Statistical test for detrending-moving-average-based multivariate regression model

Wang, Fang; Han, Gangwen; Fan, Qingju

doi:10.1016/j.apm.2023.08.006

Cited by 2 publications

(1 citation statement)

References 53 publications

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“…The feed-rate signal v(t) can be divided into three parts, v(t), v ′ (t), v ′′ (t), to represent velocity, acceleration, and jerk, respectively. Hence, the predictive model of real-time interpolation can be expressed as [32]:…”

Section: Fir Login Conditionmentioning

confidence: 99%

An Adapted NURBS Interpolator with a Switched Optimized Method of Feed-Rate Scheduling

Zhou

2024

Machines

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With the increasing demand for processing precision in the manufacturing industry, feed-rate scheduling is a crucial component in achieving the processing quality of complex surfaces. A smooth feed-rate profile not only guarantees machining quality but also improves machining efficiency. Although the typical offline feed-rate scheduling method possesses good processing efficiency, it may not provide an optimal solution due to the NP-hard problem caused by the feed-rate scheduling of continuous curve segments, which easily results in excess kinetic limitations and feed-rate fluctuations in a real-time interpolation. Instead, the FIR (Finite Impulse Response) method is widely used to realize interpolation in real-time processing. However, the FIR method will filter out a large number of high-frequency signals, leading to a low-processing efficiency. Further, greater acceleration or deceleration is required to ensure the interpolation passes through the segment end at a predefined feed rate and the deceleration in the feed rate profile appears earlier, which allows the interpolation to easily exceed the kinetic limitation. At present, a simple offline or online method cannot realize the global optimization of the feed-rate profile and guarantee the machining efficiency. Moreover, the current feed-rate scheduling that considers both offline and online methods does not consider the situation that the call of offline data and online prediction data will lead to a decrease in the real-time performance of the CNC system. Further, real-time feed-rate scheduling data tend to dominate the whole interpolation process, thus reducing the effect of the offline feed-rate scheduling data. Hence, based on the tool path with C3 continuity (Cubic Continuously Differentiable), this paper first presents a basic interpolation unit relevant to the S-type interpolation feed-rate profile. Then, an offline local smooth strategy is proposed to smooth the feed-rate profile and reduce the exceeding of kinetic limitations and feed-rate fluctuations caused by frequent acceleration and deceleration. Further, a global online smoothing strategy based on the data generated by offline pre-interpolation is presented. What is more, FIR login and logout conditions are proposed to further smooth the feed-rate profile and improve the real-time performance and machining efficiency. The case study validates that the proposed method performs better in kinetic results compared with the typical offline and FIR methods in both the simulation experiment and actual machining experiments. Especially, in actual processing experiments, the proposed method obtains a 28% reduction in contour errors. Further, the proposed method compared with the FIR method obtains a 15% increase in machining efficiency but only a 4% decrease compared with the typical offline method.

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Section: Fir Login Conditionmentioning

confidence: 99%

An Adapted NURBS Interpolator with a Switched Optimized Method of Feed-Rate Scheduling

Zhou

2024

Machines

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Coupling correlation adaptive detrended analysis for multiple nonstationary series

Wang,

Han

2023

Chaos, Solitons & Fractals

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Statistical test for detrending-moving-average-based multivariate regression model

Cited by 2 publications

References 53 publications

An Adapted NURBS Interpolator with a Switched Optimized Method of Feed-Rate Scheduling

An Adapted NURBS Interpolator with a Switched Optimized Method of Feed-Rate Scheduling

Coupling correlation adaptive detrended analysis for multiple nonstationary series

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