Instrument and method for measuring ice accretion in mixed-phase cloud conditions

Abstract The ICEMET-sensor is a novel cloud droplet and particle imaging instrument which measures icing conditions by determining the number and sizes of the supercooled droplets in a known air volume. The sensor captures digital holograms from 0.5 cm 3 sample volume with a maximum rate of 3.0 cm 3 /s. This lensless imaging instrument uses a computational imaging method to reconstruct the shadow images of the objects in the measurement volume. The size, position and shape descriptors of the individual particles and droplets are calculated and saved into a database. This data can be used to separate between cloud droplets and other particles. The calculated features are used to determine the two essential parameters needed for ice accretion modeling according to the ISO 12494 icing standard: liquid water content (LWC) of the air and median volume diameter (MVD) of the droplets. The basic working principle of the sensor and the image processing method are described. The performance of the sensor was tested in a wind tunnel under mixed-phase icing conditions. The measured LWC and MVD values were used to model ice accretion using the ISO 12494 icing standard for rotating cylinders. The modeled ice accretions were compared with weighed ice masses obtained from the wind tunnel with the same sized cylinder. The results show that accurate droplet size measurement and separation between droplets and ice crystals are essential for estimating the ice accretion rate properly. Without filtering out the ice crystals, the calculated accretion rates were overestimated by 65.6 % on average

Study of the aerodynamic sampling effects of a holographic cloud droplet instrument

Abstract Computational fluid dynamics and particle tracing simulations are presented for a cloud droplet sensor. Airspeeds and streamlines around the sensor are calculated at several wind speeds and their effect on the droplet sampling are examined. Particle tracing is used to study the effect of different wind speeds and droplet sizes on the sampling of the cloud droplets. Simulated droplet concentrations are confirmed by comparing them with measured wind tunnel data. Results demonstrate clear sampling effects that are functions of both wind speed and droplet size. Optimal compromise between maximal measurement volume and sampling effects is found and a simple approximation for sensor’s sampling bias is presented. The results show that CFD simulations can give valuable information about the sampling of droplets in an ideal environment with known droplet concentrations. Even in a wind tunnel, the true test conditions are often impossible to accurately determine. Thus by simulating the sampling effects in different conditions, the sensor can be calibrated for a wide range of naturally occurring cloud conditions

Droplet size distribution and liquid water content monitoring in icing conditions with the ICEMET sensor

Abstract Field measurement results from a novel optical cloud droplet monitoring sensor designed for icing conditions monitoring are presented. The sensor has been demonstrated at two sites in northern Finland; first at Global Atmosphere Watch Station in Pallas together with a reference icing sensor and secondly mounted on a wind turbine nacelle in eastern Finland in 2017. Test runs in an icing wind tunnel have been made where more severe icing conditions were generated. The ICEMET sensor measurement principle is based on capturing the images of cloud droplets and ice particles. Droplet properties, such as droplet size distribution (DSD) and median volume diameter (MVD), are acquired by means of image analysis of the captured images. The images and the calculated features (size, location, shape descriptors) of all the found particles are saved in a database. A volume of 0.5 cm³ is imaged in a single frame. The liquid water content (LWC) is calculated based on this known sample volume in combination with the droplet data acquired from the image analysis of the found and filtered particles (droplets only). The sensor is typically freely rotating — it aligns itself against the wind by a wing on the backside. In the rotating configuration, the maximum sampling rate is 3 cm³/s. The movement of the particles inside sample volume is frozen in the images by a nanosecond scale light flash, making the sample volume independent of the wind speed. The maximum wind speed tested in a wind tunnel with the sensor is 40 m/s. The cloud droplet sizes from 5 to 200 microns are measured by the ICEMET sensor. In this paper LWC and MVD measurement results from the field tests and the wind tunnel tests with the sensor are presented and discussed. The webpages for the sensor can be found at https://www.oulu.fi/icemet

Measuring atmospheric icing rate in mixed-phase clouds using filtered particle data

