An Expert System for Diagnosing Heavy-Duty Diesel Engine faults

Nabende, Peter; Wanyama, Tom

doi:10.1007/978-1-4020-8741-7_69

Cited by 6 publications

(3 citation statements)

References 7 publications

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“…In the work of [15], Heavy Duty Diesel Engines (HDDEs) diagnosis is proposed. HDDEs maintenance requires high technical skills and extensive experienced mechanics that are scarce.…”

Section: Review Of Related Literaturementioning

confidence: 99%

Design and Implementation of an Expert Management System for Automobile Fault Detection

Muhammed¹,

A²,

Sanusi³

2019

IJASRE

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A system has been developed to communicate with the On-Board Diagnostics system of a car using the Controller Area Network communication protocol. The system requests the stored trouble codes that might have been detected by the diagnostics system and sends them to a server. The information is accessed through a web interface. The web interface allows the user to find the solutions in the database together with the detected faults. The database also contains information about trouble codes, such as their symptoms, causes and how to fix them. Monitoring the communications while testing the prototype showed that the system works as intended and can communicate with cars from different manufacturers and extract the data. The prototype system was compared with a commercial scan tool and testing showed that they both produced the same results. The second module of the project deals with the design and implementation of an expert system for car faults diagnosis. The project is motivated by the need to guide car owners and learners' motor mechanics in the maintenance and troubleshooting of motor problems without having to resort to presumptions and conjectures. Particularly, it is expected that the proposed design would ensure that car owners have proper assistance in times of crisis and what's more, will save them from the clutches of exploitative roadside mechanics. For this purpose, a rule-based artificial intelligence (AI) technique was utilized to obtain theoretical and practical expert system parameters, and then a conceptual expert system was designed. The expert system functioning is based on the database of car faults, symptoms and their correction, which make up its knowledge base. The new system was developed using PHP and MySQL database. This language was chosen because of its easy syntax and features for developing web-based applications.

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“…In the work of [15], Heavy Duty Diesel Engines (HDDEs) diagnosis is proposed. HDDEs maintenance requires high technical skills and extensive experienced mechanics that are scarce.…”

Section: Review Of Related Literaturementioning

confidence: 99%

Design and Implementation of an Expert Management System for Automobile Fault Detection

Muhammed¹,

A²,

Sanusi³

2019

IJASRE

View full text Add to dashboard Cite

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“…Many of these approaches use diagnostic models that are static Bayesian networks, e.g. [13,18,23,25,26,46]. Others use consistency-based diagnostic models augmented with probabilities, see e.g.…”

Section: Paper E a Modeling Framework For Troubleshooting Automotivementioning

confidence: 99%

A Modeling Framework for Troubleshooting Automotive Systems

Warnquist

Kvarnström

Doherty

2016

Applied Artificial Intelligence

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This paper presents a novel framework for modeling the troubleshooting process for automotive systems such as trucks and buses. We describe how a diagnostic model of the troubleshooting process can be created using event-driven nonstationary dynamic Bayesian networks.Exact inference in such a model is in general not practically possible. Therefore we evaluate different approximate methods for inference based on the BoyenKoller algorithm. We identify relevant model classes that have particular structure such that inference can be made with linear time complexity using a novel inference algorithm called the Quickscore Variant. We show how the algorithm can be applied for inference when only a single fault is assumed and when multiple faults are possible. We also show another inference method that can be used when multiple faults are possible but a single fault is most likely.We also show how models created using expert knowledge can be tuned using statistical data. The proposed learning mechanism can use data that is collected from a heterogeneous fleet of modular vehicles that can consist of different components.The proposed framework is evaluated both theoretically and experimentally on an application example of a fuel injection system. 205Paper E.

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“…Additionally, novel approaches like Switching Unscented Kalman Filter method [19], Extreme Learning Machines [20], Online Dictionary Learning [21], and the discriminative nonnegative matrix factorization (DNMF) method [22] have been proposed. As a branch of applied artificial intelligence (AI), expert systems are also introduced in the field of fault diagnosis and have been built demonstrating good performances [23][24][25].…”

Section: Introductionmentioning

confidence: 99%

A Study of Probabilistic Diagnosis Method for Three Kinds of Internal Combustion Engine Faults Based on the Graphical Model

Liu

Jiang

2019

Mathematical Problems in Engineering

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A strategy for increasing the accuracy rate of internal combustion engine (ICE) fault diagnosis based on the probabilistic graphical model is proposed. In this method, a three-layer network with inference of probability is constructed, and both the material conditions and the signals collected from different engine parts are considered as the inputs of the system. Machine signals measured by sensors were processed in order to diagnose potential faults, which were presented as probabilities based on the components in layer 1, fault categories in layer 2, and fault symptoms in layer 3. The diagnosis model was built by using nodes and arcs, and the results depended on the connections between the fault categories and symptoms. The parameters of the network represented quantitative probabilistic relationships among all layers, and the conditional probabilities of each type of fault and relevant symptoms were summarized. Fault cases were simulated on a 12-cylinder diesel engine, and three fault types that often occur on ICEs were tested based on five different fault symptoms with different loads, respectively. The diagnostic capability of the method was investigated, reporting high accuracy rates.

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An Expert System for Diagnosing Heavy-Duty Diesel Engine faults

Cited by 6 publications

References 7 publications

Design and Implementation of an Expert Management System for Automobile Fault Detection

Design and Implementation of an Expert Management System for Automobile Fault Detection

A Modeling Framework for Troubleshooting Automotive Systems

A Study of Probabilistic Diagnosis Method for Three Kinds of Internal Combustion Engine Faults Based on the Graphical Model

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