Show simple item record

dc.contributor.advisorParlos, Alexander
dc.contributor.advisorKim, Won-Jong
dc.creatorFu, Jianxi
dc.date.accessioned2019-01-17T23:20:02Z
dc.date.available2020-08-01T06:39:00Z
dc.date.created2018-08
dc.date.issued2018-07-30
dc.date.submittedAugust 2018
dc.identifier.urihttp://hdl.handle.net/1969.1/173683
dc.description.abstractElectric motor-driven systems are basic components in most industrial processes. The four motor mechanical measurements of interest that dictate motor performance are shaft torque, shaft speed, mechanical power (motor load) and energy conversion efficiency. Torque and speed, along with the input electric power are needed to estimate load and efficiency. Mechanical performance monitoring is an ever-increasing trend, present in many industries. Such monitoring can identify equipment failures, predict system degradation, and monitor overload conditions. It also provides users with a deeper understanding of the operational demands of their machines, which is difficult to diagnose through standard vibration analysis. Nevertheless, it is extremely challenging to measure the in-situ motor shaft torque, and to a lesser extent shaft speed. A comprehensive literature survey indicates that many estimation methods exist for motor mechanical measurements. However, almost all of these methods require at least one of the following: (1) load tests involving measurements of shaft speed and torque at a stable temperature, (2) no-load tests, i.e. with motor mechanically decoupled from driven load, (3) deenergized stator resistance measurements, i.e. with motor electrically disconnected. These three conditions require a level of access to the motor under test not generally acceptable or possible in an industrial environment, i.e. these are the “intrusive” requirements of the mechanical measurement estimation methods. A non-intrusive approach to mechanical measurements is proposed, incorporating the equivalent circuit model of an operating induction motor. The estimation of the mechanical measurements is formulated as a non-linear, constrained optimization problem with the variables to be optimized being the parameters of the equivalent circuit model. The optimization problem iii is solved using the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) method. The required inputs of the proposed method are the three-phase voltage and current phasors and the motor nameplate information. The resulting parameters of the equivalent circuit model and new voltage and current phasors are used to estimate the motor mechanical measurements. Five (5) manufacturer's catalog data sheets, two (2) small motors, 1 HP and 3 HP, and two (2) larger motors, 100 HP and 200 HP, are used to test the proposed approach against direct mechanical measurements of torque and speed. The experimental results demonstrate that the proposed method achieves speed estimates within ±5 RPM of the sensor readings, which is comparable to existing non-intrusive methods. For torque, load and efficiency, the proposed method achieves accuracy within ±2-3% for high (>25%) loads, and up to ±5% errors for low (<25%) loads. The presented shaft torque accuracy is an improvement over existing, nonintrusive techniques and in the case of load and efficiency estimation is an improvement over existing, non-intrusive and even some intrusive techniques. The novel contribution of this research is the estimation of mechanical measurements based only on motor electrical measurements and motor nameplate information. The need for a torque transducer, speed sensor and any motor field testing is eliminated. Further testing is needed to establish the accuracy of the method on a wider motor population.en
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectMechanical measurementsen
dc.subjectTorqueen
dc.subjectSpeeden
dc.subjectLoaden
dc.subjectEfficiencyen
dc.subjectNon-intrusive approachen
dc.subjectequivalent circuiten
dc.subjectCMA-ESen
dc.titleA Non-intrusive Method for Mechanical Measurements in Constant Frequency Electric Motorsen
dc.typeThesisen
thesis.degree.departmentMechanical Engineeringen
thesis.degree.disciplineMechanical Engineeringen
thesis.degree.grantorTexas A & M Universityen
thesis.degree.nameDoctor of Philosophyen
thesis.degree.levelDoctoralen
dc.contributor.committeeMemberRasmussen, Bryan
dc.contributor.committeeMemberSilva-Martinez, Jose
dc.type.materialtexten
dc.date.updated2019-01-17T23:20:02Z
local.embargo.terms2020-08-01
local.etdauthor.orcid0000-0003-3928-3047


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record