Abstract: An apparatus and method for detecting structural and material defects in a fastener driven during a manufacturing process includes a driving tool capable of recording an angle-torque trace during the driving of the fastener and a machine learning engine operably connected to the driving tool for analyzing the recorded angle-torque trace. The machine learning engine can be provided with a number of sample angle-torque traces from sample fasteners and can self-determine a stored trace including tolerances for acceptable angle-torque trace data from the samples in an unsupervised learning process or protocol without the need for defined anomalous and non-anomalous samples being provided to the machine learning engine.

Abstract: An apparatus and method for detecting structural and material defects in a fastener driven during a manufacturing process includes a driving tool capable of recording an angle-torque trace during the driving of the fastener and a machine learning engine operably connected to the driving tool for analyzing the recorded angle-torque trace. The machine learning engine can be provided with a number of sample angle-torque traces from sample fasteners and can self-determine a stored trace including tolerances for acceptable angle-torque trace data from the samples in an unsupervised learning process or protocol without the need for defined anomalous and non-anomalous samples being provided to the machine learning engine.

Abstract: A system and method for monitoring viscosity changes of a fluid stored in a volume are provided. The system includes a flexible chamber configured to receive and hold the fluid, a motion generator configured to induce a wave motion within the fluid, at least one sensor affixed at least in part to a portion of the flexible chamber and configured to measure at least a strain on a portion of the flexible chamber and generate an associated strain output. The strain output is effectuated by the wave motion of the fluid within the flexible chamber and correlates to a viscosity value of the fluid. A computer or controller is configured to receive the strain output from the sensor at a given time, compare the viscosity value associated with the strain output to a reference viscosity value, and determine whether to adjust the wave motion generated by the motion generator.

Abstract: A system and method for monitoring viscosity changes of a fluid stored in a volume are provided. The system includes a flexible chamber configured to receive and hold the fluid, a motion generator configured to induce a wave motion within the fluid, at least one sensor affixed at least in part to a portion of the flexible chamber and configured to measure at least a strain on a portion of the flexible chamber and generate an associated strain output. The strain output is effectuated by the wave motion of the fluid within the flexible chamber and correlates to a viscosity value of the fluid. A computer or controller is configured to receive the strain output from the sensor at a given time, compare the viscosity value associated with the strain output to a reference viscosity value, and determine whether to adjust the wave motion generated by the motion generator.

Abstract: One embodiment of the present invention is a method for constructing a post-patient collimator for a computed tomographic (CT) imaging system, the method including steps of: edge welding collimator plates to a top rail using at least one directed energy beam welder; and edge welding the collimator plates to a bottom rail, using the at least one directed energy beam welder. The above described embodiment provides an efficient and less expensive method for manufacturing a post-patient collimator for a CT imaging system than embodiments requiring use of precision combs for accurately positioning the plates.