Characterization of Construction Equipment Sounds and Uses in the Field

Abstract

Automated data acquisition and interpretation is an area of construction research currently being developed to improve the level of productivity and the quality of decision making as it relates to project control. This thesis discusses the applicability of acoustic signal analysis as a valid remote sensory technology for extraction of data from a construction environment. The scope of this research has been limited to the study of equipment intensive operations. In demonstrating the applicability of acoustic signal analysis, key measurable characteristics of sound are first discussed, followed by an overview of the equipment used for data collection and analysis. Detailed information is then presented describing specific signal analysis modes utilized to visually identify acoustic features representative of specific types of equipment. Utilizing two types of analysis - spectral and spectrographic - results of six types of construction equipment are then presented to demonstrate qualitatively, how, through pattern recognition specific features can be used to distinguish one type of equipment from another. Further results are presented to prove that loaded hauling units can be distinguished from empty units based upon their acoustic signature. Based upon conclusions obtained from actual results of samples, potential applications for acoustic sensory technology relevant to the construction environment are provided.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1992
Accession Number
ADA262074

Entities

People

  • Joseph G. Orlowsky

Organizations

  • Pennsylvania State University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acoustic Detection
  • Acoustic Measurement
  • Acoustic Propagation
  • Acoustic Properties
  • Acoustic Signatures
  • Acoustic Waves
  • Acoustics
  • Construction Equipment
  • Control Systems
  • Detectors
  • Digital Signal Processing
  • Measurement
  • Pattern Recognition
  • Processing Equipment
  • Production
  • Signal Processing
  • Sound Waves

Readers

  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Computer Vision.
  • Systems Analysis and Design

Technology Areas

  • AI & ML