Temperature Sensor Troubleshooting Tools
It is understandable why infrared temperature sensors are difficult to troubleshoot. The fact that a sensor can make a remote temperature reading is, in itself, a difficult concept to accept.The added complexities associated with emissivity, reflectivity and optical alignment can intimidate even the most experienced plant engineers. Clearly, troubleshooting tools are required. A user must be able to confirm when the system is operating correctly and identify potential problems when it is not.
Potential interference sources for infrared temperature sensors include:
- Ambient temperature extremes.
- Stray reflected infrared energy.
- Emissivity variation.
- Dirty optics.
- Intervening optical obstructions.
In the absence of feedback and a clear understanding of how each type of interference affects a sensor reading, it is nearly impossible to verify proper operation or troubleshoot problems. Some infrared temperature sensor designs are capable of providing users with the feedback required to simplify installation, verify performance and troubleshoot failures. In addition to the target temperature, some infrared temperature sensors report parameters such as:
- Ambient temperature.
- Signal strength (a measure of emissivity).
- Signal dilution (a measure of the signal-to-noise ratio).
- Filtered temperature.
- Unfiltered temperature.
Historically, these parameters only have been available off-line, preventing their use as troubleshooting tools. Advances in microprocessor technology and implementation of intuitive user interfaces have made possible the inclusion of these parameters as a standard feature. By monitoring additional information, plant personnel can confirm proper sensor operation and identify measurement error sources.
Ambient Temperature. Most infrared temperature sensors have an upper am-bient limit of 120 to 140oF (50 to 60oC). If sensor temperature exceeds this limit, the measured value and the device's effective lifetime often are affected.
Due to their prominent use in heating applications, infrared temperature sensors frequently operate in conditions near or above their ambient temperature limit. Without any ambient temperature feedback, users may be unaware that the sensor is being overheated. Fortunately, some sensors report the measured ambient temperature and indicate an ambient alarm condition when the sensor is above a specified limit. With ambient temperature indication, users are alerted when readings may be in error or when the useful life of the equipment may be in jeopardy. Acting on the warning, users can address the sensor's cooling system before costly damage occurs.
Conditions that can influence signal strength value include surface emissivity, alignment, optics cleanliness, ob-structed views and reflections. A deviation in signal strength from the expected or typical value indicates interference from one or more of these factors. Conversely, signal strength values that are within an acceptable range provide confidence that the sensor is generating valid temperature readings.
Ratio (two-color or dual-wavelength) and multiwavelength sensors report a signal strength value and thus the measured target's effective emissivity. This can be a powerful troubleshooting tool. For example, a particularly low signal strength value led one Midwestern finishing line operator to realize that its sensor was not aligned properly through a viewing tube. Sensor feedback indicating an exceptionally low signal strength value pointed directly to the source of the problem, saving valuable time and trouble.
Signal Dilution. Signal dilution is a type of signal-to-noise measurement available on some ratio and multiwavelength sensors. A sensor indicating a signal dilution value of 60:1 is measuring 60 times more infrared energy than is required to make a valid reading. For some applications, especially those involving heavy dust, smoke, steam, dirty optics or difficult alignment, a low signal dilution value can serve as an early warning system to alert plant personnel of a potential optical attenuation problem before sensor performance becomes affected. In addition to acting as a troubleshooting aid, the signal dilution value also may be used to optimize sensor placement and alignment during installation.
For example, a Midwest steel mill was able to use the signal dilution value to optimize the installation location for a sensor measuring a stream of molten iron. The iron stream generates heavy smoke and dust when poured into a large ladle. The signal strength value was used as a quantitative measure for determining the best mounting location for viewing through the interference.
Filtered and Unfiltered Measured Temperature. Filtered temperature value is the sensor reading with the selected signal conditioning filters applied. A separate unfiltered value allows the user to monitor the unconditioned sensor data. This feature allows the user to view the raw sensor signal while the filtered signal continues to control the process. An exceptional change in the unfiltered sensor reading tends to indicate interference. By observing the timing of an intermittent interference, it usually is possible to identify the interference source and make the appropriate adjustments to the sensor setup.
Sensor feedback is critical for efficient optimization and troubleshooting of infrared temperature sensors. Hours of frustration and confusion can be avoided with the availability of the right information at the right time. A troubleshooting checklist that includes ambient temperature, signal strength, signal dilution, filtered temperature values and unfiltered temperature values provides the information required to quickly verify accurate sensor operation and troubleshoot problems when they occur.