Cold Regions Science and Technology 46 (2006) 125 – 131 www.elsevier.com/locate/coldregions
Ice sensors for wind turbines Matthew C. Homola ⁎, Per J. Nicklasson, Per A. Sundsbø Narvik University College, Box 385, 8505 Narvik, Norway Received 30 December 2005; accepted 22 June 2006
Abstract A review of ice sensor technology and the challenges for icing detection for wind turbines was performed. A total of 29 different methods for detection of icing were found, and these were then compared with a list of some basic requirements for an icing sensor for wind turbine applications. No reports of ice sensors performing satisfactorily were found, but the sensing methods using infrared spectroscopy through fiber optic cables, a flexible resonating diaphragm, ultrasound from inside the blade or a capacitance, inductance or impedance based sensor seem best suited for wind turbine icing detection. © 2006 Elsevier B.V. All rights reserved. Keywords: Ice; Icing; Ice accretion; Glaze; Rime; Atmospheric ice; Wind turbine
1. Introduction Often the best locations for wind turbines are in exposed locations where they are subject to icing of the blades. Icing of wind turbine blades can cause a variety of problems, such as; complete loss of production (Ronsten, 2004), reduction of power due to disrupted aerodynamics (Jasinski et al., 1998), overloading due to delayed stall (Jasinski et al., 1998), increased fatigue of components due to imbalance in the ice load (Ganander and Ronsten, 2003), and damage or harm caused by uncontrolled shedding of large ice chunks (Seifert, 2003). Methods of deicing the blades have been shown to work effectively, but the ice sensors used in the control systems have not reliably detected the onset of icing. The objectives of this paper were to research ⁎ Corresponding author. Fax: +47 76 96 68 10. E-mail addresses:
[email protected] (M.C. Homola),
[email protected] (P.J. Nicklasson),
[email protected] (P.A. Sundsbø). 0165-232X/$ - see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.coldregions.2006.06.005
methods of ice detection and propose a sensor that overcomes the shortcomings of previously tested icing sensors. 2. The icing problem As mentioned in the introduction, icing causes a variety of problems for wind turbines. In the case of extreme icing it may not be possible to start the turbine, due to changed aerodynamics of the blades, with subsequent loss of all possible production for quite long periods of time. One example of this is described by Ronsten (2004), where a turbine in southern Sweden was stopped for over 7 weeks during the best operating period because of icing. In addition, the buildup of ice on the blades of the turbine disturbs the aerodynamics, which can either reduce the amount of power produced or overload the turbine if it is stall regulated (Jasinski et al., 1998). The increased fatigue loads on all components of a wind turbine operating with an unbalanced ice load on the blades has been presented as a problem
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(Ganander and Ronsten, 2003) where the effects are difficult to predict due to general lack of knowledge regarding the intensity and duration of icing events. The last problem from icing does not concern the wind turbine itself, but is the risk posed by uncontrolled shedding of ice chunks. These are of special danger to service personnel, but may also affect public acceptance towards wind power if the danger requires fencing off large areas around the wind turbines. Measures to prevent icing have been used, and have been shown to work effectively (Peltola et al., 2003; LM Glasfiber, 2004; Kimura et al., 2004; Horbaty, 2005). In addition, Botura and Fisher (2003) and Battisti (2004, 2005) have presented new methods for deicing. With all of the methods that do not operate continuously it has pointed out the need for a reliable icing detector to activate the deicing system. Various sensors have been tested, but have not performed satisfactorily. To understand why this occurred, the mechanisms of icing were studied. 3. Causes of icing Two main types of atmospheric ice accumulation are traditionally defined, in-cloud icing and precipitation icing (ISO 12494, 2001). The main icing mechanisms of interest for wind turbine applications are as follows: 1) In-cloud icing a) Rime i) Hard rime ii) Soft rime b) Glaze1 2) Precipitation icing a) Wet snow b) Freezing rain In-cloud icing occurs when small, supercooled, airborne water droplets, which make up clouds and fog, freeze upon impacting a surface which allows formation of ice. These water droplets can remain liquid in the air at temperatures down to − 35 °C (Mason, 1971, p.155) due to their small size, but will freeze upon striking a surface which provides a crystallization site. The different types of rime and glaze are formed depending on the droplet sizes and the energy balance of the surface in question. For small droplets with almost 1 It should be noted that in North America glaze is generally considered to result from freezing rain. Here the definition of glaze from ISO 12494 is used.
