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Wyszukujesz frazę "flotation performance" wg kryterium: Temat

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    Wyświetlanie 1-3 z 3
    Tytuł:
    Effective circulating load ratio in mill circuit for milling capacity and further flotation process : lab scale study
    Autorzy:
    Pural, Yusuf Enes
    Çelik, Muhammed
    Özer, Mustafa
    Boylu, Feridun
    Powiązania:
    https://bibliotekanauki.pl/articles/2146931.pdf
    Data publikacji:
    2022
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    circulating load
    mill capacity
    flotation performance
    Opis:
    The design of the grinding circuits and the control of the transferring load in the ore preparation plants are of great importance from a technical and economic point of view. The importance of the circulating load for grinding process is well known and stated in the literature. However, there are not many studies on the effect on the following processes. In this study, the effect of the circulating load on both the grinding capacity and the subsequent flotation process was investigated at laboratory scale. Copper ore was used in the experiments. The circulating load was adjusted by changing the residence time of the material in the mill. Then, flotation experiments were carried out with the materials obtained at different circuit loads. The results showed that the grinding capacity can be increased up to 180% by optimizing the circulating load and it will positively affect the flotation performance. It was observed that a concentrate with the highest recovery for the same Cu grade was obtained with CLR of 150 % when compared to flotation recoveries through various CLRs. It is suggested that the circulating load should not be evaluated only in terms of the grinding process, but also the subsequent processes should be considered. Future studies in this area may contribute to industrial applications.
    Źródło:
    Physicochemical Problems of Mineral Processing; 2022, 58, 5; art. no. 149916
    1643-1049
    2084-4735
    Pojawia się w:
    Physicochemical Problems of Mineral Processing
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Column flotation performance prediction: PCA, ANN and image analysis-based approaches
    Autorzy:
    Nakhaei, Fardis
    Irannajad, Mehdi
    Mohammadnejad, Sima
    Powiązania:
    https://bibliotekanauki.pl/articles/109518.pdf
    Data publikacji:
    2019
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    image analysis
    column flotation
    froth features
    performance
    prediction
    PCA
    ANN
    Opis:
    The flotation froth surface appearance includes remarkable information, which can be employed as a helpful index for the qualitative evaluation of the process efficiency. Image analysis is a practical technology for the sake of achieving process related information that can be employed in expert controllers in order to amend flotation performance. In this paper, the intelligent modelling of relationship between froth characteristics and the metallurgical performance in a pilot column flotation of iron ore was established. Column flotation tests were carried out at a wide range of operating conditions and the froth features along with the metallurgical performances were specified for each run. The artificial intelligence models suggested for the performance parameters prediction include (1) multi-layer back propagation neural network (BPNN), (2) hybrid BPNN with principal component analysis (PCA). The hybrid network was on the basis of the PCA employment in order to decrease the number of variables to be given as input for BPNN. The relationships between the froth features and metallurgical performance factors were successfully modelled via the use of the two methods. The simulation results revealed that the prediction precision of BPNN model on the basis of all the data was relatively higher than the estimation precision of BPNN based on PCA algorithm. The Hybrid BPNN model that was trained by the pre-processed database of measurements achieved from the PCA can be considered a robust method when training time is of paramount importance in objectives of proces control.
    Źródło:
    Physicochemical Problems of Mineral Processing; 2019, 55, 5; 1298-1310
    1643-1049
    2084-4735
    Pojawia się w:
    Physicochemical Problems of Mineral Processing
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Comparison between neural networks and multiple regression methods in metallurgical performance modeling of flotation column
    Autorzy:
    Nakhaei, F.
    Irannajad, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/110822.pdf
    Data publikacji:
    2013
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    metallurgical performance
    separation
    neural networks
    nonlinear regression
    prediction
    flotation column
    Opis:
    Artificial neural networks are relatively new computational tools which their inherent ability to learn and recognize highly non-linear and complex relationships makes them ideally suited in solving a wide range of complex real-world problems. In this research, different techniques (Linear regression, Non-linear regression, Back propagation neural network, Radial Basis Function for the estimation of Cu grade and recovery values in flotation column concentrate are studied. Modeling is performed based on 90 datasets at different operating conditions at Sarcheshmeh pilot plant, a copper concentrator in Iran, which include chemical reagents dosage, froth height, air and wash water flow rates, gas holdup and Cu grade in the rougher feed and flotation column feed, column tail and final concentrate streams. The results of models were also expressed and analyzed by intuitive graphics. The results indicated that a four-layer BP network gave the most accurate metallurgical performance prediction and all of the neural network models outperformed non-linear regression in the estimation process for the same set of data.
    Źródło:
    Physicochemical Problems of Mineral Processing; 2013, 49, 1; 255-266
    1643-1049
    2084-4735
    Pojawia się w:
    Physicochemical Problems of Mineral Processing
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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