Study of Intelligent Photovoltaic System Fault Diagnostic Scheme Based on Chaotic Signal Synchronization

As the photovoltaic system consists of many equipment components, manual inspection will be very costly. This study proposes the photovoltaic system fault diagnosis based on chaotic signal synchronization. First, MATLAB was used to simulate the fault conditions of solar system, and the maximum power point tracking (MPPT) was used to ensure the system's stable power and capture and record the system fault feature signals. The dynamic errors of various fault signals were extracted by chaotic signal synchronization, and the dynamic error data of various fault signals were recorded completely. In the photovoltaic system, the captured output voltage signal was used as the characteristic values for fault recognition, and the extension theory was used to create the joint domain and classical domain of various fault conditions according to the collected feature data. The matter-element model of extension engineering was constructed. Finally, the whole fault diagnosis system is only needed to capture the voltage signal of the solar photovoltaic system, so as to know the exact fault condition effectively and rapidly. The proposed fault diagnostor can be implemented by embedded system and be combined with ZigBee wireless network module in the future, thus reducing labor cost and building a complete portable renewable energy system fault diagnostor.

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Chaos Synchronization Based Novel Real-Time Intelligent Fault Diagnosis for Photovoltaic Systems

International Journal of Photoenergy ◽

10.1155/2014/759819 ◽

2014 ◽

Vol 2014 ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Chin-Tsung Hsieh ◽

Her-Terng Yau ◽

Jen Shiu

Keyword(s):

Fault Diagnosis ◽

Real Time ◽

Chaos Synchronization ◽

Photovoltaic System ◽

Solar Photovoltaic ◽

Diagnosis System ◽

Fault Features ◽

Voltage Signal ◽

Fault Diagnosis System ◽

Solar Photovoltaic System

The traditional solar photovoltaic fault diagnosis system needs two to three sets of sensing elements to capture fault signals as fault features and many fault diagnosis methods cannot be applied with real time. The fault diagnosis method proposed in this study needs only one set of sensing elements to intercept the fault features of the system, which can be real-time-diagnosed by creating the fault data of only one set of sensors. The aforesaid two points reduce the cost and fault diagnosis time. It can improve the construction of the huge database. This study used Matlab to simulate the faults in the solar photovoltaic system. The maximum power point tracker (MPPT) is used to keep a stable power supply to the system when the system has faults. The characteristic signal of system fault voltage is captured and recorded, and the dynamic error of the fault voltage signal is extracted by chaos synchronization. Then, the extension engineering is used to implement the fault diagnosis. Finally, the overall fault diagnosis system only needs to capture the voltage signal of the solar photovoltaic system, and the fault type can be diagnosed instantly.

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An Intelligent Fault Diagnosis Technology for Distributed Photovoltaic System Based on Ensemble Voting Fusion Model

2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2) ◽

10.1109/ei250167.2020.9346855 ◽

2020 ◽

Author(s):

Hu Liu ◽

Xiangying Xie ◽

Dong Wang ◽

Xiaoguang Ma ◽

Xin Luo

Keyword(s):

Fault Diagnosis ◽

Photovoltaic System ◽

Intelligent Fault Diagnosis ◽

Fusion Model

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Bearing Fault Diagnosis Based on Chaotic Dynamic Errors in Key Components

IEEE Access ◽

10.1109/access.2021.3069566 ◽

2021 ◽

pp. 1-1

Author(s):

Bo-Lin Jian ◽

Xiao-Yi Su ◽

Her-Terng Yau

Keyword(s):

Fault Diagnosis ◽

Chaotic Dynamic ◽

Bearing Fault ◽

Bearing Fault Diagnosis ◽

Dynamic Errors

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Research on Voltage Waveform Fault Detection of Miniature Vibration Motor Based on Improved WP-LSTM

Micromachines ◽

10.3390/mi11080753 ◽

2020 ◽

Vol 11 (8) ◽

pp. 753

Author(s):

Ruirui Wang ◽

Zhan Feng ◽

Sisi Huang ◽

Xia Fang ◽

Jie Wang

Keyword(s):

