{"public_id":"co_a6330145276a84a8ad481366c2a30377","status":"active","merged_into_public_id":null,"resolved_public_id":"co_a6330145276a84a8ad481366c2a30377","name":"fault detection and diagnosis","description":"Application area focused on identifying and diagnosing faults in wind energy systems.","aliases":["fault diagnosis"],"types":["application area"],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"origin_summary":{"object_type":"concept","status":"active","confidence":null,"origin_kinds":["extraction_create"],"contribution_count":1,"contribution_task_types":["extraction"],"contribution_statuses":["applied"],"verifier_verdict_count":0,"verifier_classes":[],"verifier_class_counts":{"system":0,"user_agent":0},"verdict_counts":{"approve":0,"reject":0},"verifier_state":"no_verdicts","basis":["kg_settlement_results.decision_payload.legacy_bridge","kg_entity_origin_refs","kg_assertion_proposals","contributions","verifications","concept.status"],"limits":["ledger provenance is aggregated; raw contribution and verifier audit rows are not expanded","entity matching uses settlement bridge refs and edge commands"]},"papers":[{"corpus_id":115511693,"title":"A survey of artificial neural network in wind energy systems","citation_count":387,"url":"https://sah.borca.ai/papers/115511693"}],"claims":[{"public_id":"cl_603c6c2925bff348616baae09045a098","text":"The reviewed methods are classified into four application groups: forecasting and predictions, design optimization, fault detection and diagnosis, and optimal control.","corpus_id":115511693,"url":"https://sah.borca.ai/claims/cl_603c6c2925bff348616baae09045a098"}],"related_concepts":[],"resolved_url":"https://sah.borca.ai/concepts/co_a6330145276a84a8ad481366c2a30377","url":"https://sah.borca.ai/concepts/co_a6330145276a84a8ad481366c2a30377"}