| 1. |
- Warnquist, Håkan, 1982-, et al.
(författare)
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A Heuristic for Near-Optimal Troubleshooting Using AO*
- 2008
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Ingår i: Proceedings of the International Workshop on the Principles of Diagnosis.
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Konferensbidrag (refereegranskat)abstract
- When troubleshooting malfunctioning technical equipment, the task is to locate faults and make repairsuntil the equipment functions properly again. The AO* algorithm can be used to find troubleshootingstrategies that are optimal in the sense that the expected cost of repair is minimal. We have adaptedthe AO* algorithm for troubleshooting in the automotive domain with limited time. We propose a newheuristic based on entropy. By using this heuristic, near-optimal strategies can be found within a fixedtime limit. This is shown in empirical studies on a fuel injection system of a truck. In these results, theAO* algorithm using the new heuristic, performs better than other troubleshooting algorithms.
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| 2. |
- Warnquist, Håkan, 1982-, et al.
(författare)
-
Anytime Near-Optimal Troubleshooting Applied to a Auxiliary Truck Braking System
- 2009
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Ingår i: Proceedings of the 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes. - 9783902661463 ; , s. 1306-1311
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Konferensbidrag (refereegranskat)abstract
- We consider computer assisted troubleshooting of complex systems, for example of a vehicle at a workshop. The objective is to identify the cause of a failure and repair a system at as low expected cost as possible. Three main challenges are: the need for disassembling the system during troubleshooting, the difficulty to verify that the system is fault free, and the dependencies in between components and observations. We present a method that can return a response anytime, which allows us to obtain the best result given the available time. The work is based on a case study of an auxiliary braking system of a modern truck. We highlight practical issues related to model building and troubleshooting in a real environment.
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| 3. |
- Warnquist, Håkan, 1982-
(författare)
-
Computer-Assisted Troubleshooting for Efficient Off-board Diagnosis
- 2011
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This licentiate thesis considers computer-assisted troubleshooting of complex products such as heavy trucks. The troubleshooting task is to find and repair all faulty components in a malfunctioning system. This is done by performing actions to gather more information regarding which faults there can be or to repair components that are suspected to be faulty. The expected cost of the performed actions should be as low as possible.The work described in this thesis contributes to solving the troubleshooting task in such a way that a good trade-off between computation time and solution quality can be made. A framework for troubleshooting is developed where the system is diagnosed using non-stationary dynamic Bayesian networks and the decisions of which actions to perform are made using a new planning algorithm for Stochastic Shortest Path Problems called Iterative Bounding LAO*.It is shown how the troubleshooting problem can be converted into a Stochastic Shortest Path problem so that it can be efficiently solved using general algorithms such as Iterative Bounding LAO*. New and improved search heuristics for solving the troubleshooting problem by searching are also presented in this thesis.The methods presented in this thesis are evaluated in a case study of an auxiliary hydraulic braking system of a modern truck. The evaluation shows that the new algorithm Iterative Bounding LAO* creates troubleshooting plans with a lower expected cost faster than existing state-of-the-art algorithms in the literature. The case study shows that the troubleshooting framework can be applied to systems from the heavy vehicles domain.
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| 4. |
- Warnquist, Håkan, 1982-, et al.
(författare)
-
Planning as Heuristic Search for Incremental Fault Diagnosis and Repair
- 2009
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Ingår i: Proceedings of the Scheduling and Planning Applications Workshop (SPARK) at the 19th International Conference on Automated Planning and Scheduling (ICAPS).
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Konferensbidrag (refereegranskat)abstract
- In this paper we study the problem of incremental fault diagnosis and repair of mechatronic systems where the task is to choose actions such that the expected cost of repair is minimal. This is done by interleaving acting with the generation of partial conditional plans used to decide the next action. A diagnostic model based on Bayesian Networks is used to update the current belief state after each action. The planner uses a simplified version of this model to update predicted belief states. We have tested the approach in the domain of troubleshooting heavy vehicles. Experiments show that a simplified model for planning improves performance when troubleshooting with limited time.
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| 5. |
- Warnquist, Håkan, 1982-
(författare)
-
Troubleshooting Trucks : Automated Planning and Diagnosis
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis considers computer-assisted troubleshooting of heavy vehicles such as trucks and buses. In this setting, the person that is troubleshooting a vehicle problem is assisted by a computer that is capable of listing possible faults that can explain the problem and gives recommendations of which actions to take in order to solve the problem such that the expected cost of restoring the vehicle is low. To achieve this, such a system must be capable of solving two problems: the diagnosis problem of finding which the possible faults are and the decision problem of deciding which action should be taken.The diagnosis problem has been approached using Bayesian network models. Frameworks have been developed for the case when the vehicle is in the workshop only and for remote diagnosis when the vehicle is monitored during longer periods of time.The decision problem has been solved by creating planners that select actions such that the expected cost of repairing the vehicle is minimized. New methods, algorithms, and models have been developed for improving the performance of the planner.The theory developed has been evaluated on models of an auxiliary braking system, a fuel injection system, and an engine temperature control and monitoring system.
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| 6. |
- Warnquist, Håkan, 1982-, et al.
(författare)
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Troubleshooting when Action Costs are Dependent with Application to a Truck Engine
- 2008
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Ingår i: 10th Scandinavian Conference on Artificial Intelligence, SCAI 2008. - : IOS Press. - 9781586038670 ; , s. 68-75
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Konferensbidrag (refereegranskat)abstract
- We propose a troubleshooting algorithm that can troubleshoot systems with dependent action costs. When actions are performed they may change the way the system is decomposed and affect the cost of future actions. We present a way to model this by extending the traditional troubleshooting model with an additional state that describes which parts of the system that are decomposed. The proposed troubleshooting algorithm searches an AND/OR graph with the aim of finding the repair plan that minimizes the expected cost of repair. We present the heuristics needed to speed up the search and make it competitive with other troubleshooting algorithms. Finally, the performance of the algorithm is evaluated on a probabilistic model of a fuel injection system of a truck.We show that the expected cost of repair can be reduced when compared with an algorithm from previous literature.
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