Keys to achieving high accuracy and reliability in temperature measurement
The final result of your temperature measurement will depend on the interaction of all the devices and connections between the sensor and control system.
Temperature is the most widely measured variable in process industries and is often a critical factor in industrial processing. If a temperature measurement is not accurate, repeatable, and reliable for any reason, it can have a detrimental effect on such things as process efficiency, energy consumption, product quality, and possibly process safety.
Even a small measurement error can be disruptive or very costly in some processes. Pharmaceutical processing is an example where an inaccurate temperature measurement might ruin a batch of product worth hundreds of thousands of dollars. Another example is in a safety loop where poor performance could be costly, deadly, or both. An example might be a process that can go exothermic and possibly explode if temperature is not measured and controlled accurately. These examples emphasize that each measurement system needs to be evaluated carefully and engineered to satisfy the requirements of the process.
Links in the measurement chain
Measurements are typically made using a sensor, usually a TC (thermocouple) or an RTD (resistance temperature detector), and a signal conditioning circuit (either a transmitter or a channel of an input card to a DCS or PLC) to amplify the sensor’s low level (ohm or mV) signal to a more robust 4-20 mA current signal. These components, when combined with a field connection head and thermowell, are referred to as a temperature measurement system or assembly. Articles in this series have considered these individually, but now it’s important to consider the larger integration.
Systems are available to meet a variety of measurement accuracy and stability requirements. Some applications just look at trends, and absolute accuracy is not very important. On the other hand, others may have huge financial impact due to temperature measurement errors. Examples include off-spec production that may require reprocessing, a nuisance process shut down requiring an expensive process restart, reduced production rates, and frequent recalibration costs.
As an insight, the accuracy potential of a high-accuracy system is orders of magnitude more accurate than a loosely designed system. Over- or under-design of your system could be a very expensive oversight.
Determine system requirements
To the new or inexperienced engineer it may seem like a daunting task to select the proper temperature measurement system for an application. To design a reliable temperature measurement system, a series of questions needs to be answered to understand the application thoroughly. As a result of this, the best choice of system components can be made including the thermowell, sensor, and signal conditioning device. Performance requirements of the measurement must also be determined. Operating conditions during start-up, steady-state, and potential abnormal conditions must all be considered.
As with any task, a logical and methodical approach usually begins with understanding the performance and physical requirements of the measurement application:
- Review process P&IDs
- Compare diagrams to the actual installation
- Evaluate possible mounting locations
- Consult with process, mechanical, and environmental engineers during the component selection, and
- Plan scope and schedule with project managers.
This kind of method will usually lead to the best path to follow for a well-engineered solution.
Identify measurement performance factors
Temperature measurement system performance is influenced by a number of factors in reporting process temperature measurements. The most significant of these are defined and explained below.
Accuracy of a temperature measurement system is the degree of closeness of the measurement of a temperature to that temperature's actual (true) value.
Repeatability of a measurement system, also called precision, is the degree to which repeated measurements under unchanged conditions show the same results. As an example, an instrument could present the same value for temperature every time (under the same measurement conditions), but the value is offset from the correct value. This is repeatable but not accurate. An ideal measurement is both accurate and repeatable (Figure 1).
Stability refers to the transmitter’s ability to avoid drift in order to maintain accuracy over time. It is related to the sensor’s measurement signal, which can be influenced by humidity and prolonged exposure to elevated temperatures. Stability is maintained by using reference elements in the transmitter, against which the sensor input is compared. The leading transmitter manufacturers, to improve accuracy and stability, fully characterize every transmitter over its entire temperature range to compensate for the temperature-dependency of the digital-to-analog converter (D/A) and the analog-to-digital converter (A/D).
Stability of a transmitter is often stated in terms of percent of the reading or the expected maximum change in measured temperature in degrees C or F over a specified amount of time for each sensor type. Data is typically given in year intervals such as one, two, or five years. Typical examples from a high-end transmitter are:
- RTDs: ± 0.25% of reading, or ± 0.25 °C (0.45 °F) for five years, whichever is greater.
- TCs: ± 0.5% of reading, or ± 0.5 °C (0.9 °F) for five years, whichever is greater.
The stability specifications here refer to the transmitter performance and do not include the sensor itself. A well-made RTD is generally considered to be highly stable and will not degrade significantly over time. However, even a well-made TC will degrade measurably over time and much more quickly at high temperatures.
The critical lesson from all this discussion is that your design must recognize the performance of the entire measurement system, not just the transmitter or sensor. One way to quantify the stack-up of errors is to use a total probable error (TPE) calculation. This analyzes the probable error of the transmitter and sensor system, based on anticipated installation conditions. The components of this calculation include the root sum square of the transmitter and sensor accuracy effects (Figure 2).
Durability and reliability create confidence
It is reasonable to assume that a durable device or system will be reliable. You can depend on it to perform its intended function. Just as you would expect a durable battery in your car to reliably start the engine and run the accessories under all reasonable conditions, you would expect a durable temperature measurement system to perform under its specified conditions. Confidence is built upon a history of reliable performance.
In designing a temperature measurement system, each component should be selected to provide the reliability demanded of an application. For example, if dealing with a high-precision measurement requirement, you would not select a sensor that has an excessive drift expectation. If your environment is electrically noisy, you would not use a transmitter that did not offer intelligent filtering capability. Likewise, in a high-velocity flow application, you would not select a thermowell without performing wake frequency calculations. The common element is that you must understand the process to know what the most critical requirements are.