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솔루션 아키텍처: Aircraft engine monitoring for predictive maintenance in aerospace

Microsoft Azure’s Predictive Maintenance solution demonstrates how to combine real-time aircraft data with analytics to monitor aircraft health.

이 솔루션은 Azure 관리 서비스를 기반으로 합니다. Stream Analytics, Event Hubs, Machine Learning Studio, HDInsight, Azure SQL Database, Data FactoryPower BI. 이러한 서비스는 고가용성 환경에서 실행되고 패치되며 지원되므로, 솔루션이 실행되는 환경 대신 솔루션에 집중할 수 있습니다.

Aircraft engine monitoring for predictive maintenance in aerospaceMicrosoft Azure’s Predictive Maintenance solution demonstrates how to combine real-time aircraft data with analytics to monitor aircraft health.Data Factory: Move data, orchestrate, schedule and monitorSQL DatabaseMachine LearningPower BI Event HubStream AnalyticsHDInsightGeography Data(Blob Storage)Engine Sensor Data (Simulated)

구현 가이드

제품/설명 설명서

Stream Analytics

Stream Analytics provides near real-time analytics on the input stream from the Azure Event Hub. Input data is filtered and passed to a Machine Learning endpoint, finally sending the results to the Power BI dashboard.

Event Hubs

Event Hubs ingests raw assembly-line data and passes it on to Stream Analytics.

Machine Learning Studio

Machine Learning predicts potential failures based on real-time assembly-line data from Stream Analytics.

HDInsight

HDInsight runs Hive scripts to provide aggregations on the raw events that were archived by Stream Analytics.

Azure SQL Database

SQL Database stores prediction results received from Machine Learning and publishes data to Power BI.

Data Factory

Data Factory handles orchestration, scheduling, and monitoring of the batch processing pipeline.

Power BI

Power BI visualizes real-time assembly-line data from Stream Analytics and the predicted failures and alerts from Data Warehouse.

관련 솔루션 아키텍처