Motion sensors accelerometer

Wearable sensor-based activity recognition (WSAR) In this AR, physical sensors are attached to the body. This is a relatively new approach which emerged with the development of wearable computing. Motion sensors (accelerometers... 

Shahinpoor [930], working at the "Artificial Muscles Research Institute", University of New Mexico, Albuquerque, NM, USA, fabricated devices for a wide variety of applications based on electrochemomechanical principles, from ion conducting polymers (not CPs). These polymers included poly(acrylic acid-bisacrylamide) (PAAM), poly(2-acrylamido-2-methylpropanesulfonic acid (Poly(AMPS)), and polyacrylonitrile (PAN). While these are not CPs, Shahinpoor also indicated that similar action could be expected, with minor modifications, from CPs such as poly (ary lene vinylenes) and poly(thienylene vinylenes). Shahinpoor typically used a metal (e.g. Pt) + ion conductive polymer composite in place of the customary bilayers. Some of the applications envisioned, or demonstrated for ion conductive polymers, included microactuators, motion sensors, accelerometers, oscillating artificial muscles, inchworms, cardiac>circulation assistants, noiseless propulsion swimming robots for military applications, fully constituted contractile artificial muscles, miniature flying machines, and electrically controllable adaptive optical lenses (Fig. 21-51. The potential military applications of these have fueled much interest recently [931]. 

Body movement, posture Piezoresistive strain/ pressure sensors, accelerometers, gyroscopes, optical fibre sensors Body kinematics Dependent on motion to be analysed... 

Motion sensors based on MET technology include linear and angular accelerometers, rate sensors, gyroscopes, and seismometers. MET sensors can be configured for horizontal, vertical, and rotational sensing, as shown in Fig. 4. Despite of the difference in construction, all of them can be described in common rules-based approach. A vertical-axis sensor is considered in the following as an example. 

Sensor information collected by the T1 nodes can be transmitted automatically or on request to T2 nodes. For current motion capture applications, sensor data is transmitted as frequendy as possible. A typical packet is 17 bytes containing a node ID, accelerometer, gyroscope, and compass data. While the l C network can provide bus speeds up to 400 KHz, packet sizes and communication overhead limit effective transmission rates. Lewis estimated the impact of increasing the number of T1 nodes on effective transmission rates, and his results are shown in Fig. 27.15 [10]. 

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. 

An accelerometer is a basic technology that converts mechanical motion into an electrical signal. It is an electromechanical device that measures acceleration force, whether caused by gravity or motion. There are many different types of mechanisms involved in the accelerometers, including piezoelectric, piezoresistive, capacitive. Hall effect, magnetoresistive, and temperature sensors (Table 12.2). Piezoelectric, piezoresistive, and capacitive types are the most common in commercial devices. 

On-chip RLE sampling. A third setup uses the motion detection of both accelerometers with the same sampling parameters as in the other two setups, i.e., the sensor data is also in this semp recorded with time stamps on the /rSD card, with the run-length encoding (RLE) performed on the sensors instead of executed on the miCTO-controller. 

An example application of a sensor network system equipped with MEMS accelerometers is the measurement of restoring force characteristics of strucmres subjected to strong ground motion. Right after a severe earthquake, the damage level of the structures in disaster-stricken region has to be quickly identified. For this... 

A comparative test of these sensors (Evans et al. 2014) shows that some of them could be very useful for low-cost seismic networks. Some models have performances suitable for strong ground motion recording with acceptable SNR to be used as class C seismic accelerometers. 

Seismic Accelerometers, Fig. 18 The REFTEK 148-1 QuakeRock accelerograph, with MEMS sensor (Photo from REFTEK (www.reftek.com/products/motion-... 

For free-field stations, it is usual to build a small concrete pier on which the accelerometer (or accelerograph if the sensor is inside it) must be firmly anchored so a strong motion cannot move the instrument relative to ground Most commercial instruments include a suitable base with anchoring holes or a similar system. Other materials for pier, like a table made with steel bars, are not suitable since it may resonate with very low damping in the seismic band of interest. 

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)... 

The noise levels of strong-motion accelerometers make estimating the self-noise of such sensors easier than typical low-noise broadband sensors (Fig. 2). Since the user community is generally only interested in strong motions with frequencies from a few Hz to a few tens of seconds period, it is often possible to resolve the selfnoise using relatively short testing intervals. 

The output of a seismic sensor, a seismometer or an accelerometer, is a time-varying voltage, which is related to the ground motion by a differential equation in the time domain or by a transfer function in the frequency domain. This transfer function or response function is characterized by a number of parameters, which are assumed to be constant, at least in the short term. 

One solution may be to use multiple 3-axis instruments spaced on a rigid structure such that differences in translational accelerometers (in different instruments) can be used to obtain rotational acceleration estimates. This is often done on bridges for evaluating torsional (rotation) deck modes and could also be applied to ground motion. In this case, the classical 3-axis instrument is not redesigned however, it would have to be strategically positioned in situ very close to other 3-axis instruments. Another solution may be to have 2 sets of 3-axis sensors in one instrument, with one set fixed and the other on a 6DOF platform with the difference in the time series... 

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