Experimental Analysis of Semi-autogenous Grinding Mill Characteristics Under Different Working Conditions
- PDF / 1,330,890 Bytes
- 12 Pages / 595.276 x 790.866 pts Page_size
- 49 Downloads / 269 Views
RESEARCH PAPER
Experimental Analysis of Semi‑autogenous Grinding Mill Characteristics Under Different Working Conditions Ali Dorkhah1 · Alireza Arab Solghar1 · Masoud Rezaeizadeh2 Received: 2 February 2017 / Accepted: 21 September 2019 © Shiraz University 2019
Abstract In the present work, vibration, acoustic and thermal signals were correlated to the semi-autogenous grinding mill working parameters such as total power and inlet water flow rate, and then these parameters were monitored using vibration, acoustic and thermal analyses. Next, the influential controlling parameters were obtained to monitor the mill conditions via SPSS software and afterward by exploiting neural network method, the modified controlling parameters were acquired for the development of mill performance. It was found that the mill vibration and the bearing temperature increased with motors power. Also, the results revealed that the mill noise reduced with the increase in water flow rate. Finally, an analytical relationship between the controlling parameters and the noise as a measurable parameter was proposed. Keywords Vibration · Acoustic · Thermography · SAG mill · Condition monitoring
1 Introduction Tumbling mills are main equipment of mineral industries. These mills with a giant cylindrical configuration with the diameter of 10–12 m are used for the grinding of ores. Semiautogenous grinding of ore plays a vital role in a mineral processing plant. Since all ores have to be ground before any other process is carried on, any stop of the mill will shut down all downstream processes. Consequently, it will impose a high cost on the plant productions. Thus, with condition monitoring of the SAG mill behaviors employing vibration, acoustic and thermal signals, the relevant parameter can be diagnosed and monitored. Accordingly, the mill may work on its optimum conditions without the concern of any imminent problem like mill congestions and unplanned stops. In recent years, many studies have been devoted to the development of mill diagnostic tools to find parameters that affect grinding efficiency. * Alireza Arab Solghar [email protected] 1
Department of Mechanical Engineering, School of Engineering, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran
Faculty of Mechanical and Material Engineering, Graduate University of Advanced Technology, Mahan, Iran
2
Zeng and Forssberg (1993, 1994) have correlated signal characteristics to grind parameters such as power draw, feed rate, pulp density and product size by generating power spectra of the vibration signals. Later, Zeng (1994) has examined nine different locations on the trunnion bearings and on the bearing for the pinion axis to select the best place for situating a vibration sensor using an accelerometer. He deduced that in order to collect the maximum amount of pertinent vibration data, the vibration sensor should be placed on the bearing of the pinion axis. Moreover, Zeng and Forssberg (1995) concluded that both the projection to the latent structure and the principle compo
Data Loading...
