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This study presents a new fault diagnosis method based on a two-stage manifold learning framework to further improve fault diagnosis accuracy. First of all, nonlinear de-noising method with unsupervised manifold learning is presented, by combining advantages of manifold learning in mining of nonlinear structure and phase space reconstruction in representation of signal and noise spatial distribution...
This paper first gives a brief review of Integrated Vehicle Health Management (IVHM) concept, functions and architecture, then summarizes recent international research and development activities in this area especially in commercial aviation industry. A clear trend is that IVHM has become a focus in aerospace industry. All commercial aircraft manufacturers have spent significant amount of resources...
Ultrasonic sparse array can increase the resolution by enlarging the aperture without adding system complexity, and it has characteristics of large scanning range and high detection accuracy, which is one of the most promising applications of ultrasonic nondestructive testing technology. The application of reciprocity theory to scattering of guided waves by flaws was studied. A finite element model...
The application of Structural Health Monitoring (SHM) technology will bring revolutionary changes in maintenance strategy of civil aircraft composite structure from scheduled maintenance to Condition-Based Maintenance (CBM) which means the maintenance job will be applied based on the real time conditions of aircraft structure. Its application would promote the operational safety and maintenance efficiency...
The key of early fault detection is weak signal detection. But traditional chaos detection methods can deal with weak signals of single frequency and limited signal to noise ratio, and when noise is too strong, performance of the detection system is decreased. Thus it can't meet the needs of an aircraft rotor system's early fault detection, including weak signal, strong noise and multi-frequency....
Conventional reliability demonstration test based on statistical method is widely used in industry as it is simple and convenient to apply. But for the products with high reliability and long life, this test method fails to satisfy the demand for short cycle and low cost, and is liable to cause the phenomenon of over-test and short-test. This paper gives a step-stress accelerated sequential probability...
In this paper, a new kernel-domain spectrum based method is proposed to analyze the non-Gaussian and nonlinear characteristics of vibration signal for fault diagnosis of wind turbine. The proposed approach consists of the following key steps. First, the raw vibration signal measured from the wind turbine is divided into groups for data pre-process. The bispectrum method is then applied to the group...
Degradation trend estimation of rolling bearing is widely applied in many engineering applications. With the rapid development of sensors, massive data will be acquired because of the monitoring of machinery. So how to extract and use the effective data from the big data for trend estimation has profound research value. The least square support vector machine (LSSVM), which is a kind of novel artificial...
Background noise reduction has been studied for many years. However, unwanted human speech noise suppression is not well discussed due to sparsity of the speech signal. Traditional blind source separation (BSS) methods such as independent component analysis (ICA) assume the prior knowledge of the number of sources and require that the number of sources must equal the number of sensors. Above limitations...
Bridge is among the most important structures on high speed railway. The operation and management must meet the requirements in terms of reliability, availability, maintainability and safety. A prognostic and health management system used for bridges on high speed railway is first proposed in this paper. This new system is a user-oriented tool, providing guidance or information for inspection, repair...
Operating reliability has great significance for equipment condition monitoring and health evaluation. In terms of equipment to be evaluated, reliability assessment is a personalized problem. Traditional reliability assessment method relies on the probability and mathematical statistics methods, and has limited practical significance when it is used for real-time monitoring of a specific equipment...
This paper focuses on the fault tolerant control (FTC) approach using model reference adaptive control (MRAC). The fault in flight control system will lead to destructive accident. Firstly a new general post-fault system model of both additive and multiplicative actuator faults was presented. The new strange of MRAC will overcome the disadvantages of the previous ones, that is, the fault information...
Rolling element bearings are among the most frequently encountered components in the majority of rotating machines. Thus, prognostic and health management (PHM) of rolling bearing plays an important role on the working status of the machine system. Remaining useful life (RUL) prediction is the core of PHM. It's well known that original auto-regression (AR) model is suitable for the prediction of linear...
The number of extracted features for fault diagnosis in rotating machinery can grow considerably due to the large amount of available data collected from different monitored signals. Usually, feature selection or reduction are conducted through several techniques proposing a unique set of representative features for all available classes; nevertheless, in feature selection, it has been recognized...
Due to the fact that the cables in aircraft power system are complex, of large number branch points and hard to detect, this paper proposes a fault diagnosis method for Y shaped cable network combining the optimized search algorithm with Spread Spectrum Time Domain Reflectometry (SSTDR) by using the relationship between the reflection coefficient of the faulty branch and the detection port, based...
Fault diagnosis plays a crucial role to maintain healthy conditions in rotating machinery. This paper proposes a framework to detect new patterns of abnormal conditions in gearboxes, that would be associated to new faults. This is achieved through a Hybrid Heuristic Algorithm for Evolving Models in scenarios of Classification and Clustering (HHA-EMCC), which is a machine learning algorithm that can...
High density wireless sensor networks (HDWSNs) are emerging as promising techniques in a variety of fields such as target detection and tracking, military surveillance, intelligent family, preventing forest fire loss, building monitoring and control, medical diagnostic, etc. HDWSNs composed of a large number of sensors with wireless communication, computation, information acquisition, and self-adaptation...
Rolling bearing's running state has an important influence on the health condition of rotate machinery. This work focuses on the remaining useful life prediction of the rolling bearing. An auxiliary particle filter-based predictor for rolling bearing is presented. The energy spectrum feature of vibration signal is selected as the representation of system degraded states. The wavelet packet decomposition...
In order to better meet the requirements of automatic voltage control (AVC), integrating the Mvar control space and equivalent electrical distance, this paper improves the method of partitioning in the control strategy of automatic voltage control system. After analyzing the problems that exist in the traditional method, (such as one needs to artificially determine the number of partitions and a whole...
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