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Distributed DA Delivers Measurement Accuracy and Simplified Test Setup

September 1, 2009 By: Jon Semancik, VTI Instruments Corp. Sensors

Distributed DA systems offer improved measurement accuracy and easy setup when compared to centralized DA systems, however, their design must take into account signal conditioning, self-calibration, excitation, and noise rejection to achieve the most accurate and reliable measurement results.


Test engineers face challenges when measuring temperature, strain, pressure, and flow in or near a test article in electrically noisy or hazardous environments. To address these issues, they often employ a centralized approach that involves placing DA instrumentation in a control room located some distance from the test article. Transducers are then connected to the test article with cabling that can result in significant installation and ongoing maintenance expenses.

While a centralized approach provides convenient control room access to the signal conditioning and instrumentation, the long cable lengths can cause unintentional measurement error by introducing electrical noise, calibration uncertainty, bridge excitation uncertainty, and cable impedance, among other errors. Additionally, this topology has significant costs associated with implementation, such as cabling, debugging, maintenance, and setup.

To improve measurement accuracy, test engineers use a distributed measurement philosophy by placing the instrumentation near the test article. Programmable internal signal conditioning on each input channel eliminates the need for external cabling, which can lower measurement quality, increase setup time, and result in additional maintenance. A properly designed, distributed topology provides protection against adjacent channel over-voltage and noise interference that occurs when measurements are made using common filter circuitry as seen in scanning digital multimeter (DMM) architectures.

Distributed measurement systems (Figure 1) must also include a convenient mechanism for in-place self-calibration, as well as NIST-traceable calibration. Complete end-to-end internal self-calibration provides significant accuracy improvements over other test configurations. Self-calibration compensates for circuitry drift that has occurred since the last full calibration and is relatively easy to perform.

 

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Figure 1. Example of distributed measurement application

While employing distributed measurement techniques can simplify setup and improve overall performance, they also introduce a new set of challenges including synchronization, timing, and data management. LXI (LAN eXtensions for Instrumentation) has emerged as the next-generation instrumentation interface and resolves many of these issues. LXI is based on Ethernet technology, the most commonly used open platform communications interface.

LAN synchronization that incorporates the IEEE 1588 precision time protocol (PTP) enables multiple devices to be synchronized using a single LAN Ethernet connection. PTP defines a precision clock synchronization protocol for networked measurement and control systems that enables the synchronization of systems that include clocks of different precision, resolution, and stability. The most accurate and deterministic synchronization mechanism between multiple devices involves the implementation of a hardware trigger interface. As a result, the LXI standard also defines a high-performance trigger interface referred to as the Trigger Bus, which can provide the link between all devices in the test system for both triggering and clock signal distribution.

While distributed DA systems simplify some aspects of the test process, they also pose new challenges that were relatively transparent in previous generations of hardware such as measurement synchronization techniques that leverage system clock distribution and dedicated trigger lines. This article will discuss these challenges and the innovative approach adopted by instrumentation designers to make full-feature distributed DA a reality.

Distributed DA
Strategic placement of DA instrumentation around or near the test article can result in significant advantages, such as:

  • Quick setup
  • Simplified calibration and maintenance
  • Excitation source closer to Wheatstone bridges
  • Reduced cabling costs and noise
  • Minimized debugging
  • Improved transportability

The above benefits encompass the entire operational life of a project including installation, maintenance, support, and calibration. Cost savings begin at the time of installation with a reduced cost of cabling and associated installation, debugging, and testing. Simplified calibration and excitation further improves system performance. Reducing the effects of noise on transducer cables and simplifying calibration increases overall accuracy.

System Calibration
Test engineers must be confident of the integrity of the data produced by their measurement devices. This confidence is primarily achieved through instrument calibration and the use of traceable verification standards. Specifically, a traceable source is used by the instrument undergoing calibration to adjust and verify the quality of measurement. This has often been viewed as a painful but necessary process involving system disassembly and downtime.

In most cases, test engineers are required to disassemble test stations and send each individual instrument to its respective vendor's factory for calibration. Some alternatives include ordering spare instruments for each test station, hiring an outside calibration service, or constructing an in-house calibration laboratory. Reducing these costs and alleviating the downtime associated with the calibration process ultimately benefits all test and measurement applications.

Leading instrumentation manufacturers have invested significant engineering resources to simplify the calibration process and have added features that guarantee measurement accuracy. By taking advantage of the distributed measurement benefits of LXI and by designing instruments with onboard precision voltage references, calibration becomes more convenient and reliable. Specifically, vendors can embed the calibration process directly in the instrument's firmware, allowing the end user to execute a complete calibration in minutes, at the click of a button. A precision onboard voltage source can extend the calibration capabilities by also offering a self-calibration routine, which the end user can initiate at any time. This procedure guarantees precise measurements, regardless of environmental changes.

A fully integrated Web interface streamlines the calibration process. To perform a complete NIST-traceable calibration, a host computer and precision voltmeter are required. Connect the voltmeter to the instrument using banana jacks, access the Web interface using a standard Internet browser, and click the button that commands the instrument to perform the automatic factory calibration.

The instrument's firmware can be configured to recognize and communicate with several different voltmeters to measure the onboard precision voltage source. While storing this value, the instrument can route the source back through the input signal paths and reliably perform internal adjustments. The simplified equipment setup enables the process to be executed almost anywhere.

