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arduino C/C++ Coding microcontrollers Software weather station

Sunrise / Sunset – Is Arduino ahead of Its Time?

Recently I added Sun Moon Library to my DIY Arduino Weather Station.

Given a location specified as Latitude / Longitude coordinates and a date / time this clever algorithm uses astronomical math routines to provide timing of sunrise, sunset and moon age.

https://www.flickr.com/photos/jannerboy62/31589567761/

In spite of Arduino ATMega328p chipset being only an 8 bit architecture and float data type being low precision ( 6 – 7 decimal digits ) timings output by sun moon are said to be accurate to second scale.

Comparing results with UK Met Office weather forecast during testing I found Arduino sunrise / sunset timings to be out, with a margin or error of around 15 minutes.

Being suspicious of data, one sunny afternoon I found a vantage point and watched sun disappear below horizon, timing the event.

Sure enough Arduino data was indeed inaccurate.

Arduino DIY Weather Station and sensors.

What could be the problem?

While my knowledge of maths is not sufficiently advanced to properly understand each line of Sun Moon library algorithm, to eliminate possibility of faulty code I decided to try another implementation, Dusk to Dawn.

After running a test for same location, result with new library continued to show an inaccuracy of 15 minutes.

Weather Station timing (date / time) is provided by a Real Time Clock (DS3132 module) which is synced from internet via Network Time Protocol (NTP). A quick check showed date and time to be correct, although manual correction for daylight savings time (DST) seemed sub-optimal.

This pointed to a coordinate error.

Google gives my location Bournemouth, UK as Longitude / Latitude 50.7192° N, 1.8808° W.

Google results for Latitude / Longitude Bournemouth, UK

These coordinates are defined in Weather Station code as:

// Lat/Long: Bournemouth 50.7192° N, 1.8808° W
#define LOC_latitude    50.7192
#define LOC_longtitude  1.8808

Here was the problem.

Checking cooordinates for another location, London, UK ( 51.5074° N, 0.1278° W ) Arduino gave sunrise / sunset with only a minor ( < 1 minute) difference in timing.

Bournemouth is West of Greenwich Meridian (zero line for Longitude) by approx 107 miles. Each degree of latitude is approximately 69 miles (111 kilometers) apart.

Google gives coordinates (50.7192° N, 1.8808° W) as decimal degrees and “N/S/E/W”, a human friendly representation.

Arduino code expects decimal degrees and Plus/minus symbol.

ISO 6709 International Standard defines Longitude as a number preceded by a sign character. A plus sign (+) denotes east longitude or the prime meridian, and a minus sign (-) denotes west longitude or 180° meridian (opposite of the prime meridian)

Similarly, according to Microsoft, “The latitude is preceded by a minus sign ( – ) if it is south of the equator (a positive number implies north)”.

Updating Weather Station to include latitude minus symbol, code now provided accurate timings –

// Lat/Long: Bournemouth 50.7192° N, 1.8808° W
#define LOC_latitude    50.7192
#define LOC_longtitude  -1.8808

In navigation, the 1 in 60 rule states that for each degree off (or displacement) over a distance of 60 nautical miles (NM), it will result in 1 NM off course

A trans Atlantic journey by boat from Southampton to New York ( 2974.5 nautical miles ), given a similar error in bearing of ~2 degrees might arrive in Boston or possibly Washington.

Sunrise / Sunset times on Arduino LCD Weather Station display

We were in agreement at last, today sunrise would occur at 06:25 and sunset at 19:46.

References:

https://github.com/steveio/arduino/blob/master/WeatherStation/WeatherStation.ino

https://en.wikipedia.org/wiki/ISO_6709#Longitude

https://docs.microsoft.com/en-us/previous-versions/mappoint/aa578799(v=msdn.10)?redirectedfrom=MSDN

https://stackoverflow.com/questions/51626412/getting-negative-values-of-latitude-and-longitude

https://www.metoffice.gov.uk/weather/forecast

Categories
circuits Internet of Things microcontrollers sensors Software weather station

Weather Station Wind Vane

What types of sensor can be used for a weather vane? How to track angular position using a rotary encoder? How easy is calibration? What coding considerations for a weather station wind direction project?

Mesopotamian base-60 number system resulted in our idea of 360° in a full circle. Early compasses described 32 points and eight cardinal directions of wind, serving as navigational aids for maritime exploration.

