Examples/Data acquisition systems
Data acquisition · Case studies
Data Acquisition System Examples
Data acquisition and monitoring systems Sciotex has designed, programmed and built, from automotive CAN bus logging and remote facility monitoring to physiological measurement in research labs.
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Case studies
Data acquisition systems we have designed and built
Each system was engineered around specific sensors, signals and data requirements. Filter by application, then open a case study for the architecture and measurements.
CAN Bus Data Logger and Automotive Test System
Reads an automotive computer over CAN bus, logs the data and uses it to set test conditions through DAQ outputs.
- CAN bus interface
- Data logging
- Manual and automatic modes
Microvolume Spectrophotometer Software
Commercial and in-house software for USB microvolume spectrophotometers and a fluorometer, with user methods and custom reports.
- USB instruments
- Multi-level users
- Custom reports
Mouse Conditioning Test System
Runs time-dependent stimulation recipes and measures physiological responses from multiple subjects at once.
- Stimulus recipes
- Multiple subjects
- Physiological data
Multi-Experiment R&D DAQ Software
Flexible data acquisition software that runs simultaneous experiments on one PC, each controlling its own hardware setpoints.
- Simultaneous experiments
- Setpoint control
- Under NDA
Electrotechnology Laboratory Monitor
Simultaneous monitoring and logging of data from five test stations distributed throughout a laboratory.
- 5 test stations
- Distributed logging
- Under NDA
Treadmill Physiology Monitor
Collects physiological data from horses on a treadmill, together with treadmill speed and angle of incline.
- Physiological data
- Speed and incline
- Under NDA
Stimulus and Response System
Applies complex stimulus voltage waveforms to biological samples while logging and analyzing the tissue response.
- Waveform stimulus
- Response analysis
- Under NDA
Glove Box Test System
Opens and closes car glove boxes automatically while monitoring component forces, with high-speed logging of unusual events.
- Force monitoring
- High-speed event logging
- Under NDA
Injection Molding Monitoring System
Monitors and logs the operation of an injection molding machine and alerts operators to fault conditions.
- Machine monitoring
- Fault alerts
- Under NDA
Remote Environmental Monitoring System
Logs temperature, humidity, particulates and vibration at critical facilities and escalates alarms by text and voice.
- 4 environmental variables
- Text and voice alarms
- Watchdog and auto-reboot
Magnetic Field Mapper
Acquires, analyzes and archives 3D maps of the magnetic field around large cylindrical probes used in oil wells, with overlay comparison plots.
- 3D field mapping
- Run overlays
- Under NDA
Have signals that need capturing?
Tell us what you need to measure, how fast and how accurately.
Start the conversation →Many of our systems are built under NDA. Ask us about work in your industry.
What we measure
The measurement engineering behind these systems
Good data starts at the sensor. These are the details that decide whether a data acquisition system can be trusted.
High-speed data acquisition
Sample rates, throughput and the architecture that keeps up with fast signals.
Read the article →Signal conditioning
What each sensor needs before it reaches the digitizer.
Read the article →Sampling rate and anti-aliasing
Nyquist, filters and choosing a rate that captures the real signal.
Read the article →Thermocouple measurement
Cold-junction compensation, accuracy and wiring done right.
Read the article →Ground loops and isolation
Finding ground loops and isolating channels before they corrupt data.
Read the article →Data acquisition software
Ready-to-run, LabVIEW, Python or custom: how to choose.
Read the article →How a project runs
From signal list to trusted data
Whether it is one lab rig or a plant-wide monitoring system, every data acquisition project goes through the same four stages.
Signals and requirements
Channels, sensor types, sample rates and the accuracy budget are defined before hardware is chosen.
Sensors and conditioning
Sensors, signal conditioning, isolation and DAQ hardware are selected to meet that budget.
Software
Acquisition, logging, live display, analysis and reports in LabVIEW, Python or C#.
Validation and support
Checked against reference signals, then deployed, documented and supported.
Go deeper
Learn more about data acquisition
Start a project
Have signals that need capturing?
Tell us what you need to measure, how fast and how accurately. An engineer will follow up to discuss feasibility and the right architecture.
- Production, lab and R&D data acquisition
- All hardware, all languages, AI and traditional
- Designed, programmed, built and supported in the US since 1997
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