instantaneous freezing, soft rime forms. With medium sized droplets and slightly slower freezing, hard rime forms. If the buildup of rime is such that a layer of liquid water is present on the surface during freezing, glaze forms. Precipitation icing is due to rain or snow freezing on contact with a surface. Precipitation icing can have much higher rates of mass accumulation than in-cloud icing, with possibly greater resulting damage. Relative frequency for the two types of icing is dependent on geographic location and climate. Wet snow can stick to surfaces when in the temperature range of 0–3 °C, while freezing rain requires surface temperatures below 0 °C. A physical model for icing is described by Eq. (3.1), as detailed by Makkonen (1994 p.53) and in ISO 12494 (2001). dM ¼ a1 da2 da3 dwdvdA dt
ð3:1Þ
Where A is the cross sectional area of the object with respect to the direction of the particle velocity vector, w is the mass concentration of the particles, v is the relative velocity of the particles and the α terms are correction factors with values in the range 0.0–1.0. The collection efficiency (or collision efficiency), α1, represents the flux density of particles striking the surface in relation to the maximum possible. The sticking efficiency, α2, represents the ratio of the flux density of particles sticking to the surface to the flux density of the particles striking the surface. The accretion efficiency, α3, represents the rate at which ice builds up on the surface in relation to the flux density of particles sticking to the surface. 4. Methods of detection Icing can be detected either directly or indirectly. The direct methods detect some property change caused by the accretion of ice. These include mass, reflective properties, electrical or thermal conductivity, dielectric coefficient and inductance. The indirect methods are based upon detecting the weather conditions that lead to icing, such as humidity and temperature, or detecting the effects of icing, such as a reduction in power production. They then use a model, either empirical or deterministic, to determine when icing is occurring. The methods found for detection of ice are listed here. Though the sensor types have many references associated with them, the references listed for each type here are not meant to be exhaustive but focus on those that describe the measurement principles. In addition, the trade name
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or name of the manufacturing company is included where possible.
d) Frequency of generated noise (Seifert, 2003) e) Change in blade resonant frequency
1) Direct detection a) Damping of ultrasonic waves in a wire, Labko (Luukkala, 1995) b) Damping of ultrasonic waves on the wing surface (Chamuel, 1984; Watkins et al., 1986) c) Inductance change (Lee and Seegmiller, 1996) d) Impedance change (Wallace et al., 2002) e) Capacitance change, IDI (Geraldi et al., 1996) f) Temperature rise with heat (Maatuk, 2004) g) Temperature curves when heat is applied to small areas (Lardiere and Wells, 1998) h) Resonant frequency of a probe — magnetostriction, Goodrich, formerly Rosemount (Cronin et al., 2001; Goodrich 2002a,b,c,d) i) Resonant frequency of a probe — piezoelectric, Vibro-Meter (Vibro-Meter, 2005) j) Microwave waveguide (Magenheim, 1977) k) Reflected light from inside (Fedrow and Silverman, 1994; Noack, 1998; Kim, 1998) l) Fiber optic cable with special clad (Klainer and Milanovich, 1990) m) Flexible diaphragm (DeAnna, 1999) n) Mechanical resistance to piezoelectric expansion (Goldberg and Lardiere, 1993) o) Piezoelectric pressure sensor to detect ice and turbulence (Gerardi et al., 1993) p) Reflection of polarized infrared light, Goodrich (Goodrich, 2001e) q) Infrared spectroscopy, Infralytic (Infralytic, 2005) r) Ice blocking an exit hole is detected (Khurgin, 1989; Pettler and Roberts, 1998) s) Reflective light sensor, HoloOptics (Westerlund, 2004) t) Stereo imaging from web cameras (Seifert, 2003) u) Ultrasound system from inside the blade (Hansman and Kirby, 1986) v) Surface impedance and temperature, Instrumar (Chan, 2005) w) Ice collecting cylinder, AerotechTelub (AerotechTelub, 2005) x) Surface acoustic wave sensor (SAW) (Galipeau, 2005) 2) Indirect detection a) Dew point and temperature (Makkonen et al., 2005) b) Actual power output vs. predicted from wind speed c) Anemometers with and without heating (Craig and Craig, 1995)
