For many real-world applications, engineers must measure environmental or structural parameters, such as temperature or vibration using sensors.
These, in turn, require signal conditioning before a data acquisition device can effectively and accurately measure the signal. Signal conditioning provides a distinct advantage over data acquisition devices alone because it enhances both the performance and measurement accuracy of data acquisition systems.
Data acquisition systems
With the speed and accuracy of modern data acquisition devices, it is easy to overlook the need for signal conditioning. While plug-in DAQ devices specifically and accurately measure voltage signals, voltage is only one of many I/O types required by modern measurement and automation applications.
Many of today’s data acquisition systems must also measure signals from sensors that detect physical, chemical, or mechanical phenomena. Several of these sensors such as RTDs and strain gauges must have signal conditioning to return any measurement and they all require conditioning to return accurate measurements.
While data acquisition devices have become progressively more intricate, the basic principles of data acquisition remain the same, users must connect to the signal, apply the necessary signal conditioning, digitise the signal and display the data. With this in mind, the three vital components of all data acquisition systems are as follows:
* Signal conditioning (to condition the signal/sensor).
* Data acquisition device (to digitise the conditioned signal).
* Software (to analyse, record, and display the acquired signal data).
The component most often forgotten, yet fundamentally important, is signal conditioning. A large portion of the world’s measurable signals must be detected with sensors, most of which require some sort of signal conditioning for the data acquisition device to read them accurately. Thus, a data acquisition system must not only incorporate the digitiser and application software, but also tightly integrated signal-conditioning hardware.
Data acquisition devices are used in a variety of applications. In laboratories, in field services and on manufacturing plant floors, these devices act as general-purpose measurement tools well suited for measuring voltage signals.
However, for many real-world applications, measurement of environmental or structural parameters such as temperature or vibration made with sensors is required. These sensors, in turn, require signal conditioning before a data acquisition device can effectively and accurately measure the signal. Signal conditioning provides a distinct advantage over data acquisition devices alone because it enhances both the performance and measurement quality of data acquisition systems.
To illustrate the necessity of signal conditioning, consider a thermocouple. To measure thermocouple signals accurately, amplification, filtering, and cold-junction compensation must be provided.
Amplification is required because of the small magnitude of the signal should be provided as close to the thermocouple as possible to increase the signal-to-noise ratio. While amplification helps reduce the effect of noise on the signal, filtering must also be provided to eliminate environmental noise from power lines and other electric devices. Cold-junction compensation is also necessary to offset any temperature difference that exists between the measurement junction of the thermocouple and the junction with the data acquisition device.
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