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Skip to Search Results- 13Fault Detection
- 4Fault Diagnosis
- 4Machine Learning
- 3Hidden Markov Models
- 2Gaming
- 2Process Monitoring
- 1Alla, Hemanth Reddy
- 1Arifin, B M Sirajeel
- 1Bahador Rashidi
- 1Gonzalez, Ruben T
- 1Hajizadeh, Mohammad
- 1Hunter, Garett A. C.
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Application of Data Mining Techniques for Fault Diagnosis and Prognosis of High Pressure Fuel Pump Failures in Mining Haul Trucks
DownloadFall 2021
Mining companies are investing in fewer but larger equipment, and downtime associated with larger equipment now represents a higher percentage of operational capacity loss. Thus, it is essential to frequently and accurately monitor the health of this equipment to avoid unscheduled breakdowns and...
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Spring 2022
Artificial Neural Network (ANN) has gained great interest in industrial applications due to their supremacy in modelling complex process behaviour. Applications of ANN include process modelling, optimization and fault diagnosis. However, pure data-driven approaches that use only observations to...
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Fall 2014
While there has been much literature in the area of system monitoring and diagnosis, most of these techniques have a relatively small scope in terms of the faults and performance issues that they are built to detect. When implementing several monitors simultaneously on a single process, a single...
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Data-Driven Fault Detection, Isolation and Identification of Rotating Machinery: with Applications to Pumps and Gearboxes
DownloadFall 2012
Fault diagnosis plays an important role in the reliable operation of rotating machinery. Data-driven approaches for fault diagnosis rely purely on historical data. Depending on how a diagnosis decision is made, this thesis divides data-driven fault diagnosis approaches into two groups:...
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Fall 2016
Nowadays, industrial processes are becoming highly complex and integrated due to the applications of advanced distributed control systems. As multiple production units with thousands of actuators are operating at the same time, the reliability issue of process plants naturally arises. To ensure...
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Spring 2020
As the process control industry and production lines become highly complex and significantly invested with high-dimensional variables, process health monitoring attracts more attention from the domain experts and process operators. Since data is ubiquitous nowadays thanks to the advanced computer...
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Fault Detection and Diagnosis in Nonlinear Systems, with a Focus on Mining Truck Suspension Strut
DownloadSpring 2014
Classical fault detection methods do not completely satisfy the reliability requirement for complex and highly nonlinear stochastic systems. One solution to this problem is to use more advances fault detection methods such as multiple models to simulate system in different operating...
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Fall 2015
A large volume of literature exists on fault detection and isolation for industrial processes. In a general view, these various methods may be divided into process model based and process history based fault diagnosis. In both classes, there has been a recent focus on extracting the temporal...
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Fall 2018
Fault Detection, Isolation and Remediation of Real Processes",,eng,"Fault Detection, Change Detection, Leak Detection, Control Valve Stiction, Stiction-Compensation","The goal of process control and monitoring system is to operate the process plants safely, reliably and in fault-free mode. Even a...
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Gesture Recognition using Hidden Markov Models, Dynamic Time Warping, and Geometric Template Matching
DownloadFall 2013
Gesture recognition is useful in many applications, including human-computer interaction, automated sign language recognition, medical applications, and many more. The main focus of this thesis is to improve the isolated gesture recognition accuracy of Hidden Markov Models (HMMs) and to provide a...