A LPV modeling of turbocharged spark-ignition automotive engine oriented to fault detection and isolation purposes

2018 ◽  
Vol 355 (14) ◽  
pp. 6710-6745 ◽  
Author(s):  
Gianfranco Gagliardi ◽  
Francesco Tedesco ◽  
Alessandro Casavola
Keyword(s):  
Fault Detection ◽  
Spark Ignition ◽  
Fault Detection And Isolation ◽  
Automotive Engine

A survey on diagnostic methods for automotive engines

2011 ◽  
Vol 13 (1) ◽  
pp. 41-64 ◽  
Author(s):  
J Mohammadpour ◽  
M Franchek ◽  
K Grigoriadis
Keyword(s):  
Fault Detection ◽  
Fault Detection And Diagnosis ◽  
Diagnostic Methods ◽  
Fault Detection And Isolation ◽  
State Regulations ◽  
Automotive Engine ◽  
Automotive Engines ◽  
Detection And Diagnosis ◽  
Negative Impacts ◽  
Component Faults

Faults affecting automotive engines can potentially lead to increased emissions, increased fuel consumption, or engine damage. These negative impacts may be prevented or at least alleviated if faults can be detected and isolated in advance of a failure. United States Federal and State regulations dictate that automotive engines operate with high-precision onboard diagnosis (OBD) systems that enable the detection of faults, resulting in higher emissions that exceed standard thresholds. In this paper, we survey and discuss the different aspects of fault detection and diagnosis in automotive engine systems. The paper collects some of the efforts made in academia and industry on fault detection and isolation for a variety of component faults, actuator faults, and sensor faults using various data-driven and model-based methods.

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.

Fault detection and isolation for PEM fuel cell stacks using fuzzy clusters

2007 ◽  
Author(s):  
Michael Buchholz ◽  
Gwendaelle Pecheur ◽  
Jens Niemeyer ◽  
Volker Krebs
Keyword(s):  
Fuel Cell ◽  
Fault Detection ◽  
Pem Fuel Cell ◽  
Fault Detection And Isolation
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