Prediction of noise emission in the machining of wood materials by means of an artificial neural network


ÖZŞAHİN Ş., Singer H.

NEW ZEALAND JOURNAL OF FORESTRY SCIENCE, vol.52, pp.1-10, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 52
  • Publication Date: 2022
  • Doi Number: 10.33494/nzjfs522022x92x
  • Journal Name: NEW ZEALAND JOURNAL OF FORESTRY SCIENCE
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Agricultural & Environmental Science Database, BIOSIS, CAB Abstracts, Compendex, Environment Index, Geobase, Directory of Open Access Journals
  • Page Numbers: pp.1-10
  • Keywords: artificial neural network, noise emission, machining, wood, prediction, POWER-CONSUMPTION, SAW BLADE, LEVEL, PARAMETERS, PRESSURE, STRENGTH, MOISTURE, WEAR
  • Karadeniz Technical University Affiliated: Yes

Abstract

Background: Noise produced during machining of wood materials can be a source of harm to workers and an environmental hazard. Understanding the factors that contribute to this noise will aid the development of mitigation strategies. In this study, an artificial neural network (ANN) model was developed to model the effects of wood species, cutting width, number of blades, and cutting depth on noise emission in the machining process.