Back Frame Research Articles

Analysis of Temperature Field of Very Large Aperture Radio Telescope

With the increase of antenna aperture and frequency, the influence of solar heat on its performance becomes more and more serious. In this paper, the thermal model of the 110 m aperture radio telescope to be built in Xinjiang is established to study its temperature field characteristics on the summer solstice. The results are as follows: during the day, the highest temperature of the main reflector can reach 42.86∘C, which appears at 14 o’clock, and the temperature of the legs also reaches the peak of 41.74∘C at the same time. The horizontal temperature difference of the back frame will exceed 1∘C at 5, 18, and 19.5 o’clock, the antenna pointing performance will be greatly affected. The temperature field at night is also not uniform, and the temperature difference of the pitching structure is significantly higher than that of other components, with the maximum temperature difference of 6.42∘C. Through the method of numerical simulation and test, it is proved that the wall thickness difference of components is the main reason for the large temperature difference at night.

A Vascular Feature Detection and Matching Method Based on Dual-Branch Fusion and Structure Enhancement.

How to obtain internal cavity features and perform image matching is a great challenge for laparoscopic 3D reconstruction. This paper proposes a method for detecting and associating vascular features based on dual-branch weighted fusion vascular structure enhancement. Our proposed method is divided into three stages, including analyzing various types of minimally invasive surgery (MIS) images and designing a universal preprocessing framework to make our method generalized. We propose a Gaussian weighted fusion vascular structure enhancement algorithm using the dual-branch Frangi measure and MFAT (multiscale fractional anisotropic tensor) to address the structural measurement differences and uneven responses between venous vessels and microvessels, providing effective structural information for vascular feature extraction. We extract vascular features through dual-circle detection based on branch point characteristics, and introduce NMS (non-maximum suppression) to reduce feature point redundancy. We also calculate the ZSSD (zero sum of squared differences) and perform feature matching on the neighboring blocks of feature points extracted from the front and back frames. The experimental results show that the proposed method has an average accuracy and repeatability score of 0.7149 and 0.5612 in the Vivo data set, respectively. By evaluating the quantity, repeatability, and accuracy of feature detection, our method has more advantages and robustness than the existing methods.

Blowout Fluid Velocity Measurement Method based on High-speed Sequence Images

Given the high-temperature and high-pressure environment after the blowout, the staff usually cannot calculate and analyze various blowout parameters at close range and thus take effective measures to control accidents quickly. In this paper, a blowout fluid velocity measurement method is proposed based on high-speed sequence images, and simulation experiments are conducted. The scene conditions of blowout accidents are simulated and analyzed. On this basis, cameras are adopted to shoot a large number of simulated blowout fluid videos from different angles under outdoor conditions. Afterward, the video is converted into a multi-frame image, and the blowout fluid image feature point detection and extraction model are established based on the orb (oriented fast and rotated brief) algorithm. On the feature points extracted by the model, the gms algorithm is used to match the features of the blowout fluid images in the front and back frames. Additionally, the wrong matching points are eliminated using the ransac (random sample consensus) algorithm, and the obtained feature point pairs are employed into the flow velocity calculation model for flow velocity calculation. The results demonstrate that the measured fluid velocity is more accurate. The method proposed in this study can provide reliable data support for early blowout emergency rescue.

Dynamic characteristics of a compliant seat coupled with the human body and a manikin during the exposure to the whole-body vibration: effect of the polyurethane foam, the track position and the measurement location.

Transmissibility is used to assess dynamic responses of the occupant-seat system, and most studies have exclusively assessed the transmissibility from the floor to the cushion or the backrest surface with the human body. In this investigation, the vertical vibration transmitted from the floor to six specific locations both on the seat surface and the frame when the seat was fixed on three positions on the track was examined utilizing an SAE J826 manikin and 12 male adults (0.25 to 20 Hz) for a duration of 120 seconds at three vibration amplitudes. The transmissibility from the floor to the headrest frame, the cushion surface, the headrest surface, the seat back frame, and the seat back surface all exhibited a principal peak frequency within 4-5 Hz. With the exception of the cushion frame, the principal peak frequency and the peak transmissibility in transmissibilities to all positions decreased with increasing vibration amplitude, indicating the non-linearity within the occupant-seat system. It was also found modifying seat track positions minimally affected the seat transmissibility to either the surface or the frame of the seat. Polyurethane foam amplified vibration at peak frequency, simultaneously enhancing static sitting comfort and reducing the vertical vibration transmission above peak frequency.

