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Intelligent diagnosis methods for plant machinery

Huaqing WANG, Peng CHEN, Shuming WANG,

《机械工程前沿（英文）》 2010年第5卷第1期页码 118-124 doi: 10.1007/s11465-009-0084-z

摘要： This paper reports several intelligent diagnostic approaches based on artificial neural network and fuzzy algorithm for plant machinery, such as the diagnosis method using the wavelet transform, rough sets, and fuzzy neural network; the diagnosis method based on the sequential inference and fuzzy neural network; the diagnosis approach by the possibility theory and certainty factor model; and the diagnosis method on the basis of the adaptive filtering technique and fuzzy neural network. These intelligent diagnostic methods have been successfully applied to condition diagnosis in different types of practical plant machinery.

关键词： intelligent diagnosis neural network fuzzy algorithm adaptive filtering plant machinery

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Efficacy of intelligent diagnosis with a dynamic uncertain causality graph model for rare disorders of

Dongping Ning, Zhan Zhang, Kun Qiu, Lin Lu, Qin Zhang, Yan Zhu, Renzhi Wang

《医学前沿（英文）》 2020年第14卷第4期页码 498-505 doi: 10.1007/s11684-020-0791-8

摘要： Disorders of sex development (DSD) are a group of rare complex clinical syndromes with multiple etiologies. Distinguishing the various causes of DSD is quite difficult in clinical practice, even for senior general physicians because of the similar and atypical clinical manifestations of these conditions. In addition, DSD are difficult to diagnose because most primary doctors receive insufficient training for DSD. Delayed diagnoses and misdiagnoses are common for patients with DSD and lead to poor treatment and prognoses. On the basis of the principles and algorithms of dynamic uncertain causality graph (DUCG), a diagnosis model for DSD was jointly constructed by experts on DSD and engineers of artificial intelligence. “Chaining” inference algorithm and weighted logic operation mechanism were applied to guarantee the accuracy and efficiency of diagnostic reasoning under incomplete situations and uncertain information. Verification was performed using 153 selected clinical cases involving nine common DSD-related diseases and three causes other than DSD as the differential diagnosis. The model had an accuracy of 94.1%, which was significantly higher than that of interns and third-year residents. In conclusion, the DUCG model has broad application prospects as a computer-aided diagnostic tool for DSD-related diseases.

关键词： disorders of sex development (DSD) intelligent diagnosis dynamic uncertain causality graph

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Multi-model ensemble deep learning method for intelligent fault diagnosis with high-dimensional samples

Xin ZHANG, Tao HUANG, Bo WU, Youmin HU, Shuai HUANG, Quan ZHOU, Xi ZHANG

《机械工程前沿（英文）》 2021年第16卷第2期页码 340-352 doi: 10.1007/s11465-021-0629-3

摘要： Deep learning has achieved much success in mechanical intelligent fault diagnosis in recent years. However, many deep learning methods cannot fully extract fault information to recognize mechanical health states when processing high-dimensional samples. Therefore, a multi-model ensemble deep learning method based on deep convolutional neural network (DCNN) is proposed in this study to accomplish fault recognition of high-dimensional samples. First, several 1D DCNN models with different activation functions are trained through dimension reduction learning to obtain different fault features from high-dimensional samples. Second, the obtained features are constructed into 2D images with multiple channels through a conversion method. The integrated 2D feature images can effectively represent the fault characteristic contained in raw high-dimension vibration signals. Lastly, a 2D DCNN model with multi-layer convolution and pooling is used to automatically learn features from the 2D images and identify the fault mode of the mechanical equipment by adopting a softmax classifier. The proposed method, which is validated using the bearing public dataset of Case Western Reserve University, USA and a one-stage reduction gearbox dataset, has high recognition accuracy. Compared with other classical deep learning methods, the proposed fault diagnosis method has considerable improvements.

