Programmable Logic Controller is the heart of many industrial automation and process control systems, which monitors, controls, and actuates complex system variables. Employing multiple sensors and actuators, industrial automation and process-control systems use PLCs to measure and control analog process variables such as pressure, temperature, and flow. PLCs are found in diverse applications, such as industrial factories, oil refineries, medical equipment, and aerospace systems that require high accuracy and robust long-term operation. In addition, the competitive marketplace demands lower cost and shorter design times.
Hence, designers of industrial equipment and critical infrastructure encounter momentous challenges to meet their customers’ stringent accuracy, noise, drift, speed, and safety requirements.
Inside The PLC
Figure 1 shows a simplified signal chain for a PLC used in industrial automation and process-control systems. The PLC typically comprises analog and digital input/output modules, a central processing unit, and power-management circuitry.
Figure 1: Typical PLC signal chain
In industrial applications, analog input modules acquire and monitor signals from remote sensors located in harsh environments characterised by extreme temperature and humidity, vibration, and explosive chemicals. Typical signals include single-ended or differential voltages with 5, 10, ±5V, and ±10V full-scale ranges, or current loops with 0 to 20mA, 4 to 20mA, and ±20mA ranges. When long cables with substantial electromagnetic interference are encountered, current loops are often used due to their inherently high noise immunity.
Analog output modules typically control actuators, such as relays, solenoids and valves, to complete the automated-control system. They typically provide output voltages with 5, 10, ±5V, and ±10V full-scale ranges and 4 to 20mA current-loop outputs.
Typical analog I/O modules include 2, 4, 8, or 16 channels. To meet stringent industry standards, these modules require protection against overvoltage, overcurrent, and EMI surges. Most PLCs include digital isolation between the ADC and the CPU and between the CPU and the DAC. High-end PLCs may also incorporate channel-to-channel isolation, as specified by International Electrotechnical Commission standards. Many I/O modules include per-channel software programmable single-ended or differential input ranges, bandwidth and throughput rate.
In modern PLCs, the CPU performs numerous control tasks in an automated manner, employing real-time access to information to make intelligent decisions. The CPU may embody advanced software and algorithms, and web connectivity for diagnostic error checking and fault detection. Commonly used communication interfaces include RS-232, RS-485, industrial Ethernet, SPI, and UART.
Discrete DAQ Implementation
Industrial designers can build analog modules for PLCs or similar data-acquisition systems with discrete high-performance components, as shown in Figure 2. Key design considerations include input signal configuration, overall system speed, accuracy and precision. The signal chain presented here utilises the ADG1208/ADG1209 low-leakage multiplexer, AD8251 fast-settling programmable-gain instrumentation amplifier, AD8475 high-speed funnel amplifier, AD7982 differential-input 18-bit PulSAR ADC, and ADR4550 ultra-low-noise voltage reference. This solution provides four different gain ranges, but with maximum input signals of ±10V, designers will have to worry about multiplexer’s channels switching and settling times, and other analog signal conditioning challenges. In addition, achieving true 16-bit performance at 1MSPS can be a major challenge, even when using these high-performance components.
Figure 2: Analog input signal chain using discrete components
The AD7982 specifies a 290ns transient response from a full-scale step. Thus, to guarantee the specified performance while converting at 1MSPS, the PGIA and funnel amp must settle in less than 710ns. However, the AD8251 specifies 785ns settling time to 16 bits (0.001%) for a 10-V step, so the maximum throughput that can be guaranteed for this signal chain will be less than 1 MSPS.
Manufactured in iCMOS; a proprietary, high-voltage industrial process technology, the 16-bit, 1MSPS ADAS3022
data-acquisition IC integrates an 8-channel, low-leakage multiplexer; a high-impedance PGIA with high common-mode rejection; a precision, low-drift 4.096V reference and buffer, and a 16-bit successive-approximation ADC, as shown in Figure 3.
Figure 3: Functional block diagram of ADAS3022
This complete sensor-to-bits solution utilises only one-third of the board space of discrete implementations, helping engineers to simplify their designs while reducing the size, time to market and cost of advanced industrial data-acquisition systems. Eliminating the necessity to buffer, level shift, amplify, attenuate, or otherwise condition the input signal and the concerns regarding common-mode rejection, noise and settling time, it alleviates many of the challenges associated with designing a precision 16-bit, 1MSPS data-acquisition system. It delivers the best-in-class 16-bit accuracy (±0.6-LSB typical INL), low offset voltage, low drift over temperature and optimised noise performance (91dB typical SNR) at 1MSPS, as shown in Figure 4. The device is specified over the –40°C to +85°C industrial temperature range.
