Diagnosis of multiple faults using a double parallel two-hidden-layer extreme learning machine

Multiple faults are easily confused with single faults.In order to identify multiple faults more accurately,a highly efficient learning method is proposed based on a double parallel two-hidden-layer extreme learning machine,called DPTELM.The DPT-ELM method is a variant of an extreme learning machine(ELM).There are some issues with ELM.First,achieving a high accuracy requires too many hidden nodes;second,the direct connection between the input layer and the output layer is ignored.Accordingly,to deal with the above-mentioned problems,DPT-ELM extends the single-hidden-layer ELM to a two-hidden-layer ELM,which can achieve a desired performance with fewer hidden nodes.In addition,a direct connection is built between the input layer and the output layer.Since the input layer weights and the thresholds of the two hidden layers are determined randomly,this simplifies the improved model and shortens the calculation time.Additionally,to improve the signal to noise ratio(SNR),an adaptive waveform decomposition(AWD)algorithm is used to denoise the vibration signal.Then,the denoised signal is used to extract the eigenvalues by the time-domain and frequency-domain methods.Finally,the eigenvalues are input to the DPT-ELM classifier.In this paper,two groups of rolling bearing data at different speeds,which were collected from a real experimental platform,are used to test the method.Each set of data includes three single fault states,two complex fault states and a healthy state.The experimental results demonstrate that the DPT-ELM method achieves fast learning speed and a high accuracy.Moreover,based on 10-fold cross-validation,it proves to be an effective method to improve the accuracy with fewer hidden nodes.     

基于三支决策的医院分级诊疗决策研究

人口众多与医疗资源不均衡加剧了看病难问题,分级诊疗是我国医疗改革的重要举措之一.通过引入三支决策理论,将分级诊疗分为就诊、住院观察和转院3个决策类型,在考虑患者分诊风险的基础上,利用贝叶斯理论求得决策阈值,从而给出了分级诊疗的定量决策方法,通过实例验证了三支决策在分级诊疗决策研究中的可行性.     

Research and application of hierarchical model for multiple fault diagnosis

1.INTRODUCTION Failureanalysisanddiagnosisoflarge scalesystems havereceivedconsiderableattentionduringtherecent years[1～3].Thesesystemshaveevolvedfromthepre viousonesbasedonheuristicknowledgeofsymptom faultassociationstothemorerecentonesbasedon structure,behaviorandfunctionalityofthedevice andsubsystemtobediagnosed[4].Inthecaseof complexsystem,theapplicationofmodel baseddiag nosisalgorithmsbecomescomputationallyverydiffi cultorevenintractable.Ahierarchicaldiagnosisap proachcansignificant…     

An Approach to the Fault Diagnosis and Testability in Analog Circuits at Module Level

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点模式识别ANN的区域分划特征

化学工程中许多过程识别问题，可归结为点模式识别，本文以区域分划或覆盖为基础，研究用于点模式识别的ＡＮＮ的性能，提出分划映射的ＡＮＮ表示－σ网络及其学习算法，并建立它的“知识积累”机制－σ网络的序贯学习。     

神经网络在肺癌早期鉴别诊断中的研究与应用

研究了人工神经网络方法（ＮＮ）在生物医学工程和生命科学中的应用。提出了改进反传算法（ＭＢＰ）并用于肺癌早期诊断：发现其对几类病人的识别和预测时，分类正确率高，临床诊断预测力强。     

机械密封的相态判断及相态稳定性分析

本文对机械密封的几种不同相态的模型及其工作稳定性进行了讨论和分析,提出机械密封相态稳定性的判据和稳定区界限。最后给出相态稳定性的主要影响因素和控制相态稳定性的指标。利用p-T图可以判断机械密封的相态,进一步了解密封工作的稳定性并帮助作故障分析,以便采用相应的措施来保证机械密封工作稳定、安全可靠。这些相态稳定性界限、汽化温差、判断相态的方法和故障分析方法可供实际参考使用。     

生物技术与生命伦理学的历史与新进展

目的讨论关于伦理与知识的基本哲学问题,并给出当代欧洲有关生物伦理争论的例子。方法结合实例的分析方法。结果认为知识的伦理是一种有益的态度,可以用来克服知识发展过程中所遇到的或派生出的矛盾。结论伦理和知识之间的矛盾依然存在于当代社会中。     

Decentralized and overall condition monitoring system for large-scale mobile and complex equipment

It is an urgent project to realize online and overall condition monitoring and timely fault diagnosis for large-scale mobile and complex equipment. Moreover, most of the existing large-scale complex equipment has quite insufficient accessibility of examination, although it still has quite a long service life. The decentralized and overall condition monitoring, as a new concept, is proposed from the point of view of the whole system. A set of complex equipment is divided into several parts in terms of concrete equipment. Every part is processed via one detecting unit, and the main detecting unit is connected with other units. The management work and communications with the remote monitoring center have been taken on by it. Consequently, the difficulty of realizing a condition monitoring system and the complexity of processing information is reduced greatly. Furthermore, excellent maintainability of the condition monitoring system is obtained because of the modularization design. Through an application example, the design and realization of the decentralized and overall condition monitoring system is introduced specifically. Some advanced technologies, such as, micro control unit (MCU), advanced RISC machines (ARM), and control area network (CAN), have been adopted in the system. The system's applicability for the existing large-scale mobile and complex equipment is tested.     

小电网故障定位的研究

关于模拟电路故障诊断的多频率法对小型电网的短路故障及开路故障定位的研究表明,选择适当的测试频率及诊断精度,能准确地诊断出故障点,并可用微机迅速地完成诊断。