5. Some basic requirements for successful detection Detection of icing on wind turbines has different requirements than detection of icing on aircraft or for meteorological purposes. This is evident when sensors designed for other purposes do not perform adequately when mounted on wind turbines. The best position for the detection of icing on a wind turbine is on the blade itself, and as close to the tip as possible. This for three reasons, the first reason is based on the model for icing as described in Eq. (3.1). The rate of ice accretion is directly related to the relative velocity of the supercooled water droplets, and it is at the blade tip that the highest velocity occurs. The second reason is that the blade tips can experience icing due to low clouds even though the nacelle is ice-free. At Pori, in Finland, measurements showed the number of in-cloud icing periods at 84 m was six times the number of incloud icing periods at 62 m (Säntti et al., 2003). The third reason is that the outer ends of the blades sweep a larger volume and collect water or ice from the entire volume. An icing sensor for mounting on the blade tip of a wind turbine requires that several points be considered during the design phase. Some of the most important are, lightning protection, the difficulty in accessing the sensor in the event of failure, and the problems associated with mounting a sensor on the flexing material of the blade. Though there have been problems with attaching wires or cable to wind turbine blades, it is now common for blades to have lightning protection cables and collectors integrated and an additional set of wires to a sensor may be no more difficult to integrate or prone to breakage than the lightning protection. Alternatively the sensor can be a wireless unit for retrofitting of existing wind turbines. In spite of the difficulties associated with mounting a sensor on the blade, it can be assumed that as the length of the blades used on wind turbines increase, it will be more and more necessary that the detection of icing takes place on the tips of the blades themselves, and not on the nacelle both because of higher rates of accretion on the blade tips, and because the blade tips are more likely to reach low clouds. Therefore comparison of the sensors was based on the requirement that sensing must occur on the blade. A high sensitivity sensor is required for several reasons. The first is that deicing by heating of the blades requires a much higher heating power if the airflow over
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the blade changes from laminar flow to turbulent flow, due to the increased heat removal by the turbulent air (Makkonen et al., 2001). Secondly, a large safety risk from ice cast is already present with the accumulation of 1–2 cm of ice on the leading edge. Thirdly, power production from the wind turbine is reduced already with the formation of surface roughness, with corresponding loss of income. A fourth requirement for wind turbine icing sensors is the ability to detect ice over a large area. There are several reasons for this. The first is that ice accumulation does not always occur in the same locations on the blade, but the location varies depending on the mechanism of ice accumulation. Glaze icing can occur over large areas of the blade, with water running back and freezing away from the leading edge. Rime icing generally occurs on the leading edge, around the stagnation point, but the exact location can vary depending on the angle of attack. Also, accumulated ice can be shed from the blades. This can result in some areas of the blade having little or no ice while other areas have large accumulations present. These indicate that an ice sensor for wind turbines should be able to detect ice at more than one or two points. 6. Method analysis 6.1. Unsuitable methods The following methods have some apparent disadvantages that make them less suited for detection of icing on wind turbines. Some of the sensors may be able to be modified such that they would work well for wind turbines, but the consideration of this was beyond the scope of this paper. Damping of waves on wing method (1b) seems by definition not as sensitive as desired due to the large mass difference between the blade material and a thin ice layer. The piezoelectric system monitoring the pressure on the wing (1o) was demonstrated with a 2.5 cm ice horn, which does not demonstrate the level of sensitivity needed. The temperature change methods (1f, 1g) will have trouble detecting very thin layers of ice. This is due to the fact that if the layer of ice melts through during the heating cycle the desired temperature rise will not occur. This system must also be turned on and off, and can only detect ice at the time when it is turned on. Using reflected light from an ice covered window (1k) out from the blade is a very simple idea that would probably work well for rime ice, but is expected to have difficulties with very thin layers of clear ice, for example
