Rule-based Fault Diagnosis of Hall Sensors and Fault-tolerant Control of PMSM

Hall sensor is widely used for estimating rotor phase of permanent magnet synchronous motor(PMSM). And rotor position is an essential parameter of PMSM control algorithm, hence it is very dangerous if Hall senor faults occur. But there is scarcely any research focusing on fault diagnosis and fault-tolerant control of Hall sensor used in PMSM. From this standpoint, the Hall sensor faults which may occur during the PMSM operating are theoretically analyzed. According to the analysis results, the fault diagnosis algorithm of Hall sensor, which is based on three rules, is proposed to classify the fault phenomena accurately. The rotor phase estimation algorithms, based on one or two Hall sensor(s), are initialized to engender the fault-tolerant control algorithm. The fault diagnosis algorithm can detect 60 Hall fault phenomena in total as well as all detections can be fulfilled in 1/138 rotor rotation period. The fault-tolerant control algorithm can achieve a smooth torque production which means the same control effect as normal control mode (with three Hall sensors). Finally, the PMSM bench test verifies the accuracy and rapidity of fault diagnosis and fault-tolerant control strategies. The fault diagnosis algorithm can detect all Hall sensor faults promptly and fault-tolerant control algorithm allows the PMSM to face failure conditions of one or two Hall sensor(s). In addition, the transitions between health-control and fault-tolerant control conditions are smooth without any additional noise and harshness. Proposed algorithms can deal with the Hall sensor faults of PMSM in real applications, and can be provided to realize the fault diagnosis and fault-tolerant control of PMSM.

Rough Set Theory Based Approach for Fault Diagnosis Rule Extraction of Distribution System

As the first step of service restoration of distribution system,rapid fault diagnosis is a significant task for reducing power outage time,decreasing outage loss,and subsequently improving service reliability and safety.This paper analyzes a fault diagnosis approach by using rough set theory in which how to reduce decision table of data set is a main calculation intensive task.Aiming at this reduction problem,a heuristic reduction algorithm based on attribution length and frequency is proposed.At the same time,the corresponding value reduction method is proposed in order to fulfill the reduction and diagnosis rules extraction.Meanwhile,a Euclid matching method is introduced to solve confliction problems among the extracted rules when some information is lacking.Principal of the whole algorithm is clear and diagnostic rules distilled from the reduction are concise.Moreover,it needs less calculation towards specific discernibility matrix,and thus avoids the corresponding NP hard problem.The whole process is realized by MATLAB programming.A simulation example shows that the method has a fast calculation speed,and the extracted rules can reflect the characteristic of fault with a concise form.The rule database,formed by different reduction of decision table,can diagnose single fault and multi-faults efficiently,and give satisfied results even when the existed information is incomplete.The proposed method has good error-tolerate capability and the potential for on-line fault diagnosis.

面向智能辅助决策的飞行器安控系统构建研究

新一代人工智能技术能够提高飞行器试验安控系统的辅助决策能力,满足地面安控目标数量增多、故判规则量增大、故判时效性高等新需求,具有广阔的应用前景。在对飞行器试验地面安控需求分析的基础上,设计面向智能辅助决策的地面安控系统总体框架,增加了数据与模型管理模块;接着构建了辅助决策知识库,主要包括故障弹判据、速度判据、位置判据和预示落点判据等规则库;在此基础上提出数据和规则协同驱动的故障预测方法。该系统既利用历史积累试验数据对深度神经网络模型进行训练,又利用规则库提高专家经验对模型预测精度的贡献,能够提高故障智能预测能力,满足飞行器安控智能辅助决策需求。

