YLⅡ-4000J烟气轮机的振动监测与故障诊断

利用状态监测与故障诊断技术对YLⅡ-4000J型烟气轮机的振动超标问题进行了研究。用CAMD6100动态监测系统对机组的振动进行了测试，并对测试数据、振动频谱和轴心轨迹等进行了全面分析；结合机组的历史状况和结构，找出了故障的原因，提出了相应的改造措施。机组改造后振动有较大幅度的降低，符合国家标准。研究结果为大型旋转机械的状态监测与故障诊断提供了有用的实践经验。图8表2参7     

基于虚拟仪器的水轮机组监测与诊断分析系统

随着水电机组在国家电力工业中的比重和水轮发电机组单机功率的增加,对水电机组的状态监测和故障诊断技术提出了更高的要求.采用虚拟仪器系统作为开发平台设计并组建水轮发电机组监测和故障诊断系统,该系统实现了水轮发电机组振动信号的数据采集、数据处理和分析,并进行故障诊断.     

风力发电机组状态监测系统设计与应用

风力发电机组状态监测系统的设计可以有效降低机组的检修维护费用,保障机组的安全稳定运行。对风力发电机组状态监测和故障诊断技术进行了深入的研究,设计了风力发电机组状态监测系统,并详细介绍了系统的结构与功能。通过系统在大型风力发电场的成功应用,验证了其对风力发电机组状态监测与诊断的有效性。     

水轮发电机组状态监测与故障诊断系统研究

本文设计了水轮发电机组状态监测与故障诊断系统的结构,并针对此结构设计了相应的硬件与软件。该系统可以实时记录机组运行中的振动、摆度等数据,并以图形和表格的形式反映给用户。本系统还包含故障诊断专家系统,系统能根据所测数据及时诊断出机组的故障,并自动生成报告。该系统已在索风营等多个电站投入运行,结果表明该系统能准确反映机组运行情况,对机组故障做出准确的诊断。     

风电机组状态检修的探讨

为了降低检修成本,提出风电机组状态检修。风电机组状态检修的内容包括数据采集、在线监测、故障诊断、故障预测、状态检修决策和实施。提出风电机组状态检修的两种模式：基于风电机组状态监测信号分析与特征提取的故障诊断检修模式;基于风电机组状态监测（含性能检测）及专家系统的智能化故障诊断与决策的检修模式。     

基于VMD-CNN的水电机组故障诊断

为提高水电机组故障诊断精度,减少在振动信号特征选取过程中对专业经验的依赖,提出了一种融合变分模态分解和卷积神经网络的故障诊断方法。首先对水电机组振动信号进行变分模态分解得到若干分量,并利用这些分量构造时间图,然后搭建深度卷积神经网络对时间图进行特征提取和故障识别,建立分量和故障状态的映射关系。以实测水电机组轴向振动信号进行应用检验,并采用多组对比试验,结果表明该方法与其他方法相比故障识别准确率更高。研究成果为水电机组智能故障诊断提供了新思路。     

风电运营维护中的状态监测研究

通过状态监测与故障诊断技术的有效实施,实现基于可靠性的设计改造与运行维护,从而使风电机组提高运行效率,实现优质安全运行。     

机组状态监测与故障诊断系统在紧水滩水电厂的应用

介绍紧水滩水电厂机组状态监测系统的构成，分析振动摆度监测、水力压力脉动监测、水轮机效率监测、水轮机汽蚀监测的技术特点，以及智能故障诊断系统的基本结构。     

灯泡贯流式机组的状态监测与故障 诊断系统设计

灯泡贯流式水力组以其可利用水头资源丰富,机组效率高等优势,广泛应用于我国中、低水头电站领域。但由于其自身结构的独特,时常导致机组在运行过程中出现非正常振动现象,威胁机组的正常运行。从其自身结构特点入手,针对灯泡贯流式机组的常见振动故障,进行测点重新布置,设计并搭建了机组振动监测与故障诊断平台,最后,对黄河河口电站的部分振动故障进行了分析,总结。     

