Classification of defects in energy storage equipment

What is Defect Classification in power equipment?

Defect classification in power equipment differs from general tasks such as news classification and sentiment analysis 5; it belongs to a specialized domain with data that is challenging to obtain. Firstly, the need for authentic power equipment defect data in defect classification tasks requires prolonged observation and collection.

What is Defect Classification 2 3 4?

Many studies on defect classification 2, 3, 4 have focused solely on identifying defect grades to broadly assess equipment health, neglecting critical information such as defective components and defect categories.

Are materials defects energy storage units?

Energy storage occurs in a variety of physical and chemical processes. In particular, defects in materials can be regarded as energy storage units since they are long-lived and require energy to be formed. Here, we investigate energy storage in non-equilibrium populations of materials defects, such as those generated by bombardment or irradiation.

Can a power equipment defect model identify specific defect types?

The model based on this dataset only focuses on the defect phenomenon and grade in the power equipment defect record and fails to fully utilize the information provided by the defect occurrence to identify specific defect types. Tian et al. 9 selected defect phenomena and fault categories from defect records as the focus of their study.

What are power equipment defect types?

According to the classification standards for primary equipment defects in power transmission and transformation, power equipment defect types encompass the defective component, component type, location, defect description, defect grade, and classification criteria.

What is equipment Defect Classification & why is it important?

Accurate identification and classification of equipment defects are essential for assessing the health of power equipment and making informed maintenance decisions. Traditional defect classification methods, which rely on subjective manual records and intricate defect descriptions, have proven to be inefficient.