Understand How Data Acquisition Systems Work

Key takeaways:

Data acquisition systems or units drastically reduce the number of instruments you need to simultaneously measure hundreds of devices or test points.
Switching hardware, like multiplexers and matrix switches, is key to the efficient use of data acquisition systems.
By combining modules and software, you can both scale up and scale out your total data acquisition (DAQ) capacity.

Automated testing involves careful coordination of various instruments and test sequences to simulate real-world behaviors. Without data acquisition systems, such automated testing would be considerably more expensive and laborious to set up.

We have previously talked about the basics of data acquisition systems and their applications. In this article, we dive into the internals of DAQ hardware and their technical aspects.

What is a data acquisition system?

In electronics testing, a data acquisition system (DAQ system) is a centralized measurement instrument that takes simultaneous readings from dozens of devices or hundreds of test points while the inputs and outputs of connected waveform generators, oscilloscopes, power supplies, loads, and other instruments are coordinated to simulate real-world scenarios.

The illustration below depicts a single data acquisition unit with a built-in multimeter measuring multiple input and output voltages of a DUT through its many channels.

Data Acquisition Systems DAQ systems Flow DC Power System Eload

Fig 1. DAQ systems can simultaneously measure multiple inputs and outputs

Without DAQs, such testing would require dozens of additional multimeters, power meters, and other measurement instruments and synchronization between all of them.

A DAQ is an assembly of measurement hardware and software with the following characteristics:

High measurement capacity: A typical DAQ system has dozens to thousands of measurement channels. This allows simultaneous, continuous, high-speed measurements of inputs to and outputs from many devices under test (DUTs) as well as many test points on each DUT.
Variety of measurements: A DAQ system can measure a wide variety of electrical, wireless, optical, physical, and digital characteristics. They include:
- analog electrical measurements like voltages, currents, resistances, radio frequency (RF) power, or light intensity
- physical characteristics like temperature, humidity, acceleration, stress, and sound
- digital metrics like counters and totals
Scalability: Most modern DAQ systems have highly modular designs to allow adding capacity or features through plug-and-play USB DAQ hardware modules. Such modules include additional channels, multiplexers for scanning multiple channels, matrices for connecting multiple test points at one time, and switches for control over aspects like the routing of signals to different instruments and for sourcing or sinking high power. Additionally, multiple DAQ units can be stacked and coordinated to scale up total measurement capacity.
Automation: Modern DAQ systems allow fine-grained control over all aspects of measurements — e.g., timing, enabling or disabling, coordinated readings across multiple instruments, routing of signals, and much more. These features are essential for test automation, especially high-volume quality control using automated test equipment (ATE).
Data recording: A key aspect of data acquisition systems is reliable, high-capacity, real-time data logging of inputs, outputs, and timestamps with high accuracy. (DAQs have built-in digital multimeters with six or more digits of resolution.) These data logging capabilities are essential for offline data analysis, event correlation, and visualization.

In the rest of this article, we explore the technical aspects of data acquisition systems in detail.

What are the key components of a data acquisition unit?

Daq System Components | Key Components of a Data Acquisition System and Flow Schematic

Fig 2. DAQ system components

The key components of a DAQ system are:

sensors or transducers to convert the phenomenon being measured into electrical signals
signal conditioning circuitry to make the measured signals suitable for digitization and storage
data acquisition and switching hardware for signal management and digitization
data logger for storing and transmitting the data
DAQ software for data analysis and visualization

In the following sections, we explore each of these subsystems in more detail.

Sensors or Transducers

Thermocouple Sensors

Fig 3. Thermocouple sensors

Sensors or transducers detect and measure various characteristics like voltages, temperature, pressure, flow, or light intensity. They convert physical phenomena into electrical signals like voltages, currents, or resistances that can be recorded by the DAQ system.

Sensor choice depends on the specific characteristic to be measured:

For temperature measurements, we use thermocouples, thermistors, or resistance temperature detectors (RTDs).
For motion and vibration analysis, we use accelerometer sensors.
For measuring stresses, we use strain gauges.

