Aiming at the problem of redundancy in the phase space reconstruction of sample entropy algorithm, the phase space reconstruction process of sample entropy algorithm was replaced by a symbolic variable matrix, and an improved sample entropy algorithm was established. The analysis of white noise and powder noise simulation signals shows that the improved sample entropy algorithm can extract signal features effectively and has high computational efficiency. In the past, bearing clearance faults of complex compressors were studied, and the improved sample entropy algorithm was applied to extract features and compared with sample entropy. The feature extraction results of the method are highly consistent with the sample entropy algorithm, and the computational efficiency of the algorithm is much higher than that of the sample entropy algorithm.

Multi-label learning is a common problem in real application scenarios. The construction of large-scale multi-label datasets often means high cost, so semi-supervised learning technology appears. At present, most semi-supervised learning is mainly used in the field of single label classification. Although semi-supervised learning in the field of multiple labels classification has made some progress, there is still much room for improvement in training time consumption, training effects and the use of potential relationships between labels. A multi-label semi-supervised curriculum learning model was proposed under the dual structure semi supervised course learning under dual structure(SSCD) to solve the above problems. Firstly, a curriculum learning scheme based on dual difference was designed, which greatly reduces the training time and improves the robustness of the model. Secondly, a single attention mechanism was designed to explore the potential relevance between labels. The performance of SSCD in the prediction task was evaluated on three open test datasets, and the results compared with four benchmark models show that the comprehensive indicators of SSCD are optimal in all aspects. Finally, the structure ablation experiment was carried out to prove the effectiveness of the proposed single attention mechanism.

In rock image recognition, achieving rapid and accurate identification of rocks is crucial for the digitalization of rocks. Among the challenges faced in intelligent rock recognition is the issue of image blurring caused by environmental factors such as lighting and humidity. In light of this, a novel deep learning approach (MobileNetV3-small-RegNetX) was proposed for rock image recognition, which is suitable for scenarios with limited resources such as mobile devices. Building upon the RegNet network, transfer learning methods, combining the advantages of the MobileNetV3 residual structure with squeeze-and-excitation (SE)modules was employed to effectively optimize feature extraction and network structure, leading to a significant improvement in detection speed. To validate the accuracy of this approach, comparative experiments were conducted between the new model and current mainstream lightweight models (DenseNet and ShuffleNet). The results demonstrate that the new model proposed exhibits high precision (82.15%) and fast processing (0.06 GFLOPs). Additionally, the model demonstrates good adaptability to environmental factors such as lighting and humidity-induced image blurring.

In order to explore the effects of different internal fixation systems on the biomechanical characteristics of the spine after orthopedic idiopathic scoliosis, a theoretical basis for the improvement of the internal fixation system was provided from the perspective of biomechanics. Based on reverse engineering, topology optimization and finite element modeling techniques, the finite element model of idiopathic scoliosis was established by taking actual cases as examples. The personalized fusion device was designed. Two kinds of internal fixation systems were established, namely full fixation and interval fixation. To simulate idiopathic scoliosis surgery and compare the biomechanical differences between spine and internal fixation system under different physiological conditions. The results show that the average stress of cortical bone and cancellous bone is increased by 17.19% and 12.37%, respectively, compared with that of interlocking nails. The maximum equivalent stress of fibrous annulus matrix and nucleus pulposus is increased by 1.78% and 1.1%, respectively, compared with that of full nailing. The maximum equivalent stress of pedicle screws is 11.64% higher than that of interlocking screws. The average stress of interbody fusion is increased by 6.15% compared with that of interbody fusion. In conclusion, compared with the interspaced nailing scheme, the total nailing scheme is better in vertebrae safety, but the risk of screw slip and screw loss is higher. Compared with the total nailing scheme, the interstice nailing scheme has better spinal fusion effect and effectively alleviates stress occlusion, but the incidence of bone hyperplasia is increased.

