GASP: Gap Analysis for Spark Plug

Spark plugs are vital components in a variety of industries, yet their fault diagnosis is still performed manually. We propose a vision-based, low-power spark plug fault diagnosis system. We present two use cases for the designed system. The first use case involves gap calculation at the manufacturing and segregation unit thereby assisting in industrial automation. The second use case demonstrates the application of the designed vision-based system for the diagnosis of different states of the spark plug along with the gap analysis thus assisting the maintenance personnel to recognize faulty pieces.