freezing rain. This is due to the fact that thin layers of clear ice need not disturb the optical path. The blade resonant frequency (2e) will not change until the ice layer becomes significant compared to the blade material, which means the sensitivity of these systems is too low. The methods using damping of ultrasonic waves in wire (1a), resonant frequency of a probe (1h, 1i), ice collecting cylinder (1w), dew point and temperature (2a), and two anemometers (2c), as well as the HoloOptics (1s) and Instrumar (1v) sensors all are mounted on the nacelle of the turbine, and have therefore limited applicability. In the event that they are modified such that they can be mounted on the blade tip they can be suitable. And in any case they can be applicable in the absence of a blade mounted sensor. Actual power output vs. predicted power output (2b) is a safety check which should already be implemented and a difference may have other causes than icing of the blades. Therefore this method is not considered further here. 6.2. Methods that require further examination The system using a microwave waveguide (1j) must be investigated further as it is stated that the method has a high sensitivity, but the suitability for wind turbines was not clear (Joseph et al., 2004). No documentation of sensitivity was found for the systems relying on enough ice to block an exit hole (1r) or to prevent expansion (1n). Though they may be able to perform adequately, this must be verified. A system using polarized light (1p) could be interesting since it could perhaps examine the blades from a distance. The mounting of the sensor such that the pressure side of the blade is seen requires more study, as current systems using polarized light ice detection have a range limitation of less than 30 m. Web cameras (1t) can be useful during testing of various sensors, and to record the conditions at the wind turbine, but have not yet been demonstrated to be suitable for ice detection for several reasons. In arctic regions there is little light during much of the winter, which requires artificial lighting. This artificial lighting, if in the visible spectrum, can be negative for the visual environmental impact of the wind turbine installation. The second, and perhaps more important reason is the lack of suitable automated image analysis tools, but image analysis is an area in rapid change, which may make this system viable in the near future. A system based on a surface acoustic wave (SAW) sensor (1x) can detect both ice and water as well as
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distinguish between them. These sensors have been commercially introduced for dew point detection (Vetelino et al., 1996), but could be modified for use on wind turbines. SAW waves are very sensitive to mass accretion on their surface, and would only be suitable for an icing onset sensor, as any appreciable ice accretion would completely attenuate the propagating waves. The fiber optic cable with clad (1l) would have gaps in the clad which became filled with ice. Similar types of fiber optic chemical sensors have been shown to have high sensitivities to hydrocarbons, pesticides and carbon monoxide and it has been stated that they could be designed as icing sensors. (Klainer et al., 1997). A change in the frequency of noise (2d) sounds interesting, but will require further investigation to determine how background noise and varying wind speeds affect the data.
detector and will therefore require multiple sensors and this method is not suitable for retro-fitting due to mounting on the inside of the blade. The capacitance, inductance and impedance (1c, 1d, 1e) type of measuring appear the most promising due to several factors. The sensors can detect ice formation within an area and not just one point. The sensing elements/electrodes can be very thin and conform to the blade surface, allowing retrofitting of existing wind turbines. Detection of changes of electrical properties is well known and the electronics are very light and have low power consumption. It was also found that icing sensors for airplanes are currently available which use capacitance and impedance. In addition, it may be possible to combine sensing of all three elements to give an even better indication of icing.
