Yigen Zeng

Monitoring grinding parameters by vibration signal measurement : a primary application

Abstract Grinding plays an important role on energy consumption and subsequent separation stage in a mineral processing plant. To maintain higher grinding efficiency, the operating parameters must be continuously monitored and adjusted close to the setup of the optimal operating conditions. It is difficult and expensive to trace the frequent variations of the grinding parameters by traditional methods in commercial scale operation. Since mechanical grinding emits strong vibration signals, it can be picked up by commercially available instrument in the form of time-domain waveform. The variations of the vibration signals were governed by the changes of the grinding state. A primary application was studied based on industrial scale measurements, where the mechanical vibration was picked up by an accelerometer and acoustic pressure changes by a microphone. The digitised time-domain source signals were processed by digital signal processing technique. The variable grinding parameters were the power draw, the feed rate, the pulp density, and the particle sizes of the mill feed and ground product. By principal component analysis and parameter identification, the variations of the grinding parameters were related to the changes of the source vibration signals. By vibration measurement, a new alternative could be developed for monitoring the operating parameters in grinding.

Monitoring grinding parameters by signal measurements for an industrial ball mill

Abstract Mechanical grinding emits a high-intensity vibration signal that contains information on the mill operating state. Vibration signals from the mill are presented in the form of both mechanical vibration and acoustic pressure. To apply these source signals to monitoring of grinding parameters, industrial scale grinding tests were performed with an iron ore at LKAB, Malmberget. Three operating parameters were considered: the feed rate, the mill feed size and the pulp density of mill discharge. The measured response parameters were the ground product size, the power draw and the pulp temperature. The source signals of the time-domain waveforms were simultaneously sensed by accelerometer and microphone so as to obtain a “stereograph” of grinding. The signals were first stored on a DAT recorder and then converted into digital format by an oscilloscope. The digitised waveforms were transformed into frequency-domain spectra by power spectral estimation. The variations on the power spectra can be described by a few “latent” variables derived by principal component analysis. Finally, close relations were established between key grinding parameters and “latent” variables by multiple regression. Using signal measurements, an automatic and efficient strategy can be developed to monitor operating parameters for the control system in a ball grinding circuit.

Effects of operating parameters on vibration signal under laboratory scale ball grinding conditions

Abstract Experiments were performed under batchwise wet grinding conditions with dolomite. The vibration signal was received by an accelerometer and transmitted to a vibrometer. The vibration signal was first stored on a Digital-Audio-Tape recorder in voltage format during the grinding tests. The original signal was then resampled and converted into data format for an IBM or compatible personal computer by a digital oscilloscope. The Root-Mean-Square and the power spectrum were estimated on the time-domain vibration signal. A partial correlation analysis was applied to the frequency-domain spectrums to detect the non-zero correlation between the frequency bands and the operating parameters in grinding. A stepwise regression analysis was used to locate the key frequency bands for describing the changes of a particular operating parameter. After vibration analysis, the operating parameters in grinding, e.g., the mill speed, the powder filling, the pulp density, the pulp temperature and the batchwise grinding time were found to be strongly correlated with a few frequency bands. It is therefore possible to develop an efficient method for monitoring the operating parameters in grinding based on the vibration signal.

Multivariate statistical analysis of vibration signals from industrial scale ball grinding

Abstract Multivariate statistical modelling based on vibration signal analysis was performed at commercial scale grinding. The source digital signals consist of three channels of mechanical vibrations obtained at the axial, horizontal and vertical directions. The feed rate, power draw, pulp temperature were collected automatically by the control system while samples of the feed material and ground product of the ball mill were manually taken to determine the particle size distributions and pulp densities. Using projection to the latent structure (PLS) and/or principle component regression (PCR), empirical models between grinding parameters of interests and the vibration signals were built based on the training data set collected in two weeks, thus the new grinding parameters could be automatically predicted whenever the vibration signals were known. The modelling results show that both the PCR and PLS model can be used to predict grinding parameters online.

Application of vibration signals to monitoring crushing parameters

Abstract Vibration measurements for fine crushing have been performed on a laboratory scale jaw crusher on dolomite. The original vibration signal was sensed by an accelerometer and stored on a DAT recorder during the whole testing period. The vibration signal was resampled and converted into an IBM PC compatible data format with a digital oscilloscope. The time-domain vibration signal was analysed with the aid of a digital signal processing technique. The crushing process can be inspected by replaying the sample of the time-domain waveform. The variation of the vibration pattern was described by a few ‘latent’ variables obtained by principal component analysis. Relations were established between the crusher setting, the product size and the latent variables by multiple regression. Measurement of the vibration signal provides a new strategy for monitoring crushing processes.

