Automated cycle time measurement and analysis of excavator's loading operation using smart phone-embedded IMU sensors

N. Mathur, S. S. Aria, T. Adams, C. R. Ahn, S. Lee

Research output: Contribution to conferencePaper

4 Citations (Scopus)

Abstract

Measurement and analysis of duty cycle of construction equipment is essential from the perspective of making decision with regards to controlling idle time and realizing productivity improvement. However, current monitoring techniques like Vehicle Health Monitoring Systems (VHMS) are either too expensive and/or are not compatible with outdated equipment fleets and equipment across different manufactures. To address these issues, we aim to develop a non-invasive technique of using a smart phone to measure the various activity modes (e.g. wheel base motion, cabin rotation and arm movement for excavator) and subsequently duty cycle of construction equipment. The smart phone is mounted inside the cabin of construction equipment to automatically capture engine vibration signatures in form of three-dimensional acceleration. Various time and frequency domain features are extracted from this raw data and are tested and classified into different equipment actions using machine learning algorithms from WEKA (Waikato Environment for Knowledge Analysis) data mining set. The classification accuracy on a random sample generated from various experiments on hydraulic excavator (CAT 330CL) was turned out to be between 72-86%. The average cycle time measurement accuracy based on predicted labels for equipment actions was around 88.5%. This result demonstrates the potential use of the proposed technique as an affordable system for automated and real time measurement of construction equipment duty cycle to facilitate detailed productivity analysis.

Original languageEnglish (US)
Pages215-222
Number of pages8
StatePublished - Jan 1 2015
Event2015 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2015 - Austin, United States
Duration: Jun 21 2015Jun 23 2015

Other

Other2015 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2015
CountryUnited States
CityAustin
Period6/21/156/23/15

Fingerprint

Construction equipment
Excavators
Time measurement
Sensors
Productivity
Monitoring
Learning algorithms
Data mining
Learning systems
Labels
Wheels
Decision making
Hydraulics
Health
Engines
Experiments

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Computer Science Applications

Cite this

Mathur, N., Aria, S. S., Adams, T., Ahn, C. R., & Lee, S. (2015). Automated cycle time measurement and analysis of excavator's loading operation using smart phone-embedded IMU sensors. 215-222. Paper presented at 2015 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2015, Austin, United States.

Automated cycle time measurement and analysis of excavator's loading operation using smart phone-embedded IMU sensors. / Mathur, N.; Aria, S. S.; Adams, T.; Ahn, C. R.; Lee, S.

2015. 215-222 Paper presented at 2015 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2015, Austin, United States.

Research output: Contribution to conferencePaper

Mathur, N, Aria, SS, Adams, T, Ahn, CR & Lee, S 2015, 'Automated cycle time measurement and analysis of excavator's loading operation using smart phone-embedded IMU sensors' Paper presented at 2015 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2015, Austin, United States, 6/21/15 - 6/23/15, pp. 215-222.
Mathur N, Aria SS, Adams T, Ahn CR, Lee S. Automated cycle time measurement and analysis of excavator's loading operation using smart phone-embedded IMU sensors. 2015. Paper presented at 2015 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2015, Austin, United States.
Mathur, N. ; Aria, S. S. ; Adams, T. ; Ahn, C. R. ; Lee, S. / Automated cycle time measurement and analysis of excavator's loading operation using smart phone-embedded IMU sensors. Paper presented at 2015 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2015, Austin, United States.8 p.
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