电站蒸汽轮机热力参数的回归分析建模

在应用ＧＬＲ法对电站传感器进行在线故障自动检测时,需要有所测热力参数的精确模型与传感器的实际输出相比较而形成残差序列。本文介绍以电站蒸汽轮机热力参数的实测数据为根据的多元线性回归分析建模方法。利用该法对某３００ＭＷ电站用汽轮机的主要热力参数所建立的仿真模型已成苗用于传感器的ＧＬＲ检测,检测的灵敏高度,伪报警低,说明所建立的仿真模型是正确和有效的。     

电站锅炉补给水处理流程全工况故障检测方法研究

复杂工业流程存在多稳态工况切换及切换的过渡过程,导致传统PCA(principal component analysis)故障检测方法易于误报故障。本研究提出了基于稳态因子的过渡过程判别方法及基于相似因子的工况自适应匹配方法,将其融入PCA构建了新的故障检测方法,且将该方法用于电站锅炉补给水处理流程的故障检测。以该流程的全工况运行数据对算法进行了验证,结果表明:此方法能有效消除过渡过程的影响,并能通过工况匹配提高故障检测性能且减少故障误报,可以实现水处理流程的全工况故障检测。     

提高传感器故障检测能力的研究

提高传感器故障检测系统检测小故障的能力,对提高工业过程的安全和经济性有重要意义.通过推导证明:对过程数据进行指数加权滑动平均(EWMA)滤波后,(T2H)指标的阈值保持不变,而T2H备指标相对于滤波前得到放大,因此滤波后T2H指标的故障检测精度得到提高,有利于及时检测到更小的传感器故障,提高了T2H指标检测小故障的能力,降低误报率,更易区分传感器的偏差故障和漂移故障.由于EWMA滤波会滤除一定的过程噪声,因此不推荐采用滤波方法检测传感器精度下降的故障.     

车用发动机动态检测系统研究ECU

总结发动机现有故障检测方法的特点,并提出了利用传感器信号模拟器模拟发动机工况与状态的动态检ECU ECU测方法。对发动机电子控制系统的传感器进行了分类,并提出了各类传感器信号的模拟方法。在此基础上,提出了发动机ECU ECU故障检测所需要模拟的工况与状态及模拟方法,并说明了能适于不同型号发动机检测的连接方法。     

光储联合电站建模与仿真

为解决光伏电站发电的波动性与不稳定性,介绍了光伏电站与全钒液流电池储能电站联合运行的系统结构,基于PSCAD/EMTDC仿真平台,建立了光伏电池、光伏控制系统、全钒液流电池及其控制系统的电气模型,对并网及故障模式下光储联合电站系统的运行情况进行了仿真研究。结果表明,光储联合电站运行时储能系统能很好地平抑光伏电站的输出功率波动,故障模式下能维持光伏电站的稳定运行。全钒液流电池储能电站可提高光伏电站运行的经济性与可靠性,同时增强了光伏电站输出的可预测性。     

基于信息冗余的DEH系统传感器故障检测

及时检测出传感器故障并采取降级运行措施，可保证ＤＥＨ系统在传感器故障情况下的稳定运行。作者基于调节级压力、功率信号间存在信息冗余的事实，提出了用软件来实现对ＤＥＨ系统中传感器故障的检测，并给出了两种方法，具有节省投资、硬件结构简单的特点。     

光伏直流配电故障诊断及火灾风险评估技术

长期服役的光伏发电系统直流配电故障概率高、火灾风险及危害大,严重影响光伏电站的运行安全、发电与出力能力,并对电站运维提出故障与火灾精准检测的技术挑战。为此,从生产现场直流配电柜故障分析入手,揭示接触不良、绝缘劣化、故障电弧、电气火灾的演变机理;分析国内外故障电弧诊断与火灾检测技术的理论成果应对在运电站电弧火灾的有效性,提出故障电弧预诊断与火灾检测技术的应用解决方案。研究结果表明,提出的故障电弧诊断与火灾检测技术应用方案,弥补直流继电保护对串联电弧故障无法保护的不足,能够有效诊断故障电弧并检测烟雾和高温,避免火灾及其扩大事故的发生。     

基于BP网络的故障诊断方法及其在电站中的应用

电站机组可能会发生各种故障，有些故障没有明显征兆。为能诊断这类故障，需要新的方法。提出了根据当前技术条件下可以测量到的参数，而不一定是故障特征参数，进行故障诊断的思路。介绍了BP人工神经网络的结构和学习方法，提出了基于BP网络的模式识别能力，建立电站性能监测与诊断系统的新思路和方法。利用该方法，对电站设备性能下降故障的程度进行了成功诊断。图2表2参3     

基于主元分析的热力系统传感器故障检测指标

基于主元分析的传感器故障检测方法是一种以数据统计为依据的重要故障检测方法.已有的研究一直忽视了对Hotelling T2和Hawkins T2H指标在传感器故障检测中的意义和作用的讨论.通过分析T2和T2H指标在主元分析的热力系统传感器故障检测中的不同适用性,提出了应用T2H的故障检测方法.该方法克服了T2统计参数对传感器小故障不敏感的问题.仿真实验的结果验证了该结论.     

