929results about How to "Avoid performance degradation" patented technology

The invention discloses a low-orbit communication satellite load multilink cooperative transmission system, and belongs to the technical field of satellite communication. In order to solve the problems of insufficient link reliability, low utilization rate of resources in constellations, weaker emergency response and fault-tolerant capability and higher operation cost, the invention is composed of a plurality of low-orbit communication satellites, realizes global seamless coverage through reasonably deployed constellation configuration, ensures that a user can obtain stable communication service in any area, and improves the user experience. A multi-link cooperative communication mechanism is adopted, through real-time link quality evaluation and dynamic link selection, rapid switching of link faults is achieved, communication reliability is improved, a dynamic path adjustment technology is combined, a forwarding path of data in a constellation is optimized according to an actual link state, data transmission time delay is effectively reduced, and data transmission efficiency is improved. According to the time-space change of the flow demand, communication link resources are scheduled in real time, the utilization efficiency of system resources is optimized, and the communication demand of a high-priority task is guaranteed.

The invention belongs to the technical field of front-end development, and particularly relates to a React framework-based tree component optimization method fusing virtualization rendering and increment rendering. Comprising the steps of S1, data preprocessing; S2, dynamic virtualization rendering: dynamically calculating a node index range in a visible area according to a real-time scrolling position of a user viewport, only rendering nodes in the range, and realizing seamless lazy loading of data through scrolling event monitoring; s3, intelligent incremental updating: identifying changed nodes through a state change comparison algorithm, and executing local re-rendering only for the changed nodes based on a component life cycle control mechanism of a React framework; and S4, lazy loading cooperative control. The method aims at solving the problems in the aspects of performance, memory management, user experience and the like when a tree component in a React ecological system processes large-scale data, and is widely applied to various Web application program development scenes needing to display and operate a large-scale tree data structure.

The invention provides a valve leakage diagnosis method and system based on an improved Hereum algorithm optimized SVM (Support Vector Machine), and relates to the technical field of valve leakage diagnosis. Decomposing the collected original signal to obtain a limited number of IMF components; calculating a fuzzy entropy, and constructing a feature vector; taking the feature vectors as data samples, and dividing the data samples into a training set, a verification set and a test set; using the training set to train the SVM model, and according to the classification error rate of the verification set on the trained SVM model, performing iterative optimization on the parameters of the SVM model based on an improved He-Ma algorithm to obtain an optimized SVM model; inputting the test set into the optimized SVM model to obtain a valve leakage diagnosis model; and acquiring a new acoustic emission signal, and inputting the new acoustic emission signal into the valve leakage diagnosis model to obtain a diagnosis result. The method not only can improve the classification accuracy and generalization ability of the diagnosis model, but also can enhance the stability of the model under different working conditions and environmental noise.

The invention discloses a vehicle power supply distribution control management system and method, and relates to the technical field of vehicle power supplies, and the method comprises the steps: collecting the historical driving data of a vehicle and the driving behavior data of a driver, analyzing the driving habit of the driver, and monitoring the driving state of the vehicle in real time through combining with a vehicle-mounted sensor; comprehensively judging whether the vehicle enters a high-load state or not; when the vehicle enters a high-load state, the charging and discharging power of each battery module is dynamically adjusted according to the temperature distribution and load requirements of each battery module in the battery pack; evaluating the power supply condition of each battery module according to a power adjustment result, sending an early warning prompt to a driver if the power supply is insufficient, and continuously monitoring and analyzing the temperature difference between the battery modules in the battery pack and predicting the temperature change of each battery module if the power supply is sufficient, and the cooling strategy of the vehicle system is intelligently adjusted, and temperature balance of all battery modules of the vehicle in the high-load state is achieved.

