Intelligent Plant Ltd ұсы нады
Look at multiple views of your real-time data for in-depth analysis.
Gestalt Trend is an advanced data-visualisation tool that allows you to switch between multiple views for in-depth analysis using traditional line Trends, Parallel Co-ordinate Plots (PCP), Fast Fourier Transform Analysis (FFT), Histograms, Limits, XY Scatter Plots, Cross-Correlation Graphs, Cross-Correlation Matrix, Calm Waters (3DCW1 & 3DCW2).
Share your analysis and collaborate with colleagues via small drag-and-drop files, allowing them to fully interact with your trend.
- Trends - Shows a tags value on a traditional x-axis time scale. Observe movement in analogue process values. Trends can be normalized to sit on the same y-axis, stacked or presented with multiple axis
- Parallel Co-ordinate Plots (PCP) - Presents a tags value as a dimension where the connecting lines are a moment in time. This exposes correlatons between values
- Fast Fourier Transform Analysis (FFT) - Shows frequencies in data and can be helpful to find the cause of oscillations in a process by identifying tags that have variations at the same frequency or to highlight repeating patterns that might not be obvious on a trend
- Histograms - Shows the distribution of values for tags - this can help when assessing limits for alerts/alarms
- Limits - Allows you to see the limits of all tags in value format
- XY Scatter Plots - Equipment performance can be quickly analysed with an x-y scatter of key variables. Instances of the equipment operating out of spec can be selected, switching back to a trend view can show when this happened in time
- Cross Correlation Graph - Shows how a tag varies in relation to another over time. E.G. If a pressure takes 2 minutes to affect another pressure, then a peak will be shown at 2 minutes on the scale
- Cross Correlation Matrix - Identifies if tags go up and down at the same time, or if one goes down whilst the other goes up
- Calm Waters - A way of showing deviations from normal for hundreds of points simultaneously