6.3. Suitable methods
7.1. Conclusions
The system using infrared spectroscopy (1q) has an advantage in that all electronics and serviceable components are mounted in the hub of the turbine, not on the blades. There are no extra conductors out to the blades, so no additional lightning risk is generated. The point detection is a slight disadvantage, but this can be corrected by having more points under observation. The greatest disadvantage is the difficulty in installing the system in existing blades. This is because the fiber optic cables must be installed during the construction of the blade. This system has already been built by Infralytic. This system has been independently tested in an icing wind tunnel with good results (Kimura et al., 2005). In addition, the sensor is included in the Swiss Project ‘Alpine Test Site Gütsch: Meteorological measurements and wind turbine performance analysis’ which runs within the COST 727 Action ‘measuring and forecasting atmospheric icing on structures’, which will test a variety of sensors over a three year period (Cattin, 2005). A flexible resonating diaphragm (1m) could be an effective point ice detector. The diaphragms could be produced with the correct curvature for the blade built in, and be flush-mounted. These would also have low power consumption, and perhaps could be configured to operate wirelessly. Ultrasound from inside the blade (1u) has been shown to work for measuring ice accretion on aircraft (Hansman and Kirby, 1986) with an accuracy of under 0.5 mm, and as such appears well suited for icing detection on wind turbines. This type of sensor is a point
Icing of wind turbines is a serious problem for wind power production in many areas of the world, and especially in arctic climates. The problems resulting from icing are varied, but all require that icing either be prevented or that resulting ice be removed. As indicated previously, possibly one of the most serious problems for icing of wind turbines is the risk of cast ice — ice being thrown from the blades. This may lead to regulations requiring that all turbines which can be at risk for icing have icing sensors installed, and that operation of the turbine ceases when enough ice has accreted to pose a danger to service personnel or the general public. This is one reason that highly sensitive ice detectors are needed. Though no commercial systems for deicing wind turbines under operation are available today, there is apparently, a system for deicing a stopped wind turbine by circulating hot air inside the blades (Horbaty, 2005). In addition, it appears that there are several viable alternatives, and that deicing systems will become readily available in the future. Previous research has shown that the icing sensor is often the weakest link in a deicing system, and that better icing sensors are needed. Icing is a complex phenomenon, with many different causes and types of icing. This makes the task of detection challenging. In addition accretion of icing is dependent both on the relative velocity of supercooled droplets and the height above ground level of the object in question. This makes it unlikely that detection of icing on the nacelle of a wind turbine can satisfactorily indicate the presence of ice at the blade tips of the
7. Conclusions and suggestions for further work
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turbine. This means that the best position for detection of icing on a wind turbine is on the blade itself, and as close to the tip as possible, as outlined in the earlier section Some basic requirements for successful detection. This will be more and more necessary as the length of the blades used on wind turbines increases. As it can be seen from the review of sensors which are currently available, there are no proven sensors which fulfill the needs of icing detection on wind turbines. The sensing methods that are best suited for sensors which can be mounted near the blade tips are infrared spectroscopy through fiber optic cables, a flexible resonating diaphragm, ultrasound from inside the blade and a capacitance, inductance or impedance based sensor. These sensing methods were selected because they directly measure some property of the ice itself, are sensitive to very thin layers of ice, and can be constructed with light weight or no electronics near the blade tip. Of the ice detection methods used on aircraft, the ones based on capacitance and ultrasound from within the blade seem most suitable for wind turbines. The methods based on the resonant frequency of probes have not been shown to work successfully perhaps due to either mounting on the nacelle or lower relative droplet velocities resulting in lower collection efficiencies than on aircraft. 7.2. Suggestions for further work There is yet much work to be done in the field of icing sensors for wind turbines. Several of the areas that seem to warrant the most attention are listed below. Given the need for detection at the blade tip, future work should address the difficulties associated with mounting a sensor on the blade and then getting the data from the sensor to a PC or control system. Work in this area will be relevant for almost all of the actual ice sensor types. Though mounting and testing on the nacelle is most convenient previous work has not shown that sensors on the nacelle perform satisfactorily. Alternatively, future work could concentrate on finding a way of remotely detecting ice on the blade. A capacitance based sensor system should be further developed such that a prototype can be built for testing in an icing wind tunnel. In addition, a sensor which combines capacitance, impedance and inductance should be further examined. The combination of multiple modes of sensing opens for possibilities for performing some level of cross-checking between the