Abstract In-cloud icing of objects is caused by supercooled microscopic water droplets carried by the wind. To estimate the icing rate of objects in such conditions, the liquid water content (LWC) of the icing cloud and the median volume diameter (MVD) of the droplets are measured. Mixed-phase clouds also contain ice crystals that must be ruled out in order to avoid the overestimation of the icing rate. Typically, cloud droplet instruments are not able to do this. A particle imaging instrument icing condition evaluation method (ICEMET) was used to observe in-cloud icing conditions. This lensless device uses a computational imaging method to reconstruct the shadow images of the microscopic objects. The size, position, and shape descriptors of each particle are measured. These data are then used to filter out the ice crystals. The droplet size distribution and the size of the measurement volume are used to determine the LWC and MVD. The performance of the instrument was tested under mixed-phase icing conditions in a wind tunnel and on a wind turbine. The measured LWC and MVD values were used to model the ice accretion on a cylinder-shaped object according to the ISO 12494:2017 icing standard. In the wind tunnel, the modeled ice mass was compared with the weighed ice mass collected by a cylinder. According to our results, ice accretion rates were overestimated by 65.6% on average without filtering out the ice crystals. Thus, the ability to distinguish between droplets and ice crystals is essential for estimating the icing rate properly

Weighing cylinder instrument with controlled de-icing for ice accretion measurements

Abstract Ice collecting cylinders are widely used in atmospheric icing measurements to predict the amount of ice collected by various structures in an icing environment. The mass of the accreted ice on the surface of cylinders and other object shapes can be modelled using ISO12494:2017 standard Atmospheric icing of structures which links atmospheric parameters and various object shapes. Reliable measurement of the icing conditions (icing rate) assumes an ideal cylinder-shaped surface with a fixed diameter meaning that the accreted ice layer during the measurement should be thin and free of inconsistency in ice accretion. Thus, any accreted ice should be removed before starting the measurement and the weighing sensor has to be sensitive enough to accurately measure ice loads of few tens of grams. A novel rotating cylinder based instrument, IceMan (Ice Manager), was constructed according to the guidelines of the icing standard. Unlike the other similar devices, it has ability to remove the accreted ice before each measurement and to measure ice masses from 0 to 260 g with a reasonable uncertainty of ±1.5 g making it potentially highly suitable for the assessment of icing conditions. Agreement between the ice accretion rate measured with the IceMan instrument and the icing rate calculated using the ISO 12494:2017 standard was confirmed with field measurements. The results show good agreement within the validity range of the icing model of the standard

A rotating holographic imager for stationary cloud droplet and ice crystal measurements

Abstract An optical cloud droplet and ice crystal measurement system ICEMET (icing condition evaluation method), designed for present icing condition monitoring in field conditions, is presented. The aim in this work has been to develop a simple but precise imaging technique to measure the two often missing parameters needed in icing rate calculations caused by icing clouds—the droplet size distribution (DSD) and the liquid water content (LWC) of the air. The measurement principle of the sensor is based on lens-less digital in-line holographic imaging. Cloud droplets and ice crystals are illuminated by a short laser light pulse and the resulting hologram is digitally sampled by a digital image sensor and the digital hologram is then numerically analyzed to calculate the present DSD and LWC values. The sensor has anti-icing heating power up to 500 W and it is freely rotating by the wind for an optimal sampling direction and aerodynamics. A volume of 0.5 cm³ is sampled in each hologram and the maximum sampling rate is 3 cm³/s. Laboratory tests and simulations were made to ensure the adequate operation of the measurement sensor. Computational flow dynamics simulations showed good agreement with droplet concentration distributions measured from an icing wind tunnel. The anti-icing heating of the sensor kept the sensor operational even in severe icing conditions; the most severe test conditions were the temperature − 15 °C, wind speed 20 m/s and the LWC 0.185 g/m³. The verification measurements made using NIST traceable monodisperse particle standard glass spheres showed that the ICEMET sensor measurement median diameter 25.54 µm matched well with 25.60 µm ± 0.70 µm diameter confidence level given by the manufacturer

