Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Neural Computing and Applications
Erschienen in: Neural Computing and Applications 9/2019

31.07.2018 | S.I. : Emergence in Human-like Intelligence towards Cyber-Physical Systems

Open-circuit fault detection for three-phase inverter based on backpropagation neural network

verfasst von: Zhendong Ji, Wei Liu

Erschienen in: Neural Computing and Applications | Ausgabe 9/2019

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

To realize real-time fault detection in power devices and enhance reliability of inverter circuits, this paper proposes a detection method based on Park’s transform algorithm and neural network. Park’s transform is applied to obtain the three-phase current base wave amplitude as the characteristic variable for fault detection. Faulty switch devices can be located using a backpropagation neural network in combination with simple logic analyses. The simulation results verify the effectiveness and the feasibility of the proposed method.
Vorheriger Artikel Seismic performance evaluation of existing RC structures based on hybrid sensing method
Nächster Artikel ACCP: adaptive congestion control protocol in named data networking based on deep learning

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
Cui B, Ren Z (2006) Fault detection and isolation of inverter based on FFT and neural network. Trans China Electrotech Soc 21(7):37–43 (in Chinese)
2.
An Q, Sun L, Sun L et al (2011) Recent developments of fault diagnosis methods for switches in three-phase inverters. Trans China Electrotech Soc 26(4):135–144 (in Chinese) MathSciNet
3.
Mohsenzade S, Zarghany M, Kaboli S (2018) A series stacked IGBT switch with robustness against short-circuit fault for pulsed power applications. IEEE Trans Power Electron 33(5):3779–3790CrossRef
4.
Mai-Khanh NN, Nakajima S, Iizuka T et al (2017) Experimental demonstration of non-destructive detection of IGBT fault positions by magnetic sensor. IEEE Sensors Appl Symp 1:1–4
5.
Hoevenaars AH, Evans IC, Desai B (2013) Preventing AC drive failures due to commutation notches on a drilling rig. IEEE Trans Ind Appl 49(3):1215–1220CrossRef
6.
Spee R, Wallace AK (1990) Remedial strategies for brushless DC drive failures. IEEE Trans Ind Appl 26(2):259–266CrossRef
7.
Rothenhagen K, Fuchs FW (2004) Performance of diagnosis methods for IGBT open circuit faults in voltage source active rectifiers. In: Proceedings of the 35th annual IEEE power electronics specialists conference, vol 1, pp 4348–4354
8.
Hu R, Wang J, Sen B et al (2017) PWM ripple currents based turn fault detection for multiphase permanent magnet machines. IEEE Trans Ind Appl 53(3):2740–2751CrossRef
9.
Park JH, Kim DH, Kim SS et al (2004) C-ANFIS based fault diagnosis for voltage-fed PWM motor drive systems. Proc IEEE Ann Meet Fuzzy Inf 1:379–383
10.
Zhao H, Cheng L (2018) Open-switch fault-diagnostic method for back-to-back converters of a doubly fed wind power generation system. IEEE Trans Power Electron 33(4):3452–3461MathSciNetCrossRef
11.
Karimi S, Gaillard A, Poure P et al (2008) FPGA-based real-time power converter failure diagnosis for wind energy conversion systems. IEEE Trans Ind Electron 55(12):4299–4308CrossRef
12.
An Q, Sun L, Zhao K et al (2010) Diagnosis method for inverter open-circuit fault based on switching function model. Proc CSEE 30(6):1–6
13.
Zhao GL, Liu BZ, Xiao XN et al (2004) Application of improved d-q transform without time delay in dynamic voltage disturbance identification. Power Syst Technol 28(7):53–57
14.
Lopes FV, Fernandes D, Neves WL (2013) A traveling-wave detection method based on Park’s transformation for fault locators. IEEE Trans Power Deliv 28(3):1626–1634CrossRef
15.