基于特征通流面积分析和级组故障诊断试验的1000 MW汽轮机机组功率恢复研究与工程应用

对某1 000 MW机组出力不足现象进行分析,通过开展故障诊断试验,基于弗留格尔公式对级组特征通流面积进行计算和分析,诊断出机组出力不足的主要原因为汽轮机通流面积减少。机组揭缸检修期间采取喷丸清理、叶片补焊等措施,机组出力得以恢复。通过汽轮机通流部分故障诊断,解决机组出力不足等问题,验证了该方法的准确性和有效性,为机组通流部分的状态监测与故障诊断提供了成功案列。     

Vibration‐based wind turbine planetary gearbox fault diagnosis using spectral averaging

Planetary gearboxes (PGBs) are widely used in the drivetrain of wind turbines. Any PGB failure could lead to a significant breakdown or major loss of a wind turbine. Therefore, PGB fault diagnosis is very important for reducing the downtime and maintenance cost and improving the safety, reliability, and lifespan of wind turbines. The wind energy industry currently utilizes vibratory analysis as a standard method for PGB condition monitoring and fault diagnosis. Among them, the vibration separation is considered as one of the well‐established vibratory analysis techniques. However, the drawbacks of the vibration separation technique as reported in the literature include the following: potential sun gear fault diagnosis limitation, multiple sensors and large data requirement, and vulnerability to external noise. This paper presents a new method using a single vibration sensor for PGB fault diagnosis using spectral averaging. It combines the techniques of enveloping, Welch's spectral averaging, and data mining‐based fault classifiers. Using the presented approach, vibration fault features for wind turbine PGB are extracted as condition indicators for fault diagnosis and condition indicators are used as inputs to fault classifiers for PGB fault diagnosis. The method is validated on a set of seeded localized faults on all gears: sun gear, planetary gear, and ring gear. The results have shown a promising PGB fault diagnosis performance with the presented method. Copyright © 2015 John Wiley & Sons, Ltd.     

汽轮机振动分析及故障诊断

采用状态监测技术和信号分析的手段对汽轮机机组进行了振动分析和故障诊断。通过实验和对现场测试信号的频谱分析，确定了故障的类型和振动异常的主要原因。结合工程实际提出了大修方案。方案实施后，振动大大减小振幅符合国家标准。     

Generator bearing fault diagnosis for wind turbine via empirical wavelet transform using measured vibration signals

The implementation of condition monitoring and fault diagnosis system (CMFDS) on wind turbine is significant to lower the unscheduled breakdown. Generator is one of the most important components in wind turbine, and generator bearing fault identification always draws lots of attention. However, non-stationary vibration signal of weak fault and compound fault with a large amount of background noise makes this task challenging in many cases. So, effective signal processing method is essential in the accurate diagnosis step of CMFDS. As a novel signal processing method, empirical Wavelet Transform (EWT) is used to extract inherent modulation information by decomposing signal into mono-components under an orthogonal basis, which is seen as a powerful tool for mechanical fault diagnosis. Moreover, in order to avoid the inaccurate identification the internal modes caused by the heavy noise, wavelet spatial neighboring coefficient denoising with data-driven threshold is applied to increase Signal to Noise Ratio (SNR) before EWT. The effectiveness of the proposed technique on weak fault and compound fault diagnosis is first validated by two experimental cases. Finally, the proposed method has been applied to identify fault feature of generator bearing on wind turbine in wind farm successfully.     

