DSH-PREDMNT

批量生产

基于云的网络应用,用于条件监测和预测性维护

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产品概述

描述

The Predictive Maintenance Dashboard is a cloud application based on AWS services. It provides a highly functional and intuitive interface that is tailored for the logging, visualization, and analysis of condition monitoring data from motion and acoustic vibration sensing elements, as well as temperature and other environmental data. You can use the dashboard to plot and graph real-time and historical data, monitor critical operating conditions such as running temperature, and set thresholds for automatic warnings when key parameters exceed acceptable limits. Once you collect and download the data, you can develop your own algorithms for edge processing and event visualization and collect anomalies generated from the Edge devices by using NanoEdgeTM AI Studio generated libraries.
The cloud package can receive and process data streamed directly from compatible ST sensor nodes with real-time data preprocessing capabilities, such as Fast Fourier Transforms (FFT). It also provides SDKs for the AWS Greengrass service to interface with edge gateways that manages compatible ST devices, which preprocess and store bulk data.
As the dashboard runs on a third-party cloud storage service provider, the number of ST IoT sensor nodes you can connect on a free trial basis is limited to five, for a maximum duration of 6 months. Additional monitoring based on resource consumption can be applied to keep account consumption under control.
  • 所有功能

    • Device and edge registration and configuration:
      • provisioning
      • association with assets
      • streaming time
    • Data visualization:
      • device live monitoring
      • historical trends
    • Asset health monitoring:
      • event statistics
      • data collection and download
      • historical trend analysis
      • settable failure thresholds for alerts and warnings
    • Position and status overview map of tracking system
    • Anomaly detection with NanoEdgeTM AI Studio generated libraries:
      • launches learning and inference
      • receives and shows anomalies detected
    • Events notification from devices
    • Available applications:
      • vibration monitoring
      • ultrasound monitoring
      • environmental monitoring
      • condition monitoring
      • event tracking
    • Application framework based on Amazon Web Services
    • Data volume limits:
      • automatic user notification
      • trial basis duration: 6 months
      • maximum number of devices: 5
    • User data segregation

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