scholarly journals Design and In-Water Testing of a Fault-Detection System for Unmanned Underwater Vehicle Actuators

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Matt Kemp ◽  
Jon Erickson ◽  
Scott Jensen ◽  
Sotiria Lampoudi ◽  
Eric J. Martin
Keyword(s):  
Fault Detection ◽  
False Alarm ◽  
Detection System ◽  
Underwater Vehicle ◽  
Fault Detection And Isolation ◽  
Test Results ◽  
Water Testing ◽  
Unmanned Underwater Vehicle ◽  
Testing Sequence ◽  
System Requirements

We discuss the design of a fault-detection system for an unmanned underwater vehicle (UUV) actuator and present the results of in-water testing. We first discuss the design of the system, then its integration onto the UUV, the in-water testing sequence, and finally the analysis of the test results –- missed detection and false-alarm rate. This system serves as a platform for UUV fault detection and isolation research, enabling the development of system requirements, and providing the opportunity to compare the merits of the centralized vs decentralized fault-detection design approaches.

Multiple faults detection and isolation approach applied to a kraft recovery boiler

TAPPI Journal ◽  
2014 ◽  
Vol 13 (1) ◽  
pp. 33-41
Author(s):  
YVON THARRAULT ◽  
MOULOUD AMAZOUZ
Keyword(s):  
Fault Detection ◽  
Early Detection ◽  
False Alarm ◽  
False Alarm Rate ◽  
Principal Component ◽  
Fault Isolation ◽  
Fault Detection And Isolation ◽  
Detection Scheme ◽  
Multiple Faults ◽  
Recovery Boiler

Recovery boilers play a key role in chemical pulp mills. Early detection of defects, such as water leaks, in a recovery boiler is critical to the prevention of explosions, which can occur when water reaches the molten smelt bed of the boiler. Early detection is difficult to achieve because of the complexity and the multitude of recovery boiler operating parameters. Multiple faults can occur in multiple components of the boiler simultaneously, and an efficient and robust fault isolation method is needed. In this paper, we present a new fault detection and isolation scheme for multiple faults. The proposed approach is based on principal component analysis (PCA), a popular fault detection technique. For fault detection, the Mahalanobis distance with an exponentially weighted moving average filter to reduce the false alarm rate is used. This filter is used to adapt the sensitivity of the fault detection scheme versus false alarm rate. For fault isolation, the reconstruction-based contribution is used. To avoid a combinatorial excess of faulty scenarios related to multiple faults, an iterative approach is used. This new method was validated using real data from a pulp and paper mill in Canada. The results demonstrate that the proposed method can effectively detect sensor faults and water leakage.

T-S Fuzzy Model-Based H_/H∞ Fault Detection of Larger Displacement Unmanned Underwater Vehicle

2017 ◽  
Vol 23 (3) ◽  
pp. 172-178
Author(s):  
Ji Hyun Moon ◽  
Ho Jae Lee ◽  
Moon Hwan Kim ◽  
Ho Gyu Park ◽  
Tae Yeong Kim
Keyword(s):  
Fault Detection ◽  
Fuzzy Model ◽  
Underwater Vehicle ◽  
Model Based ◽  
Unmanned Underwater Vehicle

scholarly journals Spacecraft Actuator Diagnosis with Principal Component Analysis: Application to the Rendez-Vous Phase of the Mars Sample Return Mission

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Othman Nasri ◽  
Imen Gueddi ◽  
Philippe Dague ◽  
Kamal Benothman
Keyword(s):  
Principal Component Analysis ◽  
Fault Detection ◽  
Principal Component ◽  
Component Analysis ◽  
Fault Detection And Isolation ◽  
Test Results ◽  
Sample Return ◽  
Rotation Rates ◽  
Analysis Application ◽  
Sample Return Mission

This paper presents a fault detection and isolation (FDI) approach in order to detect and isolate actuators (thrusters and reaction wheels) faults of an autonomous spacecraft involved in the rendez-vous phase of the Mars Sample Return (MSR) mission. The principal component analysis (PCA) has been adopted to estimate the relationships between the various variables of the process. To ensure the feasibility of the proposed FDI approach, a set of data provided by the industrial “high-fidelity” simulator of the MSR and representing the opening (resp., the rotation) rates of the spacecraft thrusters (resp., reaction wheels) has been considered. The test results demonstrate that the fault detection and isolation are successfully accomplished.