基于故障树和产生式规则的故障诊断专家系统设计

[目的]为充分运用核动力装置的运行管理经验辅助核动力操纵人员进行故障诊断,设计一种船用核动力装置故障诊断专家系统。[方法]首先,根据故障树与产生式规则之间的逻辑一致性,提出一种将故障树知识转化为产生式规则的方法;然后,对采用正、反向混合推理方法的专家系统知识库和推理机进行优化设计,并依据故障树最小割集和重要度分析结果设计正向推理策略以简化推理流程;最后,根据人工对故障状态判断的思路设计状态监测模块,实时采集关键设备参数以转化为专家系统可识别的设备信息。[结果]结果显示,采用所提方法可解决专家系统知识获取困难的问题,能在保证推理准确度的前提下提升推理效率,实现了专家系统的在线故障诊断功能。[结论]研究表明采用所提方法可提升专家系统获取知识的能力和推理效率,对保障核动力装置的运行管理安全具有重要意义。

一种标杆光伏组串选取方法及其在故障诊断中的应用

为实现对光伏组串故障的准确、快速诊断,以满足光伏电站数智化运维的需求,同时针对实际运行中的光伏组串基准运行状态难以确定的问题,提出一种基于实际运行数据的基准运行状态下的光伏组串(即标杆光伏组串)选取方法,并将其应用于光伏组串故障诊断中。首先利用多指标综合评价算法选取光伏标杆组串;然后利用标杆光伏组串与其他光伏组串间的输出电压、输出电流的相对误差,基于3σ准则设计了光伏组串故障诊断规则;最后利用某集中式光伏电站中光伏组串的实际运行数据对所提方法的合理性和有效性进行验证。研究结果显示:1)通过与其他光伏组串的输出功率进行对比,验证了所选标杆光伏组串的合理性;2)故障光伏组串所显示出的故障状态与基于所提出的故障诊断规则得到的结果一致,证明了此故障诊断方法的有效性。

基于关联规则的油田大型机泵设备振动故障数据采集方法

为了在不同工况下获取完整的振动故障数据,设计关联规则的油田大型机泵设备振动故障数据采集方法.提取大型机泵设备振动故障数据特征,在数据标准阈值中设定预警值与报警值,获取故障数据的全频域信息;基于关联规则方法优化振动故障数据采集完整性,通过分解、排序、更新三个步骤在处理噪声的同时保证数据完整性;引入连续采集算法判定振动数据故障阈值,优化完成油田大型机泵设备振动故障数据采集.实验表明,该数据采集方法可以在六种工况下,有效获取机泵设备回旋振动与纵向振动的完整故障数据,具备实际可行性.

基于关联规则与重构误差的二次系统故障检测方法

二次系统是否可靠直接关系整个变电站乃至系统能否安全可靠运行。随着高比例新能源并网,如何有效检测二次系统故障愈发重要。针对现有逻辑回路的故障方法对数据完备性要求较高而难以实际应用,现有二次设备的故障检测方法难以辨识正常数据和故障数据的微小差异导致计算精度无法保障的问题,提出基于关联规则与重构误差的二次系统故障检测方法。首先,利用Apriori算法求出故障报警信息与逻辑回路中故障装置的关联规则,实现逻辑回路故障快速诊断;然后,利用正常二次设备的运行数据训练个体判别器,通过衡量待判别数据的重构误差来判别二次设备运行状态,并利用集成学习模型量化设备当前故障检测概率;最后,对集成学习模型进行集成优化,以提高二次设备异常预警的可信度。利用河南省某变电站实际运行数据集进行仿真测试,验证了所提方法的有效性和准确性。

社会体育活动中其他参加者的过错认定--以体育规则为分析视角

对于《民法典》第1176条其他参加者故意或者重大过失的认定问题,原则上,体育规则违反与否可以作为认定侵权人主观上具有包含故意以及重大过失的严重过错的一种方法。但并非所有违反体育规则致人损害的行为均可认定为严重过错。判断社会体育侵权过错问题,应当将体育项目类型化,将系争纠纷具体至不同类型体育项目下讨论体育侵权过错问题。对于非对抗性运动,其他参加者违反体育规则致人损害的即认定其为严重过错;对于对抗性运动中隔网对抗运动,违反体育规则造成损害后果的行为亦认定为严重过错;对于对抗性运动中同场竞技运动,应在一般犯规同时该犯规超出了体育运动固有风险以及严重犯规时构成严重过错;对于对抗性运动中格斗对抗类运动,其他参加人违反体育规则造成损害后果的,只能认定为严重过错的必要非充分条件,还应当考量被侵害人的行为。

