Trend charts and historical data in SCADA systems - Step-by-Step Execution

Process Flow - Trend charts and historical data

Data Collection

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Store Data in Database

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Query Historical Data

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Generate Trend Chart

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Display Chart to User

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User Analyzes Trends

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Optional: Export or Alert

Data is collected from sensors, stored, queried, then shown as trend charts for user analysis.

Execution Sample

SCADA systems

1. Collect sensor data every minute
2. Save data with timestamp in database
3. Query data for last 24 hours
4. Plot data points on trend chart
5. Show chart on SCADA screen

This process collects sensor data, stores it, retrieves recent data, and displays it as a trend chart.

Process Table

Step	Action	Data State	Result
1	Collect sensor reading	Raw sensor value with timestamp	Data point ready
2	Store data point	Database updated with new entry	Data saved
3	Query last 24 hours data	Database returns list of data points	Data retrieved
4	Generate trend chart	Data points processed	Chart image created
5	Display chart	Chart rendered on screen	User sees trend
6	User analyzes chart	Visual trend available	User gains insight
7	Optional export or alert	Data/chart exported or alert triggered	Action completed

💡 Process ends after chart display and optional user actions

Status Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	After Step 5	Final
sensor_data	empty	value + timestamp	stored in DB	queried list	processed for chart	chart rendered	user views chart
database	empty	empty	updated with data point	returns data list	unchanged	unchanged	unchanged
trend_chart	none	none	none	none	created image	displayed	visible to user

Key Moments - 3 Insights

Why do we store data with timestamps?

Timestamps let us know when each data point was recorded, so the trend chart shows changes over time (see execution_table step 1 and 2).

What happens if the query returns no data?

The chart will be empty or show no trend, because no data points exist for that time range (see execution_table step 3).

How does the system update the trend chart?

It queries fresh data and regenerates the chart image each time before display (see execution_table steps 3 and 4).

Visual Quiz - 3 Questions

Look at the execution table, what is the data state after step 3?

A Database updated with new entry

B Database returns list of data points

C Data points processed

D Chart rendered on screen

💡 Hint

Check the 'Data State' column for step 3 in the execution_table.

At which step does the trend chart become visible to the user?

A Step 2

B Step 4

C Step 5

D Step 6

💡 Hint

Look for 'Display chart' and 'User sees trend' in the execution_table.

If sensor data is not collected every minute but every 5 minutes, how does the execution table change?

A Fewer data points collected and stored

B Trend chart generation step is skipped

C More data points stored in database

D User cannot analyze trends

💡 Hint

Think about how data collection frequency affects the number of data points in variable_tracker.

Concept Snapshot

Trend charts show how sensor data changes over time.
Data is collected regularly and stored with timestamps.
Historical data is queried from the database.
Charts are generated from queried data and displayed.
Users analyze trends to understand system behavior.

Full Transcript

In SCADA systems, trend charts help visualize how sensor data changes over time. The process starts by collecting sensor readings regularly, usually every minute, and storing them in a database with timestamps. When a user wants to see trends, the system queries the historical data for a specific time range, like the last 24 hours. This data is then processed to generate a visual chart, which is displayed on the SCADA screen. Users can analyze these charts to detect patterns or issues. Optionally, users can export the data or set alerts based on trends. This step-by-step flow ensures continuous monitoring and easy understanding of system performance.