基于改进BP神经网络的光伏阵列多传感器故障检测定位方法

光伏阵列由数量庞大的光伏组件构成,使得在发生故障时难以精确定位故障位置。针对这一难题,该文提出一种基于改进BP神经网络的光伏阵列多传感器故障检测定位方法,该方法将传感器分成若干个检测单元,在检测故障时,先将故障定位到检测单元;然后利用改进BP神经网络对检测单元内部的故障特征值与故障位置间的映射关系进行学习,从而实现光伏阵列故障点的检测与定位;最后提出一种新的非硬性故障判据。经过Matlab仿真测试,论证该方法的有效性及优异性。     

Sensor value validation based on implicit sensor redundancy for reliable operation of power plants

This paper presents an innovative sensor value validation technique that can systematically explore the embedded sensor redundancies in power plants and utilize them in validating sensor values. The proposed technique uses the relationships existing among the sensor values, which is called causal relations (CRs) in this paper. A data structure called a sensor redundancy graph (SRG) is formulated to explore systematically the sensor redundancies existing throughout the plants. In the SRG, CRs are represented as nodes and two CRs having a common sensor are connected with an edge. The criteria are also provided for testing whether a given sensor relationship expressed as a CR holds with the actual measurement values. If the relationship holds, the necessary condition for the validities of the sensors participated in the CR is satisfied. A technique that can examine the compatibility of the precisions among the sensors in a CR for testing the usability of the given CR is also developed based on sensor precision indices and statistical inference. The proposed technique is applied to flow meter data provided from an actual super critical steam power plant and its application potential is demonstrated.     

AP1000核电厂设备可靠性数据库开发及应用

  目的  设备可靠性数据在核电厂PSA、RCM、维修规则、可靠性保障大纲、风险指引管理等领域的重要价值,提出了开发AP1000设备可靠性数据库的必要性。  方法  对AP1000核电厂特定数据库开发过程中的一些重要问题,如独立失效的分析流程,设备和设备类的选取,可靠性参数估计方法,共因失效的分析方法和流程,核电厂特定数据以及通用数据收集和分析以及可靠性数据的应用等方面进行了探讨。  结果  提出了开发AP1000电站特定的设备可靠性数据库的技术路线。  结论  AP1000核电厂设备可靠性数据库的建立和应用,可以积累宝贵的核电厂特定运行、维修、失效、试验等数据,为核电厂运行PSA提供可靠性参数,为运行维修优化、安全管理等多个领域提供重要参考。     

Availability analysis of heat recovery steam generators used in thermal power plants

The combined-cycle gas and steam turbine power plant presents three main pieces of equipment: gas turbines, steam turbines and heat recovery steam generator (HRSG). In case of HRSG failure the steam cycle is shut down, reducing the power plant output. Considering that the technology for design, construction and operation of high capacity HRSGs is quite recent its availability should be carefully evaluated in order to foresee the performance of the power plant.This study presents a method for reliability and availability evaluation of HRSGs installed in combined-cycle power plant. The method’s first step consists in the elaboration of the steam generator functional tree and development of failure mode and effects analysis. The next step involves a reliability and availability analysis based on the time to failure and time to repair data recorded during the steam generator operation. The third step, aiming at availability improvement, recommends the fault-tree analysis development to identify components the failure (or combination of failures) of which can cause the HRSG shutdown. Those components maintenance policy can be improved through the use of reliability centered maintenance (RCM) concepts. The method is applied on the analysis of two HRSGs installed in a 500 MW combined-cycle power plant.     

Low energy hydrogen sensor

A new silicon-based hydrogen sensor for measurements at high concentrations near the lower flammable limit of hydrogen (40,000 ppm) is presented. Due to operation at room temperature the power consumption of the sensor is smaller than that of other sensors on the market by several orders magnitude. Further development of the sensor system could lead to battery powered or even energy-independent operation. As sensor fabrication is based on semiconductor technology, low-cost production can be achieved for the mass market. The sensor investigated showed good long-term stability combined with a fast response on the basis of cyclic thermal activations. This was demonstrated by a stress test that simulated the activation and measurement cycles experienced by the sensor in one year. Finite element method was used to further reduce the power consumption of the thermal activation. This resulted in an average power consumption of 2 × 10⁻⁶ W for the sensor activation.     

