fillmissing function and obtaining replacement data from reference source

Hi

I have multiple timetables, each holds data of sensors.

At times sensors malfunction and produce false results. Therefore those samples or data are to NaN.

Is it possible to use fillmissing to obtain data from the other timetables?

For examples i have 8 sensors, i would then like ot use the mean data of the other 7 to replace when every data is NaN. Can this be possible?

It would need to obtain data from the closest timestamp(maybe few seconds to few mins apart)

Thanks

Answer 1

[Himanshu]

Hello Dharmesh,

I understand that you are trying to replace NaN values in your sensor data using the mean data from other sensors when the data is NaN at a timestamp.

You can follow the below steps:

1. Initially, you can combine sensor data into a single "timetable" using the "synchronize" function.
2. Next, you can identify timestamps with all NaN values, calculate means, and replace the NaNs using "all" and "ismissing" functions.
3. You can perform time-based interpolation for remaining NaN values using the "fillmissing" function.

You can refer to the below documentation to learn more about the "timetable", "synchronize", and "fillmissing" functions in MATLAB.

Timetables - MATLAB & Simulink - MathWorks India

Synchronize timetables to common time vector, and resample or aggregate data from input timetables - MATLAB synchronize - MathWorks India

Fill missing entries - MATLAB fillmissing - MathWorks India