I am trying to represent sensor data in spectrogram form.

The data set consists of multiple 1D time series with a constant frequency of 1024 Hz taken from observations, cut into 1-minute sequences. Therefore, Each data frame has 61440 columns corresponding to all time steps contained in one minute at 1024Hz.

what I want to achieve is to split the signal into chunks (512 time steps each) and create a spectrogram image with shape(64,64,3) for that specific time interval. I don't have a background in signal processing beforehand. As I have observed so far spectrograms represent the signal in Freq. , time axis along with altitude as pixel intensities. Is it possible to achieve my goal?

what I tried so far gave me results with the (freq-interval,data-points) shape of an image
e.g. (30,512).

My real aim is to represent a signal as an image without losing features. I will then use those inputs in a classification task. I am open to any suggestions.

Thanks.