sensing modes. This could increase the reliability of the sensing system as well as the sensitivity. In general, many of the methods discussed in this paper are not fully documented for the purposes of wind turbines. Further testing of these methods both in icing wind tunnels and in full scale would give a better foundation for future reviews of this type. Continuing development and exploration of sensor methods is necessary both in the event that the existing sensors are not found sufficient, and in case a better or cheaper method of detection can be developed. Development of icing sensors which can indicate ice thickness, in addition to a sensor which indicates whether ice is present or not, must continue. This is especially important for consideration of the danger of shed ice. A turbine without deicing possibilities can perhaps be used with 1 or 2 mm of accreted ice, and decreased performance, but if ice thickness increases beyond that there becomes an increasing risk of ice which may be shed from the blades, and stoppage of the turbine must be considered. References AerotechTelub, 2005. IceMonitor — The Ice load Surveillance System. http://products.saab.se/PDBWeb/PDF/productpage_ id1239_lan1.pdf, June 14, 2005. Battisti, L., 2004. Anti-icing system for wind turbines. World Intellectual Property Organization, International publication number WO 2004/036038 A1. April. Battisti, L., 2005, emailed presentation. Ice Prevention Systems for Wind Turbines. June 28. Botura, G., Fisher, K., 2003. Development of ice protection system for wind turbine applications. Proceedings of the 2003 BOREAS VI Conference. Pyhätunturi, Finland. April. Cattin, R., 2005. Posting to
[email protected] with a link to the website http://www.meteotest. ch/cost727/index.html, November 25. Chamuel, J.R., 1984. Ultrasonic Aircraft Ice Detector Using Flexural Waves. United States Patent number 4,461,178. July. Chan, M., 2005. Email May 3. Craig, D., Craig, D., 1995. An investigation of icing events on Haeckel hill. Proceedings of the 1995 BOREAS III Conference. Saariselkä, Finland. March. Cronin, D.J., Jackson, D.G., Owens, D.G., 2001. Ice Detector Configuration for Improved Ice Detection at Near Freezing Conditions. United States Patent number 6,320,511. November. DeAnna, R., 1999. Ice Detection Sensor. United States Patent number 5,886,256. March. Fedrow, H.L., Silverman, J.H., 1994. Laser Ice Detector. United States Patent number 5,296,853. March. Galipeau, D., 2005. Email February 2. Ganander, H., Ronsten, G., 2003. Design Load Aspects due to Ice Loading on Wind Turbine Blades. Proceedings of the 2003 BOREAS VI Conference. Pyhätunturi, Finland. April. Gerardi, J.J., Dahl, P.R., Hickman, G.A., 1993. Piezoelectric sensor. United States Patent number 5,191,791. March.
M.C. Homola et al. / Cold Regions Science and Technology 46 (2006) 125–131 Geraldi, J.J., Hickman, G.A., Khatkhate, A.A., Pruzan, D.A., 1996. Measuring Ice Distribution on a Surface with Attached Capacitance Electrodes. United States Patent number 5,551,288. September. Goldberg, J.I., Lardiere Jr., B.G., 1993. Expulsive Ice Detector. United States Patent number 5,272,400. December. Goodrich, 2002a. Freezing rain sensor. Brochure: 4085 LIT 03/02. Rosemount Aerospace Inc. Goodrich, 2002b. Sensor Systems: Primary and Advisory Ice Detection Systems. Brochure: 4079 LIT 03/02. Rosemount Aerospace Inc. Goodrich, 2002c. Sensor Systems: Falcon 50 Ice Detection. Brochure: 4066 LIT 06/02. Rosemount Aerospace Inc. Goodrich, 2002d. Sensor Systems: Model 0871FA Ice Detector. Brochure: 4013 LIT 03/02. Rosemount Aerospace Inc. Goodrich, 2001e. Sensor Systems: Next Generation IceHawk Wide Area Ice Detection System. Brochure: 4001 LIT 10/01. Rosemount Aerospace Inc. Hansman Jr., R.J., Kirby, M., 1986. Measurement of ice growth during simulated and natural icing conditions using ultrasonic pulse-echo techniques. Journal of Aircraft 23, 492–498. Horbaty, R., 2005. Wind energy in cold climates — The Swiss experience. Proceedings of the 2005 BOREAS VII, Saariselkä, Finland. March. Infralytic. Ice Sensor for Rotor Blades. Brochure: IcesensorInfralytic_ EN.pdf, from www.infralytic.de, accessed April 4, 2005. ISO 12494, 2001. Atmospheric Icing of structures. ISO copyright office, Geneva, Switzerland. Jasinski, W.J., Noe, S.C., Selig, M.S., Bragg, M.B., 1998. Wind turbine performance under icing conditions. Transactions of the ASME, Journal of Solar Energy Engineering, vol. 120. American Society of Mechanical Engineers, New York, NY, USA, pp. 60–65. February. Joseph, P.J., Glynn, D.P., Joseph, J.C., 2004. From www.nasatech. com/briefs/feb04/lew17135.htrml, accessed May 5, 2006. Khurgin, B., 1989. Ice Detector with Movable Feeler. United States Patent number 4,873,510. October. Kim, J.J., 1998. Fiber Optic Ice Detector. United States Patent number 5,748,091. May. Kimura, S., Furumi, K., Sato, T., Tsuboi, K., 2004 “Evaluation of antiicing coatings on the surface of wind turbine blades for the prevention of ice accretion. Proceedings of the 7th International Symposium on Cold Region Development, CD-ROM, No.63. Kimura, S., Sato, T., Freitag, H., Tammelin, B., 2005. Icing wind tunnel test for a new ice detector. Proceedings of the 2005 BOREAS VII Conference. Saariselkä, Finland. March. Klainer, S.M., Milanovich, F.P., 1990. Optical Sensor for the Detection of Ice Formation and other Chemical Species. United States Patent number 4,913,519. April. Klainer, S.M., Coulter, S.L., Pollina, R.F., Saini, D., 1997. Advances in miniature optical waveguide sensors. Sensors and Actuators B 38–39, 76–182. Lardiere Jr., B.G., Wells, B.F., 1998. Integrated Planar Ice Detector. United States Patent number 5,790,026. August.
