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Circularly and elliptically polarized high-order harmonics have unique advantages when used in studying the chiral and magnetic features of matters. Here, we studied the polarization properties of high-order harmonic generated from alignment nitrogen molecules driven by cross-linearly-polarized two-color laser fields. Through adjusting various laser parameters and targets, such as the relative phase, the crossing angle, the intensity ratio of driving fields, and the molecular alignment angle, we obtained highly elliptically polarized high-order harmonics with the same helicity in a wide spectral range. It provides a possible and effective way to generate elliptically polarized attosecond pulses. Finally, we show the probability of controlling the spectral range of elliptically polarized harmonics.

Combining the characteristics of the existing transfer slideway and double-point hanging type two retractable devices, this paper proposes a multiple-point hoisting, fast transfer, and retractable device. According to the viscous flow theory, one-way fluid-structure interaction simulation is used for the gondola structure of the unmanned boat retractable device. Considering the influencing factors of the width of the gondola, the void ratio, the shape and distribution of the void, and the deployment angle of the guardrail, the navigation water resistance of each model is compared and analyzed, and the optimal design of the gondola device is discussed. The results show that the increase of the top width and the decrease of the front-end void ratio will lead to an increase in the water resistance of the gondola; under the same porosity, the rectangular shape performs better than the circular shape, and the smaller interval between the rectangles is more conducive to reducing the water resistance of the gondola; the increase in the angle of the side door guardrail of the gondola will lead to an increase in the navigation water resistance; the final optimized design of the gondola device meets the strength requirements under extreme conditions of high sailing speed.

The development of quantum optics theory based on the method of integration within an ordered product of operators (IWOP) has greatly stimulated the study of quantum states in the light field, especially non-Gaussian states with various non-classical properties. In this paper, the two-mode squeezing operator is derived with integral theory within the Weyl ordering product of operators using a combinatorial field in which one mode is a chaotic field and the other mode is a vacuum field. The density operator of the new light field, its entanglement property and photon number distribution are analyzed. We also note that tracing a three-mode pure state can yield this new light field. These methods represent a theoretical approach to investigating new density operators of light fields.

In our previous papers, the classical fractional Fourier transform theory was incorporated into the quantum theoretical system using the theoretical method of quantum optics, and the calculation produced quantum mechanical operators corresponding to the generation of fractional Fourier transform. The core function of the coordinate–momentum exchange operators in the addition law of fractional Fourier transform was analyzed too. In this paper, the bivariate operator Hermite polynomial theory and the technique of integration within an ordered product of operators (IWOP) are used to establish the entanglement fractional Fourier transform theory to the extent of quantum. A new function generating formula and an operator for generating quantum entangled fractional Fourier transform are obtained using the fractional Fourier transform relationship in a pair of conjugated entangled state representations.

Arrhythmia and other diseases are puzzling more and more people. Accurate detection is the key to realizing intelligent diagnosis of electrocardiogram(ECG) monitoring systems. It can prevent heart disease and effectively reduce mortality. An efficient and accurate arrhythmia detection method is urgent. In this work, a real-time automatic arrhythmia detection technology based on extreme gradient boosting (XGboost) and convolutional neural network (CNN) algorithm were developed. First, ECG signals in the MIT-BIH Arrhythmia database are preprocessed: 1) EMG interference filtering; 2) Power frequency interference suppression; 3) Baseline drift correction. Secondly, We use the cyclic singular spectrum (CISSA) algorithm to decompose the ECG after pretreatment. From the original ECG and the 7 simple signals obtained from decomposition, 23 features about the time domain, frequency domain, nonlinear dynamics and statistics are extracted respectively. Finally, XGboost and CNN algorithms are used to build a classification model, and the extracted features are classified, trained and recognized to achieve automatic detection of arrhythmia. The experimental results show that XGboost and CNN algorithms can automatically detect 98.40%, 95.65% and 97.60%, 95.12% of Category 2 and Category 4 arrhythmias, respectively.

