Illite is one of the main components in coal slime water and it sometimes makes the water extremely difficult to clarify. In this study, the aggregation mechanism of coal and illite particles was investigated using the extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory and settling experiments of slime water containing coal and illite. The results show that electrostatic energy plays a dominant role and manifests repulsive force in the long-range (>4 nm). However, the leading role becomes a hydrophobic force determined by the polar surface interaction energy in the short-range (<4 nm). A coagulant (Ca²⁺) can lower the surface electric potential to make all particles easier to coagulate, while the surface hydrophobicity of coal and illite determines whether the particles aggregate. Cationic polyacrylamide (CPAM) can promote the sedimentation of particles flocs effectively and makes the supernatant clearer due to attractive electrostatic forces while anionic polyacrylamide (APAM) flocculates particles through the bridge mechanism. Although the hydration shell on the hydrophilic surface of illite appears to be harmful for either coagulation or flocculation, illite can accelerate sedimentation when it is attached to the coal due to its higher density.

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.

In the dense medium separation system of coal preparation plant, the fluctuation of raw coal ash and lag of suspension density adjustment often causes the instability of product quality. To solve this problem, this study established a suspension density prediction model for the dense medium separation system based on Long Short-Term Memory (LSTM). First, the historical data in the dense medium separation system of a coal preparation plant were collected and preprocessed. Moving average and cubic exponential smoothing methods were used to replace abnormal data and to fill in the missing data, respectively. Second, a LSTM network was used to construct the density prediction model, and the optimal number of time steps, hidden layers, and nodes was determined. Finally, the model was employed on a testing set for prediction, and a Back-Propagation (BP) network without a time series was used for comparison. Root Mean Squared Error (RMSE) were the minimum when the number of the hidden layers, nodes, and time steps was 6, 12, and 5, respectively. In this case, the RMSE and Mean Absolute Percent Error (MAPE) of the LSTM method were 0.009 and 0.007, respectively, while those of the BP method were 0.019 and 0.015, respectively. Therefore, the model established using LSTM can be used to accurately predict the suspension density of the dense medium separation system.

Ash content is one of the most important properties of coal quality and the ash prediction of coal slurry in floatation is urgent and important for automation of the floatation process. The aim of this paper is to propose a method of ash content prediction for flotation tailings by the use of...

Online prediction models for the density components of raw coal, the float-and-sink data composition, and the expression of real-time distribution curves can be established by using a month comprehensive material of float-and-sink tests of raw coal from coal quality and preparation of a database, fast testing data, measured data from the online ash-testing instrument on the raw coal belt, and importing time as variable quantity. Real-time separation density, production yield, and ash can be predicted based on the predicted raw coal material, the required cleans yield after separation, and the online fit distribution curve, thus a real-time online optimized model can be established to predict an index of production technique and productions. Finally, the real-time controlled density in a process of a dense-medium separation can be calculated.

A novel hydrocyclone including a cylindrical screen embedded in a conventional hydrocyclone (CH), named three products hydrocyclone screen (TPHS), has been successfully designed. In TPHS, the combination of centrifugal classification and screening was employed to separate particles. In this paper, Grey theory, as an effective means to the laws of both complex and uncertainty system’s behavior with small samples, was used to investigate the operational (feed concentration and feed pressure) and structural (aperture size, spigot diameter, and vortex finder diameter) parameters on performance evaluation Hancock classification efficiency (HE), imperfection (I), and cut size (d_50c). The experiments of coal sample (0–1 mm) show that TPHS with coarser particles in underflow exhibited the absent “fish-hook”. The closeness calculated using the Grey System algorithm indicates that the performance of TPHS was closely related to the operation and structure parameters. Further, the order of grey incidence degree between different parameters and HE (or I or d_50c) is the spigot diameter and aperture size with the highest value, the feed pressure and vortex finder diameter with the middle value, and the feed concentration with the lowest value. The prediction using the GM(1, N) algorithm implies that the dynamic prediction model for the performance evaluation can be created depending on the operation, structure and previous performance value. The mean relative errors between the predicted and actual HE, I, and d₅₀ were 2.84%, 5.83%, and 3.57%, respectively, which exhibit the accurate prediction.