Papers by Keyword: Accelerometer

Abstract: Acoustic vector sensor is a kind of inertial sensors. Different from pressure-sensing sensor, it can sense the angle of target under the water. Now most suspension elements are installed on the acoustic vector sensor later. This paper outlines an acoustic vector sensor which is encased in silicon rubber. In this paper, a new structure of acoustic vector sensor is present. The radial stiffness of silicon rubber spring is analyzed by using theory and simulation calculation based on the finite element software ANSYS. At last, the acoustic vector sensor is measured. The results show that the new structural design of acoustic vector sensor could reduce the adverse impact of suspending elastic suspension elements repeatedly and improve the reliability of acoustic vector sensor.

Abstract: Considering the characteristics of light-weight and small-size liquid-filled pipes, the method of utilizing the fiber Bragg grating (FBG) sensor to explore the natural frequency of the pipe has been proposed. Meanwhile the natural frequencies of the tested pipe were obtained through the theoretical calculation and simulation analysis. The calculation results show that the mathematical model and computing method are reliable to calculate the natural frequencies of the tested pipe. The experiments show that the measurement results of the FBG sensor are closer to theoretical calculation results. Because of added mass of the sensor, the natural frequencies of the tested pipe are lowered by the accelerometer. However, the measurement results of the FBG sensor can better reflect the actual characteristics with a negligible mass. The FBG sensor can be applied to frequency measurement, especially to those structures affected by added mass of the sensor.

Abstract: This paper discusses the body posture detection problem using low cost Micro-Electro-Mechanical System (MEMS) inertial sensors, for which a complementary sensor fusion solution is proposed. Considering the impact from the noise and bias drifts, through Kalman filter to complete the multi-sensor information fusion, achieved an accurate attitude determination. The experimental results show that, after using Kalman filtering algorithm to fuse acceleration sensor and signal gyroscope, it can effectively eliminate the accumulative error and significantly better dynamic characteristics of attitude angle measurement, Improving the reliability and accuracy of body posture estimation.

Abstract: The main controller STM32F103VET6 was used as the core of the system. The change of angle and angular velocity was detected by accelerometer and gyroscope built-in six axis attitude sensor MPU6050. The double closed-loop control was used to regulate the speed of DC motor JGA25-371, so as to adjust the posture of the robot. Test shows that the whole system design is simple, good stability and anti-jamming.

Abstract: The main objective of this study is to discover and investigate greater levels of human motion activities recognition. The study presents four approaches of human motion data processing to recognize the human activities. Data collection process was performed in two ways: wearable sensor based in signal data and vision based in image data. The proposed approaches used to analyze the signal and image data are: wearable sensor using 3-space sensing with angular velocity and elevation angle as moderators, wearable sensor using statistical nine existing and a proposed developed classifiers as classification learning system, vision based using skeletonization with humerus-radius and horizontal-radius as measuring angle and vision based image-signal histogram using 2D-1D transformation method. The principal contributions of this thesis are the development of the human motion analysis methods with validated evaluation process tested on the proposed systems. The proposed systems achieved more than 98 % for signal processing and 97 % for image processing of accuracy on recognizing human activities.

Abstract: The demand for quantitative gait analysis increases due to increasing number of neurological disorder patients. Conventional gait analysis tools such as 3D motion capture systemsare relatively expensive. Therefore, there is a need to develop a low cost sensor system to obtain the spatial temporal gait parameters without compromising too much on the accuracy. This paper describesthe development of a wearable low cost sensor system which consists ofrelatively less sensing elements with 2 accelerometers, 4 force sensitive resistors (FSR) and 2 EMG electrodes. Thesensor output was validated by a vision system and the relative error was less than 5% formost of the gait parameters measured.

Abstract: The problem of bridging the gap between the traditional wired monitoring systems and the wireless ones, was the objective of an innovative network architecture that elegantly combined benefits from both approaches. The monitoring focus is on historical buildings in which installing wires maybe range from difficult (e.g., fragile constructions) to impossible (e.g., prohibitive legislation). However, this innovative approach is vulnerable with respect to synchronization issues. In particular, all data sensed by different sensors need to have the correct universal time stamp. Since under this approach there is no central entity to take a synchronization role, in this paper the use of a local NTP server is proposed and as it is shown here using experimental results, this approach suffices for the particular monitoring needs. Thus, the claim that the innovative system can efficiently support the required monitoring of ambient vibrations in historical buildings.

Abstract: Wireless sensor networks can be beneficial for monitoring ambient vibrations in historical buildings where the installation of traditionally wired system may be either difficult due to wiring difficulties or forbidden due to prohibitive legislation. In this paper, a novel wireless sensor network architecture is presented that is focusing on efficiently monitoring ambient vibrations in historical buildings. Traditional wired monitoring technologies are often difficult to be installed in historical buildings either to high costs for installing the wires or to prohibitive legislations. Employing a wireless system could be beneficial. However, as there is no wireless system of high resolution available in the market, an innovative network architecture is proposed that efficiently combines the benefits of both the wired and wireless systems. The problem of synchronization that this novel architecture introduces, is also discussed in this paper along with a possible solution.

Abstract: This study focuses on physical activity recognition of elder people using a single triaxial accelerometer attached on waist. With accelerations data acquired continuously by a wearable wireless device, a motion pattern recognition method based on acceleration time series analysis of human activity states is proposed. We use Hidden Markov Model (HMM) to identify physical activity series. Experimental result shows that the activity recognition rate is 95.7% using this method, which can play an important role in the adjuvant therapy.

Abstract: The main subject of this thesis is to study a uneasily two-wheeled self-balancing vehicle system. Two tires are placed on two sides of the body parallel in this system . Controlling the rotation of two DC motors can achieve the goal of walking upright. The circuit part is mainly made up by attitude sensors parts (including Gyroscope and Accelerometer), control circuit and the driver board. Attitude sensors measure the tilt angle and the rate of change of inclination of vehicle, and then the controller calculate the responding data and finally drive two DC motors forward or backward to produce forward or backward acceleration to make the car balancing.