Multicomponent superconductors exhibit nontrivial vortex behaviors due to the various vortex–vortex interactions, including the competing one in the recently proposed type-1.5 superconductor. However, potential candidate that can be used to study the multicomponent superconductivity is rare. Here, we prepared an artificial superconducting multilayer to act as an alternative approach to study multicomponent superconductivity. The additional repulsive length and the coupling strength among superconducting films were regulated by changing the thickness of the insulting layer. The magnetization measurements were performed to clarify the effect of the competition between the repulsive vortex interactions on the macroscopic superconductivity. The vortex phase diagram and the optimum critical current density have been determined. Furthermore, a second magnetization effect is observed, and is attributed to the upper layer, which provides the weak pinning sites to localize the flux lines. The pinning behaviors switches to the mixed type with the increase of the insulting layer thicknesses. Our results open a new perspective to the study and related applications of the multilayer superconducting systems.

This paper proposes a method to predict the charging load demand of electric vehicles considering the spatial and temporal distribution characteristics of users’ travel. Based on the central limit theorem and travel chain theory, the temporal distribution of the charging load of different functional sites is simulated by the Monte Carlo method and calculated by combining NHTS2017 data to find the total daily charging load of electric private vehicles. The results show that in the case of disorderly charging, the charging loads of different areas have more obvious temporal characteristics, and the charging service can be optimized according to this charging load characteristic.

In this study, on the basis of the SD (smooth and discontinuous) oscillator, we analyze the sliding bifurcations of a two DOF self-excited system driven by the classical conveyor belt friction. In order to elaborate the nonsmooth model named the self-excited SD oscillator, we model the friction of the conveyor belt of this system as Coulomb friction. Switching surfaces and sliding regions of this nonsmooth system are obtained based on the Filippov theory. The numerical simulations are performed to present the various scenarios of sliding bifurcation and chaotic attractors in the system. The results of this study give us an opportunity to understand clearly the bifurcation mechanism of the rich nonlinear frictional dynamics in machinery field.

We theoretically investigate the frustrated double ionization (FDI) of molecules with different alignment-dependence using a three-dimensional classical ensemble method. The numerical results show that the FDI probability decreases with increasing wavelength, which is similar to the wavelength dependence of the FDI probability of atoms. Tracing the classical trajectories reveals that the contributions to molecular FDI from single-recollision and multiple-recollision mechanisms are equal in the short wavelength regime. In the long wavelength regime, the single-recollision FDI channel dominates in FDI. The nature in which molecular FDI occurs is identified and explained.

Understanding the temperature structure of protoplanetary disks is key to interpreting observations, predicting the physical and chemical evolution of the disk, and modeling planet formation processes. In this study, we constrain the two-dimensional thermal structure of the disk around Herbig Ae star HD 163296. Using the thermo-chemical code RAC2D, we derive a thermal structure that reproduces spatially resolved ALMA observations (~0.12 arcsec (13 au) - 0.25 arcsec (26 au)) of CO J = 2-1, 13CO J = 1-0, 2-1, C18O J = 1-0, 2-1, and C17O J = 1-0, the HD J = 1-0 flux upper limit, the spectral energy distribution (SED), and continuum morphology. The final model incorporates both a radial depletion of CO motivated by a time scale shorter than typical CO gas-phase chemistry (0.01 Myr) and an enhanced temperature near the surface layer of the the inner disk (z/r, 15 pages + 11 pages of appendix, accepted to ApJS, part of MAPS collaboration

