By Jean Thilmany, Associate Editor R esearchers in fields ranging from mechanical engineering to the health sciences depend on raw data to learn about a process or structure they're investigating. A doctor, for example, might be interested in measuring and studying brain activity to gain insight into reactions to a stimulus. A mechanical engineer may want a record of events as an engine's torque level varies over time. The results may lead to a refined engine design for greater power or efficiency. The feedback they give is measured as a series of signals that serve as a kind of map to those interpreting the data.
People take pictures for a variety of purposes.
They document conditions, inspect objects, record events, or they take photos to do a detailed analysis. In the same way, data acquisition records sequential measurements that might be used to monitor a machine, test a product, or support research work. The robotics team at the Oak Ridge National Laboratories builds a computerized model of robotic parts, such as this robotic arm, then runs a series of data acquisition tests on a prototype to determine how the arm will move. Lonnie Love, a control engineer at Oak Ridge National Laboratories in Oak Ridge, Tenn., for example, has long used data acquisition to glean important information on how a robot will act in certain situations. He uses the data to program the controllers that power the robots made by the laboratory.