The invention relates to the technical field of air conditioner energy-saving systems, and discloses a central air conditioner energy-saving automatic control system and method.The central air conditioner energy-saving automatic control system comprises a sensor module, a control module, a communication module, an intelligent control algorithm module, a dynamic adjusting module and an energy-saving optimization module; the sensor module comprises a temperature sensor, a humidity sensor, a CO2 sensor, an illumination sensor and an occupation sensor, the temperature sensor is used for monitoring indoor and outdoor temperatures and providing real-time data for decision making of a control system, and an NTC (negative temperature coefficient thermistor), a PTC (positive temperature coefficient thermistor) or a DS18B20 digital temperature sensor is adopted. The environment parameters are monitored in real time, the operation state of the air conditioning equipment is dynamically adjusted, the high-energy-consumption operation mode of a traditional air conditioning system is avoided, cooling / heating according to needs is achieved, energy consumption is effectively reduced, the mode is automatically switched to the energy-saving mode in the state that the number of personnel activities is small or no one exists, and therefore the effect of remarkably reducing the operation load and energy consumption can be achieved.

The invention relates to the technical field of signal analysis and processing, in particular to an underground flow switch control method based on vibration signal analysis. The method comprises the steps that 1, vibration signals of a pump are collected through a three-axis vibration sensor, and acceleration time domain signals in the three-axis direction are obtained; performing multi-dimensional vibration spectrum component decoupling on the acceleration time-domain signal to obtain a time-frequency characteristic matrix of three-axis vibration; 2, calculating a Reynolds stress tensor based on the turbulence intensity; calculating a flow state transition criterion value according to the turbulence intensity and the Reynolds stress tensor, and establishing a flow estimation model; 3, according to the flow estimation model, dynamic response of underground flow switch control is generated; and according to the dynamic response, a self-adaptive control law for controlling the underground flow switch is generated by using a self-adaptive control method. According to the invention, the limitation of a traditional pressure sensing and flow sensing technology in a complex underground flow state is effectively overcome, and the real-time performance, the accuracy and the environmental adaptability of flow control are remarkably improved.

The invention provides a network node classification method based on a multilayer graph neural network model, and the method comprises the steps: constructing a graph according to network nodes, carrying out the preprocessing of initial node features in the graph, and obtaining an initial embedded vector; according to the initial embedding vectors of the node and the neighbor node thereof, updating the node representation by adopting a layered message passing mechanism; according to the initial embedded vectors of the nodes and the neighbor nodes thereof, the graph attention network uses an attention mechanism to calculate weights for the neighbor nodes of each node and then dynamically updates feature vectors of the nodes; a multi-head attention mechanism is adopted to splice and merge the feature vectors of the nodes output by the graph attention network and the updated node representation, and the comprehensive feature vector of each node is obtained; the comprehensive feature vectors are further optimized through graph contrast learning and a node embedding module, and optimized features are obtained; and obtaining predicted node classification according to the optimization features. According to the method, complex features of heterogeneous graph data can be effectively captured, the method has good robustness for an over-smoothing problem, more accurate heterogeneous network representation learning is realized, and the method has advanced performance and robustness in a node classification task.

The invention belongs to the technical field of intelligent control of air conditioning systems, and discloses a split type air conditioner load management system and method. The system comprises a central controller, a health management module, an adaptive integrated control module AICA and an intelligent scene recognition module. The central controller integrates various sensor information such as temperature and humidity, air quality and user physiological data, data processing and intelligent decision making are carried out through an AICA module, and dynamic optimization management of air conditioner loads is achieved. The health management module automatically adjusts the air conditioner operation mode according to the body temperature, heart rate and other physiological indexes of the user, and a comfortable environment is provided. And the intelligent scene recognition module is used for pre-judging user requirements and adjusting the operation of the air conditioner by learning a user behavior mode. The energy efficiency and the intelligent level of air conditioner operation are improved, the method is suitable for air conditioner load management of various buildings, energy can be effectively saved, and the comfort level of users is improved.