Parametric Design and Shape Sensing of Geared Back Frame Shell Structure for Floating Cylindrical Reflector Antenna off the Coast

At present, numerous reflector antennas have been constructed worldwide on land. However, there are few applications of reflector antennas directly set off the coast. To expand the application region of reflector antennas, a floating cylindrical reflector antenna (FCRA) driven by the moving mass was developed to implement the elevation angle adjustment. Firstly, the structure design is introduced in detail. The design parameters are stated and analyzed to obtain the kinematic relationship while considering the water surface constraint. Then, the effects of each variable on the rotation capacity and structural stability are discussed. Further, the feasibility of the elevation angle adjustment process is demonstrated by using a prototype model test and software simulation. Finally, the deformation analyses and shape sensing of the back frame are carried out on the basis of the inverse finite element method (iFEM). We concluded that this new structure is feasible and expected to sit off the coast. In addition, the iFEM algorithm with sub-region reconstruction was proved to be suitable for the shape sensing of the over-constrained FCRA during the angle adjustment process via several quasi-static sampling moments.

Using the Optical Pointing System to Build the Pointing Model of the Tianma 13 m Telescope

This paper describes the method of using the optical telescope to assist the Tianma 13 m radio telescope for pointing measurement and establishing the pointing error correction model. For small-aperture telescopes, there are few target sources for pointing and calibration, and it is difficult to establish a pointing model by radio method to cover the whole sky area. The Tianma 13 m radio telescope of Shanghai Astronomical Observatory is used to conduct optical-assisted pointing measurement research. A set of optical pointing system was installed on the back frame of Tianma 13 m antenna, which obtained a repeatable measurement accuracy better than 3”. In addition, through the analysis of the factors affecting the antenna pointing, a pointing error correction model containing 8 error terms, as well as the optical axis and electrical axis deviation models were established. The pointing model was brought into the antenna servo control system to cross-scan the calibration target radio source, and a pointing error of about 5” was obtained. This research can provide a reference method for high-precision pointing modeling.

Real-Time Traffic Flow Statistics Based on Dual-Granularity Classification

Article Real-Time Traffic Flow Statistics Based on Dual-Granularity Classification Yanchao Bi, Yuyan Yin, Xinfeng Liu *, Xiushan Nie, Chenxi Zou, and Junbiao Du 1 School of Computer Science and Technology, Shandong Jianzhu University, Jinan 250101, China * Correspondence: liuxinfeng18@sdjzu.edu.cn Received: 17 June 2023 Accepted: 13 September 2023 Published: 26 September 2023 Abstract: Traffic detection devices can cause accuracy degradation over time. Considering problems such as time-consuming and laborious manual statistics, high misdetection probabilities, and model tracking failures, there is an urgent need to develop a deep learning model (which can stably achieve detection accuracy over 90%) to evaluate whether the device accuracy still satisfies the requirements or not. In this study, based on dual-granularity classification, a real-time traffic flow statistics method is proposed to address the above problems. The method is divided into two stages. The first stage uses YOLOv5 to acquire all the motorized and non-motorized vehicles appearing in the scene. The second stage uses EfficientNet to acquire the motorized vehicles obtained in the previous stage and classify such vehicles into six categories. Through this dual-granularity classification, the considered problem is simplified and the probability of false detection is reduced significantly. To correlate the front and back frames of the video, vehicle tracking is implemented using DeepSORT, and vehicle re-identification is implemented in conjunction with the ResNet50 model to improve the tracking accuracy. The experimental results show that the method used in this study solves the problems of misdetection and tracking effectively. Moreover, the proposed method achieves 98.7% real-time statistical accuracy by combining the two-lane counting method.

