1. Purdue University
The spacecraft PurdueSat, classified as a nano-satellite, is currently being developed by the School of Aeronautics and Astronautics at Purdue University. The primary mission of Project PurdueSat is to achieve stable satellite orientation by performing precise attitude and pointing control using propellant-less methods. The solution for attitude determination and control is based only on the interaction between the magnetic moment generated by the satellite and the earth’s magnetic field. This calls for highly complex mathematical models and enormous numeric data processing at runtime – within and ultra low-power environment.
"The ZMobile mixed signal board based on the LabVIEW Embedded Module and the Blackfin is a promising flight computing platform for high-end nano-satellite applications.... Thanks to high-level graphical programming, DSP power becomes now accessible to Aerospace Engineers, who may not necessarily be embedded system experts."
Project Manager and Systems Engineer for the Purdue CubeSat Program
The Storegga rock slide is at the continental shelf in the European North Sea off the coast of Norway. Measuring over 800 km in length, this is the one of the world's longest rock slides on a continental shelf. A huge mound of rubble has accumulated over thousands of years, causing an extremely rough sea bed for laying natural gas pipelines.
The Norwegian high-tech firm of NAXYS AS, who specializes in intelligent underwater instrumentation and condition monitoring, has developed a long-term monitoring system to be installed at the Ormen Lange in 2007. This system was developed entirely in LabVIEW and eventually the Schmid Engineering ZBrain™ hardware deployment platform using the LabVIEW Embedded Module for ADI Blackfin.
In the end, this application which was developed in less than six months generated over 50,000 lines of C code. Within this, there were eight asynchronous threads, four of which needed inter-thread communication, analog and digital I/O, communication via acoustic modem, and programmatic sleep and wake up routines. 77% of companies state that an average embedded programmer can produce 1000 or less lines of debugged had written C code per month.
“The Ormen Lange pipeline monitoring system needed a solution that could operate in harsh conditions for long periods of time, which placed the highest demands on software and hardware reliability, in-program error handling and efficient energy management. The combination of LabVIEW and ADI Blackfin processors delivered the stability, versatility, performance and battery life we needed to meet both the time-to-market and quality requirements.”
- Harald Månum
Senior engineer at NAXYS
Fluidnet has designed a closed loop control system for the delivery of intravenous infusion fluids. The challenge was to simplify the architecture from conventional pumps while improving the performance by a wide margin.
Fluidnet used LabVIEW and NI DAQ to develop algorithms to control their innovative sensor/valve. Boston Engineering then transferred their algorithm to the LabVIEW Embedded Module for ADI Blackfin for deployment using their FlexStackTM platform.
“The use of LabVIEW in all aspects of the design process was critical to our success in getting the IV drip infusion pump completed more quickly at lower cost than our competitors. We were able to take the majority of our embedded code from the design phase all the way to the chip, significantly reducing our engineering costs and, therefore, the final cost of the solution.”
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4. University of California, Berkeley
George Anwar at the University of California Berkeley instructs the required Mechanical Engineering 102 (ME102) senior design course. Course topics include Micro Controllers, Real-Time Software, Electric Motors and Sensors, Sensors Feedback Control systems, Bearings, Clutches and Brakes. The goal of this course is to give each student an understanding of design principles and teach each student how to integrate engineering knowledge to synthesize and analyze real mechanical systems. Students are to deliver a finished running prototype by each semester end.
The LabVIEW Embedded for ADI Blackfin Module is used by engineering students to program the Analog Devices Blackfin embedded controller. LabVIEW Blackfin allows student to concentrate on the combined electrical/mechanical mechatronics problem without being required to struggle with the detailes of embedded code syntax.
See how students learn to combine mechanical simulation with real-world design: motion tracking fan simulation, motion tracking fan in production. Others projects include: self calibrating robot, gyrobot, and automatic wine bottle openers.
