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Several parameters of industrial processes are indirectly measured by multi-scale mechanical frequency spectrum. Selecting suitable mechanical sub-signals and relevant frequency spectral features for different process parameters remains an open issue. This study proposes a new optimized ensemble model based on feature selection using simple sphere criterion (SSC). Mechanical signals are adaptively...
Frequency spectral data of mechanical vibration and acoustic signals relate to difficult-to-measure production quality and quantity parameters of complex industrial processes. A selective ensemble (SEN) algorithm can be used to build a soft sensor model of these process parameters by fusing valued information selectively from different perspectives. However, a combination of several optimized ensemble...
There are complex mapping relationships among different mill load parameters and multi-scale frequency spectra of ball mill's mechanical vibration and acoustic signals. Aim at to construct an effective and meaningful soft sensor model, how to select interesting input variables of each local-scale frequency spectrum and how to fuse these different multi-scale ones jointly, is still an un-solved open...
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