References recorded in ancient China as early as 139 BC described “wind observing fan”. In classical Greece astronomer Andronicus constructed a weather vane at “tower of winds” in Athens. Weather vanes were known in many places of antiquity.

The word “vane” derives from Old English “fane” (Germanic Fahne) signifying “cloth, banner, flag” all of which can be deployed as visual wind direction indicators.

In modern times, absolute and incremental encoders are sensor devices measuring rotary position (angle) and motion. Resolution, precision and accuracy have distinct meaning.

Absolute encoders maintain position during power off or device reset. Incremental motion encoder data is relative, sensors of this type require “homing” (passing a known position) to calibrate.

Lets consider some types of rotary encoder

  • magnetic rotary encoder
  • 360° Potentiometer
  • optical encoder
  • magnetic sensor array

Magnetic Rotary Encoder

Contactless magnetic encoders track a dipole magnet attached to a rotating shaft above sensor, recording rotational angle and direction through a full turn of 360° with high resolution and precision.

Internally hall sensors measure angular position of a magnetic field presented at surface, converting this to a voltage.

On chip digital signal processing (DSP) amplifies and filters planar field data before conversion by Analogue to Digital conversion (ADC).

Having no mechanical friction leads to long expected life span.

A wide operating temperature range (-40 Deg.C to 150 Deg.C) and environmental tolerances (~80% humidity) allow for a wide potential application range.

2/3 wire I2C/SPI programmable interfaces provide standardised micro-controller connectivity and control.

AS5600 Datasheet
MLX90316 Datasheet

Potentiometer 360 degree

Several commercial wind vanes targeted at maritime applications deploy a 360° potentiometer connected directly to vane shaft.

Having a compact, space efficient design, high resolution (degrees of direction) can be tracked.

Detent (stops or clicks) add rotational resistance and a fixed set of positions but increase friction.

Electro-mechanical contacts are subject to mechanical wear and surface corrosion of contact track impacting accuracy, durability and longevity.

Optical Encoder

Optical incremental encoders – IR LED / Sensor pair with a spinning disk interrupter are accurate at very high RPM rates with low sensor latency (rise time).

Resolution is determined by interrupt light “chopper” disk design and relative position is measured by counting rotational sensor ticks.

Quadrature or two channel encoding, with a phase offset, is employed to determine rotational direction.

Calibration, including between device reset/power off is a challenge – sensor pulse counting during rotation must be relative to a fixed/known initial position.

Magnetic Sensor Array

Early compasses recorded 32 points to indicate winds as a navigational aid to sailors.

Wiring 32 sensors together requires considerable soldering & assembly skill. If 4 or 8 bit resolution is sufficient, magnetic linear hall or reed switches might be used – both are contactless, low cost and widely available.

Sensors arranged in a ring array activated by a rotating magnet allow a micro-controller to track position changes.

One approach is to use polling and a GPIO pin per sensor. Pin change interrupts can also be used for state notification.

An analogue multiplexer (CD4051) reduces number of required input pins to 4 (3 address pins, 1 data), optionally a common interrupt enables this to work with an event (interrupt) driven model.

Sensor Implementation – Polling vs Event Model

Polling, reading position at a set frequency (interval), provides consistency and allows simple computation analysis – roll-up averages for example. Higher frequency sampling results in higher precision.

In event model – an interrupt is triggered when sensor state (position) changes.

Recording position data only when direction changes is a low power consumption approach, extending operating duration of a battery powered device, especially on windless days.

To implement event driven design with a multiplexer poses a challenge, at circuit level a common interrupt line wired with isolating diodes to each sensor is required.

A change to any individual sensor triggers an interrupt, micro-controller can then check each multiplexer channel to determine position.

Calibration – how to determine magnetic north?

A compass bearing is required to determine direction relative to cardinal directions.

Wind vanes in a fixed position are manually calibrated. Electronic sensor devices can resolve orientation relative to magnetic compass.

Wind direction is defined by World Geodetic System (WGS) as direction from which wind blows and is measured clockwise from geographical north, namely, true north (meteorology) or in aviation reporting relative to magentic north. 

Visualisation – Wind Rose and Polar Distribution Charts

Wind roses, a type of polar bar chart provide a visualisation of wind distribution: direction and magnitude (velocity) frequency at a location over a given time interval.