风力机状态监测与故障诊断技术研究

介绍了风力发电机组的基本构成,对风力机常用状态监测技术及主要测量参数进行了分析研究,并分析了风力机部件的常见故障,研究了部件的故障机理,最后,分析研究了适合于风力机的多种故障诊断方法,对国内外风力机状态监测、诊断技术和系统应用现状进行了概述。研究结果对保证风力发电机组安全运行,减少故障发生率,提高风力发电机组的运行可靠性．实现基于状态维修起到了指导作用。     

基于BP网络的水轮机调节系统状态监测与故障诊断

提出了一种基于参数的水轮机调节系统状态监测和故障诊断方法,并设计了基于BP人工神经网络的实现模型,对该方法中用到的数据处理技术做了深入研究,为水轮机调节系统的状态监测和故障诊断研究提供了一种新思路。     

燃气轮机转子裂纹故障分析与诊断

振动监测和诊断是及时诊断旋转机械故障的手段之一,其中的频谱分析能有效地诊断出转子裂纹。介绍了某燃气轮机转子裂纹的振动现象、处理过程以及故障诊断。转子裂纹的振动有以下特征:裂纹转子具有刚度不对称的特点,运行中存在二倍频振动,在启停机经过转子临界转速一半时存在二倍频共振峰;随着裂纹的发展,二倍频共振峰值有增大趋势;联轴器瓢偏以及低速盘车时转子晃度也会增大。根据转子的振动特征判断该转子存在裂纹且仍在发展,检查结果验证了故障诊断的正确性,为转子裂纹的故障分析与诊断提供参考。     

风电机组故障智能诊断技术及系统研究

风电机组的状态监测和故障诊断是保证机组长期稳定运行和安全发电的关键。基于风电机组的基本结构,介绍了机组的故障类型和机理,论述了实际应用中机组的状态监测和故障诊断技术;基于BP神经网络的原理和优点,深入讨论了如何应用人工神经网络构建风电机组智能诊断系统,并给出了可行的系统设计方案和软件实现流程图。     

An engineering condition indicator for condition monitoring of wind turbine bearings

Condition monitoring (CM) of wind turbine becomes significantly important part of wind farms in order to cut down operation and maintenance costs. The large amount of CM system vibration data collected from wind turbines are posing challenges to operators in signal processing. It is crucial to design sensitive and reliable condition indicator (CI) in wind turbine CM system. Bearing plays an important role in wind turbine because of its high impact on downtime and component replacement. CIs for wind turbine bearing monitoring are reviewed in the paper, and the advantages and disadvantages of these indicators are discussed in detail. A new engineering CI (ECI), which combined the energy and kurtosis representation of the vibration signal, is proposed to meet the requirement of easy applicability and early detection in wind turbine bearing monitoring. The quantitative threshold setting method of the ECI is provided for wind turbine CM practice. The bearing run‐to‐failure experiment data analysis demonstrates that ECI can evaluate the overall condition and is sensitive to incipient fault of bearing. The effectiveness in engineering of ECI is validated though a certain amount of real‐world wind turbine generator and gearbox bearing vibration data.     

Development of a 20 kW wind turbine simulator with similarities to a 3 MW wind turbine

As the use of wind power has steadily increased, the importance of a condition monitoring and fault diagnosis system is being emphasized to maximize the availability and reliability of wind turbines. To develop novel algorithms for fault detection and lifespan estimation, a wind turbine simulator is indispensible for verification of the proposed algorithms before introducing them into a health monitoring and integrity diagnosis system. In this paper, a new type of simulator is proposed to develop and verify advanced diagnosis algorithms. The simulator adopts a torque control method for a motor and inverter to realize variable speed-variable pitch control strategies. Unlike conventional motor–generator configurations, the simulator includes several kinds of components and a variety of sensors. Specifically, it has similarity to a 3 MW wind turbine, thereby being able to acquire a state of operation that closely resembles that of the actual 3 MW wind turbine operated at various wind conditions. This paper presents the design method for the simulator and its control logic. The experimental comparison between the behavior of the simulator and that of a wind turbine shows that the proposed control logic performs successfully and the dynamic behaviors of the simulator have similar trends as those of the wind turbine.