In the process of aircraft design, various experiments are required to validate design parameters under real flight conditions. Such experiments are costly, and currently there are limited solutions for effectively dealing with scenarios such as occasional faults during these experiments. This paper proposes an on-board remote high-definition collaborative troubleshooting and flight decision-making assistance device, aiming to achieve efficient test scenario replication and decision support through remote collaboration between ground personnel and flight crew. The device utilizes several image capture devices in the cockpit and employs algorithms such as action recognition and image recognition. It utilizes highspeed satellite communication technology to structure flight data, including pilot operations, faults, and aircraft status, into a timeline script. Ground personnel can use this output script to provide corresponding solutions. Flight crew members receive real-time guidance and decision support through smart glasses. It is evaluated that this approach may save a significant amount of travel expenses and time in ground tests, flight tests, field fault diagnosis, and crew training scenarios. The innovation of the proposed device lies in the application of cloud servers for timeline script generation and the use of remote retrieval by monitoring personnel for key operation fault diagnosis. Furthermore, it incorporates intelligent recognition technology for flight guidance, enabling efficient troubleshooting and reducing the number of flight tests. Therefore, research and development costs could be reduced, and engineering change progress could be accelerated.
The airborne system architecture describes the cross-linking and hierarchical relationships and information interactions between the abstract functions and the physical implementation of the system. This study replaces the traditional empirical and document-based design of the object search and guidance function of aircraft with a model-based design based on the system modeling language. The correlation and traceability of the model help ensure the integrity and traceability of information in the design process. In addition, the design relationships between the functional and physical architectures of the model are used to validate this modeling and design approach.
The ELT (Emergency Locator Transmitter) is a device used to locate an aircraft in an emergency situation, such as an accident, in order to facilitate search and rescue efforts. Conventional ELT devices have two triggering methods, namely automatic triggering when crash acceleration is reached and manual triggering when a button on the control panel is pressed. This paper proposes an ELT triggering device based on fingerprint collection technology. By integrating the fingerprint collection device into the control button and cross-linking it with the on-board data link, the fingerprint of the triggering person is collected, stored, and compared, so as to make a judgement or seek evidence, which effectively solves the problem of false triggering of traditional triggering devices and provides a basis for subsequent investigation of emergency situations. Experiments and use case study validate the usefulness of this new device.
Today, with the proliferation of electronic system terminals and the ever-changing needs of people, a variety of reminder services have emerged, but existing reminder services are still mostly limited to smartphones, and smart wearable devices (such as smart watches with functions such as heart rate monitoring and alarms), and the relevant industries and markets are still expanding. This paper introduces a customized integrated smart carrier reminder platform, which, given the limitations of current carrier reminder functions, shifts the focus of innovation from the commonplace smartphones and wearable devices to not yet widely noticed carrier reminder services, and proposes an integrated, multifunctional smart reminder system; The idea is to receive information from the user through a variety of input methods (contact input, contactless input, programmed input, etc.), collect and process the data through a central processing system (internal and external sensors) and finally output the feedback (e.g. light, sound, smell, touch) from the output system. The advantage of this study over existing carrier alert services lies in its platform-based operation mode and high level of user interactivity. A use case is demonstrated to verify the usefulness of the proposed system.
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