搜索资源列表
PHM
- 故障诊断和健康预测的PHM参数和建模方法技术研究-Fault diagnosis and prediction of PHM health parameters and modeling technology research
Artificial-Neural-Networks-for-the-Modelling-and-
- an excellent book providing an introduction to artificial neural network for modeling and fault diagnosis
bpshenjingwangluoxiugaihou
- 基于BP神经网络的发电机故障诊断程序，较全面，适合初学者和中级学员。-Generator based on BP neural network fault diagnosis procedures, more comprehensive, suitable for beginners and intermediate learners.
A-new-wind-turbine-fault-diagnosis
- 局部均值分解和经验分解LMD和EMD的结果介绍和分析，比较有用-lmd emd
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- 滚动轴承是各种机电设备中的重要部件，其主要特点是其寿命的随机性较大，且它的好坏直接影响到设备的正常运行。因而掌握轴承运行的工作状态以及故障的形成和发展是目前机械故障诊断领域中研究的重要内容之一。利用轴承的随机振动信号对其工作状态进行诊断是目前最常用的方法-Rolling is a variety of mechanical and electrical equipment is an important component, its main feature is its randomness
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- 基于循环统计理论, 对循环平稳信号进行处理, 主要研究了信号的二阶循环统计特性, 即循环自相关函数和循环谱密度, 指出循环自相关函数不为零的循环频率对应着信号中的某些故障, 并 可以对调幅信号进行解调. 通过循环频率扫描方法提取的调制源分布在循环频率域的低频段, 其结 果可用循环频率-频率- 循环谱密度的三维图表示. 用仿真信号对该方法进行验证, 并应用于滚动轴承的内、外圈及滚动体的故障诊断, 可以有效地分离出所对应的故障特征频率.-Statistical theory based on
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- 滚动轴承故障诊断是机械故障检测中一个重要方面。使用小波包分析和包络分析相结合的方法提取轴承微弱振动信号, 克服了传统包络分析方法易丢失信号有效成分的缺点。包络信号的细化谱较好体现了轴承故障信息。-Bearing Fault Diagnosis of mechanical fault detection in an important aspect. The use of wavelet packet analysis and envelope analysis method of combini
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- 齿轮箱是机械传动链中的关键且故障多发部件, 传统齿轮箱诊断方法难以对运行在变工况 下的齿轮箱故障进行准确的检测和有效识别。综述了国内外对于变工况齿轮箱故障诊断技术、研究现状及进展, 并简要讨论了变工况齿轮箱故障诊断方法的应用现状及可能的发展趋势。-Gearbox mechanical transmission chain is critical and failure-prone components, the traditional methods are difficult to dia
lijisuan
- 这是几篇关于粒计算在故障诊断中的应用，对学习粒计算的应用很有帮助。-This is a few on Granular Computing in Fault Diagnosis of learning the application of granular computing helpful.
Thermal-image-enhancement
- 热图像增强使用二维经验模式分解结合相关向量机的旋转机械故障诊断 -Thermal image enhancement using bi-dimensional empirical mode decomposition in combination with relevance vector machine for rotating machinery fault diagnosis
moving-robot
- 基于灰色关联理论的移动机械人故障诊断方法研究-Based on Grey Relational Theory mobile robot fault diagnosis method
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- 滚动轴承振动信号容易受 到随机噪声 的污染, 如 何去噪 成为滚动轴承故障诊断的关键问题之一。而传统的消噪方法可能会将信号中一些能量小的有用信号当作噪声消除, 本 文即提出 一种改进 的小波消噪方法-Rolling bearing vibration signals are easily influenced by the random noise pollution, such as any denoising become one of the key problems of rolling
9656565
- 一种新的基于遗传算法的模糊C-均值聚类的RBF神经网络-A New RBF Neural Network with GA-based Fuzzy C-Means Clustering Algorithm for SINS Fault Diagnosis
Wavelet-Networks-
- 基于小波网络及油中溶解气体分析的电力变压器故障诊断方法-Based on Wavelet Networks and Dissolved Gas Analysis of Power Transformer Fault Diagnosis
1-s2.0-S0142061512003043-main
- Power transformer fault diagnosis
1-s2.0-S0142061512003869-main
- Power transformer fault diagnosis
1-s2.0-S0378779611001878-main
- Power transformer fault diagnosis
1-s2.0-S0378779611002288-main
- Power transformer fault diagnosis
1-s2.0-S0957417410015162-main
- Power transformer fault diagnosis
71837744
- Power transformer fault diagnosis