Fault Diagnosis ◽

Fault Detection ◽

Short Term Memory ◽

Wavelet Packet ◽

Engineering Practice ◽

Detection Accuracy ◽

Reconstructed Signal ◽

Voltage Signal ◽

Diagnosis Method ◽

Lstm Network

To solve the problem of vibration motor fault detection accuracy and inefficiency in smartphone components, this paper proposes a fault diagnosis method based on the wavelet packet and improves long and short-term memory network. First, the voltage signal of the vibration motor is decomposed by a wavelet packet to reconstruct the signal. Secondly, the reconstructed signal is input into the improved three-layer LSTM network as a feature vector. The memory characteristics of the LSTM network are used to fully learn the time-series fault feature information in the unsteady state signal, and then, the model is used to diagnose the motor fault. Finally, the feasibility of the proposed method is verified through experiments and can be applied to engineering practice. Compared with the existing motor fault diagnosis method, the improved WP-LSTM diagnosis method has a better diagnosis effect and improves fault diagnosis.

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Fault diagnosis of photovoltaic system based on machine learning model fusion

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/467/1/012073 ◽

2020 ◽

Vol 467 ◽

pp. 012073

Author(s):

Xingke Guo ◽

Zhixiong Na ◽

Dayan Ma ◽

Yudong Lu ◽

Xin Luo

Keyword(s):

Machine Learning ◽

Fault Diagnosis ◽

Learning Model ◽

Photovoltaic System ◽

Model Fusion ◽

Machine Learning Model

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Status Monitoring and Fault Diagnosis Network System Based on UPnP

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.353-358.2632 ◽

2007 ◽

Vol 353-358 ◽

pp. 2632-2635

Author(s):

Pei Yu Li ◽

Da Peng Tan ◽

Tao Qing Zhou ◽

Bo Yu Lin

Keyword(s):

Fault Diagnosis ◽

Embedded System ◽

Real Time ◽

Data Storage ◽

Network Architecture ◽

Network System ◽

Time Data ◽

Status Monitoring ◽

Self Recognition ◽

Real Time Data

Aiming at some problems in the fields of industry monitoring technology (IMT) such as bad dynamic ability and poor versatility, this paper brought forward a kind of intelligent Status monitoring and Fault diagnosis Network System (SFNS) based on UPnP-Universal Plug and Play. The model for fault diagnosis network system was established according to characteristics and requirements of IMT network, and system network architecture was designed and realized by UPnP. Using embedded system technology, real-time data collection node, monitoring center node and data storage server were designed, and that supplies powerful real-time data support for SFNS. Industry fields experiments proved that this system can realize self recognition, seamless linkage and other self adapting ability, and can break through the limitation of real IP address to achieve real-time remote monitoring on line.

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Calibration and Compensation of Dynamic Abbe Errors of a Coordinate Measuring Machine

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.4038171 ◽

2017 ◽

Vol 140 (5) ◽

Cited By ~ 2

Author(s):

Daocheng Yuan ◽

Xin Tao ◽

Caijun Xie ◽

Huiying Zhao ◽

Dongxu Ren ◽

...

Keyword(s):

Error Compensation ◽

Dynamic Error ◽

Coordinate Measuring Machine ◽

Calibration Method ◽

Local Dynamic ◽

Operational Parameters ◽

Dynamic Errors ◽

Measuring Machine ◽

Reducing Costs ◽

Improving Accuracy

Error compensation technology is used for improving accuracy and reducing costs. Dynamic error compensation techniques of coordinate measuring machine (CMM) are still under study; the major problem is a lack of suitable models, which would be able to correctly and simply relate the dynamic errors with the structural and operational parameters. To avoid the complexity of local dynamic deformation measurement and modeling, a comprehensive calibration method is employed. Experimental research reveals specific qualities of dynamic Abbe errors; the results exceed the scope of ISO 10360-2 calibration method, showing the ISO 10360-2 dynamic error evaluation deficiencies. For calibrating the dynamic Abbe errors, the differential measurement method is presented based on the measurements of the internal and external dimensions. Referring probe tip radius correction, the dynamic Abbe errors compensation method is proposed for CMM end-users and is easy to use.

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