Modern phones and tablets have acceleration sensors for games, and to sense whether the device is held in portrait or landscape orientation. These sensors have become so good, they can be used to measure motion and vibrations with sufficient accuracy to determine the frequency spectra of those vibrations. accelomate is highly configurable in taking such measurements, and it calculates the spectra with a Fast Fourier Transformation (FFT; ideally the user should be somewhat familiar with the math and physics involved). It also displays all measurements and spectra.
Note that measurements and calculations require a certain amount of memory and CPU resources, so not everything might work on older (e.g. Android 2.x/3.x) devices. The quality of the spectra depends on the quality of the vibration sensor in your device. Our tests show that sensor quality varies over a wide range.
If you have specific questions on the inner workings, or feature requests, please don't hesitate to contact us.
The PRO version of accelomate features storing the spectra in a file for later analysis.
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An accelerometer can measure the static gravitation field of earth (like a tilt sensor) or it can measure measure linear acceleration (like accelerating in a vehicle), but it cannot measure both at the same time. When talking about linear acceleration in reference to an acceleration sensor, what we really mean is Linear Acceleration = Measured Acceleration - Gravity. The tricky part is determining what part of the signal is gravity.
It is difficult to sequester the gravity component of the signal from the linear acceleration. Some Android devices implement Sensor.TYPE_LINEAR_ACCELERATION and Sensor.TYPE_GRAVITY which perform the calculations for you. Most of these devices are new and equipped with a gyroscope. If you have and older device and do not have a gyroscope, you are going to face some limitations with Sensor.TYPE_ACCELERATION. Note that the implementations of Sensor.TYPE_LINEAR_ACCELERATION and Sensor.TYPE_GRAVITY tend to be poor and are skewed while the device is under periods of true linear acceleration.
A low-pass filter is a filter that passes low-frequency signals and attenuates (reduces the amplitude of) signals with frequencies higher than the cutoff frequency. The actual amount of attenuation for each frequency varies depending on specific filter design. To find the gravity component of an acceleration signal, a low-pass filter is used to pass the long term portion of the signal (which is assumed to be gravity) through the filter and to attenuate everything else. The gravity component of the signal can then be subtracted from the original acceleration signal to find the linear acceleration.
• Log all sensor data to a .CSV file
• Analog gauges display the tilt and acceleration of both the acceleration and linear acceleration sensors
• Plot sensor output to visualize data in real-time
• Visualize acceleration in two-dimensions with a vector view
• Adjust the time-constant of the low-pass filter to your needs
• Adjust the acceleration sensors output frequency to your needs
Acceleration Explorer allows the user to investigate the noise, offset and skew associated with the accelerometer sensor on Android devices. After a quick calibration process, Acceleration Explorer will calculate the magnitude of each axis and the noise associated with it. Acceleration Explorer also determines the minimum and maximum amplitudes of each axis along with the update frequency of the acceleration sensor.
Why would you want to know about noise, offset and skew?
We want to know about noise, offset and skew because they are aspects that make the sensor less accurate that we can partially compensate for. For example, you may want to implement a low-pass filter or mean filter to smooth the acceleration sensors output and knowing how much noise the sensor has is very useful. Or you may want to know how accurately your device measures gravity, tilt or acceleration.
Acceleration Explorer makes it easy to compare the performance of the acceleration sensors of multiple devices. Not every Android device is the same and knowing the range of how acceleration sensors perform can be very helpful.
Write better code!
Acceleration Explorer can help fine tune your acceleration sensor algorithms.