AR096219A1 - Método de procesamiento de señal de descarga parcial y aparato que emplea una red neuronal - Google Patents

Método de procesamiento de señal de descarga parcial y aparato que emplea una red neuronal

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Publication number
AR096219A1
AR096219A1 ARP140101864A ARP140101864A AR096219A1 AR 096219 A1 AR096219 A1 AR 096219A1 AR P140101864 A ARP140101864 A AR P140101864A AR P140101864 A ARP140101864 A AR P140101864A AR 096219 A1 AR096219 A1 AR 096219A1
Authority
AR
Argentina
Prior art keywords
waveform
similarity
criterion
signals
discharge signals
Prior art date
Application number
ARP140101864A
Other languages
English (en)
Inventor
Candela Roberto
Di Stefano Antonio
Fiscelli Giuseppe
Costantino Giaconia Giuseppe
Original Assignee
Prysmian Spa
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Prysmian Spa filed Critical Prysmian Spa
Publication of AR096219A1 publication Critical patent/AR096219A1/es

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
    • G01R31/1227—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials
    • G01R31/1263—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation
    • G01R31/1272—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation of cable, line or wire insulation, e.g. using partial discharge measurements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
    • G01R31/1227—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials
    • G01R31/1245—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of line insulators or spacers, e.g. ceramic overhead line cap insulators; of insulators in HV bushings
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
    • G01R31/14—Circuits therefor, e.g. for generating test voltages, sensing circuits
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/10—Interfaces, programming languages or software development kits, e.g. for simulating neural networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/048—Activation functions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/084—Backpropagation, e.g. using gradient descent

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computing Systems (AREA)
  • Software Systems (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Molecular Biology (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • General Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • General Engineering & Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Mathematical Physics (AREA)
  • Health & Medical Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Ceramic Engineering (AREA)
  • Testing Relating To Insulation (AREA)

Abstract

El método de procesamiento de señales de descarga parcial (1100) que comprende: establecer (1000) un primer criterio de discriminación entre los siguientes criterios: adquisición de señales de descarga, filtrado de ruido en señales de descarga, clasificación de señales de descarga; proveer (1002) una pluralidad de formas de onda de impulso asociadas con señales de forma de onda de descarga parcial detectadas; definir (1001) al menos una primera forma de onda de impulso de referencia (RF) de acuerdo con el primer criterio; llevar a cabo un primer entrenamiento (1005) de un módulo de red neuronal (800; 900) sobre la base de dicha al menos una primera forma de onda de referencia para producir un índice de similitud adaptado para asumir, en forma selectiva, un primer valor y un segundo valor representativos de una similitud / no similitud de una forma de onda de impulso de entrada con la al menos una primera forma de onda de impulso de referencia (RF), respectivamente; comparar (1006) dicha pluralidad de formas de onda de impulso con la al menos una primera forma de onda de impulso de referencia a través del módulo de red neuronal para obtener los primeros valores de índice de similitud; memorizar / rechazar (1008; 1009) cada forma de onda de impulso comparada sobre la base de los primeros valores de índice de similitud obtenidos y sobre el segundo criterio de discriminación.
ARP140101864A 2013-05-10 2014-05-08 Método de procesamiento de señal de descarga parcial y aparato que emplea una red neuronal AR096219A1 (es)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/EP2013/059715 WO2014180508A1 (en) 2013-05-10 2013-05-10 Partial discharge signal processing method and apparatus employing neural network

Publications (1)

Publication Number Publication Date
AR096219A1 true AR096219A1 (es) 2015-12-16

Family

ID=48485139

Family Applications (1)

Application Number Title Priority Date Filing Date
ARP140101864A AR096219A1 (es) 2013-05-10 2014-05-08 Método de procesamiento de señal de descarga parcial y aparato que emplea una red neuronal

Country Status (10)

Country Link
US (1) US10408873B2 (es)
EP (1) EP2994856B1 (es)
CN (1) CN105210088B (es)
AR (1) AR096219A1 (es)
AU (1) AU2013389280B2 (es)
BR (1) BR112015028010B1 (es)
CA (1) CA2909903C (es)
DK (1) DK2994856T3 (es)
ES (1) ES2760617T3 (es)
WO (1) WO2014180508A1 (es)

