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Concrete manufacturer turns to laser profiling for quality assurance

A manufacturer of pre-stressed concrete is using laser displacement sensors from Micro-Epsilon to measure the minimum profile depth of pre-stressed steel, which is critical to the quality and resistance of pre-stressed concrete.

Designed for the displacement measurement of difficult profiles on difficult target surfaces, the optoNCDT series of laser sensors are part of an inspection system developed by systems integration specialist, InSystems Automation. The inspection system checks the profile depth of incoming batches and continuously records this information to a database. The profiling is rolled onto the pre-stressed steel using an imprint roller. This means that the profile depth must be inspected across the complete range of the imprint roller.

The measuring system consists of an optoNCDT 1700 laser displacement sensor, which is mounted to a linear axis and a driven roller prism for inputting the pre-stressed steel. By moving the sensor along the linear axis, measurements are recorded and combined with a two-dimensional profile over the complete length of the imprint roller. The software calculates the profile depth for each imprint. The system measures profile depth to a very tight tolerance of 0.03mm. Repeatability of the measurement system is +/- 0.005mm, although Micro-Epsilon’s higher precision optoNCDT 2300 laser sensor can be used if higher repeatability is required. An extensive database provides full supplier and batch traceability of the pre-stressed steel used.

The optoNCDT 1700 laser displacement sensor is self-contained and has no external electronics. With no separate controller to mount, machine builders and system integrators can reduce the costs associated with wiring the sensors and free up space in their control cabinets. The sensor has a controller that automatically compensates in real time for difficult-to-measure surfaces such as shiny metal. The sensor can be used for inline and offline quality inspection tasks, dynamic part profiling and part recognition.


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