Use this URL to cite or link to this record in EThOS:
Title: Virtual sensor for stress monitoring in shafts using distributed-lumped model
Author: Athanasiou, Panagiotis
ISNI:       0000 0004 7970 9003
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2019
Availability of Full Text:
Access from EThOS:
Access from Institution:
The drilling process is a major part of the hydrocarbon extraction process from the earth. It is a very expensive process where any delay during the drilling process costs a substantial amount of money to the operators. To reduce the unexpected delays due to the shaft failure continuous monitoring of soil cutting forces are desirable. To enable monitoring of cutting forces during drilling operations a virtual sensor based on Distributed-Lumped (D-L) model of shafts is proposed. By measuring the input torque to the drive system drilling shaft the cutting forces at the end of the drilling shaft can be estimated using the D-L model. The measurement of the vibration signals due to the cutting forces are very important as they can be used for the control of the drive system, condition monitoring, the fault diagnosis and the geology of the soil. This thesis describes the technological challenges for the measurement of the vibration signals from a cutting tool operating at a depth of a few thousand meters (< 7000 meters), it proposes a virtual sensor development method using a hybrid modelling technique (Distributed-Lumped model). There are several problems relating to the task of monitoring the drilling operation remotely and under harsh environments. Generated vibrations are measured from a rotating tool and should be transferred to a stationary point. This process requires electric power to the transducers, which are attached onto the rotating tool, so the required signal can be received and processed for further analysis. This project deals with the development of a monitoring system for drilling systems using a virtual sensor which predicts the status of the torsional vibration at the end of the drill string (shaft). It is based on the frequency analysis of the vibration signal measured by accelerometers on the rotating shaft at the input side of the drill string. The signal from the rotating tool is transferred using a Short Distance Sensor Telemetry (SDST) which is the input to the virtual sensor which is capable of predicting the torsional vibration at cutting tool. Finally, the measured data from the drill rig have been analysed and compared with the results of the virtual sensor where it can be seen that the virtual sensor provides compatible results with the real data.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Engineering not elsewhere classified ; Signal analysis ; Condition monitoring ; Drilling ; Vibration ; Telemetry ; Lumped and Distributed-Lumped modelling