Does my Sensor Need an Additional Analog Filter?
Time to Read 6 min
Do you have to design an industrial data acquisition system and don't know how to configure the filters? Are you struggling with noise and interference in your product and don't know how to reduce it? Have you ever wondered if analog or digital filters are better?
These questions occur in practice again and again. An analog sensor should be connected to a digital control loop or to a data acquisition system. If there are problems with the measured signal, the call for an analog filter to eliminate the problem follows quickly. But is this also the right way? After all, it is very complex to adapt an analog filter to new requirements (except SC (Switched Capacitor) filters). Also the necessary space for an analog filter should not be underestimated. The following description shows you how you can judge for yourself whether you need additional measurement filters and whether they are correctly dimensioned.
The questions mentioned above can occur in very different situations, e.g:
- Production and testing: Here, data acquisition systems from National Instruments and other manufacturers are often used. This reduces the development effort tremendously. However, these systems often do not have adaptable, analog filters. Long test leads can also capture additional interference.
- Product development: There is hardly a product that does not have sensors and subsequent digitization. The data acquisition system is often reduced to an integrated analog-digital converter. Component costs, space requirements as well as the power consumption of the product are often important. Analog filters cause additional costs and require space. Digital filters on the other hand can increase power consumption.
Sources of Interference
Interference of the measured signal can occur both in the sensor and on the transmission line to the data acquisition system. Depending on the physical process and the measuring principle used, significant noise can also be generated in the sensor itself. For the sake of simplicity, we assume here that noise tends to be rather broadband, but interference tends to be narrowband.