MGS-104 · 产品概述
一句话定位
MGS-104 是 Pailink Intelligence™ 推出的入门级能源多物理智能体验证平台，为本科教学、AI算法入门及控制验证打造的真实物理验证环境。
产品背景
在能源与AI交叉研究领域，长期存在一个“验证鸿沟”：
-
纯仿真：快速但失真，忽略非线性、噪声、延迟等真实物理特性
-
工业实测：真实但危险，成本高、不敢做故障测试
MGS-104 的诞生，正是为了填补这一空白——在安全电压下复现工业级动态，让算法在真实硬件上跑起来。
核心价值
| 维度 | 价值 |
|---|---|
| 安全 | SELV安全特低电压，完整复现400V工业级动态响应，实验室可安全注入故障 |
| 真实 | 真实功率硬件，不是仿真，数据包含传感器噪声、时序特征、非线性效应 |
| 开放 | STM32驱动源码开放，Jetson Python采集例程，API灵活扩展 |
| 高效 | 10Hz采样、自动标注、TensorFlow/PyTorch模型一键部署 |
系统架构
核心组成
| 组件 | 数量 | 说明 |
|---|---|---|
| 边缘计算单元 | 1×Jetson Orin Nano Super | 67 TOPS算力，128GB SSD，Ubuntu 20.04 |
| 功率节点 | 4×STM32F302 | 3×DCDC + 1×ACDC |
| 通信总线 | CAN 500kbps | 实时控制 |
| 人机交互 | 10寸显示屏 | DP转mini HDMI |
| 调试工具 | 1×ZLG-USBCAN盒 | 数据监控与分析 |
| 机箱 | 亚克力材质 | 250×300×150 mm |
适用场景
| 场景 | 具体应用 |
|---|---|
| 本科教学 | 电力电子技术、自动控制原理、嵌入式系统实验 |
| AI算法入门 | 强化学习、多智能体协同、故障诊断 |
| 控制算法验证 | PID整定、能量管理策略、调度算法 |
| 科研验证 | 多节点功率协同、分布式控制 |
核心功能
| 功能 | 描述 |
|---|---|
| 实时监控 | 采集功率节点电压、电流、温度等状态参数 |
| 数据采集 | 10 Hz采样，自动标注导出，可直接用于TensorFlow/PyTorch训练 |
| 算法部署 | 支持TensorFlow/PyTorch模型一键部署，在线验证 |
| 波形显示 | 实时绘制电压/电流曲线，多通道对比 |
| CAN诊断 | 总线状态监控，错误帧统计 |
为什么选择 MGS-104
| 真实 | 安全 | 开放 | 高效 |
|---|---|---|---|
| 真实硬件，不是仿真 | SELV安全电压，可安全注入故障 | 驱动源码开放，API灵活扩展 | 数据自动标注，一键部署 |
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