Low-cost Acceleration Sensors Research Articles

IoT device-based data acquisition system with on-board computation of variables for cow behaviour recognition

Improved raw data handling is one of the requirements that research should fulfil in the design of IoT device-based data acquisition systems for enhancing the overall system performance. In this study, the system was composed of low-cost acceleration sensors broadcasting to a Raspberry PI.The main aim of this study was to develop firmware for the acceleration sensors with the purpose of maximising the battery life-time and minimising the information loss during data transfer while allowing high accuracy in the discrimination of the cow lying-standing behaviour. The attainment of these goals was achieved by using an aggregated accelerometer variable, computed on-board of the IoT device, together with the idea of saving in the payload the most recent variables.The comparisons conducted between the base firmware installed on the device and the new firmware developed showed the outstanding performance of the latter in terms of Raspberry PI CPU usage, storage memory occupation, and packet loss. The algorithms of lying-standing behaviour discrimination were implemented and assessed by using the new firmware, producing excellent values of the most used accuracy measures.

아두이노 기반 MEMS 센서의 동적 계측 성능 연구

Prior to applying the Arduino-based acceleration sensor for structural health monitoring of low- and mid-floor structures, we would like to confirm the vibration measurement performance of the Arduino-based low-cost acceleration sensor and clarify its limitations. A commercial acceleration sensor and a low-cost acceleration sensor were installed in the excitation device, and the response was measured by excitation of sin waves of various cases. The response results were compared with the measurement performance of commercial acceleration sensors and low-cost sensors. In the estimation of the excitation frequency, similar results were shown in most cases, but in the case of the magnitude estimation result, when the excitation amplitude is less than 1Hz/100mm, the estimated Magnitude value was inaccurate. In all subsequent cases, the results of the estimation of the magnitude of the low-cost acceleration sensor and the commercial acceleration sensor were similar. Based on these experimental results, it is judged that the Arduino-based low-cost acceleration sensor is generally effective in dynamic measurement of buildings.

A Smart IoT Device for Detecting and Responding to Earthquakes

The advancement of hardware and software technologies makes it possible to use smartphones or Internet of things for monitoring environments in realtime. In recent years, much effort has been made to develop a smartphone based earthquake early warning system, where low-cost acceleration sensors inside a smartphones are used for capturing earthquake signals. However, because a smartphone comes with a powerful CPU, spacious memory, and several sensors, it is waste of such resources to use it only for detecting earthquakes. Furthermore, because a smartphone is mostly in use during the daytime, the acquired data cannot be used for detecting earthquakes due to human activities. Therefore, in this article, we introduce a stand-alone device equipped with a low-cost acceleration sensor and least computing resources to detect earthquakes. To that end, we first select an appropriate acceleration sensor by assessing the performance and accuracy of four different sensors. Then, we design and develop an earthquake alert device. To detect earthquakes, we employ a simple machine learning technique which trains an earthquake detection model with daily motions, noise data recorded in buildings, and earthquakes recorded in the past. Furthermore, we evaluate the four acceleration sensors by recording two realistic earthquakes on a shake-table. In the experiments, the results show that the developed earthquake alert device can successfully detect earthquakes and send a warning message to nearby devices, thereby enabling proactive responses to earthquakes.

IN-PROCESS CONTROL WITH A SENSORY TOOL HOLDER TO AVOID CHATTER

Hydro-, steam- and gas- turbines, aircraft components or moulds are milled parts with complex geometries and high requirements for surface quality. The production of such industry components often necessitates the use of long and slender tools. However, instable machining situations together with work pieces with thin wall thickness can lead to dynamic instabilities in the milling processes. Resulting chatter vibrations cause chatter marks on the work piece surface and have influence on the tool lifetime. In order to detect and avoid the occurrence of process instabilities or process failures in an early stage, the Institute for Production Engineering and Laser Technology (IFT) developed an active control system to allow an in-process adaption of machining parameters. This system consists of a sensory tool holder with an integrated low cost acceleration sensor and wireless data transmission under real time conditions. A condition monitoring system using a signal-processing algorithm, which analyses the received acceleration values, is coupled to the NC- control system of the machine tool to apply new set points for feed rate and rotational speed depending on defined optimisation strategies. By the implementation of this system process instabilities can be avoided.

Design of Semi-Active Roller Guides for High Speed Elevators

Comfort is an important topic in the elevator industry, and among the different factors which affect it, vibration in the car is one of the most important. Passengers not only perceive this phenomenon as an unpleasant effect, but also as a signal of the elevator safety level, and therefore it is of great importance to mitigate it. Although mature technologies are available for reducing vibration in low speed elevators, the increased number of high buildings and sky-scrappers, forces the development of new technologies for medium and high speed elevators. Active vibration control techniques are widespread used for damping vibration in different industrial environments, but their application to the elevator industry normally imply expensive solutions, with bulky and heavy actuators which highly burden its application. As alternative, the cheaper and lighter semi-active vibration systems based on passive elements capable of modifying their properties in response to external commands represent an appealing option. In this paper, we describe a design method for a semi-active roller guide based on a commercial magneto-rheological damper. Different control strategies based on low cost acceleration sensors are also analyzed.

Hybrid Positioning through Extended Kalman Filter withInertial Data Fusion

In wireless sensor networks (WSNs), hybrid algorithms are widely used in order to improve the final positioning accuracy. This paper presents a hybrid positioning algorithm which combines time of arrival (TOA) and received signal strength (RSS) measurements using two different radio technologies, ultra wide band (UWB) and ZigBee, respectively. The TOA measurements are used to estimate the distances between a mobile node and a set of anchor nodes. Both UWB- based distance estimates and RSS measurements based on ZigBee are simultaneously processed by an Extended Kalman Filter (EKF). Moreover, a low cost inertial device is also used to acquire acceleration measurements which proved to be useful in order to detect the motion of the mobile node. This information has also been integrated in the EKF algorithm accordingly. The performance of the final hybrid positioning algorithm is compared with the conventional EKF which uses a single type of range measurements, TOA or RSS. Simulation results based on a real measurements campaign, show that the hybrid algorithm significantly improves positioning accuracy. In addition, a further improvement has been achieved by applying the motion detection approach based on inertial measurements performed by the low cost acceleration sensor.

J041024 広帯域加速度センサを用いたミニトマト茎部の超音波AE測定([J041-02]超音波計測・解析法の新展開(2))

Ultrasonic acoustic emission (AE) can be detected by an AE sensor at a stem of a plant when cavitation occurs in the xylem. Wideband acceleration sensor with high sensitivity was used for the measurement of AE at stem of miniature tomato in this study because of low cost compared to AE sensor. The waveforms obtained by acceleration sensor exhibited the center frequency which coincided with the resonant frequency of the sensor while the AE sensor delivered various waveforms. On the other hand, the sensitivity of AE detection by the acceleration sensor was almost same as that by the AE sensor. The both sensors showed that AE occurrence rate was higher at daytime than that at nighttime because the cavitation tended to occur at daytime. The both sensors exhibited the similar behavior of AE occurrence for 20 days. The low-cost acceleration sensor, therefore, has the possibility to apply AE measurement for health monitoring of tomato cultivation.

A Low Cost Tool for Diagnosis of Antifriction Bearings

Sound conducted through solids has been used to diagnose failures of machines for a long time. Many companies offer expensive equipment to measure and analyse vibrations. Faults in antifriction bearings can be detected at an early stage of failure using this equipment In this paper the effect of faults in antifriction bearings on signal analysis methods will be discussed. The results lead to a new tool for low cost diagnostic equipment which is based on enveloped signals and uses a low cost acceleration sensor.