On/In-line monitoring of cleaning in place operation using a passive acoustic emission sensor technology

In industrial environments where hygiene, operational efficiency, and sustainability are critical, Clean-in-Place (CIP) systems are increasingly employed to automate the cleaning of internal surfaces in equipment and pipelines without disassembly. This study investigates the use of Passive Acoustic Emission (PAE) sensing as a nonintrusive, real-time monitoring method to assess the effectiveness of CIP processes. A vertical pipe rig was constructed and systematically fouled using glucose solutions at varying concentrations (20 % and 30 % w/w). Cleaning cycles were conducted using water and water-surfactant mixtures at controlled flow rates (2150–3150 L/hr). A VS900-M piezoelectric acoustic sensor recorded acoustic signals throughout the cleaning process. Time-domain and frequency-domain analyses, including Power Spectral Density (PSD), were used to evaluate changes in signal behavior across cleaning cycles. Results showed that the PAE sensor reliably detected changes in fouling thickness, flow dynamics, and foam formation. Higher glucose concentrations yielded dampened signals due to increased acoustic impedance, while increased flow rates and successive cleaning cycles progressively restored signal intensity and waveform regularity. Surfactant presence influenced acoustic profiles, with critical micelle concentrations leading to foam-induced signal attenuation. PSD analysis revealed that by the third or fourth CIP cycle, signal spectra closely resembled that of a clean reference condition, indicating optimal cleaning. This work demonstrates the potential of PAE sensing as a diagnostic tool for in situ CIP monitoring. Its non-invasive nature, sensitivity to physical and chemical cleaning parameters, and compatibility with real-time data processing support its application in industries where hygiene and resource efficiency are paramount.