NDIR Humidity Measurement

T. Stolberg-Rohr, R. Buchner, A. Krishna, L. Munch, K. Pihl, J. S. Hansen, S. Tojaga, H.G. Moos, J. M. Jensen Danfoss IXA,

Vejle/Denmark, Thomine@danfoss.com

Abstract—Danfoss IXA is developing a multi gas sensor that utilizes NDIR spectroscopy to simultaneously measure various gasses such as CO2 and humidity. NDIR spectroscopy is vastly ignored in commercial humidity sensing although humidity is absorbing radiation in large parts of the infrared spectrum, seemingly making it an obvious measurand for NDIR spectroscopy. The present work elaborates on the reason for this contradiction and explains why NDIR, despite all, is suitable for humidity measurements and specifically beneficial in aggressive environments where an optical approach allows for non-contact measurement which might enhance the long term stability. It is shown that the performance of the developed NDIR spectroscopy-based prototype can compete with commercially available humidity sensors in the ranges of interest for indoor climate control.

I. MOTIVATION Reliable humidity sensors are essential in many different

applications and a very large number of humidity sensors based on various technologies exists. A thorough review of different types of humidity sensors for different applications is given in [1]. Most popular are the inexpensive capacitive sensors accounting for about 75 % of the humidity detection market [2]. The capacitive sensors, which measure the relative humidity, come in many varieties based on different materials. However, they all have one major drawback in common, namely the need for physical contact between the sample and the sensing element which causes the sensors to drift considerably [3]. In the present article, we suggest non dispersive infrared (NDIR) spectroscopy for humidity measurements. An approach vastly ignored by the large industry of humidity sensing. The optical principle allows for protection of the sensing element as described by Buchner et al. [4] resulting in enhanced long term stability and thereby a more reliable measurement. This is particularly demanded in agricultural applications where the presence of NH3 and H2S are severely challenging today’s commercially available humidity sensors.

II. CHALLENGES OF THE NDIR HUMIDITY SENSOR & THE WAY AROUND THEM

When NDIR spectroscopy, a well established technology for the measurement of various gasses, is generally neglected for humidity measurements [1][2][5], despite the fact that humidity is known to absorb in very large parts of the

infrared region, it naturally has its reasons. Here we list some of the issues that could account for the disregarding of NDIR spectroscopy:

A. Cost The NDIR spectroscopy technology relies on expensive

components compared to the inexpensive capacitive sensors for which the sensing element is available down to prices of 1 €. Such affordable prices compensate partly for the unavoidable drift of the sensor elements by allowing for frequent exchange of the sensor or sensor element. However, for climate control in chicken and pig stables more reliable sensors are highly demanded. The accuracy and reliability of the humidity sensor can be directly converted into growth efficiency and energy savings as it enables a more effective climate control, ensuring optimal psycrometric conditions for the animals and reducing the energy used for warming up unnecessary intake of cold air in cold environments. Furthermore, the relative cost can be reduced by combining the humidity measurement with an NDIR CO2 measurement by which the main components can be utilized for the simultaneous measurement of humidity and CO2.

B. Preference of Relative humidity over absolute humidity There is a general preference for measuring relative

humidity (RH) rather than absolute humidity (AH) within the area of climate control. The well-being of humans, animals, bacteria, etc. is affected by the relative humidity. In [6] it was found that the productivity of laying hens can be directly related to RH. Furthermore, in many applications condensation is to be avoided and this also relates to RH. Thus there are in many indoor applications good reasons for requesting an RH humidity sensor.

The NDIR sensor, on the contrary, measures AH, which has to be converted into relative humidity in order to comply with the marked request. This calculation is strongly temperature dependent and demands an accurate temperature measurement. In section III we discuss the consequences of the required conversion in more details and argue why, what is apparently a major drawback should, in fact, count in favor for an absolute measurement of humidity.

C. Sensitivity to instability in source temperature Despite the strong presence of humidity absorption in the

infrared spectrum the integrated absorption cross section is

978-1-4244-9289-3/11/$26.00 ©2011 IEEE

Figure 1. Absorption lines of H2O (black) shown together with those of CO2(red). Data are from the HITRAN database, extracted via the spectralcalc.com homepage.

