Enhanced Attitude and Altitude Estimation for Indoor Autonomous UAVs

In recent years the use of Unmanned Aerial Vehicles (UAVs) has considerably grown in the civil sectors, due to their high flexibility of use. Currently, two important key points are making them more and more successful in the civil field, namely the decrease of production costs and the increase in navigation accuracy. In this paper, we propose a Kalman filtering-based sensor fusion algorithm, using a low cost navigation platform that contains an inertial measurement unit (IMU), five ultrasonic ranging sensors and an optical flow camera. The aim is to improve navigation in indoor or GPS-denied environments. A multi-rate version of the Extended Kalman Filter is considered to deal with the use of heterogeneous sensors with different sampling rates, and the presence of non-linearities in the model. The effectiveness of the proposed sensor platform is evaluated by means of numerical tests on the dynamic flight simulator of a quadrotor. Results show high precision and robustness of the attitude estimation algorithm, with a reduced computational cost, being ready to be implemented on low-cost platforms.

Solving Multiple Triggering Problem of Ultrasonic Distance Measurement by Debouncing

In recent years, multiple measurement systems fusion technologies have developed rapidly. Ultrasonic ranging is paid much attention because it has the advantages of directly measuring short-distance targets, high longitudinal resolution, and a wide application range. However, when the ultrasonic distance measurement is carried out by assembling the circuit board, it is found that the switch is triggered multiple times, and the measurement data is inaccurate. This paper proposes a new method that adding debounce to improve the accuracy of measurement. Besides, Some suggestions are provided to decrease the operation difficulty in the actual measurement process. Based on the experimental result, the accuracy and efficiency of ultrasonic distance measurement are greatly improved via this method proposed in this paper. By the way, the single-chip computer simulation technology simulates the ranging phenomenon in the experiment.

Acoustic Simulation for Performance Evaluation of Ultrasonic Ranging Systems

The recent growing interest in indoor positioning applications has paved the way for the development of new and more accurate positioning techniques. The envisioned applications, include people and asset tracking, indoor navigation, as well as other emerging market applications, require fast and precise positioning. To this end, the effectiveness and high accuracy and refresh rate of positioning systems based on ultrasonic signals have been already demonstrated. Typically, positioning is obtained by combining multiple ranging. In this work, it is shown that the performance of a given ultrasonic airborne ranging technique can be thoroughly analyzed using renowned academic acoustic simulation software, originally conceived for the simulation of echographic transducers and systems. Here, in order to show that the acoustic simulation software can be profitably applied to ranging systems in air, an example is provided. Simulations are performed for a typical ultrasonic chirp, from an ultrasound emitter, in a typical office room. The ranging performances are evaluated, including the effects of acoustic diffraction and air frequency dependent absorption, when the signal-to-noise ratio (SNR) decreases from 30 to −20 dB. The ranging error, computed over a point grid in the space, and the ranging cumulative error distribution is shown for different SNR levels. The proposed approach allowed us to estimate a ranging error of about 0.34 mm when the SNR is greater than 0 dB. For SNR levels down to −10 dB, the cumulative error distribution shows an error below 5 mm, while for lower SNR, the error can be unlimited.

A System in Package Based on a Piezoelectric Micromachined Ultrasonic Transducer Matrix for Ranging Applications

This paper proposes a system in package (SiP) for ultrasonic ranging composed of a 4 × 8 matrix of piezoelectric micromachined ultrasonic transducers (PMUT) and an interface integrated circuit (IC). The PMUT matrix is fabricated using the PiezoMUMPS process and the IC is implemented in the AMS 0.35 µm technology. Simulation results for the PMUT are compared to the measurement results, and an equivalent circuit has been derived to allow a better approximation of the load of the PMUT on the IC. The control circuit is composed of a high-voltage pulser to drive the PMUT for transmission and of a transimpedance amplifier to amplify the received echo. The working frequency of the system is 1.5 MHz.

LPWAN in Civil Engineering

Wave overtopping is a dangerous phenomenon that, in a port environment, takes place when waves that are higher than the port's breakwater meet it and water passes over the structure. This event can lead to property damage or physical harm to port workers. It is difficult to detect an overtopping, so this chapter proposes a solution to the overtopping detection problem by describing the design and development of a system that can detect an overtopping event in real-time and in a real environment. To achieve this goal, the proposed overtopping detection system is based on devices that use ultrasonic ranging sensors and communicate using the Sigfox low-power wide-area network, together with a backend that processes the data the devices send, issuing alerts to inform the interested parties that an overtopping took place.

Metal Roof Fault Diagnosis Method Based on RBF-SVM

Metal roof enclosure system is an important part of steel structure construction. In recent years, it has been widely used in large-scale public or industrial buildings such as stadiums, airport terminals, and convention centers. Affected by bad weather, various types of accidents on metal roofs frequently occurred, causing huge property losses and adverse effects. Because of wide span, long service life and hidden fault of metal roof, the manual inspection of metal roof has low efficiency, poor real-time performance, and it is difficult to find hidden faults. On the basis of summarizing the working principle of metal roof and cause of accidents, this paper classifies the fault types of metal roofs in detail and establishes a metal roof monitoring and fault diagnosis system using distributed multisource heterogeneous sensors and Zigbee wireless sensor networks. Monitoring data from strain gauge, laser ranging sensor, and ultrasonic ranging sensor is utilized comprehensively. By extracting time domain feature, the data trend characteristics and correlation characteristics are analyzed and fused to eliminate erroneous data and find superficial faults such as sensor drift and network interruption. Aiming to the hidden faults including plastic deformation and bolt looseness, an SVM fault diagnosis algorithm based on RBF kernel function is designed and applied to diagnose metal roof faults. The experimental results show that the RBF-SVM algorithm can achieve high classification accuracy.