Remote Fault Detection in Conveyor System Using Drone Based on Audio FFT Analysis

드론을 활용하고 음성 FFT분석에 기반을 둔 컨베이어 시스템의 원격 고장 검출

  • Yeom, Dong-Joo (Department of Electrical and Electronic Engineering, Semyung University) ;
  • Lee, Bo-Hee (Department of Electrical Engineering, Semyung University)
  • 염동주 (세명대학교 전기전자공학과) ;
  • 이보희 (세명대학교 전기공학과)
  • Received : 2019.09.10
  • Accepted : 2019.10.20
  • Published : 2019.10.28


This paper proposes a method for detecting faults in conveyor systems used for transportation of raw materials needed in the thermal power plant and cement industries. A small drone was designed in consideration of the difficulty in accessing the industrial site and the need to use it in wide industrial site. In order to apply the system to the embedded microprocessor, hardware and algorithms considering limited memory and execution time have been proposed. At this time, the failure determination method measures the peak frequency through the measurement, detects the continuity of the high frequency, and performs the failure diagnosis with the high frequency components of noise. The proposed system consists of experimental environment based on the data obtained from the actual thermal power plant, and it is confirmed that the proposed system is useful by conducting virtual environment experiments with the drone designed system. In the future, further research is needed to improve the drone's flight stability and to improve discrimination performance by using more intelligent methods of fault frequency.


Supported by : Semyung University


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