Technology and tank maintenance: An AI-based diagnostic system for the Abrams tank

被引：3

作者：

Baur, E ^{[1
]}

Dumer, J ^{[1
]}

Hanratty, T ^{[1
]}

Helfman, R ^{[1
]}

Ingham, H ^{[1
]}

机构：

[1] USA,RES LAB,AMSRL,SC,II,ABERDEEN PROVING GROUND,MD 21005

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 1996年 / 11卷 / 02期

关键词：

D O I：

10.1016/0957-4174(96)00031-0

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The U.S. Army holds title to one of the most envied weapon systems developed-the Abrams main battle tank (MBT). Militarily, this weapon represents the epitome of lethality and survivability on today's modern battlefield To combat difficulties associated with maintaining this sophisticated weapon, the U.S. Army Research Laboratory (ARL) and the U.S. Army Ordnance Center and School (OC&S) combined technologies from artificial intelligence with Army tank maintenance doctrine to develop an expert diagnostic system to assist Abrams' mechanics. The system, known as turbine engine diagnostics (TED), targets the mechanic's ability to effectively and efficiently diagnose and repair the Abram's engine and transmission The OC&S estimates that TED will save over $8 million annually by enhancing the Abrams mechanic's troubleshooting capabilities. Limited fielding of TED began in July 1994 to 60 National Guard units in 30 stares. Active units of the U.S. Army will receive TED in fiscal year 1996. This paper examines the relevant background, development issues, system overview test results, and future efforts surrounding the TED project.

引用

页码：99 / 107

页数：9