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Figure 3. Temperature dependence of the transferred error caused by an error in the temperature measurement of 0.5 ºC and 0.2 ºC. Percentage of RH reading means that at an RH of 70 %rh an error of 3 % of reading corresponds to 2.1 %rh.

Figure 2. The uncertainty in the relative humidity depends strongly on the temperature since the absolute amount of humidity that can be contained in the air depends on the temperature. If the sensor were measuring with an accuracy of 2 %rh at 18 ºC, then the accuracy at -10 ºC would be as low as 14 %rh.

not nearly as strong as that of CO2. The absorption line intensities of humidity and CO2 are shown in Fig. 1. With the optical filter setup used in the Danfoss IXA multi gas sensor, a change in the CO2 level of 150 ppm gives an order of magnitude larger change in the signal compared to a change in AH of 0.3 g/m3 (examples of requested accuracies in the marked). Thus for a similar setup, the signal to noise ratio of the humidity measurement is weaker, requiring more source intensity and/or better signal processing. Such factors add to the complexity of the system but are in general solvable. Yet, the weaker signal to noise ratio does have one critical drawback in an increased impact of instabilities in the IR-source temperature. Aging effects of the black body sources are unavoidable, and while such problems are already challenging the stability of NDIR CO2 sensors, the problem is much larger for an NDIR humidity sensor. However, rapid development in the stability of infrared sources together with a specially optimized filter setup covered by Danfoss IXA patents [8], reducing the sensitivity towards changes in the source temperature, helps overcoming this issue. The Danfoss IXA optical filter setup for humidity sensing is developed with focus on decreasing the impact from drift in source temperature and is estimated to reduce the impact by an order of magnitude compared to commercially available filters.

III. ABSOLUTE HUMIDITY VERSUS RELATIVE HUMIDITY The general preference of RH over AH implies that the

AH measured by the NDIR sensor must be converted into RH. This conversion brings with it a few temperature related challenges. First, the amount of absolute humidity (g/m3) that can be contained in the air is highly temperature dependent, i.e. at lower temperatures 1 unit of RH (%rh) corresponds to less AH (g/m3) than at higher temperatures. The consequence of this is that the achievable accuracy is correspondingly temperature dependent. Fig. 2 shows how an accuracy of 0.3 g/m3 H2O transforms into %rh at different temperatures. While it at 18 ºC corresponds to 2 %rh and to 1 %rh at 30 ºC, it is as high as 6 %rh at 0 ºC and even worse below 0 ºC. The absolute accuracy can be improved but it will always be the case that the relative humidity measurement by NDIR is significantly better at room temperature than in a freezing environment, and this will reflect on the sensor specifications. However, in many

practical applications it is of much greater importance to have reliable humidity measurements at room temperature and above than it is to measure with a high accuracy below 0 ºC. This is the case in most indoor climate control or in animal farming where the humidity must not exceed a certain level for the comfort of the animals or people and the regulation will always take place at comfortable temperatures. In pig and chicken stables the regulation temperature will not be below 15 ºC [7].

Another and more critical issue caused by the temperature dependence of the conversion between AH and RH is that uncertainties in the temperature measurement are transferred to the RH output. For this reason the temperature measurement must be extremely good. If, for instance, the temperature measurement has an error of 0.5 ºC, it will result in an error in the calculated relative humidity of more than 2 %rh (at 15 ºC and 70 %rh) simply due to temperature, leaving no room for other contributions to the inaccuracy, among these the calibration uncertainty, if the specifications are to compete with capacitive sensors. Fig.3 shows the resulting error in RH reading at different temperatures corresponding to two different temperature errors, +0.2 ºC

Figure 4. Relatively linear and well defined response to absolute humidity. The calibration curve is well-fitted with a single exponential decay, the parameters of which are almost identical from system to system allowing for a one or two point calibration.

Figure 5. Measurement result with a prototype (blue points) shown together with a commercially available sensor, Vaisala HMT330 (red line). The measurement was carried out at 26 ºC. The unfiltered resolution (3σ) is 1 %rh. At 15 ºC this corresponds to a resolution of 2 %rh. With filtering we expect to get the resolution down to 0.5 %rh at 15.

and +0.5 ºC. Also in this case, the error becomes larger at lower temperature.

