Data Visualization⭐ Featured Skill

Energy Storage PACK Weld Quality Intelligent Detection System

技能

Energy storage battery PACK production line weld quality intelligent detection system, based on X-ray and ultrasonic non-destructive testing technology, solving problems of batch returns and safety accidents caused by cold joints and missing welds in the energy storage industry

能源矿业数字化技能
Install Command
npx openclaw skills install industry-energy-storage-pack-weld-defect-detection
Version
1.0.0
Author
shuzhihui
Updated
Thu Jul 09 2026 00:00:00 GMT+0000 (Coordinated Universal Time)

Features

- **X光焊缝缺陷识别**:对电池模组激光焊接点进行X射线成像分析,自动识别虚焊、气孔、裂纹、未熔合等20+类缺陷,检出率达99.5%

- **超声波熔深检测**:利用相控阵超声波技术检测铝合金巴片焊接熔深,自动判定是否达到工艺要求的最小熔深阈值

- **批次追溯管理**:记录每个焊点的检测图像、缺陷类型、位置坐标,与电芯条码关联形成完整的质量追溯档案

- **工艺参数闭环反馈**:将检测结果与焊接设备参数(激光功率、焊接速度、离焦量)进行相关性分析,输出工艺优化建议

Use Cases

- **储能集装箱PACK产线100%全检**:某储能集成商出口海外的集装箱PACK产品,因虚焊问题遭遇批量退货。部署焊缝检测系统后,在线100%检测每个焊点,单日检测能力达5000+焊点,退货率从2.3%降至0.15%

- **电芯极耳焊接质量抽检升级**:某动力电池工厂原采用人工抽检方式,抽检比例仅5%。升级为AI视觉+超声波融合检测后,实现100%在线检测,及时发现熔深不足的异常批次,避免质量事故

Installation

npx openclaw skills install industry-energy-storage-pack-weld-defect-detection

使用示例

`分析这批电池模组的X光图像,识别虚焊和气孔缺陷`

`检测激光焊接巴片的熔深是否达到2.5mm工艺要求`

`输出最近72小时内所有焊缝缺陷的统计报告和根因分析`