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- 저자 : Zhaocheng Wei (검색결과 2 건)
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A new analytical ICCE and force prediction model for wide-row machining of free-form surface
Minglong Guo,Zhaocheng Wei,Jia Wang,Minjie Wang,Xiaoyu Wang,Shengxian Liu 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.1
Cutting force is the most intuitive reflection of various influencing factors in the milling process, which is important for improving machining quality and efficiency. For the widerow milling with flat-end mill of free-form surface, an analytical in-cut cutting edge (ICCE) algorithm is studied in detail, and overall cutting force model is further constructed. The cutter location points along tool path are discretized into small oblique planes. Taking the oblique plane machining as the new object, the relative position of flat-end mill and workpiece in five-axis machining is defined parametrically. By constructing a semi-enclosed space in which the cutting edge participates in cutting, the ICCE is directly obtained. By analyzing the cutting force of oblique plane, the cutting force model of free-form surface can be established by spatial coordinate transformation. The simulation and experiment have demonstrated the correctness and effectiveness of the proposed ICCE algorithm and force prediction model.
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Structured Compressive Sensing-Based Spatio-Temporal Joint Channel Estimation for FDD Massive MIMO
Zhen Gao,Linglong Dai,Wei Dai,Byonghyo Shim,Zhaocheng Wang IEEE 2016 IEEE TRANSACTIONS ON COMMUNICATIONS Vol.64 No.2
<P>Massive MIMO is a promising technique for future 5G communications due to its high spectrum and energy efficiency. To realize its potential performance gain, accurate channel estimation is essential. However, due to massive number of antennas at the base station (BS), the pilot overhead required by conventional channel estimation schemes will be unaffordable, especially for frequency division duplex (FDD) massive MIMO. To overcome this problem, we propose a structured compressive sensing (SCS)-based spatio-temporal joint channel estimation scheme to reduce the required pilot overhead, whereby the spatio-temporal common sparsity of delay-domain MIMO channels is leveraged. Particularly, we first propose the nonorthogonal pilots at the BS under the framework of CS theory to reduce the required pilot overhead. Then, an adaptive structured subspace pursuit (ASSP) algorithm at the user is proposed to jointly estimate channels associated with multiple OFDM symbols from the limited number of pilots, whereby the spatio-temporal common sparsity of MIMO channels is exploited to improve the channel estimation accuracy. Moreover, by exploiting the temporal channel correlation, we propose a space-time adaptive pilot scheme to further reduce the pilot overhead. Additionally, we discuss the proposed channel estimation scheme in multicell scenario. Simulation results demonstrate that the proposed scheme can accurately estimate channels with the reduced pilot overhead, and it is capable of approaching the optimal oracle least squares estimator.</P>
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