scholarly journals DETEKSI DAN ISOLASI KESALAHAN BERBASIS PD DESCRIPTOR OBSERVER MENGGUNAKAN HUKUM CTC PADA ROBOT MANIPULATOR

2016 ◽  
Vol 1 (2) ◽  
pp. 36-42 ◽  
Author(s):  
Titi Andriani
Keyword(s):  
Fault Detection ◽  
False Alarm ◽  
Robot Manipulator ◽  
Fault Detection And Isolation ◽  
Residual Noise ◽  
Descriptor Observer ◽  
Computed Torque

Secara umum robot dapat meningkatkan produktivitas produksi yang memberikan keuntungan lebih. Dalam bidang industri misalnya, penggunaan robot ditujukan untuk menggantikan peran manusia dalam melaksanakan tugas-tugas yang membutuhkan tenaga besar dan ketelitian tinggi. Terjadinya kesalahan sensor pada robot dapat menyebabkan penurunan hasil produksi. Untuk keperluan proses monitoring, deteksi dan isolasi kesalahan (Fault Detection and Isolation/FDI) memainkan peranan penting dalam memberikan informasi tentang kesalahan sistem untuk memungkinkan rekonfigurasi yang tepat. Untuk FDI yang berbasis residual, tugas yang sangat penting adalah teknik desain observer yang mampu mengestimasi sinyal kesalahan pada pengukuran sehingga miss detection dan false alarm dapat dihindari. Selain itu, harus dipilih metode kontrol yang tepat yang mampu mengatasi ketidaklinieran pada robot manipulator. Computed Torque Controller (CTC) adalah kontroler nonlinier yang telah digunakan secara luas pada kontrol robot manipulator. Kontrol ini didasarkan pada linearisasi umpan balik dan perhitungan torsi yang diperlukan lengan robot menggunakan hukum kontrol umpan balik nonlinear. Untuk sistem dengan noise pengukuran, observer Proportional Derivative (PD) dikonstruksi untuk mengestimasi residual noise pengukuran. Gain proportional dipilih untuk memastikan kestabilan dinamika error yang diestimasi dan gain derivative dipilih untuk mengurangi amplifikasi noise. Observer PD selanjutnya diaplikasikan pada mekanisme deteksi dan isolasi kesalahan sensor robot manipulator. Dengan menerapkan CTC pada robot manipulator, didapatkan sinyal kontrol umpan balik linier yang menjadi input bagi modified PD descriptor observer. Transformasi pemodelan robot manipulator ke dalam sistem augmented descriptor sehingga diperoleh formulasi desain observer yang baru yang mampu mengestimasi kesalahan pengukuran dan dapat diterapkan pada mekanisme FDI untuk memberikan sinyal alarm yang sesuai dengan sinyal kesalahan yang diinputkan pada pengukuran yang disimulasikan.

Optimized fault detection using bond graph in linear fractional transformation form

2021 ◽  
pp. 095965182098561
Author(s):  
Mahdi Ouziala ◽  
Youcef Touati ◽  
Sofiane Berrezouane ◽  
Djamel Benazzouz ◽  
Belkacem Ouldbouamama
Keyword(s):  
Fault Detection ◽  
Detection System ◽  
Main Idea ◽  
Bond Graph ◽  
Fault Detection And Isolation ◽  
Linear Fractional Transformation ◽  
Estimated Parameters ◽  
Robust Fault Detection ◽  
Uncertainty Calculation ◽  
Adaptive Thresholds

This article deals with the optimal robust fault detection problem using the bond graph in its linear fractional transformation form. Generally, this form of the bond graph allows the generation of two perfectly separate analytical redundancy relations, that are used as residual and threshold. However, the uncertainty calculation method gives overestimated thresholds. This may, for instance, lead to undetectable faults. Therefore, enhancing the robustness of fault detection and isolation algorithms is of utmost importance in designing a bond graph–based fault detection system. The main idea of this article is to develop optimized thresholds to ensure an optimal detection, otherwise this article proposes a method to detect tiny magnitude faults concerning parameter’s uncertainties. This work considers the issue of optimal fault detection as an optimization problem of the gap between the residuals and its threshold. New uncertainty values will be calculated in a way that these estimated parameters ensure the desired optimized gap between residuals and thresholds. These estimated uncertainty values will be used to generate optimized adaptive thresholds. Through these thresholds, we increase the sensitivity of the residuals to tiny magnitude faults, and we ensure an optimal and early detection.

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