An image can be degraded due to many environmental factors like foggy or hazy weather,low light conditions,extra light conditions etc.Image captured under the poor light conditions is generally known as non-uniform il...An image can be degraded due to many environmental factors like foggy or hazy weather,low light conditions,extra light conditions etc.Image captured under the poor light conditions is generally known as non-uniform illumination image.Non-uniform illumination hides some important information present in an image during the image capture Also,it degrades the visual quality of image which generates the need for enhancement of such images.Various techniques have been present in literature for the enhancement of such type of images.In this paper,a novel architecture has been proposed for enhancement of poor illumination images which uses radial basis approximations based BEMD(Bi-dimensional Empirical Mode Decomposition).The enhancement algorithm is applied on intensity and saturation components of image.Firstly,intensity component has been decomposed into various bi-dimensional intrinsic mode function and residue by using sifting algorithm.Secondly,some linear transformations techniques have been applied on various bidimensional intrinsic modes obtained and residue and further on joining the transformed modes with residue,enhanced intensity component is obtained.Saturation part of an image is then enhanced in accordance to the enhanced intensity component.Final enhanced image can be obtained by joining the hue,enhanced intensity and enhanced saturation parts of the given image.The proposed algorithm will not only give the visual pleasant image but maintains the naturalness of image also.展开更多
滇东南地区位于华南地块右江海西-印支地槽褶皱带,区内蕴含着我国重要的钨、锡、银、铅、锌等多金属矿产,是华南岩浆成矿带的重要组成部分。这些矿产均围绕个旧、薄竹山和老君山3个复式花岗岩体分布,其中已有大量资料证明个旧花岗岩体(...滇东南地区位于华南地块右江海西-印支地槽褶皱带,区内蕴含着我国重要的钨、锡、银、铅、锌等多金属矿产,是华南岩浆成矿带的重要组成部分。这些矿产均围绕个旧、薄竹山和老君山3个复式花岗岩体分布,其中已有大量资料证明个旧花岗岩体(秦德先等,2008;毛景文等,2008;程彦博等,2008;Cheng Y B et al.,2013)和老君山花岗岩体(Yan D P et al.,2006;张斌辉等,2012;蓝江波等,2016)与成矿有着密切的成因联系,而对于薄竹山地区的研究相对薄弱,程度较低,且该区控矿条件和矿化类型与个旧、都龙等超大型锡多金属矿田有一定可比性,因此其深部拥有巨大的找矿潜力。展开更多
Concentration of elements or element groups in a geological body is the result of multiple stages of rockforming and ore-forming geological processes.An ore-forming element group can be identified by PCA(principal com...Concentration of elements or element groups in a geological body is the result of multiple stages of rockforming and ore-forming geological processes.An ore-forming element group can be identified by PCA(principal component analysis)and be separated into two components using BEMD(bi-dimensional empirical mode decomposition):(1)a high background component which represents the ore-forming background developed in rocks through various geological processes favorable for mineralization(i.e.magmatism,sedimentation and/or metamorphism);(2)the anomaly component which reflects the oreforming anomaly that is overprinted on the high background component developed during mineralization.Anomaly components are used to identify ore-finding targets more effectively than ore-forming element groups.Three steps of data analytical procedures are described in this paper;firstly,the application of PCA to establish the ore-forming element group;secondly,using BEMD on the o re-forming element group to identify the anomaly components created by different types of mineralization processes;and finally,identifying ore-finding targets based on the anomaly components.This method is applied to the Tengchong tin-polymetallic belt to delineate ore-finding targets,where four targets for Sn(W)and three targets for Pb-Zn-Ag-Fe polymetallic mineralization are identified and defined as new areas for further prospecting.It is shown that BEMD combined with PCA can be applied not only in extracting the anomaly component for delineating the ore-finding target,but also in extracting the residual component for identifying its high background zone favorable for mineralization from its oreforming element group.展开更多
Grinding chatter is a self?induced vibration which is unfavorable to precision machining processes. This paper proposes a forecasting method for grinding state identification based on bivarition empirical mode decompo...Grinding chatter is a self?induced vibration which is unfavorable to precision machining processes. This paper proposes a forecasting method for grinding state identification based on bivarition empirical mode decomposition(BEMD) and least squares support vector machine(LSSVM), which allows the monitoring of grinding chatter over time. BEMD is a promising technique in signal processing research which involves the decomposition of two?dimen?sional signals into a series of bivarition intrinsic mode functions(BIMFs). BEMD and the extraction criterion of its true BIMFs are investigated by processing a complex?value simulation chatter signal. Then the feature vectors which are employed as an amplification for the chatter premonition are discussed. Furthermore, the methodology is tested and validated by experimental data collected from a CNC guideway grinder KD4020 X16 in Hangzhou Hangji Machine Tool Co., Ltd. The results illustrate that the BEMD is a superior method in terms of processing non?stationary and nonlinear signals. Meanwhile, the peak to peak, real?time standard deviation and instantaneous energy are proven to be e ec?tive feature vectors which reflect the di erent grinding states. Finally, a LSSVM model is established for grinding status classification based on feature vectors, giving a prediction accuracy rate of 96%.展开更多
基金This research is financially supported by the Deanship of Scientific Research at King Khalid University under research grant number(R.G.P 2/157/43).