Investigation of PEMFC fault diagnosis with consideration of sensor reliability

Despite the wide range of applications for the polymer electrolyte membrane fuel cell (PEMFC), its reliability and durability are still major barriers for further commercialization. As a possible solution, PEMFC fault diagnosis has received much more attention in the last few decades. Due to the difficulty of developing an accurate PEMFC model incorporating various failure mode effects, data-driven approaches are widely used for diagnosis purposes. These methods depend largely on the quality of sensor measurements from the PEMFC. Therefore, it is necessary to investigate sensor reliability when performing PEMFC fault diagnosis.In this study, sensor reliability is investigated by proposing an identification technique to detect abnormal sensors during PEMFC operation. The identified abnormal sensors will be removed from the analysis in order to guarantee reliable diagnostic performance. Moreover, the effectiveness of the proposed technique is investigated using test data from a PEMFC system, where fuel cell flooding is observed. During the test, due to accumulation of liquid water inside the PEMFC, the humidity sensors will give misleading readings, and flooding cannot be identified correctly with inclusion of these humidity sensors in the analysis. With the proposed technique, the abnormal humidity measurements can be detected at an early stage. Results demonstrate that by removing the abnormal sensors, flooding can be identified with the remaining sensors, thus reliable health monitoring can be guaranteed during the PEMFC operation.     

基于多尺度时间窗口的核电运行数据关联性分析方法研究

[目的]核电运行数据具有维度高、体量大等特点,而核电厂内部系统的复杂性导致难以构建相应的机理模型,因此依靠人工从核电数据中筛选出具有关联性的参数非常困难,而非关联性参数的混入将极大地影响模型精度,通过提高模型精度以达到精准建模的目的。[方法]文章提出了一种基于多尺度时间窗口的关联分析方法,该方法对目标参数进行状态切换点提取,依据不同传感器所记录数据的特点对各个传感器进行分类,再针对不同种类的传感器设计符合其特点的检测窗口,利用从目标参数所提取到的状态切换时间点,对各个传感器的相应时间邻域进行状态切换检测,计算各个传感器与目标传感器的关联匹配率来判断其关联性大小。[结果]利用真实的核电厂历史运行数据展开实验,通过建立的关联匹配率规则,成功地筛选出了与目标传感器具有关联性的传感器参数。[结论]实验结果表明,文章所提出的方法可以更为准确地筛选出关联性参数,与常用的皮尔逊相关系数相比,文章所提出的方法准确性更高。     

CODOG动力装置实验台转速测量系统的研究

在改进的CODOG动力装置物理模拟实验台上，对主机切换过程中瞬时转速测量系统的硬件设计和软件编程进行了介绍，该测量系统可与转速传感器相配接用于检测各种机械转速。     

基于核主元分析和GRU神经网络的电站辅机故障预警研究

为解决电站辅机运行工况多变、结构复杂以及故障频发等问题,提出了一种基于核主元分析(KPCA)和门控循环单元(GRU)神经网络的电站辅机故障预警方法。通过核主元分析法提取电站辅机设备故障征兆参数,进行原始数据的约简。采用GRU神经网络进行电站辅机设备故障预警模型的建立。以神华福建某电厂HP843/Dyn中速磨煤机为例进行故障预警模型的训练、测试以及验证,该方法可以有效且提前发现中速磨煤机故障征兆。     

天然气再燃降低燃煤锅炉NOx排放的研究

天然气再燃是一种可行、经济且高效的降低锅炉烟气中NOx排放的方法。介绍了它的原理与应用现状，在多功能燃烧实验台上研究了天然气再燃对NOx排放的影响，分析了在各种工况下的实验数据，得出影响脱除NOx效果的因素，并与某电厂石油气再燃实炉改造的结果作了对比，证明了再燃技术的可行性。     

基于卡尔曼滤波器的控制系统传感器故障诊断

控制系统故障诊断在生产中十分重要,而传感器作为控制系统中最容易发生故障的环节,对其故障做出及时正确的预报尤为重要。介绍了卡尔曼滤波器的原理,以及基于卡尔曼滤波器的控制系统传感器故障诊断方法,从仿真结果可以看出这种方法在故障诊断中的实用性和有效性。