Harmonic Fault Diagnosis in Power Quality System Using Harmonic Wavelet

Kordestani, Mojtaba; Safavi, Ali Akbar; Saif, Mehrdad

doi:10.1016/j.ifacol.2017.08.2370

Cited by 9 publications

(7 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Harmonic fault diagnosis and identification using a modified WT known as the harmonic WT is used in [14]. The denoising of the signal and detection of motor bearing faults using the WT has been proposed in [45].…”

Section: Comparison Of This Study With Existing Studiesmentioning

confidence: 99%

“…The STFT is useful for smooth signals; if sudden variations are present in the signal, such as voltage or current waveforms, the fixed window of operation of STFT makes it fail to detect complex uncertainties [13]. The WT allows the decomposition of the signal into the time domain and frequency domain representation, which gives precise information about the variations and transients [14]. Moreover, for high-frequency components present in the signal, the WT applies a short window, and for low-frequency components, the WT applies a long window of operation [15].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Spectrum Analysis for Condition Monitoring and Fault Diagnosis of Ventilation Motor: A Case Study

et al. 2021

View full text Add to dashboard Cite

In modern power systems, since most loads are inductive by nature, there is an ongoing power quality issue and researchers’ interest in improving the power factor is widespread, as inductive loads have a low power factor that depletes the system’s capacity and has an adverse effect on the voltage level. The measurement and acute analysis of voltage- and current-level waveforms is essential to tackle power quality issues. This article presents a detailed case study and analysis of real-time data measured from a frequency converter, which is used to operate the motor of a ventilation system. The output of the frequency converter is a highly distorted current wave. A hybrid Fourier transform (FT)- and wavelet transform-based solution has been proposed here to diagnose and identify the causes of motor failure in the ventilation system. The traditional FT did not give a detailed analysis of this type of signal, which is highly contaminated by noise. Therefore, first, the signal is preprocessed for data denoising using the wavelet transform. Second, the Fourier analysis is performed on the filtered signal for frequency analysis and segregation of fundamental frequency components, higher-order harmonics, and suppressed noise. The spectrum analysis reveals that the noise is generated due to the rapidly switching circuits in the frequency converter and this unfiltered signal at the output of the frequency converter causes motor failure.

show abstract

Section: Comparison Of This Study With Existing Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spectrum Analysis for Condition Monitoring and Fault Diagnosis of Ventilation Motor: A Case Study

et al. 2021

View full text Add to dashboard Cite

show abstract

“…with P(x, y) being the crack region result by the proposed method; R(x, y) is the ground truth. In order to assess the performance of classification systems, we have calculated five performance measures which are as follows [36,37]: e performance parameters (AC, SE, SP, P, and DSC) for cracks segmentation which are presented in equations ( 6)- (10). e accuracy (AC)…”

Section: Performances Evaluationmentioning

confidence: 99%

“…e combination of the approach (RF) method [8,9] and wavelets [10,11] is used to detect the edges of the cracks. Amet et al [12] also presented a method for edge defect detection based on wavelet decomposition and cooccurrence as a descriptor to extract the characteristics of the images to classify the images as defective or nondefective.…”

Section: Introductionmentioning

confidence: 99%

An Automatic Detection by Classification of Cracked Pixels or Noncracked Pixels in Road Surface

Taifi

Azougaghe

et al. 2021

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Automatic detection and monitoring of the condition of cracks in the road surface are essential elements to ensure road safety and quality of service. A crack detection method based on wavelet transforms (2D-DWT) and Jerman enhancement filter is used. This paper presents different contributions corresponding to the three phases of the proposed system. The first phase presents the contrast enhancement technique to improve the quality of roads surface image. The second phase proposes an effective detection algorithm using discrete wavelet (2D-DWT) with “db8” and two-level sub-band decomposition. Finally, in the third phase, the Jerman enhancement filter is usually used with different parameters of the control response uniformity “ τ ” to enhance for cracks detection. The experimental results in this article provide very powerful results and the comparisons with five existing methods show the effectiveness of the proposed technique to validate the recognition of surface cracks.

show abstract

“…The permanent presence of non-linear loads in electrical systems results in current and voltage distortions, which can produce detrimental effects depending on the type of load and its interaction with other system components. According to [11], harmonic distortions are commonly found in faulted power distribution systems and in most cases contains harmonic of third, fifth, seventh, ninth and 11th orders. Work in [11] also presents a methodology to detect harmonics in power systems using wavelet transform.…”

Section: Introductionmentioning

confidence: 99%

Voltage Harmonic Impacts on Electric Motors: A Comparison between IE2, IE3 and IE4 Induction Motor Classes

et al. 2020

View full text Add to dashboard Cite

Global energy systems are undergoing a transition process towards renewable energy and energy efficiency practices. Induction motors play an important role in this energy transformation process since they are widely used as industrial loads, representing more than 53% of global energy consumption. With more countries adopting minimum energy performance standards through more efficient induction motors, comparisons between these new technologies in the presence of electrical disturbances must be systematically evaluated before adopting a substitution policy in the industry. To this end, this work presents a comparative analysis of the impact of harmonic voltages on the performance and temperature rise of electric motors classes IE2, IE3 and IE4 in the same operational conditions in view of future substitutions. The results show that under ideal operating conditions the IE4 class permanent magnet motor has better performance in terms of consumption and temperature, however presenting non-linear characteristics. In the presence of voltage harmonics, this scenario changes completely according to the harmonic content. Finally, aiming to analyze the harmonics influence in the motor temperature rise a statistical analysis by means of Spearman correlation matrices is presented.

show abstract

Harmonic Fault Diagnosis in Power Quality System Using Harmonic Wavelet

Cited by 9 publications

References 21 publications

Spectrum Analysis for Condition Monitoring and Fault Diagnosis of Ventilation Motor: A Case Study

Spectrum Analysis for Condition Monitoring and Fault Diagnosis of Ventilation Motor: A Case Study

An Automatic Detection by Classification of Cracked Pixels or Noncracked Pixels in Road Surface

Voltage Harmonic Impacts on Electric Motors: A Comparison between IE2, IE3 and IE4 Induction Motor Classes

Contact Info

Product

Resources

About