Deployable structure based on double-layer Miura-ori pattern

With the requirements for improvement of earth observation range and accuracy, large-scale two-dimensional deployable antennas are urgently needed. In this paper, a deployable structure for a planar antenna with one degree of freedom and a flat reflection surface that can realize two-dimensional deployment with a compatible back frame is proposed based on a double-layer Miura-ori pattern. First, an antenna folding scheme with rectangular facets is proposed with the Miura-ori pattern. Through the method for hinge removal and replacement, a deployable antenna mechanism with a flat reflection surface is accomplished. Then, a kinematic model of the deployable structure is established to analyze its kinematic characteristics and prove the equivalence of motion before and after changing the hinges. By converting the rotating pairs between the two layers of origami into cylindrical pairs, a thick-panel form of double-layer origami is constructed. On this basis, a compatible back frame for the planar antenna mechanism is designed and a corresponding prototype is fabricated. The work paves the way to design deployable structures.

A Novel Unsupervised Video Anomaly Detection Framework Based on Optical Flow Reconstruction and Erased Frame Prediction.

Reconstruction-based and prediction-based approaches are widely used for video anomaly detection (VAD) in smart city surveillance applications. However, neither of these approaches can effectively utilize the rich contextual information that exists in videos, which makes it difficult to accurately perceive anomalous activities. In this paper, we exploit the idea of a training model based on the "Cloze Test" strategy in natural language processing (NLP) and introduce a novel unsupervised learning framework to encode both motion and appearance information at an object level. Specifically, to store the normal modes of video activity reconstructions, we first design an optical stream memory network with skip connections. Secondly, we build a space-time cube (STC) for use as the basic processing unit of the model and erase a patch in the STC to form the frame to be reconstructed. This enables a so-called "incomplete event (IE)" to be completed. On this basis, a conditional autoencoder is utilized to capture the high correspondence between optical flow and STC. The model predicts erased patches in IEs based on the context of the front and back frames. Finally, we employ a generating adversarial network (GAN)-based training method to improve the performance of VAD. By distinguishing the predicted erased optical flow and erased video frame, the anomaly detection results are shown to be more reliable with our proposed method which can help reconstruct the original video in IE. Comparative experiments conducted on the benchmark UCSD Ped2, CUHK Avenue, and ShanghaiTech datasets demonstrate AUROC scores reaching 97.7%, 89.7%, and 75.8%, respectively.

Vulnerability assessment of RC buildings with irregularities using probabilistic analysis

Modern construction comprises of large number of reinforced concrete structures with geometric irregularities. Even though these types of structures have good serviceability and aesthetic appearance, such structures show high vulnerability during earthquakes. The present study investigates the performance of multistorey RC buildings, with different irregularities under seismic excitations, using Pushover analysis. Fragility curve, defined as the probability of reaching or exceeding of a specific damage state under a seismic excitation, provides an estimate of possible damage during occurrence of an earthquake. Four structural models of multi storey reinforced concrete buildings with different configurations consisting of bare frame with plan irregularity, setback frame, set back frame with shear wall without openings and set back frame with shear wall with openings are considered. Three-dimensional models of the structures with different geometric irregularity are generated and pushover analysis of each model is carried out using the software ETABS. The capacity curves generated using pushover analysis are transformed into bilinear curves and the roof displacement at the yield and ultimate levels are obtained. The procedure asper ATC-40 is followed to find the performance point from this nonlinear analysis. Later the damage probability is calculated based on the damage state levels, and curves of fragility are generated. To quantify the damage of the structure using fragility curve, damage state levels are fixed as Slight, Moderate, Extreme and Collapse Damage Level. The results of pushover analysis indicate the effect of enhancement of the stiffness of the setback frame by providing shear wall without openings, but no significant effect in terms of stiffness and ductility while including shear wall with openings. Based on the damage state level chosen and fragility analysis of the four structural models, the structural system with setback frame with shear wall without openings has shown better performance.

