Equipment has been developed to test x-ray sensor designs suitable for texture analysis and plasticity prediction of rolled sheet in the production environment. A general method has been developed to optimize the complete sensor design by minimizing the rms error of the sensor's texture and property estimates for the sheet. A versatile reflection, x-ray diffraction sensor has been designed and built for the laboratory to test how accurately the optimized designs classify the quality of commercial rolled product. Experimental testing with the laboratory sensor was made on two sets of specimens: (1) a set of cold-rolled and annealed, interstitial-free steels; and (2) a set of hot-rolled, 3004 alloy aluminum sheets. Tests performed on the aluminum specimens showed that an optimized design sampling the mid-plane texture is able to classify the quality of the set's members; an optimized design sampling the surface texture can also perform the same classification. Tests performed on the steel specimens showed that an optimized design sampling the mid-plane texture can predict the average r-value, r¯, and the 2-fold anisotropy measure, (r90-r0)/2, with an accuracy of s = 0.10 and 0.03, respectively; an optimized design sampling the surface texture of the sheet can predict the same plasticity measures with an accuracy of s = 0.18 and 0.06. As a whole, the work has demonstrated the following: (1) workable reflection sensors can be developed for certain industrial applications; however, optimized transmission sensors are generally superior because the mid-plane texture leads to more accurate predictions, (2) statistically reliable predictions of the bulk texture and plasticity of commercial sheet can be made using specialized sensor designs that measure 10 to 50 pole densities, and (3) the general method developed to optimize the sensor design significantly reduces the sensor error---by as much as 140% over the unoptimized designs.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.34689 |
| Date | January 1997 |
| Creators | Blandford, Peter. |
| Contributors | Szpunar, J. A. (advisor) |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Doctor of Philosophy (Department of Mining and Metallurgical Engineering.) |
| Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
| Relation | alephsysno: 001614280, proquestno: NQ37035, Theses scanned by UMI/ProQuest. |
Page generated in 0.0025 seconds