Mechatronic Design - ME102 Berkeley
5. Boston Engineering
Boston Engineering used a multifaceted approach to build a tension controller for film developing in a digital printing kiosk. In a film printer, the color media spools are fed through the printer head by a drive motor, with the take-up and feed motors controlling the tension. Vibrations from the cutter head, the varying number of photos printed at a time, and variances in the speed of either motor can affect the tension on the substrate. Developing a low-cost product was one of this project's key objectives.
They monitored the position of two dancers measured with analog Hall-effect sensors to indirectly control the substrate tension. The control system adjusts the position of both motors to keep the feed and take-up tensions within a commanded set point. If this tension is not precisely controlled, the registration error causes a photo to have offset colors.
Boston Engineering chose to prototype their system using NI CompactRIO COTS embedded system. They chose to run the supervisory program on the embedded controller and the motor control algorithm on the FPGA to provide the greatest similarity in programming models between the prototype and the end system. To run the control algorithm on the FPGA, they converted the zero-pole-gain model into a filter similar to the one in the LabVIEW Digital Filter Design Toolkit. They then used the toolkit to generate code for the filter that would execute on the FPGA. Because floating-point arithmetic is very resource-intensive on an FPGA, we used the toolkit to automatically generate fixed-point code. We could then quickly iterate on the design by optimizing the quantization options until the final filter was stable.
Finally, Boston Engineering used the NI LabVIEW Embedded Module for ADI Blackfin Processors to deploy the same generated code to their custom hardware solution for final deployment.
6. Bluetechnix - Tinyboards
Bluetechnix is the maker of the Tinyboards - a set of sophisticated off-the-shelf development platforms based on the Analog Devices Blackfin processors. These tiny core and development boards are designed for rapid prototyping and low volume deployment for the applications in a space and power constrained environment. Tinyboards save development costs and risk significantly by providing manufactured and validated hardware that can minimize the hardware development cycle.
Recently, Bluetechnix has announced support for the LabVIEW Embedded Module for Analog Devices Blackfin Processors. In addition to the features provided by the core LabVIEW module, the Tinyboards LabVIEW Board Support package features drivers for additional peripherals such as a CMOS camera over PPI, a flash memory card for removable, nonvolatile storage, and a serial -> USB converter chip for easy USB communication to a host PC.
In addition, Bluetechnix has announced support of a NI CompactRIO custom module that features a Blackfin processor, and LabVIEW drivers for communication with the FPGA. This module is expected later this year.
Tinyboards Hardware Platform
7. Schmid Engineering - zMobile
High quality of rail- and tramways directly influence the passengers comfort and safety as he travels by public transport. Therefore quality assurance during both the installation and operational/maintenance phase is a must. Prior to concreting rails during installation, their correct position must be verified. Failure to comply results in high follow up costs. During the daily operation, rail- and tramways are exposed to extreme mechanical stress and so unavoidably wear out in time. Therefore rails are monitored and maintained. Schmid Engineering is developing a small, manually operated and reliable measurement system supporting both phases using the LabVIEW Embedded Module for ADI Blackfin Processors.
The LabVIEW Embedded Module for ADI Blackfin is used to program the ZBrain – an off-the-shelf OEM core module designed using the ADSP-537 Blackfin processor. Once the measured data is acquired and stored to nonvolatile, removable memory, the geo-referenced rail measurements are fed into a profile browser, realized with LabVIEW 8. The operator browses through the profile while observing the digital map and places notes on the graph. Finally a visual report for the maintenance staff is generated.
"With regards to complex math algorithms, handling and managing multi-sensor signals and running six asynchronous kernel tasks LabVIEW exceeds the conventional C-Approach. The "G" environment allowed Schmid Engineering to prototype all critical parts long before hardware was available (Statelogic, FFT's, Pattern matching, etc)."
- Marco Schmid
zBrain Hardware Platform
8. Related Links
Learn more about targeting embedded systems with LabVIEW