Embedded system based solid-gas mass flow rate meter using optical tomography

• Main Author: Chiam, Kok Thiam
• Format: Thesis
• Language: English
• Published: 2006
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/5295/1/ChiamKokThiamMFKE2006.pdf; http://eprints.utm.my/id/eprint/5295/
• Institution: Universiti Teknologi Malaysia

Monitoring solid-gas flow in terms of flow visualization and mass flow rate (MFR) measurement is essential in industrial processes. Optical tomography provides a method to view the cross sectional image of flowing materials in a pipeline conveyor. Important flow information such as flow concentration profile, flow velocity and mass flow rate can be obtained without the need to invade the process vessel. The utilization of powerful computer together with expensive Data Acquisition System (DAQ) as the processing device in optical tomography systems has always been a norm. However, the advancements in silicon fabrication technology nowadays allow the fabrication of powerful Digital Signal Processors (DSP) at reasonable cost. This allows the technology to be applied in optical tomography system to reduce or even eliminate the need of personal computer and the DAQ. The DSP system was customized to control the data acquisition of 16x16 optical sensors (arranged in orthogonal projection) and 23x23 optical sensors (arranged in rectilinear projections) in 2 layers (upstream and downstream). The data collected was used to reconstruct the cross sectional image of flowing materials inside the pipeline, velocity profile measurement and mass flow rate measurement. The mass flow rate result is sent to a Liquid Crystal Display (LCD) display unit for display. For image display purpose, the reconstructed image was sent to a personal computer via serial link. In the developed system, the accuracy of the image reconstruction was increased by 12.5% by using new hybrid image reconstruction algorithm. The processing time required to obtain flow velocity was 12 times faster by using Sensor To Sensor cross correlation in frequency domain instead of Pixel to Pixel cross correlation in time domain. By optimizing the overall system, the developed system is capable of producing a Mass Flow Rate measurement in only 430 ms.