Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Fault diagnosis method of npc photovoltaic inverter based on hidden Markov model

A Hidden Markov, photovoltaic inverter technology, applied in instruments, measuring electrical variables, measuring devices, etc., can solve the problems of slow diagnosis speed and low recognition rate, and achieve the effect of fast speed and high fault recognition rate

Inactive Publication Date: 2018-12-14
JIANGSU UNIV
View PDF6 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problems existing in the prior art, the present invention proposes a fault diagnosis method for NPC photovoltaic inverters based on hidden Markov model, which solves the problems of low recognition rate and slow diagnosis speed in traditional inverter fault diagnosis

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Fault diagnosis method of npc photovoltaic inverter based on hidden Markov model
  • Fault diagnosis method of npc photovoltaic inverter based on hidden Markov model
  • Fault diagnosis method of npc photovoltaic inverter based on hidden Markov model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0031] The technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments, but the protection scope of the present invention is not limited thereto.

[0032] Hidden Markov Model (HMM) is a statistical model used to describe a Markov process with hidden unknown parameters. The Hidden Markov Model was founded in the 1970s, spread and developed in the 1980s, and became an important direction of signal processing. It has been successfully used in the fields of speech recognition, behavior recognition, text recognition and fault diagnosis.

[0033] The hidden Markov model is a double random process, not only a random event between state transitions, but also a random process between state and output.

[0034] Hidden Markov model has five basic elements, namely a five-tuple {N,M,π,A,B}:

[0035] Among them, N: the number of states implied in the model, and N states use θ 1 ,θ 2 ,...θ N Indicat...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an NPC photovoltaic inverter fault diagnosis method based on a hidden Markov model, and belongs to the technical field of power electronics application and fault diagnosis. Based on the topology structure of an NPC photovoltaic inverter, a dynamic pattern recognition method-a hidden Markov model widely used in the field of speech recognition is introduced to NPC photovoltaic inverter fault diagnosis. A left-right hidden Markov chain is adopted for modeling to perform fault diagnosis on the NPC photovoltaic inverter. Compared with the existing NPC photovoltaic inverter fault diagnosis method, the hidden Markov model of the invention needs fewer training samples, the number of iteration steps is far smaller than that of a conventional NPC photovoltaic inverter fault diagnosis method, the time for model training is short, the fault recognition rate is high, and recognition is quick. Moreover, a dynamic process can be handled properly, monitoring and diagnosis can be carried out in the dynamic process of system running, and therefore, a fault in an NPC photovoltaic inverter can be discovered in time.

Description

technical field [0001] The invention belongs to the technical field of power electronics application and fault diagnosis, and in particular relates to a fault diagnosis method of an NPC photovoltaic inverter based on a hidden Markov model. Background technique [0002] Under the circumstances that the current environmental situation is increasingly severe and resources are increasingly scarce, adjusting the proportion of energy, developing and utilizing clean energy has gradually become the top priority of the energy strategies of countries all over the world. Among the various development and utilization of solar energy, the application in the field of photovoltaic power generation technology is the most common and valuable. [0003] Modern control technology has been widely used in the field of photovoltaic power generation, which has prompted the development of photovoltaic power generation control technology to become larger and more complex. While reducing the cost of ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/00
CPCG01R31/00
Inventor 郑宏王若隐朱文王一帆
Owner JIANGSU UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com