The invention discloses a rigidity-adaptive three-degree-of-freedom low-frequency electromagnetic vibration isolator, and belongs to the technical field of precise vibration isolation. The rigidity-adaptive three-degree-of-freedom low-frequency electromagnetic vibration isolator comprises three sets of low-frequency electromagnetic vibration isolators formed by connecting rigidity-adaptive electromagnetic arrays and spiral springs in parallel. The spiral spring stably supports the load in a passive mode and effectively isolates vibration of middle and high frequency bands; the rigidity self-adaptive electromagnetic array generates high negative rigidity through a moving magnetic array and a fixed magnetic array which are composed of four columns of vertically magnetized equal-cross-section cubic permanent magnets, coil current is adjusted in real time through acceleration feedback, external excitation and load mass changes are responded, the negative rigidity is dynamically adjusted, and the requirement for three-degree-of-freedom near-full-band vibration isolation is met. The vibration isolator has adjustable low dynamic rigidity in the vertical and horizontal rotation freedom degrees, the vibration isolation frequency is low, the frequency band is wide, a super-quiet environment is provided for tip equipment, and the instrument precision is remarkably improved.

The invention provides an elastic configuration and bidirectional collaborative adaptation system for application computing tasks, and relates to the technical field of computers. Equipment and network states are monitored in real time by applying an elastic configuration mechanism of a computing task, execution tasks and nodes in a task graph are dynamically adjusted, task response time is optimized, meanwhile, collaborative optimization is performed between an equipment end and a cloud end by applying a bidirectional collaborative adaptation algorithm of computing network resources, computing resources are reasonably distributed, and the computing efficiency is improved. The limitation of single optimization dimension in the prior art is overcome, in addition, the system adopts a self-adaptive learning mechanism, a task unloading strategy and a resource management scheme are continuously optimized by utilizing machine learning and a neural network model, the long-term performance is improved, and the technical scheme not only improves the dynamic response capability of the system, but also improves the reliability of the system. In addition, global optimization of resources is realized in a multi-user and multi-task environment, and task execution time and energy consumption are reduced.

The invention provides a multi-gun-head charging pile power distribution method, medium and system, and belongs to the technical field of charging piles, and the method comprises the steps: firstly obtaining the historical operation data of a charging pile, and building a mathematical model containing a plurality of error terms, such as equations of charging power, time, battery capacity and the like; then, a hybrid model is constructed, and the hybrid model comprises a multi-branch neural network and a mathematical model so as to adapt to charging piles of different scales; and training by adopting historical data to obtain a power distribution model. In the actual charging process, real-time data are input, power distribution is adjusted, and feedback data are collected at the same time. And on the basis of real-time data and prediction errors, a lightweight Lora model is utilized to perform continuous fine adjustment on the fusion sub-network, and the main model is updated regularly. Through a mathematical modeling and machine learning modeling fusion mode, the technical problem that existing multi-gun-head charging pile power distribution is mainly carried out through a simple preset or fixed mode, and complex charging scenes and requirements cannot be well adapted is solved.

The invention discloses a method and a device for cooling a battery pack of an electric automobile, and relates to the technical field of electric automobiles, and the process method comprises the following specific steps: real-time monitoring: installing intelligent sensing equipment in and around each battery module of the battery pack, monitoring key parameters of temperature and pressure of the battery pack in real time, and simultaneously monitoring the temperature and the pressure of the battery pack; according to the invention, key parameters of temperature, pressure, current and voltage of the battery pack are monitored in real time through the intelligent sensing device, and thermal management data of the battery pack are processed and analyzed in real time in combination with a big data analysis technology. The battery performance reduction and the safety risk caused by too high or too low temperature are avoided, the thermal management requirements of the battery pack under different working conditions are better met, and the use efficiency and the safety of the battery pack are improved.

