Application of Uncertainty Methods for the Design of Multi-Parameter Macro-Measurement Systems

Multi-parameter macro-measurement systems are large scale, complex measurement systems designed to measure more than one parameter from a given test specimen. The purpose of applying analytical uncertainty methods during the design process is to increase the accuracy of the overall measurements without incurring the costs of building a prototype. An approach to implementing the law of propagation of uncertainty to the design of multi-parameter macro-measurement systems is formulated. It includes studying the relative uncertainty contributions of each individual measurement to the overall measurement and primarily incorporates symbolic sensitivity analyses and secondarily numerical (or statistical) analyses, to determine critical individual measurements and sources of uncertainty to the overall measurements. The matrix notation established is formulated to prepare the information for computer implementation. An example application to the measurement of vehicle inertia properties is provided.