Six Sigma-Based Frequency Response Analysis for Power Transformer Winding Deformation
Winding deformities in distribution transformers pose significant risks to operational reliability and system safety. Frequency response analysis (FRA) is a well-established technique for identifying mechanical faults; however, its diagnostic reliability is hindered by subjectivity in interpreting r...
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MDPI AG
2025-04-01
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| author | Bonginkosi A. Thango |
| author_facet | Bonginkosi A. Thango |
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| collection | DOAJ |
| description | Winding deformities in distribution transformers pose significant risks to operational reliability and system safety. Frequency response analysis (FRA) is a well-established technique for identifying mechanical faults; however, its diagnostic reliability is hindered by subjectivity in interpreting response signatures. This study proposes a novel diagnostic technique, termed FRA6σ, which integrates Six Sigma (6σ) statistical tools with FRA to enable objective fault detection. The methodology employs control charts (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="false"><mrow><mi>X</mi></mrow><mo>¯</mo></mover></mrow></semantics></math></inline-formula> chart, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="false"><mrow><mi>R</mi></mrow><mo>¯</mo></mover></mrow></semantics></math></inline-formula>-chart) to monitor deviations from baseline signatures and utilizes process capability indices (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>C</mi></mrow><mrow><mi>p</mi></mrow></msub></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>C</mi></mrow><mrow><mi>p</mi><mi>k</mi></mrow></msub></mrow></semantics></math></inline-formula>) to quantify the severity of deviations. Three transformer cases were evaluated across five defined frequency regions (10 Hz to 2 MHz), each associated with distinct physical fault types. The FRA6σ approach successfully identified early-stage faults across all cases. In one instance, axial and radial winding deformation was detected with a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>C</mi></mrow><mrow><mi>p</mi></mrow></msub></mrow></semantics></math></inline-formula> of 1.0 and corresponding range chart violations, preceding any visible damage. Another case revealed inter-turn insulation degradation in the 100 kHz–1 MHz band with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>C</mi></mrow><mrow><mi>p</mi><mi>k</mi></mrow></msub></mrow></semantics></math></inline-formula> values below 0.9, prompting immediate intervention. Compared to traditional FRA interpretation, the proposed method improved diagnostic sensitivity by 31.25% and enabled fault detection earlier based on retrospective physical inspection benchmarks. The integration of Six Sigma with FRA provides a structured, quantifiable, and repeatable approach to transformer fault diagnostics. FRA6σ enhances early detection of winding deformities and dielectric issues, offering a robust alternative to subjective analysis and supporting predictive maintenance strategies in power systems. |
| format | Article |
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| institution | DOAJ |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-04-01 |
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| spelling | doaj-art-ff37f13a476a440f8b7539a1a5774dc22025-08-20T03:06:31ZengMDPI AGApplied Sciences2076-34172025-04-01157395110.3390/app15073951Six Sigma-Based Frequency Response Analysis for Power Transformer Winding DeformationBonginkosi A. Thango0Department of Electrical and Electronic Engineering Technology, University of Johannesburg, Johannesburg 2092, South AfricaWinding deformities in distribution transformers pose significant risks to operational reliability and system safety. Frequency response analysis (FRA) is a well-established technique for identifying mechanical faults; however, its diagnostic reliability is hindered by subjectivity in interpreting response signatures. This study proposes a novel diagnostic technique, termed FRA6σ, which integrates Six Sigma (6σ) statistical tools with FRA to enable objective fault detection. The methodology employs control charts (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="false"><mrow><mi>X</mi></mrow><mo>¯</mo></mover></mrow></semantics></math></inline-formula> chart, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="false"><mrow><mi>R</mi></mrow><mo>¯</mo></mover></mrow></semantics></math></inline-formula>-chart) to monitor deviations from baseline signatures and utilizes process capability indices (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>C</mi></mrow><mrow><mi>p</mi></mrow></msub></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>C</mi></mrow><mrow><mi>p</mi><mi>k</mi></mrow></msub></mrow></semantics></math></inline-formula>) to quantify the severity of deviations. Three transformer cases were evaluated across five defined frequency regions (10 Hz to 2 MHz), each associated with distinct physical fault types. The FRA6σ approach successfully identified early-stage faults across all cases. In one instance, axial and radial winding deformation was detected with a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>C</mi></mrow><mrow><mi>p</mi></mrow></msub></mrow></semantics></math></inline-formula> of 1.0 and corresponding range chart violations, preceding any visible damage. Another case revealed inter-turn insulation degradation in the 100 kHz–1 MHz band with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>C</mi></mrow><mrow><mi>p</mi><mi>k</mi></mrow></msub></mrow></semantics></math></inline-formula> values below 0.9, prompting immediate intervention. Compared to traditional FRA interpretation, the proposed method improved diagnostic sensitivity by 31.25% and enabled fault detection earlier based on retrospective physical inspection benchmarks. The integration of Six Sigma with FRA provides a structured, quantifiable, and repeatable approach to transformer fault diagnostics. FRA6σ enhances early detection of winding deformities and dielectric issues, offering a robust alternative to subjective analysis and supporting predictive maintenance strategies in power systems.https://www.mdpi.com/2076-3417/15/7/3951six sigmacontrol chartrange chartprocess capability indexprocess capability performance indexdistribution transformer |
| spellingShingle | Bonginkosi A. Thango Six Sigma-Based Frequency Response Analysis for Power Transformer Winding Deformation Applied Sciences six sigma control chart range chart process capability index process capability performance index distribution transformer |
| title | Six Sigma-Based Frequency Response Analysis for Power Transformer Winding Deformation |
| title_full | Six Sigma-Based Frequency Response Analysis for Power Transformer Winding Deformation |
| title_fullStr | Six Sigma-Based Frequency Response Analysis for Power Transformer Winding Deformation |
| title_full_unstemmed | Six Sigma-Based Frequency Response Analysis for Power Transformer Winding Deformation |
| title_short | Six Sigma-Based Frequency Response Analysis for Power Transformer Winding Deformation |
| title_sort | six sigma based frequency response analysis for power transformer winding deformation |
| topic | six sigma control chart range chart process capability index process capability performance index distribution transformer |
| url | https://www.mdpi.com/2076-3417/15/7/3951 |
| work_keys_str_mv | AT bonginkosiathango sixsigmabasedfrequencyresponseanalysisforpowertransformerwindingdeformation |