Early chatter identification based on optimized VMD with multi-band information fusion and compression method in robotic milling process

Undesirable self-excited chatter has always been a typical issue restricting the improvement of robotic milling quality and efficiency.Sensitive chatter identification based on processing signals can prompt operators to adjust the machining process and prevent chatter damage.Compared with the traditional machine tool,the uncertain multiple chatter frequency bands and the band-moving of the chatter frequency in robotic milling process make it more challenging to extract chatter information.This paper proposes a novel method of chatter identification using optimized variational mode decomposition(OVMD)with multi-band information fusion and compression technology(MT).During the robotic milling process,the number of decomposed modes k and the penalty coefficient a are optimized based on the dominant component of frequency scope partition and fitness of the mode center frequency.Moreover,the mayfly optimization algorithm(MA)is employed to obtain the global optimal parameter selection.In order to conquer information collection about the uncertain multiple chatter frequency bands and the band-moving of the chatter frequency in robotic milling process,MT is presented to reduce computation and extract signal characteristics.Finally,the cross entropy of the image(CEI)is proposed as the final chatter indicator to identify the chatter occurrence.The robotic milling experiments are carried out to verify the proposed method,and the results show that it can distinguish the robotic milling condition by extracting the uncertain multiple chatter frequency bands and overcome the band-moving of the chatter frequency in robotic milling process.

WO_(3)@Fe_(2)O_(3) Core-Shell Heterojunction Photoanodes for Efficient Photoelectrochemical Water Splitting

Photoelectrochemical(PEC) hydrogen production from water splitting is a green technology to convert solar energy into renewable hydrogen fuel. The construction of host/guest architecture in semiconductor photoanodes has been proven to be an effective strategy to improve solar-to-fuel conversion efficiency. In this study, WO_(3)@Fe_(2)O_(3) core-shell nanoarray heterojunction photoanodes are synthesized from the in-situ decomposition of WO_(3)@Prussian blue(WO_(3)@PB) and then used as host/guest photoanodes for photoelectrochemical water splitting, during which Fe_(2)O_(3) serves as guest material to absorb visible solar light and WO_(3) can act as host scaffolds to collect electrons at the contact. The prepared WO_(3)@Fe_(2)O_(3) shows the enhanced photocurrent density of 1.26 m A cm^(-2)(under visible light) at 1.23 V. vs RHE and a superior IPEC of 24.4% at 350 nm, which is higher than that of WO_(3)@PB and pure WO_(3)(0.43 m A/cm^(-2) and 16.3%, 0.18 m A/cm^(-2) and 11.5%) respectively, owing to the efficient light-harvesting from Fe_(2)O_(3) and the enhanced electron-hole pairs separation from the formation of type-Ⅱ heterojunctions, and the direct and ordered charge transport channels from the one-dimensional(1D) WO_(3) nanoarray nanostructures. Therefore, this work provides an alternative insight into the construction of sustainable and cost-effective photoanodes to enhance the efficiency of the solar-driven water splitting.