Mechanical Shock may be defined as a sudden change in velocity and is a major design consideration for a wide variety of systems. The structural response to mechanical shock must be measured and characterized during the engineering development of these systems so that they will survive all environments during their service lifetime. These environments may include (but are not limited to): handling and transportation shocks, shocks during system delivery to a target, and shock originating from an explosive or pyrotechnic event. These different shock environments have a velocity change range from about 1 meter per second to 51 meters per second (40 – 2000 ips). Conversely acceleration magnitudes range from <1 g in earthquakes to 200,000 g in differentiated LDV measured pyroshocks. This Mechanical Shock Testing & Data Analysis Short Course will provide a comprehensive treatment of mechanical shock test techniques and data analysis for shocks from 100g to 200,000g. Mechanical shock instrumentation from low frequency techniques for underwater explosions to high frequency techniques for ballistic shock will be reviewed in detail along with the techniques and data analyses to evaluate the instrumentation measuring these shocks.
This course is highly recommended for all lead technicians and managers of environmental test laboratories. Managers and engineers on projects requiring shock testing will benefit greatly.
Mechanical shock test techniques from package testing to conventional mechanical shock machines to pyroshock simulations and Hopkinson bar techniques will be presented. Design procedures for mechanical shock equipment will be discussed in detail. Where possible, theoretical bases for mechanical shock test techniques are provided. Mechanical shock data analysis and interpretation will be a major focus of all presentations and discussions and will include shock data examination and editing as well as interpolation, trend removal, and integration with MATLAB. This course includes the state-of-the-art shock data evaluation techniques to detect “BAD” data, techniques to salvage “BAD” data and requirement for data acquisition systems to collect “GOOD” data.