東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Fault diagnostics for intelligent ve...

Ganguli, Ankur.

FindBook

Google Book

Amazon

博客來

Fault diagnostics for intelligent vehicle applications.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Fault diagnostics for intelligent vehicle applications./
作者:	Ganguli, Ankur.
面頁冊數:	152 p.
附註:	Source: Dissertation Abstracts International, Volume: 65-02, Section: B, page: 0986.
Contained By:	Dissertation Abstracts International65-02B.
標題:	Engineering, Mechanical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3121835
ISBN:	0496691868

Fault diagnostics for intelligent vehicle applications.
Ganguli, Ankur.

Fault diagnostics for intelligent vehicle applications. - 152 p.

Source: Dissertation Abstracts International, Volume: 65-02, Section: B, page: 0986.

Thesis (Ph.D.)--University of Minnesota, 2004.

Highway safety and traffic congestion issues have motivated a tremendous amount of research in the area of vehicle/highway automation. The research objective of this thesis is the development of fault diagnostic systems that can monitor the health of sensors on an automated vehicle and identify the source of any fault that occurs.

ISBN: 0496691868Subjects--Topical Terms:

783786
Engineering, Mechanical.

Fault diagnostics for intelligent vehicle applications.
LDR:03310nmm 2200349 4500 001 1839317
005 20050627125018.5
008 130614s2004 eng d
020 $a 0496691868
035 $a (UnM)AAI3121835
035 $a AAI3121835
040 $a UnM $c UnM
100 1 $a Ganguli, Ankur. $3 1927713
245 1 0 $a Fault diagnostics for intelligent vehicle applications.
300 $a 152 p.
500 $a Source: Dissertation Abstracts International, Volume: 65-02, Section: B, page: 0986.
500 $a Adviser: Rajesh Rajamani.
502 $a Thesis (Ph.D.)--University of Minnesota, 2004.
520 $a Highway safety and traffic congestion issues have motivated a tremendous amount of research in the area of vehicle/highway automation. The research objective of this thesis is the development of fault diagnostic systems that can monitor the health of sensors on an automated vehicle and identify the source of any fault that occurs.
520 $a A new fault diagnostics methodology is developed for LTI systems that can be implemented using Linear Matrix Inequalities (LMIs). The LMI formulation provides for explicit calculation of the fault detection filter matrix and can be used for sensor health monitoring. The conditions required on the system for application of the methodology are only mildly stronger than observability.
520 $a The above methodology is used to develop a fault diagnostic system for lateral vehicle sensors and implemented on a Navistar truck at the MnRoad research facility. Results based on experimental data show that the lateral diagnostic system is able to monitor the health of the GPS, gyroscope and lateral accelerometer on the truck.
520 $a Longitudinal vehicle dynamic models can be highly nonlinear. A systematic fault diagnostics methodology for a class of nonlinear systems is developed. The approach involves extending the LTI FDI methodology, discussed above, to Lipschitz nonlinear systems. Again, the LMI formulation provides for explicit calculation of the fault detection filter matrix so that stability and directionality are preserved even in the presence of a Lipschitz nonlinearity.
520 $a The above nonlinear FDI technique is used to develop a fault diagnostic system for the longitudinal dynamics. The longitudinal dynamics considered includes a parametric engine model. A parameter identification algorithm is developed which uses data obtained from simple on-the-road tests and provides parameters for any particular engine. The FDI system is tested using experimental data and is shown to adequately monitor the health of the engine rpm sensor, the manifold pressure sensor and the velocity sensor.
520 $a This research project makes fundamental contributions to the field of fault diagnostics by developing systematic fault diagnostic methods for linear systems and for a class of nonlinear systems. It also addresses some of the major challenges in developing reliable fault diagnostic systems for automated vehicle applications.
590 $a School code: 0130.
650 4 $a Engineering, Mechanical. $3 783786
650 4 $a Engineering, Automotive. $3 1018477
650 4 $a Engineering, Civil. $3 783781
690 $a 0548
690 $a 0540
690 $a 0543
710 2 0 $a University of Minnesota. $3 676231
773 0 $t Dissertation Abstracts International $g 65-02B.
790 1 0 $a Rajamani, Rajesh, $e advisor
790 $a 0130
791 $a Ph.D.
792 $a 2004
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3121835