Application of artificial intelligence techniques for fault diagnostics of autonomous underwater vehicles

Inzartsev, Alexander; Pavin, Alexander; Kleschev, Alexander; Грибова, В. В.; Eliseenko, Grigory

doi:10.1109/oceans.2016.7761098

Cited by 19 publications

(11 citation statements)

References 5 publications

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“…The work presents the ontology of the anomalous processes diagnosis as a result of a synthesis of modern decision support methods for diagnosis (published in available literature) and our many years of experience of intelligent systems development for diagnosis in various domainsmedicine, agriculture, robotics, and so forth. 21,26,35 The need to create such a unified ontology of a problem area is dictated by the need to reduce the complexity of creating intelligent DSS for diagnosis of processes in various domains, in which the ontological approach is used as a method of implementing such systems. In Section 2 it was discussed that the choice of this implementation method is due to modern requirements for systems with KBs.…”

Section: Discussionmentioning

confidence: 99%

“…So, the ontologies for diagnosing faults of an autonomous underwater robot and ontology for diagnosing the state of crops were created. 26,35 The universal ontology of anomalous processes diagnosis summarizes all the results obtained. Currently, a diagnostic solver based on this ontology is being implemented.…”

Section: Discussionmentioning

confidence: 99%

“…The overload of the AUUV engine can be caused by boundary modes of movement, characterized by increased load on the screw or jamming of the engine shaft due to the fact that fish, fishing net or grass got in. As for AUUV, engine overload caused by jamming of the engine shaft can be eliminated by rotating the engine in the opposite direction 26 A typical problem of the onset of diarrhea is the preceding event: the time of ingestion of “suspicious food” is 3

\pm

3 h before the onset of diarrhea 27,28 .…”

Section: Methodsmentioning

confidence: 99%

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Ontology of anomalous processes diagnosis

Грибова

Шалфеева

2020

Int J Intell Syst

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The diagnosis is complex in domains where processes occur over time inside systems or objects, changing and affecting other processes and characteristics. A large number of knowledge-based systems have been developed to increase the efficiency of the diagnostic process. But the models of knowledge of such systems do not simultaneously take into account all types of temporal relationships: changes in the values of attributes over time, taking into account the time intervals that have passed from the moments when the process began to develop and external influences, and so forth. The article considers the universal ontology of knowledge about the diagnosis of processes in various domains as a generalization and the result of many years of experience of the authors in the creation of intelligent systems for the diagnosis of processes. The ontology allows us to formalize anomalies as developing internal processes that are not inherent in a normally functioning system. On its basis (in its terms) knowledge bases and software components for decision support systems are constructed. In the case of a need for a domain-oriented ontology, it will only be necessary to redefine some concepts and relations which are features of specific domains.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

\pm

3 h before the onset of diarrhea 27,28 .…”

Section: Methodsmentioning

confidence: 99%

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Ontology of anomalous processes diagnosis

Грибова

Шалфеева

2020

Int J Intell Syst

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“…However, there are growing industry investments in autonomous systems for routine inspection and intervention activities, which promise to reduce long-term installation maintenance costs by taking on tasks previously requiring manned vessels and ROVs. 16 Improvements in AUV monitoring and emergency systems are increasing platform reliability and mission success rate (Inzartsev et al, 2016).…”

Section: Thruster-driven Subsurface Vehiclesmentioning

confidence: 99%

Future Vision for Autonomous Ocean Observations

Whitt¹,

Pearlman²,

Polagye

et al. 2020

Front. Mar. Sci.

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Whitt et al. Future of Autonomous Ocean Observations reductions. Cost reductions could enable order-of-magnitude increases in platform operations and increase sampling resolution for a given level of investment. Energy harvesting technologies should be integral to the system design, for sensors, platforms, vehicles, and docking stations. Connections are needed between the marine energy and ocean observing communities to coordinate among funding sources, researchers, and end users. Regional teams should work with global organizations such as IOC/GOOS in governance development. International networks such as emerging glider operations (EGO) should also provide a forum for addressing governance. Networks of multiple vehicles can improve operational efficiencies and transform operational patterns. There is a need to develop operational architectures at regional and global scales to provide a backbone for active networking of autonomous platforms.

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“…Knowledge‐based systems allow for humans to automatically generate rule sets that a vehicle can use to form expectations during a mission. Inzartsev, Pavin, Kleschev, Gribova, and Eliseenko () present a set of such techniques for the diagnosis of faults onboard AUVs.…”

Section: Meeting the End User Requirementsmentioning

confidence: 99%

Review of mission planning for autonomous marine vehicle fleets

Thompson

Guihen

2018

Journal of Field Robotics

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The deployment of a fleet of autonomous marine vehicles (AMVs) allows for the parallelisation of missions, intervehicle support for longer deployment times, adaptability and redundancy to in situ mission changes, and effective use of the right vehicle for the right purpose. End users and operators of AMVs face challenges in planning complex missions due to the limitations of their vehicles, dynamic, operationally constrictive, and unstructured environments, and in minimising risks to equipment, the mission, and personnel. Automated mission planning for AMV fleets can be a tool to reduce the complexity of programming vehicle tasking, and to perform validity assessments for end user-specified goals, allowing the operator to focus on risk assessment. We present a critical review of the current advances in automated planning for AMV fleets, investigating the limitations of available state-ofthe-art tools and providing a road map of the goals and challenges based on analysis of field reports and end user initiatives.

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Application of artificial intelligence techniques for fault diagnostics of autonomous underwater vehicles

Cited by 19 publications

References 5 publications

Ontology of anomalous processes diagnosis

Ontology of anomalous processes diagnosis

Future Vision for Autonomous Ocean Observations

Review of mission planning for autonomous marine vehicle fleets

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