Several industrial coal processes are largely determined by the distribution of particle sizes in their feed.Currently these parameters are measured by manual sampling,which is time consuming and cannot provide real t...Several industrial coal processes are largely determined by the distribution of particle sizes in their feed.Currently these parameters are measured by manual sampling,which is time consuming and cannot provide real time feedback for automatic control purposes.In this paper,an approach using image segmentation on images of overlapped coal particles is described.The estimation of the particle size distribution by number is also described.The particle overlap problem was solved using image enhancement algorithms that converted those image parts representing material in lower layers to black.Exponential high-pass filter(EHPF) algorithms were used to remove the texture from particles on the surface.Finally,the edges of the surface particles were identified by morphological edge detection.These algorithms are described in detail as is the method of extracting the coal particle size.Tests indicate that using more coal images gives a higher accuracy estimate.The positive absolute error of 50 random tests was consistently less than 2.5% and the errors were reduced as the size of the fraction increased.展开更多
At present, the ballistic Target tracking has a higher demand in convergence rate and tracking precision of filter algorithm. In the paper, a filter algorithm was improved based on particle filter. The algorithm was c...At present, the ballistic Target tracking has a higher demand in convergence rate and tracking precision of filter algorithm. In the paper, a filter algorithm was improved based on particle filter. The algorithm was carried out from the aspects such as particle degradation and particle diversity lack. A novel ballistic coefficient parameter model was built, and was expanded to the state vector for filtering. Finally, the improved algorithm was simulated by MATLAB software. The simulation results show that the algorithm can obtain better convergence speed and tracking precision.展开更多
In the Raymond mill grinding processes,high-accuracy control for the current of Raymond mill is vital to enhance the product quality and production efficiency as well as cut down the consumption of spare parts.However...In the Raymond mill grinding processes,high-accuracy control for the current of Raymond mill is vital to enhance the product quality and production efficiency as well as cut down the consumption of spare parts.However,strong external disturbances,such as variations of ore hardness and ore size,always exist.It is not easy to make the current of Raymond mill constant due to these strong disturbances.Several control strategies have been proposed to control the grinding processes.However,most of them(such as PID and MPC)reject disturbances merely through feedback regulation and do not deal with the disturbances directly,which may lead to poor control performance when strong disturbances occur.To improve disturbance rejection performance,a control scheme based on PI and disturbance observer is proposed in this work.The scheme combines a feedforward compensation part based on disturbance observer and a feedback regulation part using PI.The test results illustrate that the proposed method can obtain remarkable superiority in disturbance rejection compared with PI method in the Raymond mill grinding processes.展开更多
基金the Creative Research Groups Science Fund of the National Natural Science Foundation of China(No.50921002)
文摘Several industrial coal processes are largely determined by the distribution of particle sizes in their feed.Currently these parameters are measured by manual sampling,which is time consuming and cannot provide real time feedback for automatic control purposes.In this paper,an approach using image segmentation on images of overlapped coal particles is described.The estimation of the particle size distribution by number is also described.The particle overlap problem was solved using image enhancement algorithms that converted those image parts representing material in lower layers to black.Exponential high-pass filter(EHPF) algorithms were used to remove the texture from particles on the surface.Finally,the edges of the surface particles were identified by morphological edge detection.These algorithms are described in detail as is the method of extracting the coal particle size.Tests indicate that using more coal images gives a higher accuracy estimate.The positive absolute error of 50 random tests was consistently less than 2.5% and the errors were reduced as the size of the fraction increased.
文摘At present, the ballistic Target tracking has a higher demand in convergence rate and tracking precision of filter algorithm. In the paper, a filter algorithm was improved based on particle filter. The algorithm was carried out from the aspects such as particle degradation and particle diversity lack. A novel ballistic coefficient parameter model was built, and was expanded to the state vector for filtering. Finally, the improved algorithm was simulated by MATLAB software. The simulation results show that the algorithm can obtain better convergence speed and tracking precision.
基金Projects(61504027,61573099)supported by the National Natural Science Foundation of ChinaProject(BK20140647)supported by the Natural Science Foundation of Jiangsu Province,ChinaProject supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions,China
文摘In the Raymond mill grinding processes,high-accuracy control for the current of Raymond mill is vital to enhance the product quality and production efficiency as well as cut down the consumption of spare parts.However,strong external disturbances,such as variations of ore hardness and ore size,always exist.It is not easy to make the current of Raymond mill constant due to these strong disturbances.Several control strategies have been proposed to control the grinding processes.However,most of them(such as PID and MPC)reject disturbances merely through feedback regulation and do not deal with the disturbances directly,which may lead to poor control performance when strong disturbances occur.To improve disturbance rejection performance,a control scheme based on PI and disturbance observer is proposed in this work.The scheme combines a feedforward compensation part based on disturbance observer and a feedback regulation part using PI.The test results illustrate that the proposed method can obtain remarkable superiority in disturbance rejection compared with PI method in the Raymond mill grinding processes.