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CA2948690C (en) * 2014-05-16 2022-04-26 Prysmian S.P.A. A partial discharge acquisition system comprising a capacitive coupling electric field sensor
KR101787901B1 (ko) * 2016-06-14 2017-11-15 엘에스산전 주식회사 전력설비 진단장치
EP3535625B1 (en) * 2016-12-07 2021-02-24 Arilou Information Security Technologies Ltd. System and method for using signal waveform analysis for detecting a change in a wired network
EP3577475A1 (en) * 2017-03-02 2019-12-11 Rosemount Inc. Trending functions for partial discharge
CN107192929B (zh) * 2017-06-21 2023-11-03 贵州电网有限责任公司电力科学研究院 用于特高频监测系统校验的gis局放信号源系统及使用方法
CN107942210A (zh) * 2017-11-14 2018-04-20 国网上海市电力公司 变压器脉冲电流局部放电波形的分类和去噪方法及系统
JP7130542B2 (ja) * 2018-12-12 2022-09-05 株式会社日立製作所 部分放電検出装置及び部分放電検出方法
JP7282000B2 (ja) * 2019-08-30 2023-05-26 株式会社日立製作所 部分放電判定装置及び方法
US11313895B2 (en) 2019-09-24 2022-04-26 Rosemount Inc. Antenna connectivity with shielded twisted pair cable
CN110768661B (zh) * 2019-10-21 2022-10-28 中国科学技术大学 一种基于神经网络的锁相放大器
IT202000004303A1 (it) * 2020-03-02 2021-09-02 St Microelectronics Srl Circuito per rilevare scariche parziali, dispositivo, sistema e procedimento corrispondenti
CN111985528B (zh) * 2020-07-06 2024-04-23 国网天津市电力公司 一种基于pdgan的电缆局放数据增强方法
CN112782538A (zh) * 2020-12-25 2021-05-11 深圳供电局有限公司 基于超低频电源开断信号的电缆局部放电检测方法和装置
CN112698170A (zh) * 2021-01-18 2021-04-23 上海格鲁布科技有限公司 基于时域波形的特高频局部放电检测抗干扰方法
CN112949109B (zh) * 2021-01-26 2023-04-07 西北核技术研究所 基于深度神经网络的架空线电磁脉冲传导环境的预测方法
CN113447769A (zh) * 2021-05-31 2021-09-28 华东电力试验研究院有限公司 基于二维特征参数平面的pd脉冲群手动快速提取系统
JP7412392B2 (ja) * 2021-08-06 2024-01-12 株式会社日立製作所 部分放電判定装置及び方法
CN113376494B (zh) * 2021-08-16 2021-11-09 国网江苏省电力有限公司电力科学研究院 一种电缆火情隐患潜在缺陷的检测方法
CN114167238A (zh) * 2021-12-03 2022-03-11 广东电网有限责任公司广州供电局 电缆局部放电的检测方法、装置、系统、设备及存储介质
CN114065824B (zh) * 2022-01-17 2022-04-19 陕西公众电气股份有限公司 一种对局部放电信号类型快速识别的方法
CN114777818B (zh) * 2022-03-09 2024-03-15 西门子数控（南京）有限公司 编码器的信号激励单元及编码器
CN115166453B (zh) * 2022-09-08 2023-01-24 国网智能电网研究院有限公司 基于边缘实时射频脉冲分类的局放连续监测方法及装置
CN116226647B (zh) * 2023-05-06 2023-07-28 北京云道智造科技有限公司 电力电缆局部放电模式的识别方法、装置、设备及介质

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JP3100757B2 (ja) * 1992-06-02 2000-10-23 三菱電機株式会社 監視診断装置
JP3107357B2 (ja) 1995-06-12 2000-11-06 日立電線株式会社 部分放電判別法
JP4157636B2 (ja) * 1999-01-28 2008-10-01 株式会社日立製作所 ガス絶縁機器の部分放電診断装置
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Also Published As

Publication number Publication date
US10408873B2 (en) 2019-09-10
WO2014180508A1 (en) 2014-11-13
CN105210088B (zh) 2018-07-13
AU2013389280B2 (en) 2019-11-21
CA2909903A1 (en) 2014-11-13
DK2994856T3 (da) 2019-12-09
US20160116520A1 (en) 2016-04-28
AU2013389280A1 (en) 2015-10-29
BR112015028010B1 (pt) 2022-07-19
CN105210088A (zh) 2015-12-30
ES2760617T3 (es) 2020-05-14
BR112015028010A2 (es) 2017-09-05
EP2994856B1 (en) 2019-09-11
CA2909903C (en) 2020-11-24
EP2994856A1 (en) 2016-03-16

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