In-process Detection of Fastener Grip Length Using Embedded Mobile Wireless Sensor Network-based Pull Type Tools

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: integrating a strain gage, an LVDT, a pressure sensor, and a mote on a pull-type pneumatic tool; monitoring process parameters coming from embedded sensors communicated wirelessly and generating process signatures in real-time; detecting anomalies in real-time in the process signatures for quality problems related to the grip length deviation. A feature extraction-based methodology is employed to make decisions for grip length deviations in the form of normal grip, over grip, and under grip.