Prior to each DA sequence, the device can also execute a self-calibration procedure directly from the software or a Web browser interface. Before any measurement is taken, users can initiate a self-calibration sequence that routes the precision source back through the actual input signal path. Whenever the device undergoes changes in its surrounding thermal environment, this process can be executed to ensure the highest degree of measurement quality.

Integrated Signal Conditioning
To properly use distributed instrumentation, all aspects of the measurement device must be made available at the point of placement. Therefore, features such as cold junction compensation (CJC), filtering, shunt calibration, and transducer excitation must all be accessible from, and integrated into, the remote instrumentation.

A thermocouple—one of the most commonly used temperature measurement devices—generates a low-level voltage known as the thermal electromotive force when two dissimilar metals are placed in contact with one another. This voltage is in the microvolt-level range. For example, a Type K thermocouple will generate 39 µV at 1°C with a F.S. operational range of ~60 mV.

Gain stages are used to ensure that the signal is amplified to a level where small changes in temperature can be resolved. A gain of 100 would amplify a 1200°C Type K thermocouple (48.838 mV) input to a level of 4.8838 V. Without the necessary gain stages, the measured signal will have significantly lower resolution and be more susceptible to noise fluctuations.

Microvolt-level signals are also very susceptible to the effects of 60 Hz interference. Therefore, instrumentation must employ techniques to minimize the effects of 60 Hz interference on the measured signal. This is particularly important in industrial environments where the thermocouple is exposed to significant electrical noise from motors, generators, welding devices, lighting, and other sources.

Many thermocouple measurement devices, such as DMM-based systems, provide some level of programmable 60 Hz rejection. However, this bandwidth limiting is achieved through the setting of the ADC integration rate. Specifically, 60 Hz rejection is improved by integrating over an integer number of power line cycles (PLCs). This approach may reduce the effects of 60 Hz noise, but it also results in substantially slower sampling rates.

Less-accurate PC-based relay multiplexer devices typically do not offer any analog filtering and rely on averaging or other software techniques to manipulate data. This can present difficulties when accurate, clean data are required across the measurement spectrum. External filtering circuits may become necessary to improve signal integrity, providing lower noise but increasing system cost and complexity.

Leading instrumentation designers do not rely on the ADC to provide bandwidth limiting, nor do they rely on software oversampling and averaging techniques. Instead, bandwidth limiting occurs in each channel's signal conditioning path, which permits the channel to be independently set to a specific cutoff frequency.

A flexible approach allows for multiple cutoff frequency ranges that typically span between 4 Hz and 1 kHz bandwidth. For many thermocouple and low-level voltage measurements, 4 Hz is a suitable cutoff frequency since it maximizes the 60 Hz rejection. However, there are instances when multiple cutoff frequency selections are useful. Higher cutoff frequency selections work well for fine-gauge thermocouples and high-speed voltage measurements (Figure 2).

 

Click for larger image Figure 2. Individual signal path and filtering  (Click image for larger version)

The CJC circuit is at the heart of any truly accurate thermocouple measurement instrument. Even an isothermal block with significant thermal mass will slowly change temperature in phase with its surroundings. Therefore, measurement errors are guaranteed if these effects are underestimated or incorrectly addressed, especially when the instrumentation is distributed.

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Figure 3. CJC isothermal interface

The accuracy of a typical multiplexer PC card and DMM-based system is about 1.0°C–1.5°C. Factors that may reduce accuracy include low thermal mass isothermal blocks, incorrect/insufficient CJC sensor placement, and terminal blocks located too close to adjacent heat sources such as power supplies and displays. Poorly designed CJC sensor circuits and input-to-CJC thermal coupling mechanisms can also cause errors.

Precision temperature measurement instruments incorporate multiple high-precision CJC mechanisms, significant thermal mass, careful placement of parts that generate internal temperature gradients, and self-calibration. The CJC sensor is typically a precision thermistor that can be located at strategic points on the isothermal block. Higher channel count systems will also incorporate multiple isothermal blocks (with additional thermistors) to eliminate gradients at different connection points (Figure 3). Considering these factors, a system-level measurement accuracy of 0.2°C–0.4°C is possible.

Many of the issues affecting thermocouple measurements also impact distributed bridge measurements. Unlike thermocouples that generate a voltage based on a dissimilar metal junction, bridge devices require excitation sources, bridge completion resistors, and shunt calibration capabilities.

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Figure 4. Shunt calibration calculation where R = resistance, V = voltage, Gf = gauge factor, L = length, and ε = microstrain

Test engineers must be able to remotely access and program a distributed measurement instrument to perform shunt calibration or modify the type of bridge completion required without sending a technician to each location. Shunt calibration can provide the user with a high degree of confidence relative to the integrity of the transducer and associated cabling (Figure 4).

Ensuring that the excitation voltage is accurate is another key to obtaining valid strain measurements. A comprehensive system will incorporate built-in excitation and provide independent ADC circuitry to measure its voltage. Conversion to microstrains (ε) is then accomplished by using the actual measured value at the transducer, resulting in more accurate measurements.

Conclusions
Distributed DA implementations can greatly simplify the end user's installation and maintenance and provide savings in time and material. For accurate distributed measurements, instrumentation designers must include key functionality such as internal signal conditioning, self-calibration, excitation, and noise rejection.

Developing instrumentation with communication interfaces based on the Ethernet-based LXI standard will also ensure that Ethernet connectivity and performance are not compromised. Solutions must adhere to the LXI Class A hardware Trigger Bus requirements to provide the necessary synchronization and timing functionality. This approach establishes reliable time correlation between thousands of distributed channels with tremendous architectural flexibility.






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