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01_​Preprocessing_​Time_​Alignment_​and_​Visualization

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Anomaly Detection. Time Alignment & Visualization

This workflow preprocesses and visualizes sensor data for anomaly detection:
- Read FFT preprocessed data files with date, time, FFT frequency, and FFT amplitude
- Standardize the data by binning the frequencies and averaging the data by sensor, frequency bin and date
- Perform timestamp alignment
- Join all files by date
- Visualize the preprocessed data in a line plot, scatter matrix, correlation matrix, autocorrelation matrix, and heatmap

URL: Manufacturing Purchasers: There's a Better Way to Calculate your Economic Quantity https://www.knime.com/blog/economic-order-quantity
URL: Anomaly Detection for Predictive Maintenance - Exploratory Data Analysis https://www.knime.com/blog/anomaly-detection-for-predictive-maintenance-EDA

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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On NodePit since: 2019-07-12
Last update: 2025-01-22
Created with KNIME version: v5.1.1
Tags: anomaly detectiontime series analysistime alignmentIoTInternet of Thingsscatter matrixcorrelation matrixpredictive maintenancesensormanufacturing

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