Obviously, speed is important. Austin, Texas-based vendor National Instruments Corp. (NI, www.ni.com) is finding that end-users of data acquisition (DAQ) products are increasingly asking for multiple gigabits per second on multiple channels, simultaneously, says Nathan Yang, NI’s DAQ product manager. That’s true “not just for just multiple ADCs (analog-to-digital converters) but even single ones, which are now multi-function.” Power hungry
Because those digital input/output (I/O), as well as analog I/O, are “power hungry, especially at gigabit rates,” that means that end-users need “higher-powered buses,” Yang notes. One example would be the PXI Express bus. But another solution is universal serial bus (USB)-enabled systems, he notes. “USB data acquisition can sustain 20-to-30 million bits per second [Mbps], from the ground up.” He notes that USB can be sufficient for high-speed transfer only if the device manufacturer “has set the system to use it—not just buying a USB converter, slapping in it and expecting it to work.”While getting data to the buses may be customized by the user, the transfer’s still got to work without delay. Because the only bottleneck with the USB systems is the USB serialization, says Yang, one workable solution has been using a field programmable gate array (FPGA) chip. It allows “all data to pass at the same time, to simultaneously steam to all USB end points.”Filtering those data dovetails with end-users’ need for faster, higher-rate processing. Higher-resolution devices, such as 18-bit ones that provide better filtering, now find use with USB-enabled systems. With these 18-bit-resolution devices, the maximum data transfer rate can be in the 20-to-30 Mbps range, Yang comments. With older 16-bit-resolution devices, that rate would less, but still close to the 20-to-30 Mbps rate, he adds. But the challenge here is not only transfer, but also power dissipation in the DAQ device itself, Yang explains. With the higher-resolution device, power dissipation is higher, meaning there is more waste heat generated. Heat-exchange solutions include use of gels and aluminum to transfer the heat out of the DAQ device. “As with any high-accuracy measuring device, you want the device to reach steady-state temperature as quickly as possible,” he states. Filtering is very important to achieve increased accuracy, he also adds. Within software filtering, though, there hasn’t been much recent advance, he says. With hardware filtering, that’s not the case, however—and this is where the FPGA chip also comes into play. Hardware filters typically are located next to the sensor. But with an FPGA, which Yang says “can be thought of as a hardware filter that is software configurable,” end-users can “reprogram that FPGA to filter, depending on the application requirement.” Also, on-board data analysis can be put onto the chip, he adds.Because pricing on FPGA technology has dropped, Yang forecasts more use of it. “FPGA is the best—and only—way to proceed with fast, deterministic, real-time analysis,” he observes, though “programming an FPGA chip is a very hard thing to do.” Even so, he predicts that “as more people understand the use of FPGAs, the more that technology will be adopted in data acquisition.” Yang also now sees new, non-traditional applications of DAQ systems, including their use in embedded systems in medical applications designed for high accuracy, as well as in structural monitoring. But what he calls the “biggest move” in DAQ is migration to external systems—“from plug-ins to USBs outside the computer box.” Translated, that means very strong movement to modularity and “the ability to reuse ADCs,” he remarks. That will improve companies’ competitiveness. C. Kenna Amos, [email protected], is an Automation World Contributing Editor.
Because those digital input/output (I/O), as well as analog I/O, are “power hungry, especially at gigabit rates,” that means that end-users need “higher-powered buses,” Yang notes. One example would be the PXI Express bus. But another solution is universal serial bus (USB)-enabled systems, he notes. “USB data acquisition can sustain 20-to-30 million bits per second [Mbps], from the ground up.” He notes that USB can be sufficient for high-speed transfer only if the device manufacturer “has set the system to use it—not just buying a USB converter, slapping in it and expecting it to work.”While getting data to the buses may be customized by the user, the transfer’s still got to work without delay. Because the only bottleneck with the USB systems is the USB serialization, says Yang, one workable solution has been using a field programmable gate array (FPGA) chip. It allows “all data to pass at the same time, to simultaneously steam to all USB end points.”Filtering those data dovetails with end-users’ need for faster, higher-rate processing. Higher-resolution devices, such as 18-bit ones that provide better filtering, now find use with USB-enabled systems. With these 18-bit-resolution devices, the maximum data transfer rate can be in the 20-to-30 Mbps range, Yang comments. With older 16-bit-resolution devices, that rate would less, but still close to the 20-to-30 Mbps rate, he adds. But the challenge here is not only transfer, but also power dissipation in the DAQ device itself, Yang explains. With the higher-resolution device, power dissipation is higher, meaning there is more waste heat generated. Heat-exchange solutions include use of gels and aluminum to transfer the heat out of the DAQ device. “As with any high-accuracy measuring device, you want the device to reach steady-state temperature as quickly as possible,” he states. Filtering is very important to achieve increased accuracy, he also adds. Within software filtering, though, there hasn’t been much recent advance, he says. With hardware filtering, that’s not the case, however—and this is where the FPGA chip also comes into play. Hardware filters typically are located next to the sensor. But with an FPGA, which Yang says “can be thought of as a hardware filter that is software configurable,” end-users can “reprogram that FPGA to filter, depending on the application requirement.” Also, on-board data analysis can be put onto the chip, he adds.Because pricing on FPGA technology has dropped, Yang forecasts more use of it. “FPGA is the best—and only—way to proceed with fast, deterministic, real-time analysis,” he observes, though “programming an FPGA chip is a very hard thing to do.” Even so, he predicts that “as more people understand the use of FPGAs, the more that technology will be adopted in data acquisition.” Yang also now sees new, non-traditional applications of DAQ systems, including their use in embedded systems in medical applications designed for high accuracy, as well as in structural monitoring. But what he calls the “biggest move” in DAQ is migration to external systems—“from plug-ins to USBs outside the computer box.” Translated, that means very strong movement to modularity and “the ability to reuse ADCs,” he remarks. That will improve companies’ competitiveness. C. Kenna Amos, [email protected], is an Automation World Contributing Editor.