The table below lists the various types of sensors out there.

Different Types of Sensors and Their Typical Outputs | Thermocouples and Resistence

Fig 4. Different types of sensors and their typical outputs

How does the choice of sensors impact the design and performance of a data acquisition system?

The choice of sensors required for a particular application influences the selection of the DAQ system as well based on its functional and performance capabilities. Some key aspects to consider include:

Signal conditioning requirements: Some sensors require special signal conditioning to make their outputs compatible with DAQ. For example, since thermocouples produce very low-voltage signals, amplifiers are needed to boost them up.
Measurement accuracy and resolution: High-precision sensors for critical applications like avionics testing require matching performance from the data acquisition components like the analog-to-digital converter.
Sampling rate: The sensor also dictates the required sampling rate to capture useful data. For example, high-speed physical phenomena (like vibrations in a turbine blade) result in high-frequency sensor data. The DAQ system's data sampling and processing speeds must match that data frequency.

Signal Conditioning

The electrical analog input from a sensor often requires conditioning to make it suitable for digitization and storage. Signal conditioning may involve one or more steps like:

amplification to boost low-voltage signals
attenuation to weaken high-voltage signals
filtering to remove unwanted frequencies or noise
linearization to compensate for nonlinear responses

What role does signal conditioning play in the accurate measurement of data in a data acquisition system?

Signal conditioning steps like linearization and filtering are crucial for accurate measurements.

For example, when measuring RF signal power, filtering is used to first reduce the noise in the signal to increase the accuracy of the reading.

Another example is compensating for the nonlinear response of a thermocouple temperature sensor. A change in its measured voltage does not correspond to a linear change in temperature. This complicates the entire downstream process of analog-to-digital conversion, data analysis, and visualization, which would require the use of inverse nonlinear formulas to convert voltages back to accurate temperatures.

Instead, for convenience and accuracy early on, signal conditioning is applied directly to the signal to linearize it so that voltage changes linearly correspond to temperature changes.

Data acquisition and switching hardware

This subsystem is primarily responsible for measuring the conditional analog signals and transforming them into digital values using an analog-to-digital converter (ADC). It's also responsible for the accurate synchronization of data collection across hundreds of channels.

Additionally, control plane components like multiplexers, matrices, and switches are used in this subsystem for solving various measurement challenges that arise when hundreds of sensors and DUTs are involved.

What measurement hardware do DAQ systems use?

To measure the analog output voltages, currents, or resistances of the conditioning subsystem, a typical DAQ uses a digital multimeter (DMM).

Some DAQs, like the modular 34980A, have built-in DMMs that you can optionally use for all measurements. Alternatively, if higher precision or missing features are required, suitable DMM modules or external standalone DMMs can be connected, and the conditioned signals can be routed there to get the readings.

Some modules are used to measure digital signal characteristics like counters and pulse widths.

How does analog-to-digital conversion work in a DAQ system?

Conversion of the analog signal levels to digital values for storage and analysis is done by an analog-to-digital converter (ADC). The ADC is typically part of the DMM in whatever form it's being used for measurements.

There are several ADC conversion techniques grouped into two types:

Integrating techniques: They measure the average input over a certain time interval, which helps to reduce the effects of noise sources.
Non-integrating techniques: They sample the instantaneous values of the input signal (including noise) during very short time intervals.

The resolution of the ADC and the range of values determine the precision of a measured quantity.

What are the common switching techniques in DAQ systems?

Let's first understand what problems are addressed by control systems like switching hardware.

DAQs are used to simultaneously measure dozens of DUTs and hundreds of test points while test sequences simulate various real-world events. This means measurements must be started and stopped in sync with the test events. Additionally, the number of other connected test and measurement instruments is limited, which means you have to dynamically connect the same few instruments to different DUTs or test points in sync with the test events.

