Recorded in a journal:
|Tao of Pooh||10/1/1986|
|Heinlin||The Cat Who Walked Through Walls||1/1/1987|
|John Crowley||The Deep||10/1/1987|
|Mark Helprin||Dove of the East||10/1/1987|
|John Crowley||Little Big||10/1/1987|
|Strugatsky||Noon 22nd Century||11/1/1987|
|Nietche||Genealogy of Morals||2/1/1988|
|Phillip K Dick||The Penultimate Truth|
|Phillip K Dick||God’s Eye|
Flight 1 – Failure to launch (I moved the ESC’s the night before and forgot to check the directions again). Broke 1 prop.
Flight 2 – A bit bumpy on the throttle and I lost 2 legs but otherwise good.
Flight 3 – Some good stable flight until I switched on “Baro” mode (“alt hold” in APM) and it took off to the moon. I switched it off but it was going over my head and I didn’t have control so I dropped it. Went down through the tree. Broke 2 props, 2 controller mounts, and almost every tie wrap. Not too bad, as I needed to take it apart anyway. I want to add a +
This is the first charge of the new battery pack using the cells from the Chevy Volt. Generally it charged perfectly except that it never reached the Vhi cutoff voltage of 50.4. Maybe this isn’t a bad thing?
I thought that lithium batteries would continue to draw and needed to be cut off when they were full. In this case the current just dropped off to almost nothing as the voltage neared the cutoff.
In preparation for the pi class I wanted to get a motor running and found this excellent tutorial:
It works great once I realized the motor has a 64:1 gear reduction and you need kilo-steps to see it moving. Also while the code was very simple it looked it was written in C. I decided to make it more pythonic:
#!/usr/bin/python # ___ ___ _ ____ # / _ \/ _ \(_) __/__ __ __ # / , _/ ___/ /\ \/ _ \/ // / # /_/|_/_/ /_/___/ .__/\_, / # /_/ /___/ # # Stepper Motor Test # # A simple script to control # a stepper motor. # # Author : Matt Hawkins # Date : 11/07/2012 # Changes to be more pythoning 8 November 2014 # # http://www.raspberrypi-spy.co.uk/ # # Import required libraries import time import RPi.GPIO as GPIO # Use BCM GPIO references # instead of physical pin numbers GPIO.setmode(GPIO.BCM) # Define GPIO signals to use # Pins 18,22,24,26 # GPIO24,GPIO25,GPIO8,GPIO7 StepPins = [24,25,8,7] # Set all pins as output for pin in StepPins: # print "Setup pins" GPIO.setup(pin,GPIO.OUT) GPIO.output(pin, False) # Define some settings StepCounter = 0 WaitTime = 0.020 # Define simple sequence Seq1 = [[1,0,0,0], [0,1,0,0], [0,0,1,0], [0,0,0,1]] # Define advanced sequence # as shown in manufacturers datasheet Seq2 = [[1,0,0,0], [1,1,0,0], [0,1,0,0], [0,1,1,0], [0,0,1,0], [0,0,1,1], [0,0,0,1], [1,0,0,1]] # Choose a sequence to use Seq = Seq1 while True : StepCounter = 0 for step in Seq : for pin,phase in zip(StepPins,step) : if phase : # print " Step %d Enable %i" %(StepCounter,pin) GPIO.output(pin, True) else: GPIO.output(pin, False) StepCounter += 1 # Wait before moving on time.sleep(WaitTime)
home.newts.org is a tiny Raspberry Pi Linux computer. Currently it runs pyweather to connect my Davis Vantage Pro2 weather station to wunderground.com. It also runs my tf mud client in a screen session and has a Cherokee web server that consolidates some information about the house and the solar power generation.
