Photovoltaic panel defect and crack detection instrument

What is PV panel defect detection?

The task of PV panel defect detection is to identify the category and location of defects in EL images.

How to detect cracks in PV panels?

According to another study [ 69 ], a hybrid method involving a CNN pre-trained network of VGG-16 and support vector machines (SVM) has been proposed as an effective method of detecting cracks in PV panels. This model works by extracting features from EL images and making predictions about whether they will be accepted or not, as shown in Figure 10.

Does varifocalnet detect photovoltaic module defects?

The VarifocalNet is an anchor-free detection method and has higher detection accuracy 5. To further improve both the detection accuracy and speed for detecting photovoltaic module defects, a detection method of photovoltaic module defects in EL images with faster detection speed and higher accuracy is proposed based on VarifocalNet.

Where can I find a research article about PV module defect detection?

A comprehensive search was conducted in reputable academic databases, including but not limited to IEEE Xplore and Google Scholar. Keywords such as “PV module defect detection,” “solar cell crack detection,” and “CNN-based defect detection” were used to retrieve relevant articles.

How are defects detected in photovoltaic models?

The detection of defects in photovoltaic models can be categorized into two types. The first type involves analyzing the characteristic curves of electrical parameters, such as current, voltage, and power of the photovoltaic system.

How is a deep crack detected in a PV cell?

Digital image processing is used to calculate the area of a deep crack, as the power loss of a PV cell is proportional to the area of the crack. All the cracks were first labeled using CVAT software based on how they affect the output power efficiency. Then four different deep-learning models are used to detect and segment the cracks.