Gradient-based fuzzy fault isolation in residual-based fault detection systems

2014 ◽  
Author(s):  
Francisco Serdio ◽  
Edwin Lughofer ◽  
Kurt Pichler ◽  
Thomas Buchegger ◽  
Markus Pichler ◽  
...  
Keyword(s):  
Fault Detection ◽  
Fault Isolation ◽  
Detection Systems ◽  
Gradient Based

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.

Image-Based Versus Signal-Based Sensors for Machine Fault Detection and Isolation

2014 ◽  
Author(s):  
Heshan Fernando ◽  
Vedang Chauhan ◽  
Brian Surgenor
Keyword(s):  
Fault Detection ◽  
High Speed ◽  
Fault Isolation ◽  
Video Data ◽  
Fault Detection And Isolation ◽  
Single Camera ◽  
Multiple Faults ◽  
Multiple Sensors ◽  
Machine Fault ◽  
And Performance

This paper presents the results of a comparative study that investigated the use of image-based and signal-based sensors for fault detection and fault isolation of visually-cued faults on an automated assembly machine. The machine assembles 8 mm circular parts, from a bulk-supply, onto continuously moving carriers at a rate of over 100 assemblies per minute. Common faults on the machine include part jams and ejected parts that occur at different locations on the machine. Two sensor systems are installed on the machine for detecting and isolating these faults: an image-based system consisting of a single camera and a signal-based sensor system consisting of multiple greyscale sensors and limit switches. The requirements and performance of both systems are compared for detecting six faults on the assembly machine. It is found that both methods are able to effectively detect the faults but they differ greatly in terms of cost, ease of implementation, detection time and fault isolation capability. The conventional signal-based sensors are low in cost, simple to implement and require little computing power, but the installation is intrusive to the machine and readings from multiple sensors are required for faster fault detection and isolation. The more sophisticated image-based system requires an expensive, high-resolution, high-speed camera and significantly more processing power to detect the same faults; however, the system is not intrusive to the machine, fault isolation becomes a simpler problem with video data, and the single camera is able to detect multiple faults in its field of view.

scholarly journals Estimation and Fault Diagnosis of Lithium-Ion Batteries: A Fractional-Order System Approach

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Shulan Kong ◽  
Mehrdad Saif ◽  
Guozeng Cui
Keyword(s):  
Fault Diagnosis ◽  
Fault Detection ◽  
Fractional Order ◽  
Sliding Mode ◽  
Estimation Error ◽  
Lithium Ion ◽  
Fault Isolation ◽  
Sliding Mode Observer ◽  
Fault Detection And Isolation ◽  
Order System

This study investigates estimation and fault diagnosis of fractional-order Lithium-ion battery system. Two simple and common types of observers are designed to address the design of fault diagnosis and estimation for the fractional-order systems. Fractional-order Luenberger observers are employed to generate residuals which are then used to investigate the feasibility of model based fault detection and isolation. Once a fault is detected and isolated, a fractional-order sliding mode observer is constructed to provide an estimate of the isolated fault. The paper presents some theoretical results for designing stable observers and fault estimators. In particular, the notion of stability in the sense of Mittag-Leffler is first introduced to discuss the state estimation error dynamics. Overall, the design of the Luenberger observer as well as the sliding mode observer can accomplish fault detection, fault isolation, and estimation. The effectiveness of the proposed strategy on a three-cell battery string system is demonstrated.

Edge-based Explainable Fault Detection Systems for photovoltaic panels on edge nodes

2021 ◽  
Author(s):  
Seshapalli Sairam ◽  
Subathra Seshadhri ◽  
Giancarlo Marafioti ◽  
Seshadhri Srinivasan ◽  
Geir Mathisen ◽  
...  
Keyword(s):  
Fault Detection ◽  
Photovoltaic Panels ◽  
Detection Systems ◽  
Edge Based

scholarly journals FLISR Approach for Smart Distribution Networks Using E-Terra Software—A Case Study

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3333 ◽  
Author(s):  
Duy Le ◽  
Duong Bui ◽  
Cao Ngo ◽  
Anh Le
Keyword(s):  
Fault Detection ◽  
Management System ◽  
Processing Time ◽  
Distribution Network ◽  
Data Communication ◽  
Distribution Networks ◽  
Fault Isolation ◽  
Service Restoration ◽  
Minimum Number ◽  
Terminal Units

A smart grid concept has been defined in recent years, which emphasizes the importance on smart protection and measurement devices, reliable data communication and high security, optimal energy management system, and fault detection, location, isolation and service restoration (FLISR) of distribution networks (DNs). The main objectives of the FLISR approach are to achieve fast fault processing time, reduce the minimum number of interrupted customers, and improve the power supply reliability of the distribution. The conventional FLISR approach is to use signals of fault indicators (FIs) with distribution network states. The discrete installation of FIs to switches or reclosers may slow the processing time of fault detection and location, so it is necessary to develop a more efficient FLISR approach for smart distribution networks using functions of feeder terminal units (FTUs). In this paper, pick-up and tripping signals of overcurrent (OC) relays in combination with distribution grid states (e.g., switching status of devices, loss of voltage…) sent from feeder terminal units (FTUs) are used to detect and locate different fault types. Fault isolation and service restoration of black-out areas are then performed by solving an objective function with two main constraints, including (i) restoring the possible maximum number of out-of-service loads; and (ii) limiting the minimum number of switching operation. Thirteen performance factors (PF) are used for the post-fault service restoration process, consisting of: (i) Power Flow Violations (PFV), (ii) Bus Voltage Violations (BVV), (iii) Total Operation Cost (TOC), (iv) Lost Power (LP), (v) Outage Customer (OC), (vi) Number of Switching Steps (NSS), (vii) Power Losses (LOSS); (viii) Customer Minutes Interruption (CMI), (ix) Load Minutes Interruption (LMI), (x) MAIFI, (xi) SAIFI, (xii) SAIDI, and (xiii) Protection Validation (PRV). E-Terra platform of a distribution management system (DMS) is used to implement the proposed FLISR approach. Simulation and experiment results from a real 22 kV distribution network are also analysed to validate this FLISR approach. As a result, the novel FLISR approach has the ability to identify effectively the over-reaching of OC relays, indicate a mis-coordination risk of adjacent protection devices on the same feeder, and get the total processing time of fault detection, location and isolation as well as ranking all possible service restoration plans in distribution network at less than two minutes.

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