木材加工综述：锯切过程的表征、优化和监控,Wood Material Science & Engineering

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木材加工综述：锯切过程的表征、优化和监控
Wood Material Science & Engineering ( IF 2.2 ) Pub Date : 2018-04-23 , DOI: 10.1080/17480272.2018.1465465
Vahid Nasir ₁ , Julie Cool ₁

Affiliation

摘要锯切是最常见的加工工艺，存在于初级和次级木材加工领域。本文的目的是回顾它是如何受到不同因素的影响的。识别并解释了当前与各种加工因素、过程监控和传感器选择相关的挑战。因此，概述了四个研究挑战和技术差距。(1) 由于文献研究的切割工艺、木材种类、测量方法和切割速度范围不同，报告的结果相互矛盾，因此在将结果与文献中的结果进行比较时需要特别考虑。(2) 实验室测试条件还不能完全代表锯木厂的极端切削条件。应更加重视那些苛刻的工业切削条件。(3)木材切割研究缺乏多目标优化方法，建议锯末产生应与表面质量和功耗同时分析。(4) 与金属切削相比，使用人工智能方法进行木材锯切监控的研究很少，在设计自适应控制系统时应优先考虑。结合智能监控和多目标优化方法应该为控制锯切过程铺平道路，从而实现更高的表面质量和成本效益的加工。这表明锯屑的产生应与表面质量和功耗同时进行分析。(4) 与金属切削相比，使用人工智能方法进行木材锯切监测的研究很少，在设计自适应控制系统时应优先考虑。结合智能监控和多目标优化方法应该为控制锯切过程铺平道路，从而实现更高的表面质量和成本效益的加工。这表明锯屑的产生应与表面质量和功耗同时进行分析。(4) 与金属切削相比，使用人工智能方法进行木材锯切监测的研究很少，在设计自适应控制系统时应优先考虑。结合智能监控和多目标优化方法应该为控制锯切过程铺平道路，从而实现更高的表面质量和成本效益的加工。

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A review on wood machining: characterization, optimization, and monitoring of the sawing process

ABSTRACT Sawing is the most common machining process and is present in both primary and secondary wood transformation sectors. The objective of this paper is to review how it is affected by different factors. The current challenges associated with various machining factors, process monitoring, and sensor selection were identified and explained. Consequently, four research challenges and technological gaps were outlined. (1) Contradictory results have been reported due to different cutting processes, wood species, measurement methods, and cutting speed range studied in literature, so special consideration needs to be taken when comparing results with those available in the literature. (2) Laboratory test conditions cannot yet fully represent the extreme cutting conditions in sawmills. More emphasis should be placed on those harsh industrial cutting conditions. (3) Research on wood cutting lacks multi-objective optimization approach, which suggests that sawdust generation should be simultaneously analysed with surface quality and power consumption. (4) Compared with metal cutting, little research has been conducted on wood sawing monitoring using an artificial intelligence approach, which should be prioritized in designing adaptive control systems. Combining intelligent monitoring and multi-objective optimization approaches should pave the way for controlling the sawing process so higher surface quality and cost efficient machining is achieved.

更新日期：2018-04-23

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