Monitoring of a simulated milling circuit: Fault diagnosis and economic impact

Wakefield, Brandon Jason; Lindner, Brian; McCoy, John T.; Auret, Lidia

doi:10.1016/j.mineng.2018.02.007

Cited by 25 publications

(9 citation statements)

References 47 publications

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“…Fault detection is commonly carried out using principal component analysis (PCA) or its extensions/modifications [107], and it has been used in flotation systems [124,125] and milling circuits [126,127]. Fault diagnosis, i.e., the identification of variables associated with faulty conditions, is usually achieved via the use of approaches based on PCA.…”

Section: Artificial Intelligence (Ai) Applied To Multiphase Systemsmentioning

confidence: 99%

“…Fault diagnosis, i.e., the identification of variables associated with faulty conditions, is usually achieved via the use of approaches based on PCA. Some applications of these methods include flotation [128][129][130] and grinding [126,127]. For example, Wakefield et al [127] simulated a milling circuit for investigating faults related to particle size estimates and mill liners.…”

Section: Artificial Intelligence (Ai) Applied To Multiphase Systemsmentioning

confidence: 99%

“…Some applications of these methods include flotation [128][129][130] and grinding [126,127]. For example, Wakefield et al [127] simulated a milling circuit for investigating faults related to particle size estimates and mill liners. They applied statistical tools (PCA) for detecting faults, in conjunction with process topology data-driven techniques (Granger causality) for root cause analysis.…”

Section: Artificial Intelligence (Ai) Applied To Multiphase Systemsmentioning

confidence: 99%

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Trends in Modeling, Design, and Optimization of Multiphase Systems in Minerals Processing

2019

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Multiphase systems are important in minerals processing, and usually include solid–solid and solid–fluid systems, such as in wet grinding, flotation, dewatering, and magnetic separation, among several other unit operations. In this paper, the current trends in the process system engineering tasks of modeling, design, and optimization in multiphase systems, are analyzed. Different scales of size and time are included, and therefore, the analysis includes modeling at the molecular level (molecular dynamic modeling) and unit operation level (e.g., computational fluid dynamic, CFD), and the application of optimization for the design of a plant. New strategies for the modeling, design, and optimization of multiphase systems are also included, with a strong focus on the application of artificial intelligence (AI) and the combination of experimentation and modeling with response surface methodology (RSM). The integration of different modeling techniques such as CFD with discrete element simulation (DEM) and response surface methodology (RSM) with artificial neural networks (ANN) is included. The paper finishes with tools to study the uncertainty, both epistemic and stochastic, based on uncertainty and global sensitivity analyses, which is present in all mineral processing operations. It is shown that all of these areas are very active and can help in the understanding, operation, design, and optimization of mineral processing that involves multiphase systems. Future needs, such as meso-scale modeling, are highlighted.

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Section: Artificial Intelligence (Ai) Applied To Multiphase Systemsmentioning

confidence: 99%

Section: Artificial Intelligence (Ai) Applied To Multiphase Systemsmentioning

confidence: 99%

Section: Artificial Intelligence (Ai) Applied To Multiphase Systemsmentioning

confidence: 99%

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Trends in Modeling, Design, and Optimization of Multiphase Systems in Minerals Processing

2019

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“…An impediment to implementing model-based control in grinding mill circuits is the lack of sufficient real-time measurements to estimate the necessary model states and parameters for state-feedback. , The number of available real-time measurements on industrial circuits are generally far less than the size of the state vector . Therefore, the peripheral tools of the control loop, such as inferential measurements, observers and fault-detection and isolation schemes, become as important as the controller itself. ,,− …”

Section: Bottom-up Analysismentioning

confidence: 99%

Plant-Wide Control Framework for a Grinding Mill Circuit

Roux

Craig

2019

Ind. Eng. Chem. Res.

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This article proposes a generic plant-wide control framework that can be used to develop a hierarchical control structure (regulatory control, supervisory control, and optimization) to operate a single-stage closed grinding mill circuit in an economically optimal manner. An economic objective function is defined for the grinding mill circuit with reference to the economic objective of the larger mineral processing plant. A mineral processing plant in this study consists of a comminution and a separation circuit and excludes the extractive metallurgy at a metal refinery. The operational performance of a comminution circuit as represented by a single-stage grinding mill circuit, primarily depends on the performance of the grinding mill. Since grind curves define the operational performance range of a mill, grind curves are used to define the set points for the economic controlled variables for optimal steady-state operation. For a given metal price, processing cost, and transportation cost, the proposed structure can be used to define the optimal operating region of a grinding mill circuit for the best economic return of the mineral processing plant. Once the optimal operating condition is defined, the supervisory control aims to maintain the primary controlled variables at the optimal set points. A regulatory control layer ensures the stability of the plant in the presence of disturbances.

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“…Here, fault detection is defined as the indication at a specific time point that a faulty condition has started occurring, or is continuing to occur. Fault diagnosis is defined here as the indication of which measured process variables are most associated with the faulty condition, and the subsequent classification of process variables as either symptoms or causes of the faulty condition [13].…”

Section: Introductionmentioning

confidence: 99%

Study of Blockage Diagnosis for Hydrocyclone Using Vibration-Based Technique Based on Wavelet Denoising and Discrete-Time Fourier Transform Method

Wang

et al. 2020

Processes

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Hydrocyclones are extensively known as important separation devices which are used in many industrial fields. However, the general method to estimate device performance is time-consuming and has a high cost. The aim of this paper was to investigate the blockage diagnosis for a lab-scale hydrocyclone using a vibration-based technique based on wavelet denoising and the discrete-time Fourier transform method. The results indicate that the farther away the installation location from feed inlet the more regular the frequency is, which reveals that the installation plane near to the spigot generated the regular frequency distribution. Furthermore, the acceleration amplitude under blockage degrees 0%, 50% and 100% fluctuates as a sine shape with increasing time, meanwhile the vibration frequency of the hydrocyclone rises with increasing throughput. Moreover, the distribution of four dimensional and five non-dimensional parameters for the time domain shows that the standard deviation, compared to the others, reduced gradually with increases in blockage degree. Thus, the standard deviation was used to evaluate the online diagnosis of the blockage. The frequency domain distribution under different throughput reveals that the characteristic peaks consisting of the faulty frequency and multiple frequency were produced by the faulty blockage and the feed pump, respectively. Hence, the faulty peak of 16–17 Hz was adopted to judge the real-time blockage of the hydrocyclone, i.e., the presence of the characteristic peak marks the blockage, and its value is proportional to the blockage degree. The application of the online monitoring system demonstrates that the combination of the time domain and the frequency domain could admirably detect the running state and rapidly recognize blockage faults.

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Monitoring of a simulated milling circuit: Fault diagnosis and economic impact

Cited by 25 publications

References 47 publications

Trends in Modeling, Design, and Optimization of Multiphase Systems in Minerals Processing

Trends in Modeling, Design, and Optimization of Multiphase Systems in Minerals Processing

Plant-Wide Control Framework for a Grinding Mill Circuit

Study of Blockage Diagnosis for Hydrocyclone Using Vibration-Based Technique Based on Wavelet Denoising and Discrete-Time Fourier Transform Method

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