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The rocket sled, as a ground dynamic test system, combines the characteristics of the wind tunnel test and the flight test. However, some practical factors, such as shock wave interference, ground effect, and high-intensity aerodynamic noise will cause serious interference and even failure of the uniformly distributed sensors during horizontal sliding in a wide speed range. The AGARD HB-2 standard model is employed as the payload to simulate the aerodynamic and aeroacoustic characteristics during the variable acceleration period, aiming to optimize the test sensors layout. It is observed that in the high Mach number flow fields, strong coupling behaviors among complex waves will occur. The peak of wake vortex strength will appear at 1.5 s and gradually diminish over time. In addition, when the vortex between the load and the booster is monitored, its position shifts forward in the subsonic stage, then gradually moves backward and expands in the supersonic stage. Acoustic directivity is pronounced at subsonic and transonic speeds, pointing towards 75° and 135° relative to the sliding speed, respectively. These results can provide technical support for sensor layout and high-precision testing in rocket sled tests. [ABSTRACT FROM AUTHOR]

Deep learning models have been widely used in data-driven bridge structural damage diagnosis methods in recent years. However, these methods require training and test datasets to satisfy the same distribution, which is difficult to satisfy in practice. Domain adaptation transfer learning is an efficient method to solve this problem. Most of the current domain adaptation methods focus on close-set scenarios with the same classes in the source and target domains. However, in practical applications, new damage caused by long-term degradation often makes the target and source domains dissimilar in the class space. For such challenging open-set scenarios, existing domain adaptation methods will be powerless. To effectively solve the above problems, an adversarial auxiliary weighted subdomain adaptation algorithm is proposed for open-set scenarios. Adversarial learning is introduced to proposed an adversarial auxiliary weighting scheme to reflect the similarity of target samples with source classes. It effectively distinguishes unknown damage from known states. This paper further proposes a multi-channel multi-kernel weighted local maximum mean discrepancy metric (MCMK-WLMMD) to capture the fine-grained transferable information for conditional distribution alignment (sub-domain alignment). Extensive experiments on transfer tasks between three bridges verify the effectiveness of the algorithm in open-set scenarios. [ABSTRACT FROM AUTHOR]

The rapid development of the aviation industry has put forward higher and higher requirements for material properties, and the research on smart material structure has also received widespread attention. Smart materials (e.g., piezoelectric materials, shape memory materials, and giant magnetostrictive materials) have unique physical properties and excellent integration properties, and they perform well as sensors or actuators in the aviation industry, providing a solid material foundation for various intelligent applications in the aviation industry. As a popular smart material, piezoelectric materials have a large number of application research in structural health monitoring, energy harvest, vibration and noise control, damage control, and other fields. As a unique material with deformation ability, shape memory materials have their own outstanding performance in the field of shape control, low-shock release, vibration control, and impact absorption. At the same time, as a material to assist other structures, it also has important applications in the fields of sealing connection and structural self-healing. Giant magnetostrictive material is a representative advanced material, which has unique application advantages in guided wave monitoring, vibration control, energy harvest, and other directions. In addition, giant magnetostrictive materials themselves have high-resolution output, and there are many studies in the direction of high-precision actuators. Some smart materials are summarized and discussed in the above application directions, aiming at providing a reference for the initial development of follow-up related research. [ABSTRACT FROM AUTHOR]

The applications of sensors in the aerospace industry are mostly concentrated in the middle and high frequencies, and low-frequency sensors often face the problems of low power and short working bandwidth. A lightweight, thin, high-power, low-frequency broadband transducer based on giant magnetostrictive material is designed. The design and optimization processes of the core components are introduced and analyzed emphatically. The finite element simulation results are validated by the PSV-100 laser vibration meter. Three basic configurations of the work panel are proposed, and the optimal configuration is determined by modal, acoustic, and vibration coupling analyses. Compared with the original configuration, it is found that the lowest resonant frequency of the optimal configuration is reduced by 24.6% and the highest resonant frequency within 2000 Hz is 1744.9 Hz, which is 54.2% higher than that of the original configuration. This greatly improves the vibration power and operating frequency range of the transducer. Then, the honeycomb structure is innovatively applied to the work panel, and it is verified that the honeycomb structure has a great effect on the vibration performance of the work panel. By optimizing the size of the honeycomb structure, it is determined that the honeycomb structure can improve the vibration power of the work panel to its maximum value when the distance between the half-opposite sides of the hexagon is H = 3.5 mm. It can reduce the resonant frequency of the work panel; the lowest resonant frequency is reduced by 12.8%. At the same time, the application of a honeycomb panel structure can reduce the weight of the transducer. [ABSTRACT FROM AUTHOR]