Survey on IOT-based smart mirror with temperature and news

In earlier days, data was accessible through our electronic devices. Our device is similar to the daily mirror, but with advanced technology like displaying the weather forecast, temperature, time, and daily news. Using the Raspberry Pi, data will be displayed on the device. Our planned system permits us to build such mirrors that mirror to receive online news and display the mirror with present temperature, and weather reports. Our device makes use of a raspberry pi primarily based on a total processor board along with presentations that can be interfaced together. We tend to use an exactly modeled panel to construct the outer frame. Then we use specialized glass with a back frame to enclose the system. The frame cavity is currently fitted with precisely positioned mounts for the display housing to be fitted in the mirror. This is often necessary to achieve the desired effect. Currently, we use the raspberry pi to attach web victimization to an IOT circuit through the employment of a Wi-Fi module.

Local Path Planning of Autonomous Vehicle Based on an Improved Heuristic Bi-RRT Algorithm in Dynamic Obstacle Avoidance Environment.

The existing variants of the rapidly exploring random tree (RRT) cannot be effectively applied in local path planning of the autonomous vehicle and solve the coherence problem of paths between the front and back frames. Thus, an improved heuristic Bi-RRT algorithm is proposed, which is suitable for obstacle avoidance of the vehicle in an unknown dynamic environment. The vehicle constraint considering the driver’s driving habit and the obstacle-free direct connection mode of two random trees are introduced. Multi-sampling biased towards the target state reduces invalid searches, and parent node selection with the comprehensive measurement index accelerates the algorithm’s execution while making the initial path gentle. The adaptive greedy step size, introducing the target direction, expands the node more effectively. Moreover, path reorganization minimizes redundant path points and makes the path’s curvature continuous, and path coherence makes paths between the frames connect smoothly. Simulation analysis clarifies the efficient performance of the proposed algorithm, which can generate the smoothest path within the shortest time compared with the other four algorithms. Furthermore, the experiments on dynamic environments further show that the proposed algorithm can generate a differentiable coherence path, ensuring the ride comfort and stability of the vehicle.

Back Frame Optimization of a Large Radio Telescope Based on Force Cone Method

A new research perspective is proposed to optimize the topology of truss structure by force cone method, which involves force cone drawing rules and growth rules. Through the comparison with the mature variable density topology optimization method, the effectiveness of force cone method is verified. This kind of new method is simple and easy to understand (no need to master complex structural optimization design theory). Besides, it is time-saving in finite element calculations, and can obtain an optimized truss layout easily. By drawing the force cone, its application on a large radio telescope's back frame structure shows that, compared with the existing one in terms of structural stiffness, Root Mean Square (RMS) precision, and beam stress distribution, the optimized back frame using the force cone method has higher stiffness, better RMS, more uniform stress, and lighter weight.

VSLAM method based on object detection in dynamic environments.

Augmented Reality Registration field now requires improved SLAM systems to adapt to more complex and highly dynamic environments. The commonly used VSLAM algorithm has problems such as excessive pose estimation errors and easy loss of camera tracking in dynamic scenes. To solve these problems, we propose a real-time tracking and mapping method based on GMM combined with YOLOv3. The method utilizes the ORB-SLAM2 system framework and improves its tracking thread. It combines the affine transformation matrix to correct the front and back frames, and employs GMM to model the background image and segment the foreground dynamic region. Then, the obtained dynamic region is sent to the YOLO detector to find the possible dynamic target. It uses the improved Kalman filter algorithm to predict and track the detected dynamic objects in the tracking stage. Before building a map, the method filters the feature points detected in the current frame and eliminates dynamic feature points. Finally, we validate the proposed method using the TUM dataset and conduct real-time Augmented Reality Registration experiments in a dynamic environment. The results show that the method proposed in this paper is more robust under dynamic datasets and can register virtual objects stably and in real time.