As an innovative new method of natural gas hydrate extraction, the recovery of hydrate particles determines the efficiency of this method and is one of the key technical links. However, due to the limited hydraulic suction, the recovery rate of hydrate particles is low. Therefore, in order to improve the recovery performance of hydrate particles, a double jet recovery scheme was innovatively proposed. In order to explore the efficiency of solid particle recovery under different working conditions, experimental research was carried out, and the recovery flow field and particle recovery rate were studied by numerical simulation. The results show that with the increase in the distance between the front-end jetting and the recovery hole (l₁) and the distance between the back-end jetting and the recovery hole (l₂), the flow field effect between the double jets weakens, resulting in the particle deposition phenomenon becoming more obvious and the number of sand piles changing from 2 to 3. When the distance between the back-end jetting and the recovery hole (l₂) is 300 mm, the particle recovery increases first and then decreases with the increase in the distance between the front-end jetting and the recovery hole (l₁). When l₁ = 300 mm, the recovery increases first and then decreases with the increase of l₂. The results further enrich the mechanism of hydrate mining and help optimize the design of mining tools.

In order to reveal the characteristics and geological significance of the main micronutrient geochemistry in the Carboniferous-Permian Taiyuan Formation in Ningdong coalfield which deposited in marine-land transition coal-accumulating environment, the X-ray fluorescence(XRF) spectrometry, inductively coupled plasma-mass spectrometry(ICP-MS), macerals identification and industrial analysis were used to study the source, occurrence and environmental significance of trace elements in coals. The results show that the content of major and trace elements in Carboniferous coals of Ningdong coalfield are varies greatly, except the Fe₂O₃ content is lower than the mean content of China coals. The Rb(5.1) is enriched in Weierkuang while other elements are slightly enriched in different micronutrient. The major and trace elements in coal are mainly occurs in clay minerals, and come from the supply of terrigenous clasts and the combination with organic matter and authigenic minerals in water-soluble state and ion state. The ratio of TiO₂/Al₂O₃indicate that the minerals in the coal are mainly derived from felsic clastic rocks, and the positive correlation between CaO and MgO indicates that they coexist in the form of dolomite. The ratio of Sr/Cu and CaO/(MgO·Al₂O₃) and the other parameters indicate the coal-accumulating period is in a warm and humid environment, it is inferred that the temperature is between 15 ℃ and 30 ℃, the ratio of Sr/Ba indicates that the coal-forming marsh is a brackish water environment, which indicates that it is affected by seawater. The parameters of Cu/Zn, V/(V + Ni), Ni/Co and V/Cr revealed that the peat-formed bog was in an anaerobic redox environment.

In recent years, multiple exploration breakthroughs have been made in the Maokou Formation of the Sichuan Basin. Currently, the overall exploration level is low.The type and distribution of sedimentary facies are still unclear. The characteristics and formation mechanism of the reservoir are unclear. Techniques such as core observation, pore permeability testing, conventional and cast thin section identification were used to clarify the sedimentary and reservoir characteristics of the 2nd Member of the Maokou Formation in the front of the Longmen Mountains in western Sichuan and to explore the main controlling factors of high-quality reservoirs.Research shows that the 2nd Member of the Maokou Formation in the front of Longmen Mountain in western Sichuan develops in a northwest southeast direction. The southern and middle sections of Longmen Mountain are the development areas of high-energy shoals of the lower sub section of the second section of Maokou Formation. The middle and northern sections of the Longmen Mountain in the upper sub section of the second section of the Maokou Formation are the development areas of high-energy dolomitized platform edge sand debris shoals. The reservoir lithology of the upper sub section of the Maokou Formation is mainly composed of residual bioclastic sandstone dolomite, bioclastic grain dolomite, and residual grain dolomite.The reservoir lithology of the lower sub section of the second section of the Maokou Formation is mainly composed of residual sandstone dolomite and residual grain dolomite. The storage space consists of intergranular dissolution pores, intergranular dissolution pores, intragranular dissolution pores, and expansion fracture pores. The second section of the Maokou Formation is Ⅱ to Ⅲ porous reservoir. The reservoir foundation is composed of high-energy beach deposits. The leaching and dissolution of atmospheric fresh water during the contemporaneous period is the key to reservoir formation. The reservoir has been improved and maintained through shallow burial dolomitization.

