Application of digital twin and IoT concepts for solving the tasks of hydraulically actuated heavy equipment lifecycle management

The paper considers an approach of using digital twin and IoT concepts for solving the tasks related to the operation and maintenance of the hydraulically actuated heavy equipment. A technique for the camera-less remote surveillance on the heavy equipment is presented. It uses the sensor data about the pressure and position of the hydraulic actuators transmitted in IoT environment to a digital twin that reproduces the motion of the machine using its dynamic model. The forces acting in the machine calculated by the digital twin give an ability to calculate the stress levels in the mechanical structure of the machine. These data can be used to estimate the fatigue life of the machine as part of the predictive maintenance practice. The problems associated with the implementation of the proposed approach are discussed and the proof of concept system and experimental results are presented.