基于大数据的网络隐患分析系统研究与应用

文章提出了一种基于大数据技术的应用方式,通过挖掘告警强关联规则深入挖掘网络故障隐患,提升故障及隐患处理效率;通过构建季节性时间序列分析模型揭示历史数据中故障隐患发生、发展的规律,对故障隐患进行有效预警,将故障隐患从被动处理的传统模式革新到主动处理的预控层面上。

基于属性可靠度置信规则库的轴承故障诊断研究

轴承故障诊断是旋转器械健康管理中的一个关键问题。然而,在工程实践中,轴承的观测数据可能会受到一些干扰因素的影响,包括传感器质量和环境中的噪声等。在传统置信规则库(BRB)中,其模型推理假定输入数据完全可靠,但不可靠的观测数据会使BRB精度降低。具有属性可靠度的置信规则库模型(BRB-r)提供了一种建模框架和分析方法,是一个能够聚合不可靠定量数据和专家知识的系统。为提高轴承故障诊断精度,提出一种基于BRBr的轴承故障诊断模型。首先,基于统计方法计算属性可靠度;然后,使用证据推理作为模型的推理机;最后,采用投影协方差矩阵自适应进化策略(P-CMA-ES)对模型进行参数优化。验证实验结果表明,BRB-r在一定程度上能够消除观测数据中不确定性信息的影响,并对不可靠数据进行有效处理,具备良好的诊断效果。

基于虚拟阻抗优化的VSG暂态功角稳定自适应控制策略

在电网短路故障发生的情况下,虚拟同步发电机系统不仅会发生暂态功角失稳,同时还可能会出现过流。为了提升虚拟同步发电机的暂态功角稳定性及故障电流限制性能,首先建立了包含电压和电流控制环、虚拟阻抗及功率控制环结构的虚拟同步发电机系统的总体控制结构,给出了虚拟阻抗功率模型建立的理论依据。对无功功率控制环路恶化暂态功角稳定性,提出了设置电压增量自由控制支路来实现提高暂态功角稳定性的方法。其次,在无功功率控制环路及电压增量自由控制支路的共同作用下,对“不考虑切除故障”和“考虑切除故障”两种不同的运行工况,提出了能够同时满足暂态功角稳定性和故障电流限制的虚拟阻抗优化方法。最后提出了虚拟同步发电机的暂态功角失稳控制和故障电流限制的自适应控制算法,以满足实际运行工况的需求,通过Simulink仿真模型验证了所提自适应控制策略的有效性和可行性。

住宅工程质量通病防治监理实施细则的编制

为有效预防和治理住宅工程质量通病,部分地区提出了住宅工程质量通病控制标准、规范或防治规定,有的地区要求监理单位编制住宅工程质量通病防治监理实施细则。目前的监理实施细则总体编制水平不高,还存在较多问题。文中从监理实施细则的常见问题、应编制的内容及编写要求等方面讨论监理实施细则的编制,以期为同行提供一定的参考。

基于关联规则的火电厂热工保护用机电系统故障分析方法

传统火电厂热工保护用机电系统故障分析方法直接对故障信号高维特征进行解析,未对系统故障微弱信号进行高效解耦提取,造成传统方法故障识别率低,因此提出基于关联规则的火电厂热工保护用机电系统故障分析方法。对系统故障微弱信号进行高效解耦提取,并在此基础上基于关联规则进行故障信号高维特征解析,设计火电厂热工保护用机电系统故障自动检测流程,实现系统故障自动检测。实验结果表明,该研究方法故障识别率更高,故障识别效果更好。

基于智能系统的光伏发电场故障检测研究

模糊推理引擎进而评估这些模糊信息,依据模糊规则库中的规则来确定是否存在潜在故障。该方案提供了光伏场在正常运行时的瞬时发电量的估计。然后,将估计功率与实际功率进行比较,若功率之间的差值超过阈值,则生成警报信号,其中模糊规则系统TSK-FRBS已在正常运行期间将光伏电站模拟器收集的数据进行了培训,通过再现正常和故障条件,在模拟框架中进行测试。结果表明,即使引入噪声数据,该系统也能识别90%以上的故障情况。

