< img height="1" width="1" style="display:none" src="https://www.facebook.com/tr?id=1241806559960313&ev=PageView&noscript=1" /> News - Intelligent Identification of PV Module Damage and Contamination Detection and Fire Hazards

Intelligent Identification of PV Module Damage and Contamination Detection and Fire Hazards

I. The Necessity of Intelligent Photovoltaic Inspection

The drone PV inspection system utilizes high-definition drone aerial photography technology and artificial intelligence algorithms to comprehensively inspect power stations in a short period of time, realizing the defect identification of photovoltaic panels, cleanliness monitoring and other functions. Compared with traditional manual inspection, drone inspection has many advantages such as high efficiency, low cost and good safety.


In practical application, the drone photovoltaic inspection system obtains a large amount of data through remote sensing technology and analyzes the data using artificial intelligence algorithms, quickly identifying defects on the photovoltaic panels such as hot spots, stains, cracks, etc., and providing a scientific and accurate inspection report, which is a basis for decision-making for the operation and maintenance personnel.


In addition, the drone PV inspection system is also able to ensure the normal operation of PV panels by real-time monitoring of the cleanliness of the PV panels, timely detection and cleaning of accumulated ash, mulch and other objects. This intelligent inspection program greatly improves the management efficiency and power generation benefits of PV power stations.


II. Deployment Program Composition

The program uses the UAV flight platform and customized machine nest with edge computing terminal to complete the daily patrol of PV power stations, and the drone inspection system deployed in the server of the centralized control center can complete the construction of the whole set of programs.


III. Deployment Program Components

1) Component Hot Spot

Hot spots caused by cell manufacturing: silicon material defects; incomplete edge removal and edge short circuit during cell manufacturing; poor sintering, excessive series resistance; excessive sintering, PN junction burn-through short circuit.

2) Zero Current Fault

The string as a whole does not generate electricity problems or other problems of battery cells, components, string may be missing parts. The direct cause of the formation of such failures is the lower current of the PV module caused by the overall heating of the panel, the root cause of such failures include short-circuit lines caused by the insurance burnt out, the line is loose resulting in a broken circuit.

3) Diode Failure

Formation of hot spots due to abnormal operation of components. Unlike the above two failures, this failure is mainly related to the photovoltaic module itself, may be the photovoltaic module internal panel failure or diode failure or failure caused by the bypass state; in addition, the junction box weld will also lead to this situation.

4) Structural Corrosion and Other Faults

5) Other Faults

Observation of natural disasters, man-made damage, pollution on the surface of PV modules such as dust, bird droppings and other faults from high altitude, and can be quickly photographed to identify for further diagnosis.


IV. Inspection Process

1. Inspection Planning: Plan the inspection path of the UAV to ensure coverage of the task area and avoid repeated inspections.

2. Autonomous Take-Off: The UAV takes off autonomously according to the preset path and coordinates, and enters the inspection state.

3. High-Definition Shooting: Equipped with a high-definition thermal infrared camera drone, the drone carries out all-round, high-definition shooting of photovoltaic panels to ensure that every subtle abnormality is captured.

4. Intelligent Analysis: Using the deployed server platform, the photographed images are analyzed in real time, and the abnormalities of the PV panels are quickly identified.

5. Data Feedback: The data obtained from the inspection is fed back to the command center in real time, providing detailed reference for subsequent operation and maintenance.

Post time: Dec-08-2023