Deuterium fractionation is dependent on various physical and chemical parameters. Thus, the formation location and thermal history of material in the solar system is often studied by measuring its D/H ratio. This requires knowledge about the deuteration processes operating during the planet formation era. We aim to study these processes by radially resolving the DCN/HCN (at 0.3" resolution) and N$_2$D$^+$/N$_2$H$^+$ (0.3 to 0.9") column density ratios toward the five protoplanetary disks observed by the Molecules with ALMA at Planet-forming scales (MAPS) Large Program. DCN is detected in all five sources, with one newly reported detection. N$_2$D$^+$ is detected in four sources, two of which are newly reported detections. We derive column density profiles that allow us to study the spatial variation of the DCN/HCN and N$_2$D$^+$/N$_2$H$^+$ ratios at high resolution. DCN/HCN varies considerably for different parts of the disks, ranging from $10^{-3}$ to $10^{-1}$. In particular, the inner disk regions generally show significantly lower HCN deuteration compared with the outer disk. In addition, our analysis confirms that two deuterium fractionation channels are active, which can alter the D/H ratio within the pool of organic molecules. N$_2$D$^+$ is found in the cold outer regions beyond $\sim$50 au, with N$_2$D$^+$/N$_2$H$^+$ ranging between $10^{-2}$ and 1 across the disk sample. This is consistent with the theoretical expectation that N$_2$H$^+$ deuteration proceeds via the low-temperature channel only. This paper is part of the MAPS special issue of the Astrophysical Journal Supplement., Accepted for publication in the Astrophysical Journal Supplement. 55 pages, 30 figures. Replacement of earlier version with updated references

Sulfur-bearing molecules play an important role in prebiotic chemistry and planet habitability. They are also proposed probes of chemical ages, elemental C/O ratio, and grain chemistry processing. Commonly detected in diverse astrophysical objects, including the Solar System, their distribution and chemistry remain, however, largely unknown in planet-forming disks. We present CS ($2-1$) observations at $\sim0."3$ resolution performed within the ALMA-MAPS Large Program toward the five disks around IM Lup, GM Aur, AS 209, HD 163296, and MWC 480. CS is detected in all five disks, displaying a variety of radial intensity profiles and spatial distributions across the sample, including intriguing apparent azimuthal asymmetries. Transitions of C$_2$S and SO were also serendipitously covered but only upper limits are found. For MWC 480, we present complementary ALMA observations at $\sim0."5$, of CS, $^{13}$CS, C$^{34}$S, H$_2$CS, OCS, and SO$_2$. We find a column density ratio N(H$_{2}$CS)/N(CS)$\sim2/3$, suggesting that a substantial part of the sulfur reservoir in disks is in organic form (i.e., C$_x$H$_y$S$_z$). Using astrochemical disk modeling tuned to MWC 480, we demonstrate that $N$(CS)/$N$(SO) is a promising probe for the elemental C/O ratio. The comparison with the observations provides a super-solar C/O. We also find a depleted gas-phase S/H ratio, suggesting either that part of the sulfur reservoir is locked in solid phase or that it remains in an unidentified gas-phase reservoir. This paper is part of the MAPS special issue of the Astrophysical Journal Supplement., Accepted for publication in The Astrophysical Journal Supplement (27 pages, 13 figures, 5 tables)

The elemental composition of the gas and dust in a protoplanetary disk influences the compositions of the planets that form in it. We use the Molecules with ALMA at Planet-forming Scales (MAPS) data to constrain the elemental composition of the gas at the locations of potentially forming planets. The elemental abundances are inferred by comparing source-specific gas-grain thermochemical models, with variable C/O ratios and small-grain abundances, from the DALI code with CO and C2H column densities derived from the high-resolution observations of the disks of AS 209, HD 163296, and MWC 480. Elevated C/O ratios (~2.0), even within the CO ice line, are necessary to match the inferred C2H column densities, over most of the pebble disk. Combined with constraints on the CO abundances in these systems, this implies that both the O/H and C/H ratios in the gas are substellar by a factor of 4-10, with the O/H depleted by a factor of 20-50, resulting in the high C/O ratios. This necessitates that even within the CO ice line, most of the volatile carbon and oxygen is still trapped on grains in the midplane. Planets accreting gas in the gaps of the AS 209, HD 163296, and MWC 480 disks will thus acquire very little carbon and oxygen after reaching the pebble isolation mass. In the absence of atmosphere-enriching events, these planets would thus have a strongly substellar O/H and C/H and superstellar C/O atmospheric composition., Comment: 19 pages, 8 figures This paper is part of the MAPS special issue of the Astrophysical Journal Supplement. Updates references for other MAPS papers

