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A Multivariable Detection Device Based on a Capacitive Microphone and Its Application to Security

机译:基于电容麦克风的多变量检测装置及其在安全中的应用

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Any sensor for detecting a certain physical variable is more or less influenced by other physical variables, which are designated as “noise.” The objective in conventional sensor design has been to minimize the noise. In this paper, however, we make use of sensing devices that are easily influenced by multiple physical variables and make full use of their multisensing characteristic. We consider such devices as multiple-input–single-output sensors. First, the output signal derived from multiple input signals must be dissociated. The input signals resulting from physical phenomena have inherent characteristics and can mathematically be modeled. Application of a Kalman filter realized by such models can provide estimates of the state variables of all input models, and thus, the input signals are dissociated. As an example, a novel sensor based on a microphone is presented. This sensor can detect various variables such as pressure and acceleration in the frequency range of 0.1 Hz to 10 kHz, temperature, and even light emission. We apply the sensor to monitor the symptoms of fire, earthquake, and break-in by an intruder from within a house.
机译:用于检测某个物理变量的任何传感器或多或少都会受到其他物理变量的影响,这些其他物理变量被称为“噪声”。传统传感器设计的目的是使噪声最小化。但是,在本文中,我们使用了容易受到多个物理变量影响的传感设备,并充分利用了它们的多传感特性。我们将这类设备视为多输入单输出传感器。首先,必须分离来自多个输入信号的输出信号。由物理现象产生的输入信号具有固有特性,可以在数学上建模。通过这样的模型实现的卡尔曼滤波器的应用可以提供所有输入模型的状态变量的估计,因此,输入信号被分离。作为示例,提出了一种基于麦克风的新型传感器。该传感器可以检测各种变量,例如0.1 Hz至10 kHz频率范围内的压力和加速度,温度甚至发光。我们将传感器应用于监视火灾,地震和入侵者从房屋内部侵入的症状。

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