A Data-Level Fusion Model for Developing Composite Health Indices for Degradation Modeling and Prognostic Analysis

Liu, Kaibo; Gebraeel, Nagi; Shi, Jianjun

doi:10.1109/tase.2013.2250282

Cited by 266 publications

(135 citation statements)

References 21 publications

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“…Data-level fusion is the lowest layer information, which directly integrates multiple sensor data. A data-level fusion scheme is applied to degradation modeling and prognostic analysis for turbofan engine [32]. The original measurements are treated by extracting fault feature information, and then the information is integrated called feature-level fusion for fault diagnosis [33].…”

Section: Data Hierarchical Fusion For Engine Gas-path Fault Diagnosismentioning

confidence: 99%

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A Novel Data Hierarchical Fusion Method for Gas Turbine Engine Performance Fault Diagnosis

et al. 2016

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Gas path fault diagnosis involves the effective utilization of condition-based sensor signals along engine gas path to accurately identify engine performance failure. The rapid development of information processing technology has led to the use of multiple-source information fusion for fault diagnostics. Numerous efforts have been paid to develop data-based fusion methods, such as neural networks fusion, while little research has focused on fusion architecture or the fusion of different method kinds. In this paper, a data hierarchical fusion using improved weighted Dempster-Shaffer evidence theory (WDS) is proposed, and the integration of data-based and model-based methods is presented for engine gas-path fault diagnosis. For the purpose of simplifying learning machine typology, a recursive reduced kernel based extreme learning machine (RR-KELM) is developed to produce the fault probability, which is considered as the data-based evidence. Meanwhile, the model-based evidence is achieved using particle filter-fuzzy logic algorithm (PF-FL) by engine health estimation and component fault location in feature level. The outputs of two evidences are integrated using WDS evidence theory in decision level to reach a final recognition decision of gas-path fault pattern. The characteristics and advantages of two evidences are analyzed and used as guidelines for data hierarchical fusion framework. Our goal is that the proposed methodology provides much better performance of gas-path fault diagnosis compared to solely relying on data-based or model-based method. The hierarchical fusion framework is evaluated in terms to fault diagnosis accuracy and robustness through a case study involving fault mode dataset of a turbofan engine that is generated by the general gas turbine simulation. These applications confirm the effectiveness and usefulness of the proposed approach.

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Section: Data Hierarchical Fusion For Engine Gas-path Fault Diagnosismentioning

confidence: 99%

“…The sensor fusion technologies using learning machine are developed, such as the integration of multiple types NNs, or combination of NN and fuzzy logic [32,33]. The essence of these fusion approaches are the data-based ones, and aero-thermodynamic characteristics of gas turbine engine is not taken into account [34].…”

Section: Introductionmentioning

confidence: 99%

A Novel Data Hierarchical Fusion Method for Gas Turbine Engine Performance Fault Diagnosis

et al. 2016

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“…Substitution of (5) into (2) gives the log generalized likelihood ratio (GLR) statistic at each sensor:…”

Section: Detection Proceduresmentioning

confidence: 99%

“…Nowadays multi-sensor systems are deployed for real-time monitoring of large scale systems, such as manufacturing systems [1], [2], power systems [3], and biological and chemical threat detection systems [4]. The sensors acquire a stream of observations, whose distribution will change when the state of the network is changed due to an abnormality or threat.…”

Section: Introductionmentioning

confidence: 99%

Multi-sensor gradual change detection

Cao

Xie

2015

2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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We develop a mixture procedure to monitor parallel streams of data for a change-point that causes gradual change of a subset of data streams. We model the gradual change as a change in the trends of the affected data streams. Observations are assumed initially to be independent standard normal random variables with zero mean. After a change-point the observations in a subset of the streams of data have mean values that increase or decrease with time. The rate of change for the affected sensors may be different for the affected sensors. The subset and the post-change means are unknown but we assume the number of affected sensors is small. Our procedure uses a mixture statistics which hypothesizes an assumed fraction p0 of affected data streams. An analytic expression is obtained for the average run length (ARL) when there is no change and is shown by simulations to be very accurate. Similarly, an approximation for the expected detection delay (EDD) after a change-point is also obtained. Numerical examples based on real-data demonstrate the good performance of the proposed procedure on real data.

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“…Automation can benefit a variety of medical applications: surgical robotics [14], remote diagnosis [15], radiation biodosimetry [16],health analytics [17] and monitored anesthesia control [18]. Okamura et al [19] provides a detailed description of recent advances in medical and healthcare robotics.…”

Section: Background and Related Workmentioning

confidence: 99%

Robot-Guided Open-Loop Insertion of Skew-Line Needle Arrangements for High Dose Rate Brachytherapy

Garg

Siauw

Berenson

et al. 2013

IEEE Trans. Automat. Sci. Eng.

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Abstract-We present a study in human-centered automation that has potential to reduce patient side effects from high dose rate brachytherapy (HDR-BT). To efficiently deliver radiation to the prostate while minimizing trauma to sensitive structures such as the penile bulb, we modified the Acubot-RND 7-axis robot to guide insertion of diamond-tip needles into desired skew-line geometric arrangements. We extend and integrate two algorithms: Needle Planning with Integer Programming (NPIP) and Inverse Planning with Integer Programming (IPIP) to compute skew-line needle and dose plans. We performed three physical experiments with anatomically-correct phantom models to study performance: two with the robot and one control experiment with an expert human physician (co-author Hsu) without the robot. All were able to achieve needle arrangements that meet the RTOG-0321 clinical dose objectives with zero trauma to the penile bulb. We analyze systematic and random errors in needle placement; total RMS error for the robot system operating without feedback ranged from 2.6 mm to 4.3 mm, which is comparable to the RMS error of 2.7 mm obtained in an earlier study for PPI-BT treatment using a robot with 3D ultrasound feedback.Note to Practitioners Brachytherapy treats cancer by delivering radioactive sources proximal to cancer sites via needles. Current methods use standardized fixed mechanical templates that force needles into parallel arrangements that may prevent needles from reaching prostate volumes blocked by the pubic arch and often require needles to puncture sensitive organs. Skew-line (non-parallel) arrangements of needles can reach targets under the pubic arch and avoid sensitive organs. However these arrangements cannot be achieved with standard templates, motivating the use of automation. We present a human-centered automation system that integrates state-of-the- Left: The current clinical approach to prostate high dose rate brachytherapy (HDR-BT) uses parallel needles guided by a mechanical template. This approach may prevent needles from reaching prostate volumes blocked by the pubic arch and often require needles to puncture sensitive organs (which can produce long-term side-effects). Right: Skew-line needle arrangements facilitated by robot guidance can avoid puncture by reaching under the pubic arch and can minimize trauma to sensitive organs such as the penile bulb which can produce side effects such as incontinence and impotence.art needle and dose planning algorithms with a modified needle insertion robot. Results suggest that the robot can achieve precision and accuracy comparable to that of expert human physician. This approach has applications to brachytherapy treatment for other organs and to other needle procedures such as biopsy and anesthetic injection.

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A Data-Level Fusion Model for Developing Composite Health Indices for Degradation Modeling and Prognostic Analysis

Cited by 266 publications

References 21 publications

A Novel Data Hierarchical Fusion Method for Gas Turbine Engine Performance Fault Diagnosis

A Novel Data Hierarchical Fusion Method for Gas Turbine Engine Performance Fault Diagnosis

Multi-sensor gradual change detection

Robot-Guided Open-Loop Insertion of Skew-Line Needle Arrangements for High Dose Rate Brachytherapy

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