We observed HCO$^+$ $J=1-0$ and H$^{13}$CO$^+$ $J=1-0$ emission towards the five protoplanetary disks around IM Lup, GM Aur, AS 209, HD 163296, and MWC 480 as part of the MAPS project. HCO$^+$ is detected and mapped at 0.3\arcsec\,resolution in all five disks, while H$^{13}$CO$^+$ is detected (SNR$>6 \sigma$) towards GM Aur and HD 163296 and tentatively detected (SNR$>3 \sigma$) towards the other disks by a matched filter analysis. Inside a radius of $R\sim 100$ au, the HCO$^+$ column density is flat or shows a central dip. At outer radii ($\gtrsim 100$ au), the HCO$^+$ column density decreases outwards, while the column density ratio of HCO$^+$/CO is mostly in the range of $\sim 10^{-5}-10^{-4}$. We derived the HCO$^+$ abundance in the warm CO-rich layer, where HCO$^+$ is expected to be the dominant molecular ion. At $R\gtrsim 100$ au, the HCO$^+$ abundance is $\sim 3 \times 10^{-11} - 3\times 10^{-10}$, which is consistent with a template disk model with X-ray ionization. At the smaller radii, the abundance decreases inwards, which indicates that the ionization degree is lower in denser gas, especially inside the CO snow line, where the CO-rich layer is in the midplane. Comparison of template disk models with the column densities of HCO$^+$, N$_2$H$^+$, and N$_2$D$^+$ indicates that the midplane ionization rate is $\gtrsim 10^{-18}$ s$^{-1}$ for the disks around IM Lup, AS 209, and HD 163296. We also find hints of an increased HCO$^+$ abundance around the location of dust continuum gaps in AS 209, HD 163296, and MWC 480. This paper is part of the MAPS special issue of the Astrophysical Journal Supplement., Comment: accepted to ApJS, 33 pages, 20 figures

Laser-induced breakdown spectroscopy (LIBS) is a fast spectral detection technology, which has been widely used in coal composition detection and soil pollution detection in recent years. In the process of detection, due to various reasons, the spectrum obtained is mixed with noise, which has a negative impact on the accuracy of subsequent analysis. In this paper, taking the detection of coal by LIBS spectrum as an example, wavelet threshold denoising is used to denoise the detection spectrum containing noise. Different threshold methods are used to compare the denoising effects through simulation, so as to make full preparations for further accurate analysis of the spectrum.

Using a three-dimensional classical ensemble model, we investigate the dependence of relative frequency and relative initial phase for nonsequential double ionization (NSDI) of atoms driven by orthogonal two-color (OTC) fields. Our findings reveal that the NSDI probability is clearly dependent on the relative initial phase of OTC fields at different relative frequencies. The inversion analysis results indicate that adjusting the relative frequency of OTC fields helps control returning probability and flight time of the first electron. Furthermore, manipulating the relative frequency at the same relative initial phases can vary the revisit time of the recolliding electron, leading that the emission direction of Ar2+ ions is explicitly dependent on the relative frequency.

