Fault Diagnosis of BLDC Motor Drive using Vibration Spectrum Analysis: Part II

Sharma, Vivek Kumar; Usman, Adil; Rajpurohit, Bharat Singh

doi:10.1109/iprecon49514.2020.9315236

Cited by 5 publications

(3 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Various fault detection techniques leverage the benefits of co-simulation tools for motor-drive applications, including inverter switch fault diagnosis [17][18][19]. In [17], the modeling of high-performance multiphase brushless AC (BLAC) machines was investigated for aerospace applications using Simulink and Ansys Twin Builder co-simulation models.…”

Section: Introductionmentioning

confidence: 99%

“…This paper used Ansys software and Simulink to analyze the PMSM drive system under various reference speeds, which further shows the effectiveness of using co-simulation of the electrical and magnetic domains to highlight all possible effects. Moreover, a co-simulation approach has been used for vibration spectrum-based fault diagnosis of BLDC motor drives [19]. Based on the vibration spectrum obtained under healthy and faulty cases, the rotor PM demagnetization fault can be diagnosed.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Robust Online Diagnostic Strategy of Inverter Open-Circuit Faults for Robotic Joint BLDC Motors

Metwly,

Logan,

Clark

et al. 2024

Machines

View full text Add to dashboard Cite

As robots are increasingly used in remote, safety-critical, and hazardous applications, the reliability of robots is becoming more important than ever before. Robotic arm joint motor-drive systems are vulnerable to hardware failures due to harsh operating environment in many scenarios, which may yield various joint failures and result in significant downtime costs. Targeting the most common robotic joint brushless DC (BLDC) motor-drive systems, this paper proposes a robust online diagnostic method for semiconductor faults for BLDC motor drives. The proposed fault diagnostic technique is based on the stator current signature analysis. Specifically, this paper investigates the performance of the BLDC joint motors under open-circuit faults of the inverter switches using finite element co-simulation tools. Furthermore, the proposed methodology is not only capable of detecting any open-circuit faults but also identifying faulty switches based on a knowledge table by considering various fault conditions. The robustness of the proposed technique was verified through extensive simulations under different speed and load conditions. Moreover, simulations have been carried out on a Kinova Gen-3 robot arm to verify the theoretical findings, highlighting the impacts of locked joints on the robot’s end-effector locations. Finally, experimental results are presented to corroborate the performance of the proposed fault diagnostic strategy.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Robust Online Diagnostic Strategy of Inverter Open-Circuit Faults for Robotic Joint BLDC Motors

Metwly,

Logan,

Clark

et al. 2024

Machines

View full text Add to dashboard Cite

show abstract

“…Acquiring information about the temperature of the IM is important because the thermal behavior of the IM influences the performance of the electrical drive train. Electrical machines should be monitored and diagnosed as per safety criteria [ 1 , 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

A Combined Model and Data-Driven Approach for the Determination of Rotor Temperature in an Induction Machine

Mocanu

Onea

Dosoftei

2021

Sensors

View full text Add to dashboard Cite

The need for protection of electrical machines comes as a demand of safety regulations in the automotive industry as well as a result of the general desire to obtain a robust and reliable electric powertrain. This paper introduces a hybrid method for estimating the temperature of the rotor of an Induction Machine (IM) based on a Nonlinear Autoregressive Network with Exogenous inputs (NARX) used as a prediction function within a particle filter. The temperature of the stator case is measured, and the information is used as an input to a NARX network and as a variable to a thermal process with first-order dynamics which serves as an observation function. Uncertainties of the NARX and thermal model are determined and used to correct the posterior estimate. Experimental data are used from a real IM test-bench and the results prove the applicability and good performance.

show abstract

Robust Control of a Three-Phase Synchronous In-wheel Motor

Mocanu

Onea

2021

IFAC-PapersOnLine

View full text Add to dashboard Cite

Fault Diagnosis of BLDC Motor Drive using Vibration Spectrum Analysis: Part II

Cited by 5 publications

References 10 publications

A Robust Online Diagnostic Strategy of Inverter Open-Circuit Faults for Robotic Joint BLDC Motors

A Robust Online Diagnostic Strategy of Inverter Open-Circuit Faults for Robotic Joint BLDC Motors

A Combined Model and Data-Driven Approach for the Determination of Rotor Temperature in an Induction Machine

Robust Control of a Three-Phase Synchronous In-wheel Motor

Contact Info

Product

Resources

About