In Process Detection of Fastener Grip Length Using Embedded Mobile Wireless Sensor Networks
In this paper, a diagnostics and root-cause analysis scheme for real-time monitoring of process quality of pull-type fastening operations is presented. The proposed approach encompasses (1) integrating a strain gage, an LVDT (Linear Variable Differential Transducer), a pressure sensor, and a mote on a pull-type pneumatic tool; (2) monitoring process parameters coming from embedded sensors communicated wirelessly via the mote and generating process signatures in real-time; and (3) detecting anomalies in real-time in the process signatures for quality problems related to the grip length deviation in pull-type fastening operations. A feature extraction-based diagnostic methodology is employed to make decisions in terms of grip length deviations in the form of normal grip, over grip, and under grip. The process signature of strain-over-displacement versus displacement has shown unique features that are extracted to determine the quality of the fastening process. In addition, air pressure is also continuously monitored in real-time during the process since it also affects the quality of the fastening operation. The overall architecture has been implemented on a Huck45 pull-type tool, which is a hand-held pneumatic fastening tool used extensively in the aerospace industry, with lock-bolt fasteners. The prototype has been tested under a variety of experimental settings in order to verify its effectiveness and validate its performance over a wide range of different sheet metal thicknesses used for fastening. The experiments have shown that the proposed approach is successful, with an accuracy of over 96%, in determining the quality of fastening operations and in communicating the quality information in real-time using a wireless network to a server. Overall, the proposed architecture has merits to (1) detect quality problems in real-time during the fastening process and (2) reduce post-process inspection, thereby improving quality while reducing cost. In addition, the proposed approach facilitates 100% data collection on each fastener as opposed to traditional statistical process control (SPC) techniques, which rely on sampling.
R. Anguswamy et al., "In Process Detection of Fastener Grip Length Using Embedded Mobile Wireless Sensor Networks," 2007 ASME International Mechanical Engineering Congress and Exposition November 2007, Seattle, Washington USA, American Society of Mechanical Engineers (ASME), Jan 2007.
Electrical and Computer Engineering
Keywords and Phrases
Automatic Inspection; Communication Systems; Wireless Networks
Library of Congress Subject Headings
Article - Conference proceedings
© 2007 American Society of Mechanical Engineers (ASME), All rights reserved.