فهرست مطالب azadeh nakhaei

Determination of chemical elements assay plays an important role in mineral processing operations. This factor is used to control process accuracy، recovery calculation and plant profitability. The new assaying methods including chemical methods، X-Ray fluorescence and atomic absorption spectrometry are advanced and accurate. However، in some applications، such as on-line assaying process، high accuracy is required. In this paper، an algorithm based on optimal estimator is presented to predict and correction on-line XRF errors. This research is based on the industrial real data collection for evaluating the performance of the presented algorithm. The quality of the obtained results was very satisfied; so that the RMS errors of Cu and Mo grades in rougher feed reduce to less than 0. 19 and 0. 006 and in final flotation concentration to less than 2. 48 and 0. 274، respectively. The results indicate that the mentioned method is quite accurate to reduce the on-line XRF errors measurement.

Global Positioning System (GPS) is proven to be an accurate positioning sensor. However, there are several sources of errors such as ionosphere and troposphere effects, satellite time errors, errors of orbit data, receiver''s errors, and errors resulting from multi-path effect which reduce the accuracy of low-cost GPS receivers. These sources of errors also limit the use of single-frequency GPS receivers due to their less accurate data. Therefore, it''s important to reduce the effect of errors on GPS systems. In order to cope with these errors and enhance GPS system''s accuracy, Differential GPS (DGPS) method can be used. The problem with this method is slow updating process of differential corrections. In this paper, three algorithms based on Kalman Filtering (KF) are proposed to predict real-time corrections of DGPS systems. The efficiency of proposed algorithms is verified based on the collected of actual data. The experimental results carried out in field tests assure the high potential of these methods to get accurate positioning data. The results show that KF with variable transition matrix is better than other methods; so that it''s possible to reduce the Root Mean Square (RMS) of positioning errors in low-cost GPS receivers to less than one meter.