STEM与日常科技·英语30篇（2）

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工业互联网如何在故障发生前预测机器异常

Industrial Internet connects factory machines to cloud platforms using sensors and Wi-Fi.
These sensors collect real-time data like temperature, vibration, and noise levels continuously.
AI algorithms analyze the data streams to detect subtle patterns that signal future breakdowns.
Unlike scheduled maintenance, predictive maintenance only intervenes when actual wear is detected.
This approach cuts downtime by up to forty percent and extends equipment lifespan significantly.
Factories using it report fewer emergency repairs and more stable production schedules.
The system learns from historical failure data, so its predictions improve over time.
Engineers receive alerts on tablets or dashboards with clear diagnostic suggestions.
Even small anomalies—like a bearing’s slight frequency shift—are flagged automatically.
Ultimately, this smart monitoring turns reactive fixes into proactive, science-based decisions.