In order to improve the technical properties of SBS modified asphalt, firstly, nano-CaCO3/SBS modified asphalt with nano-CaCO3 dosage of 1%, 2%, 3%, 4%, 5% and 6% were prepared, while the optimal nano-CaCO3 dosage was optimized by conventional laboratory experiments. Secondly, the pavement performance of SBS modified asphalt mixture and nano-CaCO3/SBS modified asphalt mixture was analyzed by relevant laboratory tests. The experimental results show that nano-CaCO3/SBS modified asphalt achieves the best performance when nano-CaCO3 dosage is 4%. Compared with SBS modified asphalt mixture, the high-temperature performance, water stability, indirect tensile strength and fatigue resistance of nano-CaCO3/SBS modified asphalt mixture are improved obviously, and the crack resistance at low-temperature is slightly decreased, but it still far meets the specification requirement. This indicates that it is possible to enhance the property of SBS modified asphalt and the performance of mixture by adding nano-CaCO3.

Near-threshold femtosecond laser produces nanostructures on the gold film, which has received much attention in applications. However, the theoretical researches on the early stage of gold film excitation induced by the femtosecond laser are scarce, because of the ultrafast and non-equilibrium characteristics. In this study, stress and temperature distributions in different thicknesses of gold film induced by the near-threshold fluences were calculated. At the fluence below the melting threshold, we found that only the 30 nm gold films might be damaged by the non-thermal deformation. At the fluence of the melting threshold, the dominant damage mechanism shifted from non-thermal deformation to thermal melting as the gold film thickness increased. Our study provided a way to distinguish the dominant damage mechanism of gold film and it was valuable for the theoretical study of near-threshold processing.

In order to explore the fire characteristics of high-speed intercity train running with fire under different door opening conditions in the tunnel, this paper studied the fire of intercity train running with fire based on the fire simulation software, calculated and designed 10 different door opening conditions, and obtained: when the side door behind the fire source is opened and the door in front of the car is also opened, the distribution range of high temperature and smoke in the fire carriage is reduced by about half, and the visibility less than 5m only exists behind the fire source. When all the front and rear doors of the train are opened, the maximum temperature at the monitoring point is the lowest. It is suggested that after passengers of the burning intercity train are evacuated to other carriages, close the corridor door of the external carriage, and open all side doors at the front and rear sides of the on-fire train carriage for ventilation and cooling.

In this paper, the GaN-based green micro light-emitting diodes (Micro-LEDs) with various sizes (from 3 to 100 μm) were fabricated and electro-optically characterized. Atom layer deposition (ALD) passivation and potassium hydroxide (KOH) treatment were applied to eliminate the sidewall damage. The size dependence of Micro-LED was systematically analyzed with current-versus-voltage and current density-versus-voltage relationship. According to the favorable ideality factor results (μm. In addition, the external quantum efficiency (EQE) droop phenomenon, luminance and output power density characteristics were depicted up to the highest current density injection condition to date (120 kA cm−2), and 6 μm device exhibited an improved EQE performance with the peak EQE value of 16.59% at 20 A cm−2 and over 600k and 6M cd cm−2 at 1 and 10 A cm−2, indicating a greater brightness quality for over 3000 PPI multiple display application. Lastly, the blue shift of 6 μm device with elevating current density was observed in electroluminescence spectra and converted to CIE 1931 color space. The whole shifting track and color variation from 1 A cm−2 to 120 kA cm−2 were demonstrated by color coordinates.

The Tibetan Plateau (TP) plays a critical role in Earth’s climate system and is highly sensitive to global warming. However, comprehensive analysis of the interaction between various climatic factors and vegetation growth across the TP is still limited. Using daily normalized difference vegetation index (NDVI) series interpolated from the 16-day satellite measurements and climatic data during 1982–2018, we investigated the spatiotemporal changes in growing season NDVI (NDVIGS) and associated climatic drivers over the TP and analyzed the responses of NDVIGS to climatic drivers for different vegetation types. Our results show that NDVIGS of the TP as a whole exhibits a significant rising trend (0.0011 year−1; P GS show apparent spatial heterogeneity over the TP with higher growth rates in forests (trend = 0.012 de−1; P −1; P −1; P −1; P GS trends in 62%, 19%, and 12% of the TP, respectively. Additionally, climatic factors show differential impacts on NDVIGS among different vegetation types. Air temperature has a predominantly positive correlation with NDVIGS for all vegetation types, while precipitation has a negative impact on plant growth in the eastern humid forest region but a generally positive impact in the other areas. Our results also highlight that the effect of VPD on NDVIGS varies among different vegetation types. These findings contribute to a systematic understanding of the possible mechanisms underlying the responses of vegetation growth to various climatic drivers across the TP.