Physically connecting one instrument to dozens of DUTs or test points is impossible. So instead, you dynamically activate connections and routes using switching hardware and programmatic control.

Multiplexers are a common type of switching hardware. They enable connecting many input channels to the signal conditioning and DMM subsystems but activate only one connection at a time. For high speeds, they typically use electronic switches like field-effect transistors and solid-state relays.

A Multiplexer Module for Single-Ended Measurements | Single-Ended Multiplexer Module

Fig 5. A multiplexer module for single-ended measurements

Another common type of system used is matrix switching. Matrix switching modules allow many-to-many connections and routing of multiple signals at the same time as shown below.

Daq Mainframe Control | How a Matrix Switching Module Works

Fig 6. How a matrix switching module works

What are the challenges in synchronizing multiple channels for simultaneous measurements?

Various scan-triggering mechanisms are used to initiate data acquisition across multiple channels simultaneously, including:

periodic time- and interval-based triggers
internal triggers that go off when a channel satisfies some condition or reaches a threshold
external triggers

For synchronized measurements, the DAQ must satisfy the following challenging requirements:

All channels and their sensors must operate at nearly the same sampling rate.
All channels must respond to the same trigger event and finish before the next trigger.
Characteristics like measurement latency and settling time of all instruments must be similar.
Data buffering in memory and real-time data processing may be needed for some channels to ensure they can keep up.

What are the common communication interfaces used in data acquisition systems?

Communication Interfaces of a Daq System

Fig 7. Communication interfaces of a DAQ system

The common communication interfaces between the DAQ, the external instruments, and supervising computers include:

Peripheral Component Interconnect (PCI) eXtensions for Instrumentation (PXI)
PXI Express (PXIe)
Ethernet Local Area Network (LAN) eXtensions for Instrumentation (LXi)
General Purpose Interface Bus (GPIB)
Universal serial bus (USB)

Data logger

The data logger subsystem is responsible for:

storing collected data on local storage media like USB drives
transmitting the digital data to connected computers
buffering of measurements in onboard non-volatile memory to keep up with fast sampling rates while already recorded data is being stored or transmitted

How does data storage work in a data acquisition system?

The data logger subsystem is responsible for storing data locally and remotely. Storage must be reliable and durable because retesting may be expensive in cost and time.

Modern DAQ devices retain measurements in non-volatile memory, which remain intact even if the device is switched off. Storage capacity is of the order of 1 million samples, which is sufficient for a week’s worth of data (20 channels scanned every five minutes). This also means data can be collected at a remote location and uploaded later to a computer in the lab.

After storing in non-volatile memory, the readings are stored in local storage media or transmitted to a connected computer. Some DAQ systems support persistence to USB flash drives, which is a convenient and portable approach.

Data acquisition software

DAQ software runs on connected computers for aggregating measurements from multiple DAQ systems, storing the data on durable storage devices like local solid-state drives or cloud stores, and running data analyses.

What are some examples of DAQ analyzer software?

Pathwave Benchvue Daq App | Daq Analyzer Software

Fig 9. PathWave BenchVue DAQ App

For Keysight DAQs, the PathWave BenchVue Data Acquisition App provides an excellent graphical user interface for programming-free data acquisition management and control. It has features like:

configures the inputs of hundreds of measurement channels across multiple data acquisition units
forwards the data to various local or remote storage devices
runs time-domain analyses on the data
runs frequency-domain analyses

The image below shows the convenient configuration of channels using PathWave BenchVue.

Channel configuration in PathWave BenchVue DAQ App

Fig 10. Channel configuration in PathWave BenchVue DAQ App

For custom data acquisition applications and programmatic control over DAQs, use the Keysight IO Libraries Suite.

Use Keysight data acquisition systems for your mission-critical testing

In this article, we explored various technical aspects of data acquisition devices and how they influence the use of the overall DAQ system.

Keysight's data acquisition systems and modules are extensively used for testing mission-critical systems in the defense, avionics, health care, telecom, and automotive sectors.

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