Noise accelerometers

In a separate trial 24 h later, the animals are presented with a startle stimulus (e.g., loud noise 70-80 db, or air puff) and their activity is recorded as a baseline. The startle stimulus can be presented in four blocks of five startles each, with 30-35 s between each startle stimulus (7). Peak and amplitude of the startle response can be recorded (e.g., using a piezoelectric accelerometer) and digitized (18). 

Noise and vibration measurements are made with microphones and accelerometers. Sometimes, sophisticated instruments like laser vibrometers are used for NVH work. Common noise fixes include cutting slots and/or chamfers on the brake pads and linings, the application of constrained layer damping noise insulators to the back of the brake pad shoe plates, and detuning the resonant frequency of mechanical brake corner components. 

For optimum noise performance the bandwidth of a sensor and its evaluation electronics should be limited to a value no larger than that required by the application. For example, an accelerometer with a noise floor of 1 mG (1 G = 9.8 m/s2) in a 1 kHz bandwidth will resolve 500 pG when its bandwidth is reduced to 250 Hz. Further bandwidth reduction results in additional improvement up to the point where a different noise source dominates (e.g., flicker noise). 

A monolithic three-axis accelerometer with three independent capacitive readout circuits on a single chip is described elsewhere [7] (Fig. 6.1.14). The circuit is similar to Fig. 6.1.10 and achieves 0.085 aF/v/Hz resolution with 100 fF sense capacitors. The noise is actually dominated by Brownian noise in the sensor itself, as tests in vacuum demonstrate. The actual capacitance resolution is therefore somewhat better than stated. This circuit uses correlated double sampling (CDS) for biasing and to reject flicker noise. 

Fig. 7.1.1 shows an example of variations in system partitioning and integration on very similar products. The Analog Devices single-chip accelerometer is in Fig. 7.1.1a and the Motorola or Bosch two-chip accelerometer is in Fig. 7.1.1b. Each has particular advantages. For example, the single chip solution may improve the signal-to-noise ratio and reduce the number of interconnects. Whereas the multiple chip system may have a better time-to-market as a result of the flexibility afforded by the separation of the MEMS processing from the circuit fabrica-...

Accelerometers generally fall into two application categories of impact or motion measurements. The specifications for each type of application vary with regard to sensitivity, zero-g offset, frequency range and noise. In all cases there is a desire to have the smallest possible package size and lowest power consumption. 

Noise within an accelerometer is created from several sources. The noise comes from the switched capacitor design, inherent thermal noise within any devices, the flickeT noise of transistors, and the Brownian noise in the g-cell transducer due to random motion of atoms (see equation 5). Signal-to-noise ratio of 60 dB is common, but lower g devices with higher gains may be worse. 

The alternating geometry of the sensors was simulated by a 90 rotation about the vehicle up-axes lasting 10 s after a resting period of 60 s. The results are presented in fig. (5) to fig. (10). After the first turn the estimation error decreaeses by a considerable amount. The tilt error is even smaller than 1 arcsec for a low noise system. The azimuth error also becomes smaller. This is due to the improvement of the observability of the gyro and accelerometer biases in a plane perpendicular to the axes of rotation, as shown in fig. (7) and fig. (9). 

Surveyors always try to verify their results with independent, redundant measurements. They use the redundant measurements for finding a statistically significant result, for raising the accuracy and for increasing the signal to noise ratio. As an independent sensor in our problem we need a second sensor, which can react on high-frequency movements which have a short relaxation time. The sensor can have a one dimensional sensitivity, because we want to measure only movements in the direction of the brake power. Therefore we used an accelerometer, which we mounted on the abutment with its sensitive axis in the direction of the brake power (Fig. 7). 

Figures 6 and 8 show the pure, but calibrated measurements of the electronic camera and the accelerometer on the abutment. This data is superimposed by a noise. The noisebandwidth before the beginning of the braking is representing the variance of the observations. The problem which we have to solve is to determine the movements of the abutment in the direction of the brakepower, which is the direction of the bridge axis, by using the observations of the electronic camera and of the accelerometer. To achieve this we have to treat both data in a joint model with the performance function S t).

Signals from the sensors are routed via high-temperature, low-noise cable to amplifiers. The amplifier output is transmitted to alarm units located within the control complex. The alarm unit compares the peak value of the accelerometer output to a predetermined threshold or "alert level" and provides an alarm to the control room operator via the Data Processing System. 

