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Low-Complexity Monitoring of DC Motor Speed Sensor Additive Faults Using a Discrete Kalman Filter Observer.

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Title: Low-Complexity Monitoring of DC Motor Speed Sensor Additive Faults Using a Discrete Kalman Filter Observer.
Authors: Uscamaita-Quispetupa, Rossy1 (AUTHOR), Sacoto-Cabrera, Erwin J.2 (AUTHOR), Coaquira-Castillo, Roger Jesus3 (AUTHOR), Utrilla Mego, L. Walter1,4 (AUTHOR), Herrera-Levano, Julio Cesar1,5 (AUTHOR), Concha-Ramos, Yesenia1,4 (AUTHOR), Moreno-Cardenas, Edison1,2,5 (AUTHOR)
Source: Energies (19961073). Mar2026, Vol. 19 Issue 6, p1485. 21p.
Subject Terms: *Kalman filtering, *Direct current electric motors, *Fault diagnosis, *Noise measurement, *Real-time computing, *Tachometer
Abstract: This article presents an online additive fault-detection system for the speed sensor of a 200 W shunt-type direct current (DC) motor, integrated into a power module controlled by an Insulated Gate Bipolar Transistor (IGBT). The system is designed to trigger an alarm signal when an additive fault occurs by comparing the Kalman Filter (KF) residual against a predefined detection threshold. Three specific fault types in the speed sensor were analyzed: offset, disconnection, and sinusoidal noise. Experimental results demonstrate effective fault detection across a speed range of 80 to 690 rpm under no-load conditions. However, when a constant torque of 0.5 Nm is applied, both the detection threshold and the subset of reliably identifiable faults must be adjusted. The main contribution of this study is the development of a customized real-time fault detection framework and the characterization of residual variations caused by unmodeled load disturbances in actual hardware. This approach improves the monitoring and fault-diagnosis capabilities of sensor systems in DC motors by quantifying the stochastic behavior of residuals under different operating constraints. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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  Availability: 1
Header DbId: enr
DbLabel: Energy & Power Source
An: 192592659
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Label: Title
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  Data: Low-Complexity Monitoring of DC Motor Speed Sensor Additive Faults Using a Discrete Kalman Filter Observer.
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  Data: <searchLink fieldCode="AR" term="%22Uscamaita-Quispetupa%2C+Rossy%22">Uscamaita-Quispetupa, Rossy</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sacoto-Cabrera%2C+Erwin+J%2E%22">Sacoto-Cabrera, Erwin J.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Coaquira-Castillo%2C+Roger+Jesus%22">Coaquira-Castillo, Roger Jesus</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Utrilla+Mego%2C+L%2E+Walter%22">Utrilla Mego, L. Walter</searchLink><relatesTo>1,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Herrera-Levano%2C+Julio+Cesar%22">Herrera-Levano, Julio Cesar</searchLink><relatesTo>1,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Concha-Ramos%2C+Yesenia%22">Concha-Ramos, Yesenia</searchLink><relatesTo>1,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Moreno-Cardenas%2C+Edison%22">Moreno-Cardenas, Edison</searchLink><relatesTo>1,2,5</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Mar2026, Vol. 19 Issue 6, p1485. 21p.
– Name: Subject
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  Data: *<searchLink fieldCode="DE" term="%22Kalman+filtering%22">Kalman filtering</searchLink><br />*<searchLink fieldCode="DE" term="%22Direct+current+electric+motors%22">Direct current electric motors</searchLink><br />*<searchLink fieldCode="DE" term="%22Fault+diagnosis%22">Fault diagnosis</searchLink><br />*<searchLink fieldCode="DE" term="%22Noise+measurement%22">Noise measurement</searchLink><br />*<searchLink fieldCode="DE" term="%22Real-time+computing%22">Real-time computing</searchLink><br />*<searchLink fieldCode="DE" term="%22Tachometer%22">Tachometer</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This article presents an online additive fault-detection system for the speed sensor of a 200 W shunt-type direct current (DC) motor, integrated into a power module controlled by an Insulated Gate Bipolar Transistor (IGBT). The system is designed to trigger an alarm signal when an additive fault occurs by comparing the Kalman Filter (KF) residual against a predefined detection threshold. Three specific fault types in the speed sensor were analyzed: offset, disconnection, and sinusoidal noise. Experimental results demonstrate effective fault detection across a speed range of 80 to 690 rpm under no-load conditions. However, when a constant torque of 0.5 Nm is applied, both the detection threshold and the subset of reliably identifiable faults must be adjusted. The main contribution of this study is the development of a customized real-time fault detection framework and the characterization of residual variations caused by unmodeled load disturbances in actual hardware. This approach improves the monitoring and fault-diagnosis capabilities of sensor systems in DC motors by quantifying the stochastic behavior of residuals under different operating constraints. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=192592659
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        Value: 10.3390/en19061485
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      – Code: eng
        Text: English
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        PageCount: 21
        StartPage: 1485
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      – SubjectFull: Kalman filtering
        Type: general
      – SubjectFull: Direct current electric motors
        Type: general
      – SubjectFull: Fault diagnosis
        Type: general
      – SubjectFull: Noise measurement
        Type: general
      – SubjectFull: Real-time computing
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      – SubjectFull: Tachometer
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      – TitleFull: Low-Complexity Monitoring of DC Motor Speed Sensor Additive Faults Using a Discrete Kalman Filter Observer.
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            NameFull: Uscamaita-Quispetupa, Rossy
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            NameFull: Sacoto-Cabrera, Erwin J.
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            NameFull: Coaquira-Castillo, Roger Jesus
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            NameFull: Utrilla Mego, L. Walter
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            NameFull: Herrera-Levano, Julio Cesar
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            NameFull: Concha-Ramos, Yesenia
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            NameFull: Moreno-Cardenas, Edison
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            – D: 15
              M: 03
              Text: Mar2026
              Type: published
              Y: 2026
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              Value: 19
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