Figure 4: INL and FFT performance of the ADAS3022
The ADAS3022 can be configured to measure up to eight single-ended inputs or four differential pairs. Seven bipolar input ranges can handle the full span of industrial signal levels (±640mV to ±24.576V), thus allowing direct connection to most sensor interfaces. The input range of each channel is independently programmable to suit different measurement and protection schemes. The on-chip multiplexer allows channel scanning and the internal reference and buffer eliminates the need for external components.
The PGIA has a large common-mode input range, true high-impedance inputs (>500MΩ), and a wide dynamic range, allowing it to accommodate 4 to 20mA current loops, accurately measure small sensor signals, and reject interference from AC power lines, electric motors, and other sources (90dB minimum CMR).
An auxiliary differential input channel can accommodate ±4.096V input signals. It bypasses the multiplexer and PGIA stages, allowing direct interface to the 16-bit SAR ADC. An on-chip temperature sensor can monitor the local temperature.
This high level of integration saves board space and lowers the overall parts cost, making the ADAS3022 ideal for space-constrained applications, such as automatic test equipment, power-line monitoring, industrial automation, process control, patient monitoring, and other industrial and instrumentation systems that operate with ±10V industrial signal levels.
Figure 5 shows a complete 8-channel data acquisition system. The ADAS3022 operates with ±15V and +5V analog and digital supplies, and a 1.8V to 5V logic I/O supply. The ADP1613 high-efficiency, low-ripple dc-to-dc boost converter allows the DAS to operate with a single 5V supply. Configured as a single-ended, primary inductance topology using the ADIsimPower design tool, the ADP1613 furnishes the ±15V bipolar supplies required for the multiplexer and PGIA without compromising performance.
Figure 5: Complete 5V, single-supply, 8-channel data-acquisition solution with integrated PGA
The single-pole low-pass filter (LPF) between the AD8475 and AD7982 (Figure 2) attenuates the kick coming from the switched-capacitor input of the AD7982 and limits the amount of high-frequency noise. The –3dB bandwidth (f–3dB) of the LPF is 6.1MHz (R = 20Ω, C = 1.3nF), allowing fast settling of the input signals while converting at 1MSPS. The ENBW of the LPF can be calculated as:
ENBW = π/2 × f–3dB = 9.6MHz
Note that this calculation ignores the noise from the voltage reference and LPF as it does not significantly affect the total noise, which is dominated by the PGIA.
Consider an example using the ±5V input range. In this case, the AD8251 is set for a gain of 2. The funnel amplifier is set to a fixed gain of 0.4 for all four input ranges, so a 0.5V to 4.5V differential signal (4Vp-p) will be applied to the AD7982. The RTI noise of the ADG1208 is derived from the Johnson/Nyquist noise equation:
(en2 = 4KBTRON, where KB = 1.38E–23 J/K, T = 300K, and RON = 270 Ω)
The RTI noise of the AD8251 is derived from its 27nV/√Hz noise density as specified in the data sheet for a gain of 2. Similarly, the RTI noise of AD8475 is derived from its 10nV/√Hz noise density using a gain of 0.8 (2 × 0.4). In each calculation, ENBW = 9.6MHz. The RTI noise of the AD7982 is calculated from its 95.5dB SNR as specified in the data sheet using a gain of 0.8. The total RTI noise of the entire signal chain is calculated based on the root-sum-square (rss) of the RTI noise from the discrete components. The total SNR of 89.5dB can be computed from the equation:
SNR = 20log(Vinrms/RTITotal)
Although the theoretical noise estimate and the overall performance of the discrete signal chain is comparable to that of the ADAS3022, especially at lower gains (G=1 and G=2), it’s not an ideal solution at higher throughput rate up to 1MSPS. The ADAS3022 can reduce cost by about 50% and board space by about 67% as compared to the discrete solution, and it can also accept three additional input ranges (±0.64V, ±20.48V, and ±24.576V) that the discrete solution cannot offer.
The next generation of industrial PLC modules will demand high accuracy, reliable operation, and functional flexibility, all in a small, low-cost form factor. The ADAS3022, with industry leading integration and performance, supports a wide range of voltage and current inputs to handle a variety of sensors in industrial automation and process control. An ideal fit for PLC analog input modules and other data-acquisition cards, the ADAS3022 will enable industrial manufacturers to differentiate their systems while meeting stringent user requirements.
Maithil Pachchigar is an applications engineer in Precision Converters business unit in Wilmington, MA since joining ADI in 2010. He supports the precision ADC product portfolio and customers in the Industrial, Instrumentation, Medical and Energy segments. He has nearly 7 years of experience in the semiconductor industry and published several technical articles. Maithil received a MSEE from San Jose State University in 2006 and an MBA from Silicon Valley University in 2010.