Laboratory and field tests on photo-electric probes and ultrasonic Doppler flow switch for remote control of turbidity and flowrate of a water-sand mixture flow


== Abstract ==

The paper describes the experimental apparatus and field tests carried on to remotely control through non-invasive and non-intrusive instruments turbidity and flowrate of a water-sand mixture flow conveyed by a pipeline. The mixture flow was produced by an innovative plant for seabed management. The turbidity was monitored by thru-beam infra-red photo-electric sensors, while flowrate was monitored by an ultrasonic Doppler flow switch. In a first phase, a couple of photo-electric sensors and a mechanical flow switch were preliminary tested in laboratory to verify installations concerns and measurement repeatability and precision. After preliminary test completion, photo-electric sensors and mechanical flow switch were installed in the real scale plant. Since the mechanical flow switch did not reach high reliability, an ultrasonic Doppler flow switch was identified and tested as alternative. Then, two couple of photo-electric sensors and ultrasonic Doppler flow switch were installed and tested on two pipelines of the plant. Turbidity and minimum flow signals produced by the instruments were integrated in the PLC logic for the automatic management of the plant. The paper also shows how ultrasonic Doppler flow switch measurement repeatability was negatively affected by the presence of the other ultrasonic Doppler flow switch working in a close pipeline and installed inside a steel casing.


== Original document ==

The different versions of the original document can be found in:

* [http://hdl.handle.net/11585/606919 http://hdl.handle.net/11585/606919] under the license https://creativecommons.org/licenses/by

* [https://iopscience.iop.org/article/10.1088/1742-6596/882/1/012008/pdf https://iopscience.iop.org/article/10.1088/1742-6596/882/1/012008/pdf]

* [http://stacks.iop.org/1742-6596/882/i=1/a=012008/pdf http://stacks.iop.org/1742-6596/882/i=1/a=012008/pdf],
: [http://stacks.iop.org/1742-6596/882/i=1/a=012008?key=crossref.3778bde90af90d40e612cfaa2262c6e1 http://stacks.iop.org/1742-6596/882/i=1/a=012008?key=crossref.3778bde90af90d40e612cfaa2262c6e1],
: [http://dx.doi.org/10.1088/1742-6596/882/1/012008 http://dx.doi.org/10.1088/1742-6596/882/1/012008] under the license cc-by

* [http://ui.adsabs.harvard.edu/abs/2017JPhCS.882a2008P/abstract http://ui.adsabs.harvard.edu/abs/2017JPhCS.882a2008P/abstract],
: [https://iopscience.iop.org/article/10.1088/1742-6596/882/1/012008/meta https://iopscience.iop.org/article/10.1088/1742-6596/882/1/012008/meta],
: [https://cris.unibo.it/handle/11585/606919 https://cris.unibo.it/handle/11585/606919],
: [https://academic.microsoft.com/#/detail/2752338825 https://academic.microsoft.com/#/detail/2752338825] under the license http://iopscience.iop.org/info/page/text-and-data-mining