How can I detect repeating chunks of data in a big dataset?

For example:
I have a measurement dataset of values measured on a given day for a year. Say 10 measurements a second.
And now I want to make sure that each dataset is unique. Due to Noise in a measurement even the same input will lead to numerically very different datasets.

But this seems not to be the case with the given dataset. E.g. plotting signals shows repeating patterns that are statistically extremely unlikely.

The problem reminds me of a diff from two text files. Is there any library/ established approach to this problem?

Edit: Data Structure is a csv:

```
Time (Seconds) | Sensor1 (Volt) | Sensor 2 (Volt) | ... | Sensor 10 (Volt)

```

I want to detect something like this:

```
Time (Seconds) | Sensor1 (Volt) | Sensor 2 (Volt) | ... | Sensor 10 (Volt)
1 | 242.2 | 234.23 |...|
2 | 423.23| 33.00 |...|
3 | 100.00| 24.23  |...|

```

...

```
123 | 242.2 | 234.23 |...|
124 | 423.23| 33.00 |...|
125 | 100.00| 24.23  |...|

```

Result I am looking for:

There is a repeating pattern for x timesteps. The biggest same data set is from ... to .... Second biggest from ... to ...