What Are Mathematical Signal Conditioners?

When doing data acquisition, you will almost always need some signal conditioning. Whether you’re dealing with noise, offsets, or just trying to get a better measurement, signal conditioners are an essential part of the data acquisition process.

Let’s look at what mathematical signal conditioners are and the different types available.

What Is a Mathematical Signal Conditioner?

Signal conditioners are devices that modify an input signal to make it more suitable for further processing. This signal can involve amplification, filtering, or even changing the signal’s voltage level. In many cases, signal conditioners make an analog signal more compatible with a digital system.

Common Types of Signal Conditioners

Several signal conditioners are available on the market, each designed for a specific purpose. An amplifier, for example, increases the amplitude of a signal while keeping its other characteristics unchanged. This amplifier can be practical when the signal is too weak to measure accurately.

Filters are another common variation that you need to know about signal conditioning. These devices remove unwanted frequencies from a signal, which can help reduce noise or eliminate interference. Low-pass filters, for example, remove high-frequency components from a signal, while high-pass filters do the opposite.

Signal conditioners can also work well to change the voltage level of a signal. This change is often necessary when interfacing with two devices that operate at different voltage levels. For instance, many digital systems use signals with a voltage level of 3.3 V or 5 V, while many analog sensors operate at much higher voltages.

When trying to interface these two devices, a signal conditioner effectively converts the sensor’s output voltage to the appropriate level for the digital system.

How To Choose a Signal Conditioner

When choosing a signal conditioner, there are a few factors you need to take into account.

1. You need to consider the type of signal you’re working with and the kind of processing you need to do.
2. You need to look at the signal conditioner’s input and output ranges to ensure it’s compatible with your system.
3. You need to consider the power requirements of the signal conditioner and make sure your data acquisition system can power it.

Signal conditioners are an essential part of any data acquisition system. By understanding how they work and the available types, you can choose the right signal conditioner for your application. 

Not only will this improve the quality of your measurements, but it will also make your data acquisition system more robust and reliable.