段底板剥离等，而且有些病害已经导致桥梁重大的安全事故与经济损失。文章对国内数十座桥梁出现的病害随时间变化发展的趋势、在空间上分布的形态等进行了分析。根据现有的理论研究成果，分析了腹板斜裂缝、底板纵向裂缝、合龙段底板分层等病害的形成机理，提出了控制裂缝等病害发生的措施，并说明了这些控制措施在泰州大桥预应力桥

关键词：预应力混凝土连续体系桥梁病害控制

HTML PDF 收藏

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

HTML PDF 收藏

电磁防护仿生原理与故障自修复机制研究

原亮,满梦华,常小龙

《中国工程科学》 2014年第16卷第3期页码 76-85

摘要：

借鉴生物神经网络信息传递的抗扰特点，开展了电磁干扰环境下通过仿生方式进行的电子电路抗扰与防护研究，以便采用新原理、新技术和新方法解决传统的电磁干扰防护手段不足的问题。通过基于布尔模型的复杂生物网络拓扑建模与简并特征分析，证明了网络简并性与功能鲁棒性之间的相互作用关系，以解决抗扰原理问题；通过构建基于神经元电路和可塑突触电路的神经网络电路模型，分析了突触权重的分布对于网络自修复特性的影响，以解决防护机制问题。进而，为电磁防护仿生原理及自修复机制的深入研究形成了一定的理论基础并完成了前期实践。

关键词：仿生学电磁仿生电磁防护简并性可塑性鲁棒性

HTML PDF 收藏

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

HTML PDF 收藏

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

HTML PDF 收藏

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

HTML PDF 收藏

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

HTML PDF 收藏

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

HTML PDF 收藏

Intelligent fault diagnostic system based on RBR for the gearbox of rolling mills

Lixin GAO, Lijuan WU, Yan WANG, Houpei WEI, Hui YE

《机械工程前沿（英文）》 2010年第5卷第4期页码 483-490 doi: 10.1007/s11465-010-0118-6

摘要： This paper presents an intelligent system that is necessary for diagnostic accuracy and efficiency in the iron and steel industry. A rule-based reseaning (RBR) intelligent diagnostic system has been developed based on many successful diagnostic applications. It can solve the difficulty in knowledge acquisition and has more precision. Its application results prove that the usability of the system is good and it will increasingly attain perfection.

关键词： rule-based reasoning fault diagnosis intelligent system gear box