Multipoint Raman spectrometer based on a time-resolved CMOS SPAD sensor

Abstract The potential of in-line Raman spectrometers for process monitoring applications has been shown for many industrial processes, but in most cases, only one measurement point has been monitored by one spectrometer. In this letter, we describe and demonstrate a novel, time-resolved method for measuring Raman spectra and fluorescence lifetimes from multiple points using a single excitation source and a single spectrometer. This technique is based on a combination of a time-resolved CMOS SPAD (single-photon avalanche diode) line sensor and a fitting optical light guiding system. The line sensor is designed to make multiple individual measurements at intervals of tens of nanoseconds and the optical light guiding system, in turn, produces matching temporal differences for optical signals from different measurement points. Thereby, signals from different points are distinguished in the time domain. A combined Raman and fluorescence lifetime monitoring of two measurement points was demonstrated with an oil-ethanol emulsion sample

Compensation of aerodynamic sampling effects of a cloud droplet instrument

Abstract Precise sampling is a crucial part of the aerosol measurement processes that ideally requires perfectly isokinetic conditions in which particles in the sampling volume move exactly the same way as they would in an undisturbed flow. Such conditions might be difficult to achieve in practical measurement situations where the direction and speed of the air stream may change continuously. We propose a novel method avoiding sampling errors due to moderately disturbed particle flow in case of an imaging cloud droplet instrument. It is shown that despite the non-isokinetic and non-isoaxial conditions accurate droplet density can be obtained by rejecting part of the measurement volume in post processing. The adjustment of the sampling volume is easily applied using a holographic imaging method, which offers multiple well-defined image planes to accurately set the boundaries of the sampling volume. To verify the hypothesis, aerodynamic sampling effects of a holographic cloud droplet instrument are studied using computational fluid dynamics (CFD) and particle tracing simulations and by comparing them with wind tunnel experiments. We found out that changes in the airflow affected the particle density mostly near the walls of the probe. It was observed that the error in droplet density could be kept under 10 % by limiting the cross-channel depth of the measurement volume to two-thirds of the full wall-to-wall distance. Further improvement was achieved by using simulation results to formulate a relation between sampled and ambient droplet concentration as a function of droplet diameter and air speed. Less than 1 % deviation in droplet density was achieved in this case compared to simulated values. Orientation of the instrument’s inlet relative to the direction of airflow was found out to have the strongest effect on the achievable accuracy. Results show that the droplets can be reliably sampled also in a non-isoaxial case if the measurement volume was further reduced. Reasonable accuracy was achieved with 10-degree deviation within limited air speed and droplet diameter range

Can health kiosks be used to identify oral health care needs?:a pilot study

Abstract Objective: The aim of this study was to investigate the reliability of digital imaging for detecting restorative treatment need among individuals in their 20s by comparing the outcome of digital imaging with clinical caries findings at the patient level. Material and methods: Five intraoral clinical daylight and digital fluorescence images were taken extraorally of 21 patients. A clinical examination was then performed by a trained and calibrated dentist. Additionally, the patients answered a multiple-choice questionnaire about their health habits. The images were analysed and caries findings were recorded. For statistical analysis, sensitivity and specificity were calculated. Results were shown as ROC curves and AUC values. All analyses were done using SPSS (version 24.0, Chicago, IL). Results: Caries lesions were most often detected in molars and least often in canines. When using the clinical status as gold standard, digital imaging gave an AUC value of 0.617, whereas the outcome by questionnaire gave an AUC value of 0.719. When using the combined outcome of digital imaging and the questionnaire, the AUC value was 0.694 with clinical validation. Conclusions: It can be concluded that health kiosks may help to reduce the number of patients waiting for dental treatment; more specifically, the questionnaire with individual feedback may provide a new instrument for providing instructions for homecare online. However, the camera system must be developed further, and dentists and dental hygienists require training to analyse the images