一种基于关联规则挖掘的配电终端单元故障分析方法

随着配电网的发展,大量配电终端单元(DTU)应用于电力系统。DTU故障会对电力系统的安全稳定运行构成威胁,因此降低DTU装置的故障发生率、提高故障排除效率具有重要意义。本文提出一种基于关联规则挖掘算法的DTU故障分析方法,首先分析DTU故障的关键因素,然后阐述Eclat算法的相关概念,并利用不同规模的DTU故障数据库对Eclat算法与FP-Growth和Apriori算法的性能进行比较,得到一种基于Eclat算法的DTU故障分析方法。利用真实的DTU故障数据库进行实验,验证了所提方法的有效性。最后,给出所提方法的应用实例,证明了其实用性。

Expert fault diagnosis system for leaching process in zinc hydrometallurgy

Leaching process is the first step in zinc hydrometallurgy, which involves the complex chemical reactions for dissolving zinc bearing material in dilute sulfuric acid. Ensuring the safe running of the process is a key point in the operation. An expert fault diagnosis system for the leaching process was proposed, which has been implemented in a nonferrous metals smeltery. The system architecture and the diagnosis procedure were presented, and the rule models with the certainty factor were constructed based on the empirical knowledge, empirical data and statistical results on past fault countermeasures, and an expert reasoning strategy was proposed which employs the rule models and Beyes presentation and combines forward chaining and backward chaining. [

Fault Diagnosis of Machine Based on Fuzzy Reliability Theory

According to life analysis in reliability theory, certain diagnosis rules can be used to diagnose machines' faults. On this basis, considering the indefiniteness in machine working states, the accurate diagnosis rule was extended to fuzzy diagnosis rule by using basic concepts and methods of fuzzy mathematics. The formulas of fault probability under different conditions were deduced. In the end, an example is given and the results of two methods were compared.

Design of a fault diagnosis scheme for a class of singular nonlinear systems

A new fault detection and diagnosis approach is developed in this paper for a class of singular nonlinear systems via the use of adaptive updating rules. Both detection and diagnostic observers are established, where Lyapunov stability theory is used to obtain the required adaptive tuning rules for the estimation of the process faults. This has led to stable observation error systems for both fault detection and diagnosis. A simulated numerical example is included to demonstrate the use of the proposed approach and encouraging results have been obtained.

基于置信规则的村镇应急避难场所暴雨灾害链风险诊断

为解决村镇应急避难场所面临暴雨灾害时的风险问题,基于故障树和置信规则库推理方法,提出暴雨灾害链和村镇应急避难场所功能破坏链相结合的场所避难功能失效风险诊断模型。根据事故致因理论推理灾害节点变量,通过故障树描述灾害链,运用关联规则从历史灾害数据中挖掘规则,建立置信规则库系统,构建村镇应急避难场所功能失效风险诊断模型,并以四川省某寄宿制学校为例进行模型验证。研究结果表明:该模型可实现不同证据组合下村镇应急避难场所功能失效风险的诊断推理;实例的模型诊断结果与实际情况吻合,证实该模型能够科学地诊断村镇应急避难场所面临暴雨等恶劣自然条件时存在的风险,可为村镇应急避难场所规划设计和应急管理提供理论支撑。

Fault Diagnosis of a Rotary Machine Based on Information Entropy and Rough Set

There exists some discord or contradiction of information during the process of fault diagnosis for rotary machine. But the traditional methods used in fault diagnosis can not dispose of the information. A model of fault diagnosis for a rotary machine based on information entropy theory and rough set theory is presented in this paper. The model has clear mathematical definition and can dispose both complete unification information and complete inconsistent information of vibration faults. By using the model, decision rules of six typical vibration faults of a steam turbine and electric generating set are deduced from experiment samples. Finally, the decision rules are validated by selected samples and good identification results are acquired.