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Friday, August 29, 2014

Rapid Data Acquisition Solves Manufacturer’s Pneumatic Valve Timing Issue

A manufacturer faced a major issue with a pneumatic-based system for rejecting faulty parts on its production line. Faulty-looking components that fail optical inspection are blown off the the line using a valve controlling an air jet, but the manufacturer discovered that the latency of the valve’s opening wasn’t optimal, so bad parts often kept moving down the line rather than being rejected as intended.

CAS Dataloggers supplied this manufacturing plant with a German rapid data acquisition system to help it solve a valve latency problem.

CAS Dataloggers supplied this manufacturing plant with a German rapid data acquisition system to help it solve a valve latency problem.

A solution was found in a high-speed data acquisition (DAQ) system from Germany’s Jäger Computergesteuerte Messtechnik GmbH (Lorsch) that enabled logging and analysis of valve latency data in order to get the timing of valve opening exactly right. Millisecond response times were optimized for the pneumatic-based quality control system using the datalogger. The solution was recommended by distributor CAS Dataloggers, based in Chesterland, Ohio.

The high-speed ADwin-Light-16 Real Time Data Acquisition and Control System from Jäger was used to measure response times from the time that air entered the valve to the time when the valve actually opened. The DAQ system was then used to trigger the manufacturing line.

Using this system, the line’s engineer found an effective way to approach the valve timing problem. The DAQ system’s analog inputs were connected to high-speed measurements from two pressure transducers, positioned upstream and downstream of the line. The continual data from the pressure sensors helped distinguish between 3 ms and 6 ms of valve openings and closures, which made a big difference in valve effectiveness, and the system allowed users to view this latency and exact frequency of missed incidences to provide real-time process monitoring.

Key to successful application of the data-acquisition system was its 32-bit digital signal processor, which used its own local memory to handle system management, data acquisition, on-line processing, and control of outputs. This way, the connected computer system resources were freed up for other tasks.

Real-time development was performed using the system’s ADbasic software. It gave access to all inputs and outputs as well as functions for floating-point operations, process control, and communication with a computer. A library with standard functions — including filtering, various examples for counter use, closed-loop controllers, and function generators — eased implementation. CAS DataLoggers also helped the user with programming advice to get the system working.

Using the DAQ system, the factory’s supervisory team was able to correct their line’s quality control problem by getting a highly-accurate view of its air valve flow behavior. The system oversaw the valve’s latency in real-time. The system’s local DSP executed these real-time processes independently of a PC, and the incorporated software handled programming for mathematical operations and functions, which were executed immediately after each sampling step.

 

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