{"title":"旋翼机状态识别的运动原语视角","authors":"Umberto Saetti, Jonathan D. Rogers","doi":"10.4050/f-0076-2020-16266","DOIUrl":null,"url":null,"abstract":"\n An alternative approach to regime recognition that is based on the notion of motion primitives is developed. The algorithm developed is non-causal and leverages the ideas of maneuvers and trims as defined in a motion primitive context. The algorithm functions in three major steps. Given a state and control input time history obtained from flight data, the first step consists of classifying the state and control time history into trim and maneuver segments. The second step leverages the information in the trim state and control vectors to classify each trim segment into a particular trim condition based on conditional (if-else-if) logic. The third step entails the classification of each maneuver segment (flown between two trim segments) as a particular maneuver condition. Importantly, maneuver classification leverages dynamic time warping in order to compensate for rate and time duration variations. Accuracy of the proposed algorithm is evaluated using SH-60B simulated flight data. Operation of the algorithm is also demonstrated using real-world piloted flight test data from a generic utility helicopter.\n","PeriodicalId":293921,"journal":{"name":"Proceedings of the Vertical Flight Society 76th Annual Forum","volume":"333 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Motion Primitive Perspective on Rotorcraft Regime Recognition\",\"authors\":\"Umberto Saetti, Jonathan D. Rogers\",\"doi\":\"10.4050/f-0076-2020-16266\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n An alternative approach to regime recognition that is based on the notion of motion primitives is developed. The algorithm developed is non-causal and leverages the ideas of maneuvers and trims as defined in a motion primitive context. The algorithm functions in three major steps. Given a state and control input time history obtained from flight data, the first step consists of classifying the state and control time history into trim and maneuver segments. The second step leverages the information in the trim state and control vectors to classify each trim segment into a particular trim condition based on conditional (if-else-if) logic. The third step entails the classification of each maneuver segment (flown between two trim segments) as a particular maneuver condition. Importantly, maneuver classification leverages dynamic time warping in order to compensate for rate and time duration variations. Accuracy of the proposed algorithm is evaluated using SH-60B simulated flight data. Operation of the algorithm is also demonstrated using real-world piloted flight test data from a generic utility helicopter.\\n\",\"PeriodicalId\":293921,\"journal\":{\"name\":\"Proceedings of the Vertical Flight Society 76th Annual Forum\",\"volume\":\"333 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Vertical Flight Society 76th Annual Forum\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4050/f-0076-2020-16266\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Vertical Flight Society 76th Annual Forum","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4050/f-0076-2020-16266","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Motion Primitive Perspective on Rotorcraft Regime Recognition
An alternative approach to regime recognition that is based on the notion of motion primitives is developed. The algorithm developed is non-causal and leverages the ideas of maneuvers and trims as defined in a motion primitive context. The algorithm functions in three major steps. Given a state and control input time history obtained from flight data, the first step consists of classifying the state and control time history into trim and maneuver segments. The second step leverages the information in the trim state and control vectors to classify each trim segment into a particular trim condition based on conditional (if-else-if) logic. The third step entails the classification of each maneuver segment (flown between two trim segments) as a particular maneuver condition. Importantly, maneuver classification leverages dynamic time warping in order to compensate for rate and time duration variations. Accuracy of the proposed algorithm is evaluated using SH-60B simulated flight data. Operation of the algorithm is also demonstrated using real-world piloted flight test data from a generic utility helicopter.