Abstract

Hydrocyclones deployed for the classification of the particles operate with a spray discharge condition in the underflow and a well-established air core in its central region. However, certain variations in the design and operating parameters of the hydrocyclone shift the underflow discharge profile to roping. The condition of roping limits the overall solid handling capacity, significantly deteriorates the product quality, leads to spigot wear, and, if not alleviated, hydrocyclone blockage. In this regard, continuous monitoring of the underflow discharge profile of the hydrocyclone is deemed necessary for maintaining its optimized operation. 

Manual identification of the underflow discharge profile of hydrocyclones is seldom feasible due to industrial site constraints. Hence, various online monitoring techniques have been proposed to identify the underflow discharge profile. A comprehensive literature review of all such monitoring techniques suggests that the vibrometry-based technique is the most promising approach based on its capabilities for industrial applications. However, the broad applicability of vibrometry-based monitoring technique for hydrocyclones in industries is still unknown.  

This dissertation addresses the key challenges in vibrometry-based condition monitoring of hydrocyclones, which have constrained their widespread industrial adoption. These challenges encompass the choice of a suitable commercially available accelerometer, its non-intrusive placement on the external surface, noise reduction through a denoising algorithm, an efficient signal processing algorithm for extracting essential vibration features to differentiate between rope and spray discharges, and the development of a user-friendly interface for seamless industrial deployment.

Correspondingly, the study first explores the applicability of a commercially available tri-axial accelerometer (ADXL345) for analyzing the vibration features of the hydrocyclone to render the technique cost-effective. For this, the hydrocyclone is fed solely with water, and the vibration features are acquired at the spigot of the hydrocyclone. The proposed parameter (total Root Mean Square, RMST) for quantifying hydrocyclone vibration features exhibits a systematic response to the hydrocyclone design and operating conditions, establishing the potential of using commercially available tri-axial accelerometers for hydrocyclone condition monitoring.

A signal processing algorithm is then developed in this study, based on the Empirical Mode Decomposition (EMD) with due consideration of filtering out the noises accompanying the flow-induced vibrations. The developed algorithm extracts specific vibration features that are differentiated for the spray and rope discharge conditions based on their Power Spectral Density (PSD) values. Further, by incorporating this algorithm, an intuitive interface has been developed for detecting the underflow discharge profile of the hydrocyclone in near-real-time. The interface identifies underflow discharge conditions and provides valuable insights into other vibration features of the hydrocyclone.