Effects of mill feed size and rod charges on grinding performance

Abstract The effects of mill feed sizes and the rod charges on ground product fineness, energy utilization and energy consumption have been investigated on a rod mill under dry batchwise grinding conditions. The effect of reducing mill feed size on product fineness decreases with grinding time, while the effects of different composition of rod charges are very small. Smaller rod diameter, coarser mill feed size and shorter grinding time will increase the energy utilization. The energy consumption in batch grinding is described by the Bond method. Using smaller rod diameter and reducing the mill feed size will optimize energy use in coarse grinding.

Vibration signal emission from mono-size particle breakage

Abstract A technique based on vibration measurement and analysis was used to study the breakage of mono-size dolomite on a hydraulic press. Up to a maximal pressure of 4 MPa, vibration signals during pressing and breakage of dolomite were picked up with two piezo-electric type accelerometers, which were screwed on to the breakage chamber and oriented in perpendicular directions. The source vibration signals were amplified and stored on a DAT recorder. A “stereo” picture was built-up for describing the breakage events based on two-channel vibration signals. The saved time-domain waveforms were converted into digital format for the personal computer, thus, the breaking history may be replayed by plotting and zooming the waveforms, from which the frequency-domain power spectra were transformed. Primary studies showed that the most significant changes on the power spectra were on the frequency range of 500 to 2500 Hz, and were caused mainly by changes in the feed sizes to the crushing chamber. Relations between the vibration signal characteristics and the parameters in mono-size breakege events were derived by multiple regression based on principal component scores. It is shown that vibration signal measurement may provide additional information for studying single particle breakage events. Two examples are used to demonstrate the application of principal component analysis.

Monitoring jaw crushing parameters via vibration signal measurement

Abstract Fine crushing tests were performed on a laboratory scale jaw crusher with dry, monosize dolomite. The source vibration signal was picked up by an accelerometer, the acceleration signal was amplified by a vibrometer, and then stored on a DAT recorder during whole testing period. For each crushing test, three vibration signal samples were taken and converted into an IBM PC accessible data format using a digital oscilloscope. The digitised vibration signal was analysed with the aid of digital signal processing technique. Through spectral inspection and principal component analysis, it was found that two major frequency bands, 250–400 and 700–900 Hz, were strongly related with the variation of the operating parameters. The first four principal components account for 91% of the total variation of the vibration signal. It was found that the inter-particle collision and attrition without breakage mainly affects the energy of the 250–400 Hz frequency band, and the variation of the frequency band of 700–900 Hz characterises the breakage events of dolomite. With the aid of the multivariate data analysis, the relationship was established between the power spectral density and the operating parameters such as the feed rate to the crusher, the close side crusher setting and the charge volume of dolomite in the crusher chamber. The product size distribution described by Gaudin equation was also related to the vibration signal. Thus, an alternative method for monitoring the operating state can therefore be developed through measuring and processing the vibration signal from crushing.

Effects of mill feed size on product fineness and energy consumption in coarse grinding

Abstract The effects of some grinding parameters on the product fineness and the energy consumption under dry batchwise coarse grinding conditions are studied on rod and ball mills. A parabolic-sine equation is suitable to describe the particle size distribution. The constants in the equation are related to the grinding parameters, which permits a mathematical analysis. A relation between energy consumption and grinding parameters is also established, and the grinding effects in the rod and ball mills are compared.

VIBRATION SIGNAL MEASUREMENT: AN ALTERNATIVE FOR DESCRIBING MECHANICAL GRINDING PROCESS

ABSTRACT Grinding of minerals by mechanical means emits a strong noise signal, which varies with the changes of the operating state. With the goal of applying the phenomenon as a monitoring techniques in grinding, the vibration signal from a laboratory scale batchwise ball mill was measured and processed under different grinding conditions. To build up a “stereo picture” of the milling state, the source vibration was picked up by means of an accelerometer (mechanical) and a microphone (acoustic pressure). The time-domain vibration signals picked up from grinding were transformed into frequency-domain spectra. The spectrum was divided into three sub-frequency bands consisting of one or more significant peaks. The power spectra were illustrated and compared by 3-D illustration. Larger differences between dry and wet grinding were found for an acoustic signal than for the mechanical vibration signal. It was found that the first two principal components’ accounted for 98% of the total variations of the mechan...