FaultDiagnosis相关论文
This paper proposes an integration fault diagnosis approach of signal-driven method and data-driven method for threeleve......
目前,ZPW-2000型轨道电路故障判别主要依赖人工对数据进行分析,该判别方式效率低、周期较长、对人工依赖程度高.为此,引入了栈式自......
Adaptive decision-level fusion strategy for the fault diagnosis of axial piston pumps using multiple
An axial piston pump is a key component that plays the role of the“heart”in hydraulic systems.The pump failure will le......
Deep learning-based fault diagnostic network of high-speed train secondary suspension systems for im
Fault detection and isolation of high-speed train suspension systems is of critical importance to guarantee train runnin......
Gear box places an important role rolling mill.Its reliability decides the machine operation.Due to the important role,i......
Fault diagnosis is essential for the normal and safe operation of dynamic systems. To improve the spatial resolution amo......
Synchronous chirp mode extraction:A promising tool for fault diagnosis of rolling element bearings u
As critical components in modern aerospace productions,rolling element bearings(REBs)generally work under varying speed ......
本文将详细介绍化工厂电气设备的常见故障，通过专业的研究，精准找出引发化工厂电气设备故障的主要原因，并提出诊断化工厂电气设备故障......
众所周知，矿山开采是非常危险的工作，现在使用机电设备能够很好的替代人工作，从而降低了矿工的伤亡率。但是矿山工作也是非常复杂的，很......
配电变压器是电力系统的重要组成部分,其安全稳定运行至关重要.如果变压器发生故障,必须及时准确地诊断故障类型.为此,论文提出了......
An Intelligent Fault Diagnosis Method of Multi-Scale Deep Feature Fusion Based on Information Entrop
For a single-structure deep learning fault diagnosis model,its disadvantages are an insufficient feature extraction and ......
A Signal Based “W” Structural Elements for Multi-scale Mathematical Morphology Analysis and Applicat
Working conditions of rolling bearings of wind turbine generators are complicated,and their vibration signals often show......
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Fault diagnosis expert system for hydraulic support is studied.The system is achieved by Turbo-prolong Language, it summ......
In order to enhance the fault diagnosis and fault tolerant ability of hybrid power system,improve reliability and stabil......
Based on analysis of action current curves change law when the speed-up turnout is normal and fault, this paper summariz......
故障诊断是未来智能电网可自愈的前提条件.为了进一步提高电网故障诊断系统的效率及准确性,文中提出了一种以数据网格为支撑,分布......
Sparse Kernel Locality Preserving Projection and Its Application in Nonlinear Process Fault Diagnosi
Locality preserving projection (LPP) is a newly emerging fault diagnosis method which can discover local manifold struct......
为了提高变压器故障诊断的正判率,本文提出了基于主成分分析和支持向量机理论的变压器故障诊断模型,该模型首先利用主成分分析法,......
模糊C 均值聚类(FCM)算法对初始化敏感、容易陷入局部最优的缺陷,遗传算法具有较强的全局寻优能力,能够克服该缺陷.将两者相结合对......
Building electrical system is an extremely crucial part in any buildings, its faults are special complex and dispersed.I......
Pneumatic control valve is the most typical actuator in industrial process and its property is closely connected to the ......
The reconstruction method,which defined in the frame of principal component analysis,is a popular and representative met......
This paper explores the Deep Belief Networks (DBNs) in the application of high-speed train vibration signals processing.......
In order to solve the difficulty of recognition in analog circuit fault diagnosis,under the two aspects of analog circui......
To adapt the model in reconfiguring fault diagnosing to dynamic environment and the needs of solving the tasks of comple......
After running for several years, in the maintenance of a tubular turbine, many through bolts melted, and fatigue fractur......
In order to detect a mechanical type of structural failure of the circuit breaker, the characteristics of the circuit br......
Fault diagnosis for spherical roller bearing using discrete wavelet transform and support vector mac
This paper presents a combined discrete wavelet transform (DWT) and supportvector machine (SVM) technique for fault diag......
In this paper,a new intelligent method for the fault diagnosis of the roller bearing is proposed based on wavelet packet......
旋转机械碰摩故障是能够产生严重危害性的常见故障之一.碰摩故障发生时会产生声发射,因此基于声发射信号诊断碰摩故障是当前研究的......
火花故障诊断能够有效地防止火花对电除尘器的损伤,提高除尘效率,节约不必要消耗的电能,并在介质恢复时能够迅速恢复正常供电,是静......
Relay protection fault diagnosis is important for the security operation of power systems.In this paper,several artifici......
Designing of a sliding mode observer (SMO) was finished based on the motion model of underwater vehicles.A flutter decre......
Practice and Reflection on the Construction of Stereoscopic Teaching Material of Automotive Fault Di
Automotive fault diagnosis subject is a both theoretical and practical course with the integrity system and maturity con......
航空发动机整机振动问题是新机研制中的难题之一，而对整机振动进行有效的测量和分析，建立故障模式 和识别系统是解决减振排故问题的......
针对传统方法在机械故障诊断时存在特征提取困难、分类器训练复杂等问题,提出了一种基于S变换和卷积神经网络(CNN)的滚动轴承故障......
利用光纤分布式传感器对长距离输油管线等高危作业区域进行安全监测已被广泛研究和应用,但在使用过程中由于各种原因导致传感光纤......
With the strong battlefield application environment of the next generation fighter, based on the design of distributed v......
Motor faults diagnosis has attracted considerable interest amongresearches during the last decades.There are some th......
This paper introduces a hardware-in-loop test system for power battery management system.In this system,battery cell......
第二代小波变换是一种基于提升原理的时城变换方法,本文介绍了第二代小波变换的原理,并将第二代小波与希尔伯特变换结合应用于一个......
Artificial neural networks (ANN) are an information-processing method of a simulation of the structure for biologica......
Web服务是目前构建分布式应用系统的重要技术途径,对Web服务故障进行明确分类并提出故障分析诊断方法是开展Web服务故障管理的基础......
The federated learning method based on model aggregation can balance data and protect privacy, but the existing methods ......
为了研制开发飞船系统故障诊断知识处理系统［１，２］，本文讨论了对飞船进行诊断问题求解时经常涉及到的几个基本概念——征兆、故障、故障判......
Diagnosability is an important property in the field of fault diagnosis.In this paper,a novel approach based on logical ......
Multi-faults diagnosis of rolling bearings via adaptive customization of flexible analytical wavelet
Multi-faults detection is a challenge for rolling bearings due to the mode mixture and coupling of multiple fault featur......
Sparse signal is a kind of sparse matrices which can carry fault information and simplify the signal at the same time.Th......
