Paper
3 November 2010 A new acceleration switch based on separated mass component and elastic component
Liping Wu, Jun Hu, Bo Yang, Qing Shao, Gang Peng
Author Affiliations +
Abstract
This paper presents a new linear inertial acceleration switch which senses inertial acceleration and gives a signal of switchpoint. It is an entire mechanical device has two particular characters: a simple structure and an environmental interference-free capability. The structure and work principle of the switch is introduced, then the design process to the spring is analyzed and simulated, and finally the rationality of this acceleration switch's design is given according to the sample's testing data. In this acceleration switch, the elastic component is a leaf spring, and the mass component is a standard steel ball. The spring and the ball are separated instead of rigidly connected, which make the whole structure is simple. When the switch is on the work direction the ball and the spring are interact, and the spring is on work; when the switch isn't on the work direction, the ball and the spring are separated; environmental external force is on the mass instead of on the spring. The spring is insusceptible on this condition. This particularity determines that the switch is highly environmental interference-free, and doesn't easily affected by environmental influence. Some parameters of the inertial switch are given as followings: (1) Overall dimension of the inertial switch is about 28mm×12mm×12mm; (2) systemic precision of the inertial switch is 1.5%; (3) the inertial switch can endure 0.2g2/Hz stochastic vibration. It is suggested that this inertial switch can be applied in high consequence system.
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Liping Wu, Jun Hu, Bo Yang, Qing Shao, and Gang Peng "A new acceleration switch based on separated mass component and elastic component", Proc. SPIE 7833, Unmanned/Unattended Sensors and Sensor Networks VII, 78330A (3 November 2010); https://doi.org/10.1117/12.864916
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KEYWORDS
Switches

Pollution control

Calibration

Mathematical modeling

Stochastic processes

Magnesium

Statistical analysis

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