Data acquisition (DAQ)

Flexible data acquisition for development, test benches and condition monitoring

Data acquisition – commonly referred to as DAQ (Data Acquisition) – covers the acquisition, digitization, transmission and analysis of physical measured variables. DAQ systems form the interface between sensors and analysis software: they condition analog sensor signals, convert them into digital measurement values and transmit the data to a PC or higher-level system for visualization, storage and analysis.

Althen DAQ solutions enable the acquisition of a wide range of measured variables and sensor types. Depending on the device, voltage, current, temperature, resistance, strain, vibration or acceleration can be measured, for example. In addition to multifunctional USB data acquisition devices, specialized modules are available for strain gauge, IEPE and vibration sensors as well as acceleration measurements.

For larger or spatially distributed measurement systems, EtherCAT-based DAQ modules provide a particularly flexible solution. Multiple measurement modules can be interconnected using standard network cables and installed in a decentralized configuration close to the respective sensors. This makes it possible to implement even complex measurement tasks with many or widely distributed measuring points in a clear and efficient way.

Connection to powerful measurement software enables configuration of the measurement channels as well as visualization, recording and analysis of the acquired data.

Precise, versatile and scalable measurement

Althen DAQ systems combine flexible sensor connectivity with fast data acquisition and powerful digital signal processing. This makes them suitable for both individual measuring points and extensive distributed measurement systems.

What to consider when selecting a DAQ system

1. Determine the measured variable and sensor type
The first step is to determine which physical variables need to be measured. Depending on the application, different input modules are required for voltage, current, temperature, strain gauges, IEPE sensors, acceleration or other signals.

2. Consider signal type and measurement range
Sensors provide different electrical output signals. The DAQ system must therefore match the respective signal level and measurement range. In addition to voltage inputs, current, thermocouple, strain gauge or IEPE inputs may be required.

3. Determine the number of measurement channels
For individual sensors, a compact single-channel or multifunction device is often sufficient. For larger measurement tasks, modular expandable systems should be selected so that additional measurement channels and sensor types can be added.

4. Determine the required sampling rate
The required measurement speed depends strongly on the application. Temperature or long-term measurements usually require significantly lower sampling rates than vibration, acceleration or dynamic strain measurements. For dynamic applications, devices with sampling rates of up to 40 or 50 kS/s are available.

5. Consider resolution and measurement accuracy
High A/D resolution makes it possible to detect small signal changes. Depending on the DAQ system, 16-bit or 24-bit A/D converters are available. For particularly demanding measurements, input accuracy, noise performance and dynamic range should also be considered.

6. Check sensor excitation and signal conditioning
Many sensors require suitable excitation or signal conditioning. Strain gauges, for example, require bridge excitation, while IEPE sensors require constant-current excitation. Specialized DAQ modules already integrate these functions, reducing the need for additional hardware.

7. Consider galvanic isolation
In industrial measurements, potential differences and electrical interference can affect signal quality. Galvanically isolated inputs or isolated front ends help decouple the measurement system from the PC and enable low-noise measurements.

8. Choose centralized or decentralized data acquisition
For spatially distributed sensors, it is often beneficial to place the measurement modules as close as possible to the measuring points. EtherCAT-based systems enable a decentralized architecture and therefore reduce long analog sensor cables.

9. Consider networking and expandability
If the measurement system is to be expanded later, a modular system architecture is particularly advantageous. IOLITE modules, for example, can be connected in series via EtherCAT. Distances of up to 50 metres between individual devices are possible.

10. Include measurement software and data analysis
In addition to the hardware, the software plays a crucial role. The measurement software should provide easy channel configuration as well as functions for visualization, storage, analysis and data export. MonoDAQ and IOLITE devices are supported by Dewesoft for this purpose.

Our technical expert team will be happy to help you optimally match sensors, signal conditioning, DAQ hardware and software to your measurement task. Contact our sales team

Typical applications for DAQ systems

DAQ systems are used wherever sensor signals need to be precisely acquired, synchronized, stored and analyzed.

Typical applications include:

• Test benches and test systems
• Research and development
• Machine and plant monitoring
• Condition monitoring
• Vibration measurements
• Condition monitoring of bearings and machinery
• Strain and load measurements with strain gauges
• Industrial quality control
• Structural and modal testing
• Structural Health Monitoring
• Temperature and climate measurements
• Current and voltage measurements
• Energy and power analysis
• Development of electronic systems
• IoT and IIoT applications
• Long-term monitoring of machinery and structures

By combining different input modules, complex measurement tasks can also include different physical variables within one system and evaluate them together.