关键词： fault intelligent diagnosis deep learning deep convolutional neural network high-dimensional samples

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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

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机泵群实时监测网络和故障诊断专家系统

高金吉

《中国工程科学》 2001年第3卷第9期页码 41-47

摘要：

应用现代信息技术和人工智能实施设备诊断工程，逐步实现状态维修和预知维修，是大型流程工业企业降低生产成本的重要途径之一。概要介绍为实现这一目标所开发的机电装备实时监测网络和人工智能诊断技术。简要介绍了基于Ethernet和FDDI开发、应用于石化企业的机、泵群实时监测网络；首次提出了黑灰白集合筛选法，在一次原因分析法和故障机理及其识别特征研究基础上，应用此方法开发的基于黑灰白集合筛选法的机械故障诊断专家系统，用于工程实践取得了满意的结果。

关键词：设备诊断工程实时监测网络人工智能诊断一次原因分析法黑灰白集合筛选法

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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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智能动力装备的全生命周期诊断和服务技术与系统研制

徐光华,梁霖,张庆,景敏卿,温广瑞,高志勇,金颖,李文海

《中国工程科学》 2013年第15卷第1期页码 79-86

摘要：

动力装备作为复杂机电系统具有应用范围广、连续作业、点多线长、危险因素众多的突出特点，针对目前动力装备存在的全生命周期监测诊断技术缺乏、智能化水平不高、服务支持不足的问题，研究开发了智能动力装备的全生命周期监测和服务支持系统。围绕动力装备全生命周期监测诊断和全生命周期性能优化、维修备件服务构建系统平台，研究了系统中的信息采集管理，动态自适应监测，健康状态预示与评估，故障预警和快速智能诊断、转子远程及现场快速动平衡维护以及智能维修决策等关键技术，最后在用户企业构建动力装备产品全生命周期监测与服务支持的示范基地，为客户提供诊断分析、状态评估、全生命周期设备管理、维修决策支持服务。

关键词：动力装备诊断和服务全生命周期

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Laboratory diagnosis for malaria in the elimination phase in China: efforts and challenges

《医学前沿（英文）》 2022年第16卷第1期页码 10-16 doi: 10.1007/s11684-021-0889-7

摘要： Malaria remains a global health challenge, although an increasing number of countries will enter pre-elimination and elimination stages. The prompt and precise diagnosis of symptomatic and asymptomatic carriers of Plasmodium parasites is the key aspect of malaria elimination. Since the launch of the China Malaria Elimination Action Plan in 2010, China has formulated clear goals for malaria diagnosis and has established a network of malaria diagnostic laboratories within medical and health institutions at all levels. Various external quality assessments were implemented, and a national malaria diagnosis reference laboratory network was established to strengthen the quality assurance in malaria diagnosis. Notably, no indigenous malaria cases have been reported since 2017, but the risk of re-establishment of malaria transmission cannot be ignored. This review summarizes the lessons about malaria diagnosis in the elimination phase, primarily including the establishments of laboratory networks and quality control in China, to better improve malaria diagnosis and maintain a malaria-free status. A reference is also provided for countries experiencing malaria elimination.

关键词： malaria laboratory diagnosis quality control malaria elimination China

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Biosensor-based assay of exosome biomarker for early diagnosis of cancer

《医学前沿（英文）》 2022年第16卷第2期页码 157-175 doi: 10.1007/s11684-021-0884-z

摘要： Cancer imposes a severe threat to people’s health and lives, thus pressing a huge medical and economic burden on individuals and communities. Therefore, early diagnosis of cancer is indispensable in the timely prevention and effective treatment for patients. Exosome has recently become an attractive cancer biomarker in noninvasive early diagnosis because of the unique physiology and pathology functions, which reflects remarkable information regarding the cancer microenvironment, and plays an important role in the occurrence and evolution of cancer. Meanwhile, biosensors have gained great attention for the detection of exosomes due to their superior properties, such as convenient operation, real-time readout, high sensitivity, and remarkable specificity, suggesting promising biomedical applications in the early diagnosis of cancer. In this review, the latest advances of biosensors regarding the assay of exosomes were summarized, and the superiorities of exosomes as markers for the early diagnosis of cancer were evaluated. Moreover, the recent challenges and further opportunities of developing effective biosensors for the early diagnosis of cancer were discussed.

关键词： biosensor exosome cancer diagnosis

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Tomographic diagnosis of defects in hydraulic concrete structure

ZHAO Mingjie, XU Xibin

《结构与土木工程前沿（英文）》 2008年第2卷第3期页码 226-232 doi: 10.1007/s11709-008-0027-5

摘要： The ultrasonic tomographic technology is applied to diagnose the defects in hydraulic concrete structure. In order to improve the precision of diagnoses, the wavelet transformation is used in the processing of ultrasonic signals. The influences of water, scale and orientation of defect, processing methods and theoretical model on image resolution are investigated. The experimental results indicate that the result of the tomographic diagnosis of a single defect is sensitive and the boundary can be clearly determined. However, the image resolution of multiple defects is not satisfactory. The water content and scale of a defect may significantly affect the imaging resolution. Defects with the orientation perpendicular to the direction of the diagnosis may have higher precision in diagnosing. The wavelet transformation technology can elevate the imaging resolution. The applied calculation model plays a very important role in improving the accuracy of detection.

