Monitoring Cleaning-In-Place by electrical resistance tomography with dynamic references

In multifunctional food and detergent production lines, accurate identification of ending point of the cleaning process for the previous product is crucial to ensure product integrity. In this paper, a commercial electrical resistance tomography system was applied to monitoring a lab Cleaning-In-Place circuit. Several image reconstruction algorithms are compared for the accurate identification of the end point and an optimized algorithm based on Tikhonov regularization with dynamic references is proposed and verified to be the best solution. The capabilities of this novel approach are discussed.