An Approach towards designing of Car Troubleshooting Expert System (original) (raw)

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

International Journal of Advances in Scientific Research and Engineering-IJASRE, 2019

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.

Implementing an Expert Diagnostic Assistance System for Car Failure and Malfunction

Applications in fault diagnosis are continuously being implemented to serve different sectors. Car failure detection is a sequence of diagnostic processes that necessitates the deployment of expertise. The Expert System (ES) is one of the leading Artificial Intelligence (AI) techniques that have been adopted to handle such task. This paper presents the imperatives for an ES in developing car failure detection model and the requirements of constructing successful Knowledge-Based Systems (KBS) for such model. In addition, it exhibits the adaptation of the ES in the development of Car Failure and Malfunction Diagnosis Assistance System (CFMDAS). However, CFMDAS development faces many challenges such as collecting the required data for building the knowledge base and performing the inferencing. Furthermore, diagnosis of car faults requires high technical skills and experienced mechanics who are typically scarce and expensive to get. Thus, systems such as CFMDAS can be highly useful in assisting mechanics for failure detection and training purposes. Moreover, capturing and retaining valuable knowledge on such domain yield more accurate and less time consuming models.

Approach towards Car Failure Diagnosis-An Expert System

International Journal of Computer Applications, 2010

The paper presents the processes that play a significant role in the development of an expert system. The research has been done to assist in the designing of an expert system for car failure diagnosis and repairs under constraint like time, place and availability of human expertise. Study of technologies for designing expert systems was undertaken to conclude best means, which are simple and easy, to implement and maintain while developing an expert system.

Developing Knowledge-Based Systems: Car Failure Detection using Expert System

Information and Knowledge Management, 2014

To develop an expert system describes the knowledge-base of the car failure detection. 19 rule-based of car fault diagnosis expert system using the Visual Basic and Microsoft Access as tools for helping inexperienced mechanic as the decision support system. During the test phase of system it never gave wrong detection according to the rules used. It can be concluded that car failure detection expert system is helpful although it might not give a complete guides and help as a human expert namely mechanical engineer do, but at least the expert system can give a temporary assistance to those who are in need of an instance help. Keywords: knowledge-base system, car failure detection, expert system, rule-based

An Expert System for Car Failure Diagnosis

Car failure detection is a complicated process and requires high level of expertise. Any attempt of developing an expert system dealing with car failure detection has to overcome various difficulties. This paper describes a proposed knowledge-based system for car failure detection. The paper explains the need for an expert system and the some issues on developing knowledge-based systems, the car failure detection process and the difficulties involved in developing the system. The system structure and its components and their functions are described. The system has about 150 rules for different types of failures and causes. It can detect over 100 types of failures. The system has been tested and gave promising results. Keywords—Expert system, car failure diagnosis, knowledge- based system, CLIPS.

Development of an Intelligent Car Engine Fault Troubleshooting System (CEFTS

Development of an Intelligent Car Engine Fault Troubleshooting System (CEFTS) , 2016

The mass production and wider use of automobiles and the incorporation of complex electronic technologies all indicate that the control of faults should be an integral part of engine design and usage. This paper discusses an expert system application for troubleshooting car engine faults using Auto-mechanic workshops in Calabar metropolis of Cross River State-Nigeria. The method of fact-finding called knowledge acquisition which is an expert system approach to extract facts was adopted in order to achieve good judgment in the use of heuristics among experts. The results are represented as a set of IF-THEN judgments that expert mechanics can rely mostly on in the troubleshooting process. The system depends on an automated matching process between symptoms and procedures. The paper developed a new prototype named Car Engine Fault Troubleshooting System (CEFTS) using C++ programming platform. The purpose of the developed prototype is to assist motorists and auto mechanics in fault troubleshooting of car engines by providing systematic and step-by-step analysis of failure symptoms and offering maintenance or service advice. The result of this development is expected to introduce a systematic and intelligent method in car engine troubleshooting and maintenance environments and also provides a troubleshooting framework for other researchers to work on.

THE DEVELOPMENT OF AN EXPERT CAR FAILURE DIAGNOSIS SYSTEM WITH BAYESIAN APPROACH

In this study we propose a model of an Expert System to diagnose a car failure and malfunction using Bayesian Approach. An expert car failure diagnosis system is a computer system that uses specific knowledge which is owned by an expert to resolve car problems. Our specific system consists of knowledge base and solution to diagnose failure of car from Toyota Avanza, one of the favorite car used in Indonesia today and applying Bayesian approach for knowing the belief of the solution. We build Knowledge representation techniques of symptoms and solution froman experts using production rules. The experimental results presented and we obtained that the system has been able to perform diagnosis on car failure, giving solution and also gives the probability value of that solution.

Expert System for Deciding a Solution of Mechanical Failure in a Car using Case-based Reasoning

The research implements a Case-based Reasoning method into an expert system to help mechanical team in an automobile service station in relation with making a specific decision to address customer complaints. A number of mechanistic criteria and potential alternatives are designed, using knowledge-based as a system backbone which is elaborated into four main general phases known as retrieving similar problems, reusing knowledge, revising solution and retaining experiences to fortify a best solution. Technically, an on line application system are constructed by Object-oriented Software Engineering (OOSE) model to serve end-users interactively. The result of this study indicates an on line expert system where the application not only can be effectively utilized by specialized team but also be able to serve as a knowledge bridge for other.

Artificial Intelligence Based Online Vehicles Troubleshooting System

Maintenance and repair of millennium car (a car manufactured from year 2000 upward), is most times is the grand challenge for most people that have them because of their embedded and electronics system in them. Maintenances of vehicles start from ability to understand the cause of some minor problems and procedures to fix it up. To prolong the life of the vehicles, there is need for the vehicle users to understand some simple preventive and corrective maintenance even if he/she would need the service of a conventional mechanics. In this case vehicle owners must be able to diagnose some minor mechanical and other related faults in their vehicle. This research study proposed a conceptual model for development of an Artificial Intelligence based online system to assist in diagnosing mechanical and other related problems in the millennium cars. This system if developed and implemented it would reduce the congestion in a mechanical workshop, also save money on maintenances since the system could render solution and some of the offers solution could be carried out by non-conventional mechanics.

An expert system for engine fault diagnosis: development and application

Journal of Intelligent Manufacturing, 1998

The mass production and wider use of automobiles and the incorporation of complex electronic technologies all indicate that the control of faults should be given an integral part of engine design and usage. Today, arti®cial intelligence (AI) technology is widely suggested for systematic diagnosis of faults where the amount of well-de®ned diagnosis knowledge is vast and the sequence of steps required to identify the fault is very long. This article describes on an expert system application for automotive engines. A new prototype named EXEDS (expert engine diagnosis system) has been developed using KnowledgePro, an expert system development tool, and run on a PC. The purpose of the prototype is to assist auto mechanics in fault diagnosis of engines by providing systematic and step-by-step analysis of failure symptoms and oering maintenance or service advice. The result of this development is expected to introduce a systematic and intelligent method in engine diagnosis and maintenance environments.