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Data Acquisition (DAQ)

Image Part Number Description / PDF Quantity Rfq
MONODAQ U-X-1

MONODAQ U-X-1

MonoDAQ

MULTIFUNCTIONAL DATA ACQUISITION

10
D1252M

D1252M

DGH Corporation

4-20MA INPUT, RS-485 OUT, MODBUS

15
M-6018-16

M-6018-16

ICP DAS USA Inc.

RS-485 REMOTE I/O BOARD: 16 CHAN

30
785816-01

785816-01

NI

USB-6349 MULTIFUNCTION I/O DEVIC

1
778511-01

778511-01

NI

NI PCI-6731 ANALOG OUTPUT BOARD

1
782607-01

782607-01

NI

USB-6002 OEM BOARD ONLY KIT (NO

6
782609-01

782609-01

NI

USB-6003 OEM BOARD ONLY KIT (NO

2
781051-01

781051-01

NI

NI PCIE-6363, X SERIES DAQ (32 A

3
DVS01

DVS01

Cordova Flow Controls

DATAVAULT LOGGER 64MB,MODBUS,USB

5
782255-01

782255-01

NI

NI USB-6361, X SERIES DAQ DEVICE

2
D2252

D2252

DGH Corporation

4-20MA IN, RS-485, PROGRAMMABLE

15
778834-01

778834-01

NI

NI PCI-6624 INDUSTRIAL 8-CHANNEL

6
779617-01

779617-01

NI

NI PCI-6232, ISOLATED (ANALOG VO

1
197201-01

197201-01

NI

USB-6255 OEM BOARD-ONLY KIT (NO

3
779069-01

779069-01

NI

NI PCI-6250, M SERIES DAQ (16 AN

3
778397-01

778397-01

NI

NI PCI-6120 S SERIES MULTIFUNCTI

1
785817-01

785817-01

NI

PCIE-6374 MULTIFUNCTION I/O DEVI

4
MONODAQ U-X-50

MONODAQ U-X-50

MonoDAQ

MULTIFUNCTIONAL DATA ACQUISITION

6
D5141M

D5141M

DGH Corporation

+/-10VIN, 4CH, RS-232,MODBUS RTU

15
782263-01

782263-01

NI

NI USB-6366, X SERIES DAQ DEVICE

0

Data Acquisition (DAQ)

1. Overview

Data Acquisition (DAQ) refers to systems that convert physical phenomena (e.g., temperature, pressure, voltage) into digital data for analysis, monitoring, and control. Modern DAQ systems integrate hardware and software to sample, condition, and process signals. They are critical in scientific research, industrial automation, automotive testing, and medical diagnostics, enabling precise data-driven decision-making.

2. Main Types and Functional Classification

TypeFunctional FeaturesApplication Examples
Portable DAQCompact, battery-powered, USB/Wi-Fi connectivityField testing, mobile diagnostics
Modular DAQCustomizable slots for various I/O modulesProduction line monitoring
Virtual Instrument DAQSoftware-centric with PC-based processingLab experiments, R&D
Industrial DAQRuggedized, high noise immunityFactory automation, HVAC systems

3. Structure and Components

A typical DAQ system comprises:

  • Hardware: Sensors/transducers, signal conditioning circuits, analog-to-digital converters (ADC), processors (e.g., FPGAs), communication interfaces (Ethernet, PCIe).
  • Software: Driver layers (e.g., NI-DAQmx), data visualization tools, analysis algorithms (FFT, filtering), and storage modules.

Example: A vibration analysis DAQ system uses accelerometers, charge amplifiers, and a PXI chassis for signal processing.

4. Key Technical Specifications

ParameterDescriptionImportance
Sampling RateMeasure of data points captured per second (up to GSPS)Determines fidelity of high-frequency signals
ResolutionADC bit depth (12-24 bits)Impacts measurement precision
Input RangeVoltage/current range compatibilityEnsures sensor compatibility
IsolationElectrical separation between channelsProtects system from surges

5. Application Fields

  • Industrial: Machine condition monitoring (e.g., Siemens SIMATIC IOT2000)
  • Automotive: Crash test data logging (e.g., Kistler KiDAQ)
  • Medical: ECG signal acquisition (e.g., National Instruments PXIe-4143)
  • Aerospace: Flight test instrumentation (e.g., Curtiss-Wright DAQ systems)

6. Leading Manufacturers and Products

ManufacturerRepresentative ProductKey Features
National InstrumentsPXIe-63638-channel, 16-bit resolution, 2MS/s sampling
Keysight Technologies34972A LXI DAQ20-bit resolution, 250kS/s, modular design
Teledyne LeCroyHDO6000 DAQ12-bit ADC, 1GHz bandwidth oscilloscope integration

7. Selection Guidelines

Consider the following factors:

  1. Application Requirements: Determine signal types (analog/digital), environmental conditions (temperature, vibration).
  2. Performance: Match sampling rate/resolution to signal characteristics (e.g., audio vs. RF).
  3. Compatibility: Ensure interface alignment (USB, PCIe) and software support (LabVIEW, MATLAB).
  4. Scalability: Modular systems allow future expansion.
  5. Budget: Balance cost with precision needs (e.g., 24-bit ADCs for high-accuracy labs).

8. Industry Trends

Future DAQ systems will emphasize:

  • Smart Integration: AI-driven edge computing for real-time analytics.
  • Wireless DAQ: IoT-enabled systems with 5G/Wi-Fi 6 connectivity.
  • Miniaturization: MEMS-based sensors reducing DAQ size.
  • High-Speed ADCs: Adoption of 10+ GSPS converters for 5G and radar testing.
  • Cloud Compatibility: Direct integration with cloud platforms (AWS, Azure) for remote monitoring.
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