A Bank of Finite Memory Filters for Fault Detection and Adjusting Detection Latency

2014 ◽  
Vol 575 ◽  
pp. 811-819
Author(s):  
Pyung Soo Kim ◽  
Eung Hyuk Lee ◽  
Mun Suck Jang ◽  
Ki Sun Song
Keyword(s):  
Fault Detection ◽  
Threshold Value ◽  
Performance Criteria ◽  
High Threshold ◽  
Detection Scheme ◽  
Time Dynamic ◽  
Fast Detection ◽  
Multiple Sensors ◽  
Detection Latency ◽  
Finite Memory

This paper proposes a new fault detection scheme using a bank of finite memory filters for discrete-time dynamic systems with multiple sensors. In the proposed scheme, fault detection is carried out by testing the consistency of two filtered estimates, which are obtained from the primary estimation filter and the auxiliary estimation filter using a bank of finite memory filters, respectively. Detection latency is considered as one of important performance criteria and focus on the improvement of detection latency even for high threshold value. Through extensive computer simulations for the F-404 engine system, it is shown that detection latency can be adjusted by the window length. Simulation results show that the trade-off between the fast detection performance and the noise-suppressing estimation performance should be needed for the proposed fault detection scheme in real applications.

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.

scholarly journals Distributed global actuator fault-detection scheme for a class of linear multi-agent systems with disturbances

2020 ◽  
Vol 53 (2) ◽  
pp. 4202-4207
Author(s):  
Anass Taoufik ◽  
Michael Defoort ◽  
Mohamed Djemai ◽  
Krishna Busawon ◽  
Juan Diego Sánchez-Torres
Keyword(s):  
Fault Detection ◽  
Actuator Fault ◽  
Multi Agent Systems ◽  
Detection Scheme ◽  
Agent Systems ◽  
Multi Agent

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 Skeletons of Near-Critical Bienaymé-Galton-Watson Branching Processes

2015 ◽  
Vol 47 (2) ◽  
pp. 530-544
Author(s):  
Serik Sagitov ◽  
Maria Conceição Serra
Keyword(s):  
Critical Case ◽  
Branching Processes ◽  
Threshold Value ◽  
High Threshold ◽  
Birth Process ◽  
Birth And Death Processes ◽  
Supercritical Case ◽  
Natural Choice ◽  
Future Reproduction ◽  
Asymptotic Representations

Skeletons of branching processes are defined as trees of lineages characterized by an appropriate signature of future reproduction success. In the supercritical case a natural choice is to look for the lineages that survive forever (O'Connell (1993)). In the critical case it was suggested that the particles with the total number of descendants exceeding a certain threshold could be distinguished (see Sagitov (1997)). These two definitions lead to asymptotic representations of the skeletons as either pure birth process (in the slightly supercritical case) or critical birth-death processes (in the critical case conditioned on the total number of particles exceeding a high threshold value). The limit skeletons reveal typical survival scenarios for the underlying branching processes. In this paper we consider near-critical Bienaymé-Galton-Watson processes and define their skeletons using marking of particles. If marking is rare, such skeletons are approximated by birth and death processes, which can be subcritical, critical, or supercritical. We obtain the limit skeleton for a sequential mutation model (Sagitov and Serra (2009)) and compute the density distribution function for the time to escape from extinction.

scholarly journals Multiple Working Mode Based Door Opening Control and Fault Detection of Mobile Modular and Reconfigurable Robot

2021 ◽  
Author(s):  
Saleh Ahmad Ali
Keyword(s):  
Fault Detection ◽  
Control Design ◽  
Torque Control ◽  
Experimental Results ◽  
Joint Torque ◽  
Detection Scheme ◽  
Door Opening ◽  
Position Errors ◽  
Internal Forces ◽  
Reconfigurable Robot

The study in this thesis addresses the problem of opening a door with a modular and reconfigurable robot (MRR) mounted on a wheeled mobile robot platform. The foremost issue with door opening problems is the prevention of occurrence of large internal forces that arise due to position errors or imprecise modeling of the robot or its environment, i.e. the door parameters, specifically. Unlike previous methods that relied on compliance control, making the control design rather complicated, this thesis presents a new concept that utilizes the multiple working modes of the MRR modules. The control design is significantly simplified by switching selected joints of the MRR to work in passive mode during door opening operation. As a result, the occurrence of large internal forces is prevented. Different control schemes are used for control of the joint modules in different working modes. For passive joint modules, a feedforward torque control approach is used to compensate the joint friction to ensure passive motion. For the active joint modules, a distributed control method, based on torque sensing, is used to facilitate the control of joint modules working under this mode. To enable autonomous door opening, an online door parameter estimation algorithm is proposed on the basis of the least squares method; and a path planning algorithm is developed on the basis of Hermite cubic spline functions, with consideration of motion constraints of the mobile MRR. The theory is validated using simulations and experimental results, as presented herein. A distributed fault detection scheme for MRR robots with joint torque sensing is also proposed in this thesis. The proposed scheme relies on filtering the joint torque command and comparing it with a filtered torque estimate that is derived from the nonlinear dynamic model of MRR with joint torque sensing. Common joint actuator faults are considered with fault detection being performed independently for each joint module. The proposed fault detection scheme for each module does not require motion states of any other module, making it an ideal modular approach for fault detection of modular robots. Experimental results have attested the effectiveness of the proposed fault detection scheme.

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