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1 Novel Classifier Fusion Approaches for Fault Diagnosis in Automotive Systems
"... Faulty automotive systems significantly degrade the performance and efficiency of vehicles, and oftentimes are the major contributors of vehicle breakdown; they result in large expenditures for repair and maintenance. Therefore, intelligent vehicle health-monitoring schemes are needed for effective ..."
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fault diagnosis in automotive systems. Previously, we developed a data-driven approach using a data reduction technique, coupled with a variety of classifiers, for fault diagnosis in automotive systems. In this paper, we consider the problem of fusing classifier decisions to reduce diagnostic errors
NOVEL CLASSIFIER FUSION APPROAHCES FOR FAULT DIAGNOSIS IN AUTOMOTIVE SYSTEMS
"... Abstract – Faulty automotive systems significantly degrade the performance and efficiency of vehicles, and oftentimes are the major contributors of vehicle breakdown; they result in large expenditures for repair and maintenance. Therefore, intelligent vehicle health-monitoring schemes are needed for ..."
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for effective fault diagnosis in automotive systems. Previously, we developed a datadriven approach using a data reduction technique, coupled with a variety of classifiers, for fault diagnosis in automotive systems [1]. In this paper, we consider the problem of fusing classifier decisions to reduce diagnostic
Residual Generation Methods for Fault Diagnosis with Automotive Applications
, 2009
"... The problem of fault diagnosis consists of detecting and isolating faults present in a system. As technical systems become more and more complex and the demands for safety, reliability and environmental friendliness are rising, fault diagnosis is becoming increasingly important. One example is autom ..."
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is automotive systems, where fault diagnosis is a necessity for low emissions, high safety, high vehicle uptime, and efficient repair and maintenance. One approach to fault diagnosis, providing potentially good performance and in which the need for additional hardware is minimal, is model-based fault diagnosis
Decentralized Diagnosis of Permanent Faults in Automotive E/E Architectures
"... Abstract-This paper presents a novel decentralized approach for the diagnosis of permanent faults in automotive Electrical and Electronic (E/E) architectures. Both, the safety-critical realtime requirements and the distributed nature of these systems make fault tolerance in general and fault diagno ..."
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Abstract-This paper presents a novel decentralized approach for the diagnosis of permanent faults in automotive Electrical and Electronic (E/E) architectures. Both, the safety-critical realtime requirements and the distributed nature of these systems make fault tolerance in general and fault
MACHINERY FAULT DIAGNOSIS
"... This research applied fuzzy c-means and fuzzy integral theories to a proposed novel two-step machinery fault diagnosis model. Distributed multiple fuzzy c-means classifiers were used to produce an initial diagnosis result by considering different features. Fuzzy measure and fuzzy integral data fusio ..."
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This research applied fuzzy c-means and fuzzy integral theories to a proposed novel two-step machinery fault diagnosis model. Distributed multiple fuzzy c-means classifiers were used to produce an initial diagnosis result by considering different features. Fuzzy measure and fuzzy integral data
1 Multi-agent decision fusion for motor fault diagnosis
"... Improvement of recognition rate is the ultimate aim for fault diagnosis researchers using pattern recognition techniques. However, unique recognition method can only recognize a limited classification capability which is insufficient for application. An ongoing strategy is the decision fusion techni ..."
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techniques. In order to avoid the shortage of single information source coupled with unique decision method, a new approach is required to generate better results. This paper proposes a decision fusion system for fault diagnosis, which integrates data sources of different types of sensors and decisions
Research Article A Novel Mittag-Leffler Kernel Based Hybrid Fault Diagnosis Method for Wheeled Robot Driving System
, 2015
"... which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The wheeled robots have been successfully applied in many aspects, such as industrial handling vehicles, and wheeled service robots. To improve the safety and reliability of wh ..."
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of wheeled robots, this paper presents a novel hybrid fault diagnosis framework based on Mittag-Leffler kernel (ML-kernel) support vector machine (SVM) and Dempster-Shafer (D-S) fusion. Using sensor data sampled under different running conditions, the proposed approach initially establishes multiple
Evolving Fuzzy Classifier based on Clustering Algorithm and Drift Detection for Fault Diagnosis Applications
"... Nowadays, in several areas, efficient fault diagnosis methods for complex machinery and equipments are required. Sev-eral fault diagnosis methods based on different theories and approaches have been proposed in the literature. In general, these methods use mathematical/statistical models, accumu-lat ..."
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new approach that combines a recursive clustering algorithm and a drift detection method and its application on dynamic systems fault diagnosis. The novel approach provides greater robustness to outliers and noise present in data from process sensors. The classifier is evaluated in fault diagnosis
A novel approach to fault diagnosis in multicircuit transmission lines using fuzzy ARTmap neural networks
- IEEE Trans. Neural Networks
, 1999
"... Abstract — The work described in this paper addresses the problems of fault diagnosis in complex multicircuit transmission systems, in particular those arising due to mutual coupling between the two parallel circuits under different fault conditions; the problems are compounded by the fact that this ..."
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Abstract — The work described in this paper addresses the problems of fault diagnosis in complex multicircuit transmission systems, in particular those arising due to mutual coupling between the two parallel circuits under different fault conditions; the problems are compounded by the fact
FLIGHT REGIME MAPPING FOR AIRCRAFT ENGINE FAULT DIAGNOSIS
"... Abstract: One of the issues that impair the performance of aircraft engine fault diagnosis is the flight regime. When an aircraft travels from one point to another in flight regime, engine performance parameters that are used for fault diagnosing change and such changes mask the parameter changes ca ..."
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in a significant increase of the costs and complexity. In this paper, a novel approach – flight regime mapping- is introduced for tackling the flight regime issue in aircraft engine fault diagnosis. The proposed flight regime mapping essentially compensates for flight regime induced parameter changes
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