Octave convolution-based vehicle detection using frame-difference as network input

Vehicle detection in video frames has been treated the same way detecting vehicle for an isolated image. However, the models designed for the isolated image are blind to fast-moving vehicles and cannot localize the moving targets partially occluded in the scene. In this case, we figure out a way to combine the classic moving target detection method with the neural network method. In this work, first, we propose to add three-differential-frames into the neural network of Yolov3 as the second input which contains the motion information on the front and back frames to detect vehicles partially occluded; second, we reform the network by using Octave Convolution to reduce memory and computational cost while boosting accuracy. We experimentally show that by using the aforementioned methods together, compared with using original YOLOv3 on UA-DETRAC data set, AP is increased by 2.31%, recall is increased by 4.01%, and precision is increased by 3.10%. We demonstrate that the proposed method is indeed effective.

Insulation Performance Comparison of Curtain Wall Systems with Existing Pipe Frames and Truss-Shaped Insulation Frames

The purpose of this study was to compare insulation performance between a base case that applied the existing steel pipe frame and an alternative case that reduced thermal bridging by applying a truss-shaped insulation frame (TIF) to a back frame type curtain wall. Insulation performance was compared by obtaining the effective U-factor and the lowest indoor surface temperature through a three-dimensional steady-state heat transfer simulation. In addition, mock-up tests were performed to compare the U-factors of the base case and alternative case. The simulation results showed that the effective U-factor of the alternative case was 36% lower than in the base case, a significant heat loss reduction. The lowest indoor surface temperature of the alternative case was 0.5 °C higher than in the base case, showing that the surface condensation risk also decreased. In the mock-up test results, the alternative case U-factor was 33% lower than in the base case, confirming the associated large heat loss reduction. For the base case, both the effective U-factor by simulation and the U-factor by the mock-up test were much higher than the design U-factor according to the Korean Design Standard, which neglects thermal bridging, indicating a significantly increased heat loss caused by this factor. For the alternative case, however, both U-factors were similar to the design U-factor.

Optimization of 110 m Aperture Fully Steerable Radio Telescope Prestressed Back Frame Structure Based on a Genetic Algorithm

Radio telescopes play an important role in lunar exploration projects, manned space flight projects, and navigation systems. China is constructing a giant 110 m aperture ground‐based fully steerable radio telescope in Qitai County, Xinjiang Uygur Autonomous Region. In this paper, a 110 m aperture fully steerable radio telescope prestressed back frame structure is proposed and optimized to improve the reflector accuracy and to reduce the weight of the telescope. First, prestressed cables are introduced into the back frame structure, and three innovative cable layout schemes are presented. Second, for stress state analysis, the wind pressure distribution on the main reflector is explored using wind tunnel experiments. Third, some improvements in genetic algorithms for addressing computational complexity are explained. Finally, the effects of prestressed cables on the weight reduction and reflector accuracy improvement are analysed. Additionally, in order to evaluate the safety of the prestressed back frame structure, its strength has been checked, and the internal force and displacement under static conditions and in earthquakes are interpreted in detail.

Durability Analysis of Automotive Seat According to the Shape of Seat Back Frame

Durability Analysis of Automotive Seat According to the Shape of Seat Back Frame

적합 브라켓 장착을 위한 레져 차량용 리어 시트 백 프레임의 러기지 리텐션 시뮬레이션 활용

적합 브라켓 장착을 위한 레져 차량용 리어 시트 백 프레임의 러기지 리텐션 시뮬레이션 활용

Structure design of LFT passenger car seat structure based on topology optimisation

The newly revised GB 13057-2014 ‘The strength of the seats and their anchorages of passenger vehicles’ replaces the static test with a dynamic test, which puts forward higher requirements on seat safety. Considering safety and lightweight design, the LFT (Long glass Fiber reinforced Thermoplastic) is used to replace the original steel seat back frame. Combined with energy absorption model and topology optimisation, the force transmission path and detail structure design under both the forward loading and rearward loading conditions are carried out. In order to analyse the occupant protection performance, numerical models of composite seat and HybridIII dummy are established, and the safety and lightweight effect of LFT seat back frame are optimised and verified.