Bearing fault diagnosis is a critical component of the mechanical equipment monitoring system. In the complex and harsh environment in which bearings operate, the fault diagnosis approach of multi-source information fusion can extract fault features more stably and extensively than the traditional single-source fault diagnosis method. However, most existing multi-source fusion methods are in infancy, and there are a number of pressing issues to address, such as subjective elements having a significant impact, excessive data redundancy, fuzzy multi-source signal fusion strategy, and insufficient accuracy. As a result, a new multi-source fusion fault diagnosis method is proposed in this paper. First, the residual pyramid algorithm is utilized to fuse the acoustic and vibration signals of multiple spatial positions respectively and then form two fused acoustic and vibration signals. Second, two improved 2D-CNN are used to extract the fault features contained in the above two signals separately to form a multi-source fault feature set. Third, an AdaBoost algorithm with a dynamic deletion mechanism is designed to fuse multi-source fault feature sets and produce the fault diagnosis findings. Finally, six different experimental data sets are used to test the performance of the model. The results reveal that the model has better generalization, higher and more stable fault diagnostic accuracy, and stronger anti-interference capacity.

Strong noise in practical engineering environments interferes with the signal of a rolling bearing, which leads to the decline of the diagnosis accuracy of intelligent diagnosis models. This paper proposes a novel hybrid model (a convolutional denoising auto-encoder (CDAE)-BLCNN) to address this problem. First, the rolling bearing vibration signal containing noise was input into the CDAE, which denoises the signal through unsupervised learning and then outputs the reconstructed data. Secondly, a hybrid neural network (BLCNN), composed of a multi-scale wide convolution neural network and a bidirectional long-short-term memory network, was used to extract intrinsic fault features from the reconstructed signal and diagnose fault types. The analysis results demonstrate that the proposed hybrid deep-learning model achieves higher detection accuracy, even under different noise levels and various rotating speeds. Compared with other models, there is a high fault recognition rate, robustness, and generalization ability, which may be favorable to practical applications.

With the development of the science and technology, the demanding of convenience and comfort when driving a car are getting higher and higher. As an important part that has a great influence on the comfort of the car driving, the car seat is also developing towards the electric direction. The electric seat is becoming the choice of more and more manufacture of automobile. However, the product quality inspection of the electric track of the car seat is still in a relatively preliminary stage. At present, the detection of the unqualified track product is mainly performed by workers listening in an anechoic room. This will lead to the high cost of construction of the anechoic chamber, low quality inspection efficiency, and instability by different quality inspection personnel. In this paper, we focus on the scraping noise detection of the electric track product, as scraping noise is the main cause of the product disqualification. Since scraping noise often features a higher energy in the high frequency band, we adopt the Short Time Fourier Transform (STFT) to acquire the total energy at different time duration. Then we model the acquired time series as summation of one sparse signal, one low-passing signal, and one noise signal. Based on the property of the three parts, the objective function is established and solved with Majorization-Minimization (MM) approach. The effectiveness of the proposed scraping detection method is verified with the real track vibration signal, and the superiority of the proposed method is verified via the comparison with other impulse detection method.