Arashloo RS, Romeral M, Salehifar M (2013) A novel broken rotor bar fault detection method using park’s transform and wavelet decomposition. In: 9th IEEE international symposium on diagnostics for electric machines, vol 1, pp 412–419
16.
Önel IY, Benbouzid ME (2008) Induction motor bearing failure detection and diagnosis: park and concordia transform approaches comparative study. IEEE/ASME Trans Mechatron 13(2):257–262CrossRef
17.
Houlian W, Gongbo Z (2018) State of charge prediction of supercapacitors via combination of Kalman filtering and backpropagation neural network. IET Electr Power Appl 12(4):588–594CrossRef
18.
Shi D, Gao Y (2013) A new method for identifying electromagnetic radiation sources using backpropagation neural network. IEEE Trans Electromagn Compat 55(5):842–848CrossRef
19.
Sun Q, Wang Y, Jiang Y (2018) A novel fault diagnostic approach for DC–DC converters based on CSA-DBN. IEEE Access 6:6273–6285CrossRef
20.
Xiao P, Venayagamoorthy GK, Corzine KA et al (2010) Recurrent neural networks based impedance measurement technique for power electronic systems. IEEE Trans Power Electron 25(2):382–390CrossRef
21.
Dong JR, Zheng CY, Kan GY et al (2015) Applying the ensemble artificial neural network-based hybrid data-driven model to daily total load forecasting. Neural Comput Appl 26(3):603–611CrossRef
22.
Das P, Banerjee I (2011) An hybrid detection system of control chart patterns using cascaded SVM and neural network–based detector. Neural Comput Appl 20(2):287–296CrossRef
23.
Lin YC, Chen DD, Chen MS et al (2018) A precise BP neural network-based online model predictive control strategy for die forging hydraulic press machine. Neural Comput Appl 29(9):585–596CrossRef
24.
Ren T, Liu S, Yan G, Mu H (2016) Temperature prediction of the molten salt collector tube using BP neural network. IET Renew Power Gener 10(2):212–220CrossRef
25.
Liu S, Hou Z, Yin C (2016) Data-driven modeling for UGI gasification processes via an enhanced genetic bp neural network with link switches. IEEE Trans Neural Netw Learn Syst 27(12):2718–2729CrossRef
26.
Chen M, Xu D, Zhang T et al (2018) A novel DC current injection suppression method for three-phase grid-connected inverter without the isolation transformer. IEEE Trans Ind Electron 65(11):8656–8666CrossRef
27.
Huang J, Liu Q, Wang X et al (2018) A carrier-based modulation scheme to reduce the third harmonic component of common-mode voltage in a three-phase inverter under high DC voltage utilization. IEEE Trans Ind Electron 65(3):1931–1940CrossRef
28.
Arora TG, Renge MM, Aware MV(2017) Effects of switching frequency and motor speed on common mode voltage, common mode current and shaft voltage in PWM inverter-fed induction motors. In: 12th IEEE conference on industrial electronics and applications, vol 1, pp 583–588
Metadaten
Titel
Open-circuit fault detection for three-phase inverter based on backpropagation neural network
verfasst von
Zhendong Ji
Wei Liu
Publikationsdatum
31.07.2018
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 9/2019
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3663-2

Weitere Artikel der Ausgabe 9/2019

Neural Computing and Applications 9/2019 Zur Ausgabe

Original Article

Speed limit sign detection and recognition system using SVM and MNIST datasets

Original Article

A novel quick seizure detection and localization through brain data mining on ECoG dataset

S.I. : Emergence in Human-like Intelligence towards Cyber-Physical Systems

Detecting adverse drug reactions from social media based on multi-channel convolutional neural networks

Original Article

Fractional Volterra LMS algorithm with application to Hammerstein control autoregressive model identification

Original Article

Adaptive memetic method of multi-objective genetic evolutionary algorithm for backpropagation neural network

Original Article

An AI-based workflow for estimating shale barrier configurations from SAGD production histories