Development and Field Evaluation of a Thin Sheet Inspection System.

Abstract

A multichannel recording system was designed and fabricated to simultaneously monitor, discriminate, and record four inspection frequencies. With this system, Lamb Wave models which are most sensitive to particular types of discontinuities can be selected. Laboratory tests demonstrated that the improved system can: (1) inspect a variety of materials such as cold rolled steels, stainless steels, ZR-CU-Mo alloys, and aluminum alloys in the thickness range of 0.060 in. to 0.110 in. and (2) detect small inclusions, slivers, and scale. Two field tests were performed. In the first test, a slow speed, high resolution study of 1100 feet of stainless steel sheets was conducted. The system was installed on the conveyor section of a variable speed sheet slitter. The sheets were about 43 in. by 120 in. and ranged in thickness from 0.030 in. to 0.060 in. Defects which represent a 3 percent thickness change were detected at an inspection speed of 30 ft./min. In the second test, 120,000 feet of coiled silicon steel were inspected on a coil slitter without curtailment of production at speeds of 100 ft./min. to 450 ft./min. The coils were 0.025 in. wide and ranged in thickness from 0.014 in. to 0.025 in. The system detected hot mill tears, laminations, and large inclusions. The laboratory and field tests demonstrated the capabilities of the Lamb Wave system for the detection of various types of discontinuities in thin sheets at high inspection rates without curtailment of production. (Author)

Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1971
Accession Number
AD0883606

Entities

People

  • I. R. Kraska
  • R. G. Prusinski

Tags

DTIC Thesaurus Topics

  • Alloys
  • Aluminum
  • Aluminum Alloys
  • Discontinuities
  • Field Tests
  • High Resolution
  • Inclusions
  • Inspection
  • Laboratory Tests
  • Production
  • Recording Systems
  • Stainless Steel
  • Steel
  • Test And Evaluation
  • Thickness

Readers

  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Metallurgy
  • Optical Fiber Sensing and Electromagnetic Propagation.