131
Lee, H., Seegmiller, B., 1996. Ice Detector and Deicing Fluid Effectiveness Monitoring System. United States Patent number 5,523,959. June. LM Glasfiber, 2004. Why De-icing of Wind Turbine Blades?. presented at Global WINDPOWER 2004, Chicago, March 28– 31. Downloaded, June 16, 2005 from http://www.lmglasfiber.dk/ DK/Events/Conference/default.htm. Luukkala, M., 1995. Detector for Indicating Ice Formation on the Wing of an Aircraft. United States Patent number 5,467,944. November. Maatuk, J., 2004. Microprocessor-Based Liquid Sensor and Ice Detector. United States Patent number 6,776,037. Aug. Magenheim, B., 1977. Microwave Ice Detector. United States Patent number 4,054,255. October. Makkonen, L., 1994. Ice and Construction — Rilem Report 13, First edition. Chapman & Hall, London, England. Makkonen, L., Laakso, T., Marjaniemi, M., Finstad, K.J., 2001. Modelling and prevention of ice accretion on wind turbines. Wind Engineering 25 (1), 3–21. Makkonen, L., Laakso, T., Säntti, K., 2005. Humidity in icing conditions. Proceedings of the 2005 BOREAS VII, Saariselkä, Finland. March. Mason, J., 1971. The Physics of Clouds. Oxford University Press, Ely House, London, England. Noack, R. J., 1998. Ice and Liquid Detector. United States Patent number 5,796,106. August. Peltola, E., Laakso, T., Antikainen, P., Peuranen, S., 2003. Prevention of icing effects. Proceedings of the 2003 BOREAS VI, Pyhätunturi, Finland. April. Pettler, P.R., Roberts, L.H., 1998. Pavement Ice Detector. United States Patent number 5,710,554. January. Ronsten, G., 2004. Svenska erfarenheter av vindkraft i kallt klimat — nedisning, iskast och avisning. Elforsk rapport 04:13, May. Seifert, H., 2003. Technical requirements for rotor blades operating in cold climate. Proceedings of the 2003 BOREAS VI, Pyhätunturi, Finland. April. Säntti, K., Tammelin, B., Laakso, T., Peltola, E., 2003. Experience from Measurements of Atmospheric Icing. Proceedings of the 2003 BOREAS VI, Pyhätunturi, Finland. April. Vetelino, K.A., Story, P.R., Mileham, R.D., Galipeau, D.W., 1996. Improved dew point measurements based on a SAW sensor. Sensors and Actuators. B, Chemical 35, 91–98. Vibro-Meter.com [online]. Accessed 14 March, 2005 at URL: http:// www.vibro-meter.com/aerospace/ice.html. Wallace, R.W., Reich, A.D., Sweet, D.B., Rauckhorst, R.L., Terry, M.J., Holyfield, M.E., 2002. Ice Thickness Detector. United States Patent number 6,384,611. May. Watkins, R.D., Gillespie, A.B., Deighton, M.O., Pike, R.B., ScottKestin, C.B., 1986. Ice Detector. United States Patent number 4,604,612. August. Westerlund, R., 2004, Swedish. Utveckling av en RetroOptisk Isindikator. External HoloOptics Slutrapport-T23, Nr. 100/1023/ 14/sv. September.
