Secondary battery 

Utilize machine vision in the secondary battery production process to inspect the thickness and defects of electrolytes and electrodes and enhance quality control.
Monitor and analyze battery performance during charge and discharge tests.

01. Electrolyte and electrode thickness and defect inspection 

Electrolyte thickness test 

Machine vision accurately measures and monitors the thickness of the electrolyte layer.
This compares the deviations during the manufacturing process with the established specifications to identify bad electrolyte layers and maintain a uniform thickness.

Electrode Inspection 

Machine vision inspects the exact location and condition of the electrodes to detect defects such as attached locations, cracks, defects, leaks, or foreign substances. This ensures the stability of the electrodes and improves their connection to the electrolyte.

Identify and remove defective products 

Machine vision identifies electrolyte and electrode defects and automatically classifies and removes defective products.
This will speed up quality issues and enhance quality control during the production process.

02. Monitoring and Analysis of Charge and Discharge Tests 

Performance Monitoring 

Machine vision monitors the secondary battery during charging and discharging tests and records performance indicators in real time. This accurately tracks the battery's voltage, current, capacity, internal resistance, etc. to monitor the battery's performance

Predict defects

Machine vision collects data and utilizes machine learning algorithms to detect battery anomalies and predict defects, proactively identifying defective batteries and preventing production interruptions

Performance Analysis 

During charging and discharging tests, machine vision analyzes the data and suggests actions to improve battery performance