文摘An image can be degraded due to many environmental factors like foggy or hazy weather,low light conditions,extra light conditions etc.Image captured under the poor light conditions is generally known as non-uniform illumination image.Non-uniform illumination hides some important information present in an image during the image capture Also,it degrades the visual quality of image which generates the need for enhancement of such images.Various techniques have been present in literature for the enhancement of such type of images.In this paper,a novel architecture has been proposed for enhancement of poor illumination images which uses radial basis approximations based BEMD(Bi-dimensional Empirical Mode Decomposition).The enhancement algorithm is applied on intensity and saturation components of image.Firstly,intensity component has been decomposed into various bi-dimensional intrinsic mode function and residue by using sifting algorithm.Secondly,some linear transformations techniques have been applied on various bidimensional intrinsic modes obtained and residue and further on joining the transformed modes with residue,enhanced intensity component is obtained.Saturation part of an image is then enhanced in accordance to the enhanced intensity component.Final enhanced image can be obtained by joining the hue,enhanced intensity and enhanced saturation parts of the given image.The proposed algorithm will not only give the visual pleasant image but maintains the naturalness of image also.
文摘滇东南地区位于华南地块右江海西-印支地槽褶皱带,区内蕴含着我国重要的钨、锡、银、铅、锌等多金属矿产,是华南岩浆成矿带的重要组成部分。这些矿产均围绕个旧、薄竹山和老君山3个复式花岗岩体分布,其中已有大量资料证明个旧花岗岩体(秦德先等,2008;毛景文等,2008;程彦博等,2008;Cheng Y B et al.,2013)和老君山花岗岩体(Yan D P et al.,2006;张斌辉等,2012;蓝江波等,2016)与成矿有着密切的成因联系,而对于薄竹山地区的研究相对薄弱,程度较低,且该区控矿条件和矿化类型与个旧、都龙等超大型锡多金属矿田有一定可比性,因此其深部拥有巨大的找矿潜力。
基金funded by the Na-tional Natural Science Foundation of China(Grant Nos.41672329,41272365)the National Key Research and Development Project of China(Grant No.2016YFC0600509)the Project of China Geological Survey(Grant No.1212011120341)
文摘Concentration of elements or element groups in a geological body is the result of multiple stages of rockforming and ore-forming geological processes.An ore-forming element group can be identified by PCA(principal component analysis)and be separated into two components using BEMD(bi-dimensional empirical mode decomposition):(1)a high background component which represents the ore-forming background developed in rocks through various geological processes favorable for mineralization(i.e.magmatism,sedimentation and/or metamorphism);(2)the anomaly component which reflects the oreforming anomaly that is overprinted on the high background component developed during mineralization.Anomaly components are used to identify ore-finding targets more effectively than ore-forming element groups.Three steps of data analytical procedures are described in this paper;firstly,the application of PCA to establish the ore-forming element group;secondly,using BEMD on the o re-forming element group to identify the anomaly components created by different types of mineralization processes;and finally,identifying ore-finding targets based on the anomaly components.This method is applied to the Tengchong tin-polymetallic belt to delineate ore-finding targets,where four targets for Sn(W)and three targets for Pb-Zn-Ag-Fe polymetallic mineralization are identified and defined as new areas for further prospecting.It is shown that BEMD combined with PCA can be applied not only in extracting the anomaly component for delineating the ore-finding target,but also in extracting the residual component for identifying its high background zone favorable for mineralization from its oreforming element group.
基金National Natural Science Foundation of China(Grant No.51475432)Zhejiang Provincial National Natural Science Foundation of China(Grant No.LZ13E050003)State Key Program of National Natural Science of China(Grant Nos.U1234207,U1709210)
文摘Grinding chatter is a self?induced vibration which is unfavorable to precision machining processes. This paper proposes a forecasting method for grinding state identification based on bivarition empirical mode decomposition(BEMD) and least squares support vector machine(LSSVM), which allows the monitoring of grinding chatter over time. BEMD is a promising technique in signal processing research which involves the decomposition of two?dimen?sional signals into a series of bivarition intrinsic mode functions(BIMFs). BEMD and the extraction criterion of its true BIMFs are investigated by processing a complex?value simulation chatter signal. Then the feature vectors which are employed as an amplification for the chatter premonition are discussed. Furthermore, the methodology is tested and validated by experimental data collected from a CNC guideway grinder KD4020 X16 in Hangzhou Hangji Machine Tool Co., Ltd. The results illustrate that the BEMD is a superior method in terms of processing non?stationary and nonlinear signals. Meanwhile, the peak to peak, real?time standard deviation and instantaneous energy are proven to be e ec?tive feature vectors which reflect the di erent grinding states. Finally, a LSSVM model is established for grinding status classification based on feature vectors, giving a prediction accuracy rate of 96%.