Piezoelectric ceramics are inexpensive functional materials which are widely used in sonar detection, home appliances, meteorological detection, telemetry and environmental protection and other applications. Sensors fabricated from these materials are compact and have fast response characteristics. Their underlying functional methodology is based on the direct piezoelectric effect whereby very small mechanical vibration signals are converted into electrical signals. Piezoelectric resonators are based on the reverse piezoelectric effect and they are widely used for the control of precision instruments and precision machinery, microelectronic components, bioengineering devices and other in applications requiring components to provide precision control of the relevant functional mechanism. In this paper, the structural evolution and design mechanism of sandwich resonators based on piezoelectric materials are reviewed, and the advantages and disadvantages of different structures are compared and analyzed. The goal is to provide a comprehensive reference for the selection, application and promotion of piezoelectric resonators and for future structural innovation and mechanism research relevant to sandwich resonators. [ABSTRACT FROM AUTHOR]

In the process of collaborative operation, the unloading automation of the forage harvester is of great significance to improve harvesting efficiency and reduce labor intensity. However, non-standard transport trucks and unstructured field environments make it extremely difficult to identify and properly position loading containers. In this paper, a global model with three coordinate systems is established to describe a collaborative harvesting system. Then, a method based on depth perception is proposed to dynamically identify and position the truck container, including data preprocessing, point cloud pose transformation based on the singular value decomposition (SVD) algorithm, segmentation and projection of the upper edge, edge lines extraction and corner points positioning based on the Random Sample Consensus (RANSAC) algorithm, and fusion and visualization of results on the depth image. Finally, the effectiveness of the proposed method has been verified by field experiments with different trucks. The results demonstrated that the identification accuracy of the container region is about 90%, and the absolute error of center point positioning is less than 100 mm. The proposed method is robust to containers with different appearances and provided a methodological reference for dynamic identification and positioning of containers in forage harvesting. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) is a very promising technology for the development of beyond 5G or 6G wireless communications due to its low complexity, intelligence, and green energy-efficient properties. In this paper, we combined IRS with physical layer security (PLS) to solve the security issue of cognitive radio (CR) networks. Specifically, an IRS-assisted multi-input single-output (MISO) CR wiretap channel was studied. To maximize the secrecy rate of secondary users subject to a total power constraint (TPC) for the transmitter and interference power constraint (IPC) for a single antenna primary receiver (PR) in this channel, an alternating optimization (AO) algorithm is proposed to jointly optimize the transmit covariance R at transmitter and phase shift coefficient Q at IRS by fixing the other as constant. When Q is fixed, R is globally optimized by equivalently transforming the quasi-convex sub-problem to convex one. When R is fixed, bisection search in combination with minorization–maximization (MM) algorithm was applied to optimize Q from the non-convex fractional programming sub-problem. During each iteration of MM, another bisection search algorithm is proposed, which is able to find the global optimal closed-form solution of Q given the initial point from the previous iteration of MM. The convergence of the proposed algorithm is analyzed, and an extension of applying this algorithm to multi-antenna PR case is discussed. Simulations have shown that our proposed IRS-assisted design greatly enhances the secondary user's secrecy rate compared to existing methods without IRS. Even when IPC is active, the secrecy rate returned by our algorithm increases with transmit power as if there is no IPC at all. [ABSTRACT FROM AUTHOR]

As an important development direction of star sensor technology, the All-Time star sensor technology can expand the application of star sensors to flight platforms inside the atmosphere. Due to intense atmospheric background radiation during the daytime, the commonly used star sensors operating in the visible wavelength range are significantly limited in their ability to detect stars, and hence the All-Time star sensor technology which is based on the shortwave infrared (SWIR) imaging system has become an effective research direction. All-Time star sensor detection capability is significantly affected by observation conditions and, therefore, an optimized selection of optical parameters, which mainly includes the field of view (FOV) and the detection wavelength band, can effectively improve the detection performance of All-Time star sensors under harsh observation conditions. This paper uses the model simulation method to analyze and optimize the optical parameters under various observation conditions in a high-altitude environment. A main parameter among those discussed is the analysis of detection band optimization based on the SWIR band. Due to the huge cost constraints of high-altitude experiments, we conducted experiments near the ground to verify the effectiveness of the detection band selection and the correctness of the SWIR star sensor detection model, which thereby proved that the optimization of the optical parameters for high altitudes was effective and could be used as a reference. [ABSTRACT FROM AUTHOR]

Based on traditional sandwich structure, two piezoelectric transducers were designed to meet the strict underwater application backgrounds such as high pressure, corrosion resistance, and high strength. Both transducers integrated most of previous researches while one transducer has a multilayer cavity structure which is different from the other structure and previous transducer structures. After a detailed simulation analysis of every structural parameter, key parameters were pointed out to have an obvious influence on its performance. Then, two models were constructed and compared with chosen sets of geometry parameters and manufacturing process, which can also provide a reference for low-frequency transducer design. The simulation results and experimental results of our transducers show a good consistency which indicates the cavity structure can reduce the resonance frequency. [ABSTRACT FROM AUTHOR]