关键词： satisfactory processing orientation tomographic diagnosis orientation perpendicular

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

《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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Method for solving the nonlinear inverse problem in gas face seal diagnosis based on surrogate models

《机械工程前沿（英文）》 2022年第17卷第3期 doi: 10.1007/s11465-022-0689-z

摘要： Physical models carry quantitative and explainable expert knowledge. However, they have not been introduced into gas face seal diagnosis tasks because of the unacceptable computational cost of inferring the input fault parameters for the observed output or solving the inverse problem of the physical model. The presented work develops a surrogate-model-assisted method for solving the nonlinear inverse problem in limited physical model evaluations. The method prepares a small initial database on sites generated with a Latin hypercube design and then performs an iterative routine that benefits from the rapidity of the surrogate models and the reliability of the physical model. The method is validated on simulated and experimental cases. Results demonstrate that the method can effectively identify the parameters that induce the abnormal signal output with limited physical model evaluations. The presented work provides a quantitative, explainable, and feasible approach for identifying the cause of gas face seal contact. It is also applicable to mechanical devices that face similar difficulties.

关键词： surrogate model gas face seal fault diagnosis nonlinear dynamics tribology

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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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中国高速列车健康监测与管理：进展及展望

王军,丁荣军

《中国工程科学》 2023年第25卷第2期页码 232-242 doi: 10.15302/J-SSCAE-2023.02.019

摘要：

随着列车运营速度不断提升、配属规模及车辆种类不断扩展，加之受长交路、多物理场耦合等复杂服役环境的影响，高速列车安全保障及经济运维的要求持续提高；高速列车健康监测与管理技术的研究与应用，为中国高速铁路的长距离、大规模、高密度运营提供了关键支撑。本文阐述了健康监测与管理对高速列车的重要价值，回顾了近20年中国高速列车健康监测与管理的发展历程：从安全监控到关键系统健康监测，再到一体化、全寿命周期的运维管理；总结了列车全方位状态监测、精准评估与诊断预测、车辆远程运维服务、智能运维决策支持等方面的重大技术突破。进一步展望了广域全过程适应性、列车数据 / 计算资源一体化管理与应用、基于健康监测与管理的列车设计、车–线–站一体化智能运维等未来发展方向，以期应对中国高速铁路面临的高效安全运维、深度降本降耗等发展挑战，推动中国高速列车技术持续领先。

关键词：高速列车；健康监测与管理；故障诊断预测；智能运维；车–线–站一体化

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Pathogenesis, diagnosis, and treatment of recurrent spontaneous abortion with immune type

Qi-De LIN, Li-Hua QIU

《医学前沿（英文）》 2010年第4卷第3期页码 275-279 doi: 10.1007/s11684-010-0101-y

摘要： Recurrent spontaneous abortion (RSA), defined as three or more consecutive pregnancy losses before 20 weeks of gestation, is difficult to treat in the clinical setting. It affects 1%–5% of women of reproductive age. In the investigations of immunopathogenesis, diagnosis, and treatment of RSA since the late 1980s, it was found that RSA was associated with abnormal maternal local or systemic immune response. The pathogenesis of autoimmune RSA was mainly associated with antiphospholipid antibody (APA), while that of alloimmune RSA was due to the disturbance of maternofetal immunological tolerance. Systemic etiological screening process and diagnosis systems of RSA with immune type were developed, and anticardiolipin (ACL or ACA) + anti-β2-GP1 antibody combining multiple assays for effective diagnosis of RSA with autoimmune type was first established. According to the dynamic monitoring of clinical parameters before and during gestation, low-dose, short-course, and individual immunosuppressive therapy and lymphocyte immunotherapy for RSA with immune type were carried out. The outcomes of the offsprings of patients with RSA were followed up, and the safety and validity of the therapies were confirmed. The research achievement leads to great progress in the diagnosis and treatment of RSA in China.

关键词： spontaneous abortion recurrent autoimmune alloimmune pathogenesis diagnosis immunotherapy