Deviation Detection in Dual Motor-Driven Industrial Doors
(2025)Department of Automatic Control
- Abstract
- This thesis investigates sensorless methods for detecting collisions and added weight in dual motor-driven industrial doors, to enhance safety without additional hardware. The study is grounded in the safety requirements outlined in EN 12453:2017 and conducted in collaboration with ASSA ABLOY. By monitoring deviations in the torque-producing current (IQ) from the motors, the developed methods identify abnormal behavior during door operation. The proposed solution employs filtering strategies, including exponential moving averages (EMA) and threshold-based detection algorithms based on torque and its derivative.
A comprehensive set of tests was performed on an OH1142P Dual Drive industrial door under various load cases and collision... (More) - This thesis investigates sensorless methods for detecting collisions and added weight in dual motor-driven industrial doors, to enhance safety without additional hardware. The study is grounded in the safety requirements outlined in EN 12453:2017 and conducted in collaboration with ASSA ABLOY. By monitoring deviations in the torque-producing current (IQ) from the motors, the developed methods identify abnormal behavior during door operation. The proposed solution employs filtering strategies, including exponential moving averages (EMA) and threshold-based detection algorithms based on torque and its derivative.
A comprehensive set of tests was performed on an OH1142P Dual Drive industrial door under various load cases and collision scenarios. The results demonstrate that the developed approach can detect added weights as small as 20 kg and collisions, although exceeding the safety-standard maximum force requirements. The system showed numerous false positives, particularly because of temperaturerelated torque variation. To address this, a compensation mechanism based on empirical modeling of temperature effects was implemented.
The proposed method shows promise as a robust, low-cost enhancement to complement existing safety mechanisms and serves as a foundation for future refinement and deployment across diverse door models and operating conditions. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9212591
- author
- Svanlund Hällsson, William and Öström, Nanna
- supervisor
- organization
- year
- 2025
- type
- H3 - Professional qualifications (4 Years - )
- subject
- report number
- TFRT-6297
- other publication id
- 0280-5316
- language
- English
- id
- 9212591
- date added to LUP
- 2025-09-18 14:17:47
- date last changed
- 2025-09-18 14:17:47
@misc{9212591,
abstract = {{This thesis investigates sensorless methods for detecting collisions and added weight in dual motor-driven industrial doors, to enhance safety without additional hardware. The study is grounded in the safety requirements outlined in EN 12453:2017 and conducted in collaboration with ASSA ABLOY. By monitoring deviations in the torque-producing current (IQ) from the motors, the developed methods identify abnormal behavior during door operation. The proposed solution employs filtering strategies, including exponential moving averages (EMA) and threshold-based detection algorithms based on torque and its derivative.
A comprehensive set of tests was performed on an OH1142P Dual Drive industrial door under various load cases and collision scenarios. The results demonstrate that the developed approach can detect added weights as small as 20 kg and collisions, although exceeding the safety-standard maximum force requirements. The system showed numerous false positives, particularly because of temperaturerelated torque variation. To address this, a compensation mechanism based on empirical modeling of temperature effects was implemented.
The proposed method shows promise as a robust, low-cost enhancement to complement existing safety mechanisms and serves as a foundation for future refinement and deployment across diverse door models and operating conditions.}},
author = {{Svanlund Hällsson, William and Öström, Nanna}},
language = {{eng}},
note = {{Student Paper}},
title = {{Deviation Detection in Dual Motor-Driven Industrial Doors}},
year = {{2025}},
}