The MR fluid-based suspension systems implemented on these various vehicles enable simultaneous ride comfort control and body motion control. As indicated in Fig. 6.85, the control system architecture for these systems processes inputs from relative position sensors at each wheel. In addition, inputs from a lateral accelerometer, yaw rate sensor, steering angle sensor and speed sensor all feed by way of a CAN BUS into the controller. The control algorithms are quite complex and seek to simultaneously optimize a wide range of performance features including overall handling, overall ride comfort, body control, road noise, head toss and a subjective safe feeling. 

Vibration can cause problems to the human body, machines and structures, as well as producing high noise levels. It is commonly measured using an accelerometer which can indicate a value in terms of acceleration, velocity or displacement. There are many types of accelerometer and associated instrumentation available which can give an analogue or digital readout or can be fed into a computerised analysis system. As with sotmd, the vibration component would be measured at particular frequencies or over a band of frequencies. 

J. Wu, G.K. Fedder, L.R. Carley, A low-noise low-offset capacitive sensing amphfier for a 50-pg/VHz monolithic CMOS MEMS accelerometer, IEEE Journal of Solid-State Circuits 39 (2004) 722-730. 

Here b means the IMU body frame e denotes the ECEF frame i indicates the inertial frame Cl is the Direction Cosine Matrix (DCM) from body frame to ECEF frame, ft is the skew-symmetric matrix for angular rate measurements is the vector of acceleration measurements from the accelerometers. F is the system matrix applied in the ECEF frame is the distance from the earth geometric center to the earth surface g is the local gravity is the position of the IMU in ECEF. The noise vector w contains, in the indicated order, gyroscope bias, acceleration bias, acceleration noise, angular rate noise, receiver clock error and receiver clock rate noise. These noise terms are described by the error covariance matrix Q in the Kalman filter routine ... 

For both the accelerometers and the gyroscopes the EKF noise values were selected according to the manufactiu er specifications as AV analysis confirmed a close match of the experimentally extracted parameters to those given in the associated datasheets. 

Seismometers can be further categorized by the lower comer frequency (—3 dB point) of the amplitude frequency response of the instmment. Geophones have lower comer frequencies from 1 to 40 Hz. Short-period seismometers have lower comer frequencies from 1 to 4 Hz, and broadband seismometers have lower comer frequencies from 0,027 to 1 Hz. Broadband seismometers typically have lower noise floors over wider bandwidths than short-period seismometers, and short-period seismometers are typically quieter than geophones. Accelerometers are approaching the performance levels of some geophones and short-period seismometers and can be considered for downhole applications too. 

The major advantages of MEMS sensors for measurement of stmcture seismic response are their small size, low power consumption, and low price in contrast with their high accuracy in measurement. For example, a typical price of MEMS accelerometers is less than 10 USD. In spite of this low cost, a MEMS accelerometer with 3 axes, 2 g full scale, 5 mm x 5 mm x 2 mm size, 1.1 mA current consumption at the input voltage of 2.7 V, and noise density of 175 fig/v/Hz is available off the shelf. 

Resolution It is the minimum acceleration amplitude that it may measure. In early accelerometer digital recorders, it was limited by the digitizer (A/D converter) resolution. In modem instmments, the digitizer is usually 24 bit, and the resolution is related to the self-noise level of both the accelerometer and the digitizer. So it is usually given as self-noise level, or it may be obtained from the dynamic range. Good-quality accelerometers have noise levels under 1 pm/s rms (root mean square). 

Figure 12 plots a small local earthquake recorded by a standard accelerometer and the simulated record with this sensor, using its real noise. The MEMS sensor shows a higher noise, but a useful signal is still available. 

Milligan DJ, Homeijer BD, Wahnsley RG (2011) An ultra-low noise MEMS accelerometer for seismic imaging. In Sensors 2011 IEEE, October 2011, Limerick, DOI 10.1109/ICSENS.2011.6127185, pp 1281-1284... 

It is interesting to note that whether a velocity sensor or an accelerometer is used, it is possible to calculate displacement, velocity, and acceleration from both t)q)es of sensors however, as is shown later, in practice, this will be frequency limited due to noise in the system. 

When testing instruments at locations where the site noise is well below the self-noise of the instrument, it is possible to attribute the power in a given frequency band entirely to the instm-ment s self-noise (Fig. 2). This often occurs when testing strong-motion accelerometers in a quiet vault or lower-grade sensor in almost any good site (Evans et al. 2010). In such cases the simple relatimi is obtained ... 

Seismometer Self-Noise and Measuring Methods, Fig. 2 Self-noise estimates for a strong-motion accelerometer using the single-sensor method (red), the Sleeman (Sleeman et al. 2006) threesensor method (green), and the Holcomb (Holcomb 1989) two-sensor method (blue). For reference the New Low-Noise Model (NLNM) is included (black)... 

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