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GHMM's NPC photovoltaic inverter fault diagnosis method based on improved hidden Markov model

A photovoltaic inverter and fault diagnosis technology, which is applied in transformer testing, instruments, and measuring electrical variables, etc., can solve the problems of low fault diagnosis recognition rate and slow diagnosis speed, and achieve the effect of improving fault recognition rate and fast recognition speed

Inactive Publication Date: 2017-08-29
JIANGSU UNIV
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Problems solved by technology

[0008] In order to solve the problems existing in the prior art, the present invention first uses the genetic algorithm to train the initial value of the probability matrix B of the optimal observation value, then trains the model, and uses the trained model for fault diagnosis, which improves the performance of the hidden Markov model. defects, and solve the problems of low recognition rate and slow diagnosis speed in traditional inverter fault diagnosis

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  • GHMM's NPC photovoltaic inverter fault diagnosis method based on improved hidden Markov model
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  • GHMM's NPC photovoltaic inverter fault diagnosis method based on improved hidden Markov model

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[0032] 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.

[0033] Hidden Markov model has five basic elements, namely a five-tuple {N,M,π,A,B}:

[0034] Among them, N: the number of states implied in the model, and N states use θ 1 ,θ 2 ,...θ N Indicates that the state q at a certain moment t ∈(θ 1 ,θ 2 ,...θ N ),Such as figure 1 shown;

[0035] M: The number of observations corresponding to each state, M observations can be used v 1 ,v 2 ,v 3 … v M Indicates that the observed value o at a certain moment t ∈(v 1 ,v 2 ,v 3 … v M ),Such as figure 1 shown;

[0036] π: initial state probability matrix, π∈{π i}, where: π i =P(q t = θ i )1≤i≤N;

[0037] A: Transition probability matrix, A={a ij}, where: a ij =P(q t+1 = θ j ,q t = θ i )1≤i, j≤N;

[0038] B: Observation value pro...

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Abstract

The invention discloses a GHMM's NPC photovoltaic inverter fault diagnosis method based on improved hidden Markov model, which belongs to the field of power electronic application and fault diagnosis technology. This method combines the hidden Markov model (HMM) with genetic algorithm before being introduced to the fault diagnosis of NPC photovoltaic inverter. When the HMM is applied for fault diagnosis, the selection of the initial value of the model could reach local optimum and affect the diagnostic accuracy. Aimed at solving this defect, the genetic algorithm is introduced, which means the HMM is combined with genetic algorithm (GHMM) for inverter fault diagnosis. Compared with the existing photovoltaic inverter fault diagnosis methods, the number of the iteration steps of the training model in the invention is far less than conventional method, and the training time is short; the recognition speed is fast. Compared with the only use of the HMM, the GHMM further improves the recognition accuracy. In the dynamic process of system operation, the GHMM monitors and diagnoses, and the model achieves the global optimum, greatly raising the fault recognition rate.

Description

technical field [0001] The invention belongs to the technical field of power electronics application and fault diagnosis, and in particular relates to an NPC photovoltaic inverter fault diagnosis method based on an improved hidden Markov model GHMM. Background technique [0002] Due to the increasingly severe environmental situation and increasingly scarce resources, the development and utilization of 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 is also widely used in the field of photovoltaic power generation. The development of photovoltaic power generation control technology has gradually become larger and more complex. The power and control system of the photovoltaic power generation system is generally pe...

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Application Information

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IPC IPC(8): G01R31/00G01R31/02G06K9/62
CPCG01R31/00G01R31/62G06F18/295
Inventor 郑宏王若隐赵伟沈思伦林勇
Owner JIANGSU UNIV
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