Restricted by topographic conditions and surrounding environment, the design spacing of double-hole tunnels in western China is often close. Therefore, the special structural form of multi-arch or small close tunnels is often used in the tunnel design. However, in the western region of China, high-intensity seismic zones are widely distributed, and the middle rock wall between the close tunnels is more susceptible under the strong earthquakes, especially the near-field ground motions, which results in large plastic deformation of local surrounding rock, and the safety operation of the tunnel was affected. Therefore, in order to study the distribution of plastic zone of surrounding rock of small close-distance tunnel under near-fault ground motion, reasonable near-fault ground motions were selected, and 3D finite element numerical models considering different tunnel close-distance and surrounding rock conditions were established. The dynamic response characteristics of small close-distance tunnel and the distribution law of plastic zone of surrounding rock were revealed. Thus, through the grouting reinforcement of the middle rock wall, the seismic effectiveness of the reinforcement measures on the plastic zone was verified. The results show that the acceleration response of the arch foot near the middle rock wall tunnel is more significant under the influence of near-field ground motion. Under transverse seismic excitation, the maximum principal stress value of the left spandrel and the right arch foot of the right line tunnel are more significant, while the minimum principal stress of the side walls and the inverted arch of the tunnel is larger. The plastic zone of surrounding rock of small-close-distance tunnel under strong earthquake is greatly affected by rock mass grade. When the tunnel spacing is 0.50 times of the tunnel span, the development of plastic zone in grade Ⅳ and grade Ⅴ surrounding rock is the most serious, and the phenomenon of plastic zone penetration of surrounding rock at the haunch of tunnel near the middle rock wall appears. Taking the plastic zone of surrounding rock as the discriminant index, the grouting reinforcement of middle rock wall is beneficial to the seismic performance of small close distance tunnel. The research results can provide a reference for the seismic safety of small close-distance tunnels in high-intensity earthquake areas.

In order to explore the application of carbon fiber composite in portable weapons, the technical research on the structural properties of the launcher and the method of composite laminating was carried out. The working pressure of a certain type of launcher was obtained through experiments, and different carbon fiber composite layering models were established by using finite element numerical simulation method. Then the mechanical properties of the launcher under working load were studied. The results show that the layering method of carbon fiber has a great influence on the stiffness and damage failure of the launcher. Under the condition of the same working pressure, the same number of layers and the total thickness, the maximum deformation of the launcher structure is 2.41 mm in the layering mode Ⅰ. The maximun deformation of mode Ⅱ is 7.66 mm, and the latter is more than 3 times of the former. According to the Hashin failure criterion, there is no damage in the carbon fiber cylinder of the mode Ⅰ, except for the 6th to 12th fiber layers in the middle of the cylinder according to the mode Ⅱ, a large range of initial damage points are found in other layers. The research results can provide reference for the stucture design of the launcher and the carbon fiber composite layering scheme.

In order to avoid wellbore failure caused by abnormal annulus band pressure and resulting safety accidents, the annulus band pressure value is accurately predicted, and preventive measures are taken in advance when it exceeds the control value. An autoregressive integrated moving average-long short term memory (ARMI-LSTM) model was proposed. The model was trained to predict the annular band pressure of example wells based on actual annular band pressure time series data and feature capture data sets, and compared with a single model and recurrent neural network (RNN) model. The results show that the model has a good performance in error, fitting accuracy and overall performance after training with actual data, which can provide a reference for improving the prediction accuracy and efficiency of annular band pressure value, and is helpful to well integrity design.