While these temperature issues appears to possess a strong demotivation factor for employing an AH sensor for the measurement of RH, this is in fact somewhat less dubious than the common practise of measuring the RH at one position in the room, expecting it to tell the RH at another position in the room. In fact, we are going to argue that the transferred temperature error even favors the AH measurement. The reason for this is that the RH varies significantly over the room as the temperature varies. A study of spatial temperature and RH variations in broiler houses with different ventilation systems is given in [9]. In tunnel houses vertical temperature gradients up to 4.1ºC were reported. If, for example, the relative humidity is desired in the surroundings of a flock of pigs or chickens but is measured 2 m above their heads, the measurement must be adjusted due to thermal gradients. This adjustment invokes a double temperature error because the conversion of RH at one position and temperature to RH at another position and temperature includes both temperatures in the calculation. Instead, it is possible to measure the AH 2 m above the animals and expect it to be representative for the AH humidity next to the animal, since the water vapour diffusion rate is very fast and the AH can be considered stable. The RH humidity can then be calculated in critical positions where the temperature is measured. In this way one AH sensor and a number of temperature sensors provide a better measure of the relative humidity in several critical areas than can be obtained with a limited number of RH sensors.

In addition, RH sensors typically measures in an air sample that is let into to the sensor element. In this process the air sample is often heated due to self-heating of the sensor. The sensor thus measures the relative humidity at an elevated temperature. If the self-heating is known this artifact can be partly compensated, however, convection will unavoidably affect self-heating of the sensor and thereby the humidity measurement. An AH sensor is not similarly affected by self-heating since temperature only has a weak impact on AH.

IV. ADVANTAGES OF NDIR FOR HUMIDITY SENSING

A. Non intrusive measurement. The optical approach of NDIR spectroscopy allows for

separation between the sensing element and the sample. In other words the sensing element as well as the emitter can be placed behind a sight glass with desired optical properties, chemical resistance, and potentially self cleaning functionality. With additionally hermitically sealing of the sensor compartment no optical components except for the chemical resistant sight glasses are in contact with the corrosive environment. This idea was already presented in [4]

B. Ultra fast response time The complete optical system, including heating of a

black body emitter, emission of infrared radiation, absorption of radiation by humidity molecules and detection of radiation

takes below 100 ms. No chemical reaction is involved. The response time of the sensor is thus solely limited by the sampling- routine and frequency.

C. Linear and well defined response The NDIR humidity sensor has a comparably linear and

very well defined response to AH. The response function of the sensor is well-fitted to a single exponential decay with parameters that a very similar from sensor to sensor, allowing for a one or two point calibration. The calibration curve is sown in Fig. 4.

V. RESULTS In Fig. 5 measurement results of an NDIR humidity

sensor prototype are shown together with a commercially available sensor, Vaisala HMT330. The unfiltered resolution (3σ) with this prototype is 1 %rh at 26 ºC. Further improvements on resolution and stability are already incorporated in a pre-product currently in production.

ACKNOWLEDGMENT The authors thank SKOV A/S for corporation in the

development of the multi gas sensor and insight into the agricultural environment.

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[4] R. Buchner et al., “A new Gas Sensor Concept for Optimisation of Environment and Energy Efficiency in Harsh Environments”, COMS2009 Copenhagen, Denmark, 2009.

[5] D. K. Roveti, “Choosing a Humidity Sensor: A Review of Three Technologies”, Sensors Magazine, July 01, 2001

[6] B. Kocaman, N. Esenbuga, A. Yildiz, E. Laçin and M. Macit, “Effect of environmental conditions in poultry houses on the performance of laying hens”, International Journal of Poultry Science 5 (1): 26-30, 2006

[7] A. Donkoh, “Ambient temperature: a factor affecting performance and physiological response in broiler chickens”, Int J Biometeorol (1989) 33: 250-265

[8] J. M. Jensen, M. Y. Benslimane, “IR sensor, especially a CO2 sensor”, United States Patent 7635845

[9] H. Xin, I. L. Berry, G. T. Tabler, T.L. Barton, “Temperature and Humidity Profiles of Broiler Houses with Experimental Conventional and Tunnel Ventilation Systems”, Applied Engineering in Agriculture, Vol. 10(4), 535-542, 1994