The document describes the components and process of an expert system for car noise diagnosis. The system uses a knowledge base collected from mechanics to store over 150 production rules relating different car noises to failures and causes. The expert system applies forward-chaining inference to match a user-reported noise to applicable rules and identify the most likely failure based on its knowledge.

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Keywords- Expert system (ES), Artificial Intelligence (AI), Car
Failure Diagnosis System (CNDS), Knowledge-Based System
(KBS), Inference engine.
Expert system components
Structure of the car noise diagnosis system
A. User Interface
User interface goes about as the primary correspondence unit for
the master framework, from which were client can ask questions and
framework can create solutions. To assemble the user interface a PC
programming dialect or an instrument is needed. The master
arrangement of auto commotion determination utilizes the C-
programming dialect to fabricate the framework. The user interface is
represented as a menu which displays the questions to the user and the
user answers with Yes or No.
B. Explanation Facility
Illustrates to the user how and why the system gave a certain
cause for the failure, i.e. explains the reasoning of the system to the
user.
C. Knowledge Base
The knowledge of the system is collected from mechanic
experts, specialized books, and from different car websites. The
knowledge base contains about 150 production rules for different types
of car failures and causes. Knowledge base in the expert system acts
as a storage unit which stores the data given as input.
Advance Car Noise Diagnosis System (CNDS) Process
The CNDS is a system with multi-tasking capabilities that is
directive for car fault detection. It Provides information sources,
knowledge interaction and evaluation regarding the technical
process to be tackled. Such tasks are failure tracing, failure
recognition, and customer advising that requires it to adopt various
types of modules. Each module’s goal is achieved by applying a
number of processes. Figure shows the system components in a
process level. One of the main characteristics of the CNDS is the
addition of the database to be in parallel with the system’s
knowledge base. An interaction is held between the knowledge base
and the database including information transfer about the processes
under execution. The database works as a temporary storage due to
its continuous change in state. The knowledge base of the system
encompasses both the derived and the heuristic knowledge about
the required car failure diagnostic process. The inference engine is
built to do the reasoning based on several algorithmic procedures
that enable it to reach the required conclusion.
Fig. Advance CFDS processes
Conclusion
In this Poster, Expert system (ES), Artificial Intelligence
(AI), Car Noise Diagnosis System (CNDS), Knowledge-Based
System (KBS), Inference engine are presented. The proposed
CNDS is utilized to assist inexperienced mechanics or
individuals who face sudden failure in the car and provide
decision support system. In addition, CNDS is considered as an
interactive training tool that can provide expert guidance in car
fault detection. Using this system, Fault diagnosis in technical
systems has done a lot of theoretical and practical attention.
Diagnosis is a complex reasoning activity, which is currently one of
the domains where Artificial Intelligence techniques have been
successfully applied as these techniques use association rules,
reasoning and decision making processes as would the human brain
in solving diagnostic problems.
Reference
• http://www.rebuilt-auto-engines.com
• http://www.speeding.co.uk/acatalog/engine.html
• Youtube; https://www.youtube.com/watch?v=RKjdnQ0sHQc
• http://www.writing.engr.psu.edu/posters.html
Sanjay Kumar, Sumanth, Surya kiran, Tulasiram, Venkata Surya Kumar, Viral kumar, (Group-6)
Presents Poster on
‘An Expert System for Car Noise Diagnosis’
Instructor
Ileana Costea, Ph.D.
MSE MSE614 SP2015
D. Inference Engine
When abnormal situation arises in the car, the KBS makes
inferences by deciding which rules are satisfied by facts stored in the
working memory and executes the rule with highest priority and
propose proper correcting solution. The rules whose patterns are
satisfied by facts in the working memory are stored in the agenda part
of the inference engine. The inference engine traces the applicable
facts that represent the corresponding symptoms (i.e. the observed
Variables or behavior) and apply them to the tagged rules. In the
proposed Car Noise Diagnosis System (CNDS), production-rules is the
chosen form for knowledge representation. Additionally, the inference
engine is the forward-chaining type (data driven mode) as shown in
Figure. Forward-chaining inference engine has the advantages of
producing solutions for the unformulated problems. In this type of
engine, the satisfactory facts that meet the rules conditions are
promoted to be triggered. All the applicable rules resulting from the
previous process make up the conflict set of rules to be implemented
according to specific order that enables solution generation.
Introduction
An Expert System is an artificial intelligence program that has
expert level knowledge about a particular domain and knows how
to use its knowledge to respond properly.
The Expert System (ES) is one of the leading
Artificial Intelligence (AI) techniques that have been adopted to
handle car failure detection. 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. Expert system on car noise
diagnosis system has the list of deficiencies in its database which
develops the relationship, standardized mean square slip, and
formant frequencies values between knowledge base and the user
quires to draw the inferences which will give the best possible
solution. Thus, systems can be highly useful in individuals and
mechanics for failure detection and training purposes. Moreover,
capturing and retaining valuable knowledge on such domain yield
more accurate and less time consuming models
Car Noise Diagnosis Expert System
Make the selection based on the noise heard
1. Abnormal Noise.
2.Chattering.
3.Clunk.
X. No idea of the noise.
Enter your selection according to the car state;
Working Memory
The noise is from engine
compartment
While starting engine
The problem is faulty starter drive
Production Rules
Rule 1
Rule 2
Rule 3
Rule 4
Fig- The production system after Rule 1 is fired
Rule 1: IF the noise come when starting engine from the engine compartment,
THEN the problem is Faulty starter drive and inspect starter drive.
Rule 2: IF the noise come from under the vehicle while changing gears,
THEN the problem is damaged U-Joint and inspect U-Joint.
Rule 3: IF the noise come from tire or wheel or wheel area,
THEN the problem is Brake Pad/Shoe contaminated with grease or brake
fluid and inspect brake pad/Shoe front.
Rule 4: IF the noise come from front of vehicle while accelerating,
THEN the problem is worn or damaged CV half shaft and inspect CV half-
shaft.
Fig-Four assumed rules in agenda