After inspecting the temperature trend during the 16 day period it was observed that all the sources measured temperature in unison at night. Solar radiation during the daytime would cause differences in the temperature recorded depending upon the location of the thermistors. Some of the general observations gathered were: Upper stay thermistors record much higher temperature than lower stay thermistors. RWIS & METAR data show similar temperature trends. METAR data seem to have higher maximums and lower minimums. They both lag with respect to temperature of up to 3hrs or 20 F when compared to the stay thermistors. Embedded VWG segment thermistors have significantly lower maximum and higher minimum. In order to gain deeper insight into the temperature characteristics of the individual thermistors we decided to choose few example days and have a magnified view of their trends. March 15 and March 16 seemed to appear to represent more days in the bracket and hence chosen for the purpose. The weather data for those days were obtained from the National Weather Service which included the sunrise, sunset, maximum and minimum temperatures, sky cover and precipitation in inches. Table 34: Weather Report on March 15 Time Conversion Local Time (EDT) Data Logger Clock (EST) RWIS Data Collected (GMT) GMT + 04:00:00 GMT + 05:00:00 National Weather Service Report (March 15) Local Information Comparison Parameter Time (EST) Value Time (EST) RWIS 2016 Air Temperature Mean Sheath Thermistor Temperature Sunrise Sunset 6:46 AM 6:42 PM 5:43 PM 73.9 F 75 F Maximum Temperature Minimum Temperature 5: 43 PM 4:29 AM 78 F 58 F 4:29 AM 62.6 F 62.5 F Average Sky 0.3 * Sky Cover: The total amount of clouds
Figure 209: Initial Plan by UT Research Team for Tower Mounting On May 16, 2013, the URT gathered at Veteran’s Glass City Skyway to mount the sensors on the tower. Horizontal cross-arms were fixed on to the tower at different heights to support the sensors. The UCII crew was divided into three groups to: set up the data loggers inside the tower cabinet, ride a bucket truck and mount the sensors at different elevations, and Upgrade the data acquisition system with new hardware and new sampling rate. Table 45: Summary of VGCS Sensor Installation Trip Crew Position Duties Tower Cabinet Setup white backplanes on shelves. Receive cables from conduit. Connect cables from each sensor to CR1000 and push new program. Reprogram with appropriate sampling rate. Setup IP address for each data logger. On the Tower (Each Sensor Location) Connect vertical cross-arm to tower. Install the gage on the arm. Let the cable down through the conduit. Repeat for all sensors. Old/Main Cabinet Location Upgrade system to CR1000. Reprogram with new scan rate. Setup new IP configuration. MOUNTING TECHNIQUES Different techniques were used to mount the sensors on the tower at different elevations. The ice detector was at the topmost level, followed by solar radiation sensor, rain tipping bucket and leaf wetness sensor. Leaf Wetness Sensor: The leaf wetness sensor was placed flat with the dielectric surface facing upward on the cross arm and firmly attached to it using zip-ties. Figure 210: Leaf Wetness Sensor Zip-tied to Cross-arm Rain Tipping Bucket: The rain bucket was screwed on to a leveling bracket which sat on a vertical pipe. This pipe was mounted on the cross arm using cross-over T joints with OD 1.9” for 1.5” IPS cross arms.
Similarly, three new functions have been introduced for the new sensors. This kind of modularity helps upgrade the existing algorithm without affecting it; that is, the existing decision algorithm for the initial UCII dashboard (seen in Chapter 6) remains the same and will work exactly the same as before, but now it is complemented by a similar algorithm employed with the new sensors which can also vote and cause the threshold to be met. The table in the next page describes the modularity of the modified ice accumulation algorithm. Figure 219: Flowchart of existing Ice Accumulation Algorithm (Agrawal, 2011) Table 46: Ice Accumulation Station Functions Ice Accumulation Stations Function Name Type Measurement Parameters Existing RWIS Web (4 Locations) Precipitation: Rain, Snow Temperature: Air Temp. METAR Web (2 Locations) Precipitation Rain, Snow (various types) Temperature: Air Temp. Proposed LocalStation1 Stay Thermistors, Leaf Wetness Sensor Precipitation: Dielectric Constant (mV) to wetness check conversion Temperature: Stay Temp. LocalStation2 Stay Thermistors, Rain Bucket Precipitation: Water collected (inches) Temperature: Stay Temp. LocalStation3 Ice Detection Sensor Ice Presence check directly. Modular: 3 new independent station functions for ice accumulation criteria The flowchart below is a good representation of the proposed ice accumulation algorithm. So far we have been using test thresholds for each of the new sensors. The proposed threshold of ice thickness by ice detector is 0.15 after which melting cycle starts. The threshold for leaf wetness sensor is 300 mV and for rain bucket is a rate of 0.1 inches/hr. These thresholds are subject to training in the real world and with more icing events and data analysis, we can settle with a more and more appropriate threshold for each of the new sensors’ icing criterion. Figure 220: Flowchart for revised ice accumulation algorithm