An innovative decision rule approach to tyre pressure monitoring

•An innovative decision rule-based approach to tyre monitoring.•The approach relies on the Dominance-based Rough Set Approach.•Two analysis levels: pressure-oriented and temperature-oriented.•The approach has been validated within an important travelling company.•Real-world tests showed that the app...

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Veröffentlicht in:Expert systems with applications 2019-06, Vol.124, p.252-270
Hauptverfasser: Egaji, Oche Alexander, Chakhar, Salem, Brown, David
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Brown, David
description •An innovative decision rule-based approach to tyre monitoring.•The approach relies on the Dominance-based Rough Set Approach.•Two analysis levels: pressure-oriented and temperature-oriented.•The approach has been validated within an important travelling company.•Real-world tests showed that the approach reduced substantially false alarms. Tyres are one of the most important safety components on a vehicle. Ignoring or failing to correctly set the tyre pressure may lead to accidents, and can affect the vehicle’s fuel efficiency and tyre lifespan. Hence, there is a need for a Tyre Pressure Monitoring System (TPMS) that can effectively monitor the tyre condition. The current threshold-based TPMSs are characterised by a high number of false alarms. This is mainly due to: (i) the non-static and dynamic relationship between tyre pressure and temperature; and, (ii) the measurement error of the pressure/temperature sensors that are used for data collection. In this paper, we propose an innovative decision rule-based approach to tyre monitoring. This approach relies on the Dominance-based Rough Set Approach (DRSA), which is a well-known multicriteria classification and preference learning method. The DRSA takes a decision table as an input and it generates a collection of if-then decision rules as an output. The issue caused by the dynamic pressure/temperature relationship is solved by fixing one of the parameters and then generating the decision rules based on the other parameter. The problem of false alarms is solved by a discretisation of the scale of the fixed parameter. Based on these solutions, we designed two types of analysis levels: pressure-oriented analysis and temperature-oriented analysis. The proposed approach has been validated and implemented within an important travelling company that operates in the South of England. The real-world tests showed that the proposed approach has improved the current system and has led to a substantial reduction of false alarms.
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Tyres are one of the most important safety components on a vehicle. Ignoring or failing to correctly set the tyre pressure may lead to accidents, and can affect the vehicle’s fuel efficiency and tyre lifespan. Hence, there is a need for a Tyre Pressure Monitoring System (TPMS) that can effectively monitor the tyre condition. The current threshold-based TPMSs are characterised by a high number of false alarms. This is mainly due to: (i) the non-static and dynamic relationship between tyre pressure and temperature; and, (ii) the measurement error of the pressure/temperature sensors that are used for data collection. In this paper, we propose an innovative decision rule-based approach to tyre monitoring. This approach relies on the Dominance-based Rough Set Approach (DRSA), which is a well-known multicriteria classification and preference learning method. The DRSA takes a decision table as an input and it generates a collection of if-then decision rules as an output. The issue caused by the dynamic pressure/temperature relationship is solved by fixing one of the parameters and then generating the decision rules based on the other parameter. The problem of false alarms is solved by a discretisation of the scale of the fixed parameter. Based on these solutions, we designed two types of analysis levels: pressure-oriented analysis and temperature-oriented analysis. The proposed approach has been validated and implemented within an important travelling company that operates in the South of England. 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Tyres are one of the most important safety components on a vehicle. Ignoring or failing to correctly set the tyre pressure may lead to accidents, and can affect the vehicle’s fuel efficiency and tyre lifespan. Hence, there is a need for a Tyre Pressure Monitoring System (TPMS) that can effectively monitor the tyre condition. The current threshold-based TPMSs are characterised by a high number of false alarms. This is mainly due to: (i) the non-static and dynamic relationship between tyre pressure and temperature; and, (ii) the measurement error of the pressure/temperature sensors that are used for data collection. In this paper, we propose an innovative decision rule-based approach to tyre monitoring. This approach relies on the Dominance-based Rough Set Approach (DRSA), which is a well-known multicriteria classification and preference learning method. The DRSA takes a decision table as an input and it generates a collection of if-then decision rules as an output. 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source Elsevier ScienceDirect Journals Complete - AutoHoldings
subjects Accidents
Alarms
Automotive parts
Data acquisition
Data collection
Dominance-based rough set approach
Dynamic pressure
Error analysis
Error detection
False alarms
Monitoring
Multiple criterion
Parameters
Rough sets
Temperature sensors
Tires
Tyre pressure
Tyre pressure monitoring system
Tyre temperature
title An innovative decision rule approach to tyre pressure monitoring
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