A DSP Based Torque Meter for Induction Motors

Fabiano Valias De Carvalho; João Onofre Pereira Pinto; Luiz Eduardo Borges Da Silva; Bimal K. Bose; Germano Lambert Torres

doi:10.1109/IECON.2003.1280016

A DSP Based Torque Meter for Induction Motors

Fabiano Valias De Carvalho, João Onofre Pereira Pinto, Luiz Eduardo Borges Da Silva, Bimal K. Bose, Germano Lambert Torres

Research output: Contribution to conference › Paper › peer-review

20 Scopus citations

Abstract

This work describes the steps to implement a torque meter for three phases induction motors, based on stator voltage and machine current measurement. The strategy is based on stator flux synthesis through Programmable Cascaded Low-Pass Filters (PCLPF). The electromagnetic torque estimation is processed by a DSP microprocessor in real time. The PCLPF filter outlines the problem of necessary numeric integration to calculate the stator flux starting from the samples of stator voltage and current. The Programmable Cascaded Low-Pass Filter is implemented using Recurrent Neural Network (RNN-PCLPF) trained by an algorithm based on Kalman filter. The DSP based implementation of a torque meter results in an equipment with the same precision when comparing with torque meters based on torsion of metallic axes, with known elastic constant and strain gauges.

Original language	English
Pages	414-418
Number of pages	5
DOIs	https://doi.org/10.1109/IECON.2003.1280016
State	Published - 2003
Externally published	Yes
Event	The 29th Annual Conference of the IEEE Industrial Electronics Society - Roanoke, VA, United States Duration: Nov 2 2003 → Nov 6 2003

Conference

Conference	The 29th Annual Conference of the IEEE Industrial Electronics Society
Country/Territory	United States
City	Roanoke, VA
Period	11/2/03 → 11/6/03

Keywords

DSP application
Kalman filter
Programmable cascade low-pass filter
Recurrent neural network
Torque estimation

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10.1109/IECON.2003.1280016

Cite this

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title = "A DSP Based Torque Meter for Induction Motors",

abstract = "This work describes the steps to implement a torque meter for three phases induction motors, based on stator voltage and machine current measurement. The strategy is based on stator flux synthesis through Programmable Cascaded Low-Pass Filters (PCLPF). The electromagnetic torque estimation is processed by a DSP microprocessor in real time. The PCLPF filter outlines the problem of necessary numeric integration to calculate the stator flux starting from the samples of stator voltage and current. The Programmable Cascaded Low-Pass Filter is implemented using Recurrent Neural Network (RNN-PCLPF) trained by an algorithm based on Kalman filter. The DSP based implementation of a torque meter results in an equipment with the same precision when comparing with torque meters based on torsion of metallic axes, with known elastic constant and strain gauges.",

keywords = "DSP application, Kalman filter, Programmable cascade low-pass filter, Recurrent neural network, Torque estimation",

author = "{De Carvalho}, {Fabiano Valias} and Pinto, {Jo{\~a}o Onofre Pereira} and {Da Silva}, {Luiz Eduardo Borges} and Bose, {Bimal K.} and Torres, {Germano Lambert}",

year = "2003",

doi = "10.1109/IECON.2003.1280016",

language = "English",

pages = "414--418",

note = "The 29th Annual Conference of the IEEE Industrial Electronics Society ; Conference date: 02-11-2003 Through 06-11-2003",

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TY - CONF

T1 - A DSP Based Torque Meter for Induction Motors

AU - De Carvalho, Fabiano Valias

AU - Pinto, João Onofre Pereira

AU - Da Silva, Luiz Eduardo Borges

AU - Bose, Bimal K.

AU - Torres, Germano Lambert

PY - 2003

Y1 - 2003

N2 - This work describes the steps to implement a torque meter for three phases induction motors, based on stator voltage and machine current measurement. The strategy is based on stator flux synthesis through Programmable Cascaded Low-Pass Filters (PCLPF). The electromagnetic torque estimation is processed by a DSP microprocessor in real time. The PCLPF filter outlines the problem of necessary numeric integration to calculate the stator flux starting from the samples of stator voltage and current. The Programmable Cascaded Low-Pass Filter is implemented using Recurrent Neural Network (RNN-PCLPF) trained by an algorithm based on Kalman filter. The DSP based implementation of a torque meter results in an equipment with the same precision when comparing with torque meters based on torsion of metallic axes, with known elastic constant and strain gauges.

AB - This work describes the steps to implement a torque meter for three phases induction motors, based on stator voltage and machine current measurement. The strategy is based on stator flux synthesis through Programmable Cascaded Low-Pass Filters (PCLPF). The electromagnetic torque estimation is processed by a DSP microprocessor in real time. The PCLPF filter outlines the problem of necessary numeric integration to calculate the stator flux starting from the samples of stator voltage and current. The Programmable Cascaded Low-Pass Filter is implemented using Recurrent Neural Network (RNN-PCLPF) trained by an algorithm based on Kalman filter. The DSP based implementation of a torque meter results in an equipment with the same precision when comparing with torque meters based on torsion of metallic axes, with known elastic constant and strain gauges.

KW - DSP application

KW - Kalman filter

KW - Programmable cascade low-pass filter

KW - Recurrent neural network

KW - Torque estimation

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T2 - The 29th Annual Conference of the IEEE Industrial Electronics Society

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A DSP Based Torque Meter for Induction Motors

Abstract

Conference

Keywords

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