#!/usr/bin/python import xml.etree.ElementTree as ET import urllib2 import re from bs4 import BeautifulSoup import time page = open('index.html').read() now = time.localtime(time.time()) day = now.tm_mday year = now.tm_year month = now.tm_mon # get the inside temperature # vera = 'http://192.168.1.4:3480/data_request?id=lu_sdata&output_format=xml' vera_xml_data = urllib2.urlopen(vera).read() root = ET.fromstring(vera_xml_data) units = root.findall(".").attrib['temperature'] thermostat = root.findall(".//devices/device[@name='Thermostat']") temperature = thermostat.attrib['temperature'] setting = thermostat.attrib['heatsp'] inside_temperature = 'Temperature = %s°%s Thermostat = %s°%s' % (temperature,units,setting,units) # Get the solar production data # solar_home_page = urllib2.urlopen('http://192.168.1.232/home').read() solar_production_page = urllib2.urlopen('http://192.168.1.232/production?locale=en').read() solar_re = re.compile(r'<!-- START MAIN PAGE CONTENT -->.*<!-- END MAIN PAGE CONTENT -->', re.MULTILINE+re.DOTALL) solar_home = solar_re.findall(solar_home_page) solar_production = solar_re.findall(solar_production_page) soup = BeautifulSoup(solar_home) tables = soup.find_all('table') solar_statistics = tables solar_data = """ %s<br> %s<br> """ % (solar_statistics,solar_production) # this was an attempt to display the nice graphs from wunderground.com # it works if you go to wunderground.com first to trigger the file to be # created but won't work otherwise. # graph_data = '<img src="http://www.wunderground.com/cgi-bin/wxStationGraphAll?day=%d&year=%d&month=%d&ID=KNHNASHU20&type=3&width=500&showtemp=1&showpressure=1&showwind=1&showwinddir=1&showrain=1">' % (day,year,month) graph_data = '<h2>%s</h2>\n%s' % (time.asctime(now),graph_data) # grr graph data generation has to be triggered by hitting wunderground graph_data = '' # Generate the web page from the template # print 'Content-type: text/html\n\n' print page % (graph_data,inside_temperature,solar_data)
This isn’t a book but not sure what it really is at all but here’s some words:
There’s stuff being circulated on FB now about radiation levels from Fukushima increasing in the US and about the EPA (Obama!) raising their safety limit instead of dealing alerting people and dealing with it. I wanted to find out what is really going on. Or at least spend an hour to see what I could learn.
First, the EPA did release a draft report to raise the safe limits on certain exposures last year although it doesn’t seem to be a response to recent events or political pressure but bureaucratic and scientific views that started a decade earlier. This will take a lot more time to untangle so I will just leave that off here with the Forbes link.
Next up, are we seeing more radiation here from Fukushima and should we worry? Fallout from nuclear testing in the 50’s and 60’s peaked before the test ban treaty. It has come back down since then. My general feeling is that the sky is not falling that as horrible as the disaster is the global effects are less than Chernobyl and nuclear testing in the 50s and 60s.
To look at this myself I got some historical data collected in Concord NH since 1981 and graphed it to the right. This big spike is apparently Chernobyl and there is no large spike to the right since Fukushima. The small spike is before(?) and there could be a little more amplitude to the noise since. This is just collection point and there are some anomalies in the data set (spike at the beginning? flats around 09 maybe the collector was broken?). My general conclusion is we are not seeing a noticeable effect in the North East. The Pacific coast or maybe other areas could of course see something different depending on the wind patterns.
Just for comparison I thought I would look at the data that I collected myself. I keep a Gamma Scout Geiger counter in t
he basement to monitor the radon. But, the software is is having trouble decoding the data. Until I get that sorted I just have the government data.
I used to believe that I couldn’t really get into solar at my house because of the angles, trees etc. But now I see they have micro grid-tie inverters (GTIs) on the order of 100s of watts so that small systems are practical. In some cases the inverter is even part of the panel. So I think I can get a few 250 watt panels to offset a little of my energy usage. The nice thing about these AC panels is that they are stand-alone and able to scale by simply adding more panels.
To compare panels I have a google docs sheet. In trying to determine how much power I might expect to get out of the panels I made a guess of the amount of sun on average and also a “performance factor” which is real world efficiency based on angles and weather, etc for our latitude and weather patterns. I made a guess of 8 hours and 60%. The Watt’s have a great solar array and lots of real time data. Looking at their yearly data I calculated a “performance factor” of about 40%. And in thinking about it more the average daily sun doesn’t matter in my spreadsheet. It is already factored in without knowing the hours.
This article is just the starting point and has the links to my data sources and calculations. I still need to research the tax incentives and ponder the different options for panels and inverters. The built in GTI and racking is nice but expensive. The external Renogy ones have an optional internet interface (gizmo!). More on the options later.
Sorry, just some set up links right now…