A subwavelength asymmetric grating refractive index (RI) sensor based on quasi-bound states in the continuum (q-BIC) with temperature self-compensation was proposed. The sensor structure consisted of a prism/asymmetric grating/analytes, where the grating layers were periodically arranged asymmetric silicon (Si) and polydimethylsiloxane. The asymmetry of the structure led to the fact that the tangential field component and the radiative field component in the grating layer were no longer in a fully decoupled state at the resonance position, creating two extremely narrow q-BIC resonance peaks, which gave the sensor a high figure of merit (FOM) and a low detection limit (DL). In addition, the thermo-optical coefficient of the materials made one of the resonance peaks more sensitive to temperature changes, realizing the temperature self-compensation of RI detection and thus improving the detection accuracy. From the results, reducing the asymmetry of the structure by modifying the parameters could theoretically make FOM > 5.1 × 106 RIU−1 and DL < 9.8 × 10−9 RIU. For the RI sensor with temperature self-compensation, FOM = 3057.85 RIU−1 and DL = 1.64 × 10−5 RIU for the RI, FOM = 0.88 °C−1 and DL = 0.057 °C for the temperature. These findings could effectively improve the temperature interference resistance of the sensor and thus the accuracy of trace substance detection.

We report the fabrication of long period gratings in fluid-cladding microfibers by directly focusing a femtosecond laser beam on the microfibers surface to induce periodical modification a long one side of the microfibers. A long period grating is fabricated in a water-cladding microfiber with a diameter of ~ 5 μm, which demonstrates a resonant attenuation of 28.53 dB at wavelength of 1588.1 nm with 10 pitches. When water cladding is changed to be refractive index oil of n= 1.33 and alcohol solution with concentration of 5%, the resonance wavelength shifts to 1575.1 nm with resonant attenuation of 24.91 dB and 1594.1 nm with resonant attenuation of 35.9 dB, respectively. The long period grating demonstrates different temperature sensitivities of–0.524 nm/°C,–0.767 nm/°C and–1.316 nm/°C for water, alcohol solution and refractive index oil cladding microfibers, respectively, which means the alterable liquid cladding allows the availability of tunable wavelength and sensitivity. The fluid-cladding protects the microfibers from external disturbance and contamination and allows more flexibility in controlling the transmission property and sensing characteristics of long period gratings, which can be used as fiber devices and sensors for chemical, biological, and environmental applications.

Seismic detection technology has been widely used in safety detection of engineering construction abroad. Although it has just started in the field of engineering in our country, its role is becoming more and more important. Through computer technology, micro-seismic detection can provide accurate data for the construction safety detection of large-scale projects, which has important practical significance for the rapid and effective identification of micro-seismic signals. Based on this, the purpose of this article is to study the feature extraction and classification of microseismic signals based on neural games. This article first summarizes the development status of microseismic monitoring technology. Using traditional convolutional neural networks for analysis, a multi-scale feature fusion network is proposed on the basis of convolutional neural networks and big data, the multi-scale feature fusion network is used to research and analyze microseismic feature extraction and classification. This article systematically explains The principle of microseismic signal acquisition and the construction of multi-scale feature fusion network. And use big data, comparative analysis method, observation method and other research methods to study the theme of this article. Experimental research shows that the db7 wavelet base has little effect on the Megatron signal.

When a tire bursts, the flying fragments may break through the wing, damage the precision instruments inside it, and cause huge economic losses. In this paper, the impact of tire fragments on the fuselage structure is simulated, and the dynamic response of the structure under different postures of impacting different structures and fragments is analyzed. The damage caused by different impact modes is analyzed and compared, the harshest impact conditions are selected, and the corresponding improvement measures are given according to the impact results. It is found that the strain of the frame truss structure is the smallest when the fragments impacts on the front side, but it may lead to the fracture of the frame truss on the back side, resulting in secondary fragments splashing. When impacting in different postures, the edge impact is the most dangerous. Although it penetrates the skin, it is very close to the failure value.

This article selects artificial intelligence technology as the research object, and specifically analyzes the application of this technology in intelligent buildings. On the basis of clearly defining the concept of artificial intelligence technology, an analysis of the way to realize the intelligentization of intelligent buildings is carried out. Select specific examples to conduct simulation experiments on the application of artificial intelligence technology in intelligent buildings, and provide practical reference for the construction industry.