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 Precipitation: Rain, Snow RWIS Web (4 Locations) Temperature: Air Temp. Precipitation Rain, Snow (various types) METAR Web (2 Locations) Existing Temperature: Air Temp. Precipitation: Dielectric Constant (mV) to Stay Thermistors, Leaf LocalStation1 wetness check conversion Wetness Sensor Temperature: Stay Temp. Stay Thermistors, Rain Precipitation: Water collected (inches) LocalStation2 Bucket Temperature: Stay Temp. Proposed 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 icing criterion. sensors’ Figure 220: Flowchart for revised ice accumulation algorithm
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
134489_Draft%20Report.docx