The invention belongs to the technical field of computer application, and relates to an operation inspection equipment fault detection method and system based on an improved deep learning model, and the method comprises the steps: obtaining original data, employing EEMD to decompose the original data for feature enhancement, obtaining a decomposition signal, carrying out the noise reduction of the decomposition signal, and obtaining a feature signal after noise reduction; according to the feature signals after noise reduction, a deep learning model is constructed based on Resnet and a dynamic Transform encoder, and the prediction probability of each fault category is output; a ZOA optimization algorithm is used to optimize hyper-parameters of a deep learning model, an optimization model is obtained, the performance of the optimization model is evaluated, an optimal model is obtained, and the prediction probability of each fault category is output, so that false report and missing report of faults can be effectively reduced in a fault detection task, potential safety hazards caused by the fact that the faults are not found in time are reduced, and the fault detection efficiency is improved. Therefore, the stability and reliability of the power system are improved.

The invention discloses a capacitive battery active equalization circuit and a method thereof. The capacitive battery active equalization circuit comprises a plurality of single batteries, a power MOS (Metal Oxide Semiconductor) tube circuit, an energy storage circuit and a control loop, the control loop comprises an ADC module, a PID module, a constant current controller and a power MOS tube driving module. The corresponding end of the ADC module is electrically connected with the corresponding ends of the plurality of single batteries and the PID module; the corresponding end of the PID module is connected with the corresponding end of the power MOS tube driving module through the constant current controller; and the corresponding end of the power MOS tube driving module is electrically connected with the corresponding end of the power MOS tube circuit. Compared with the scheme in the current market, the device has the advantages of low cost, small size, easiness in integration, simplicity in control, high safety and the like, and can store the energy of the battery with high voltage to the capacitor and carry the energy stored on the capacitor to the battery with low voltage, so that the aim of balancing the electric quantity of the battery is fulfilled.

The invention relates to a COB LED self-adaptive thermal management system, and aims to improve the heat dissipation performance and prolong the service life of a COB LED through an intelligent temperature monitoring and adjusting means. The system comprises an infrared thermal imaging module which is used for obtaining real-time thermal images of a COB LED packaging substrate and an LED unit; the image processing module is used for analyzing the acquired thermal image and identifying a hot spot area; and the current adjusting module is used for dynamically adjusting the driving current of the corresponding LED unit according to the identified hot spot area so as to slow down the generation of hot spots. If the current adjustment cannot sufficiently reduce the hot spot temperature, the cooling mechanism control module starts a cooling mechanism, including adjusting the fan speed, prompting a user to optimize external environment heat dissipation conditions, or partially shutting down the LED unit in extreme cases to reduce heat generation. According to the system, by combining real-time thermal imaging, intelligent current regulation and cooling mechanisms, the COB LED system is ensured to maintain a stable temperature in a high-efficiency working state, so that the overall light output efficiency is improved, and the service life of the LED is prolonged.

The invention discloses a UI effect picture recognition method and system based on a multi-modal large model, and a medium. The method comprises the following steps: constructing a multi-modal pre-training model based on image coding, multi-modal projection and text coding; performing fine tuning training according to the historical image data and the multi-modal pre-training model to obtain a multi-modal large model; constructing a vector database based on the built-in component data structure; obtaining a to-be-recognized UI effect picture, and outputting first recognition data based on the multi-modal large model and the to-be-recognized UI effect picture; and searching a vector database for the first identification data by using a retrieval algorithm, and outputting generation information corresponding to the UI effect picture to be identified. The method has the beneficial effect that the generation consistency and efficiency of the UI effect picture are ensured.

The invention relates to the technical field of artificial intelligence, and provides a search method and device, electronic equipment and a readable storage medium. The method comprises the following steps: acquiring a search term for searching; matching the search terms through a preset database to obtain an initial matching result; obtaining a target search term according to the search term and the initial matching result, and performing semantic extension on the target search term to obtain at least one extended search term; searching by utilizing a target search term and at least one extended search term to obtain a first search result corresponding to the target search term and a second search result corresponding to the at least one extended search term; and determining a target search result corresponding to the search term according to the first search result and the second search result. Through initial semantic matching, semantic extension and comprehensive analysis, a more accurate and comprehensive search result meeting the search intention of the user can be provided for the user.

The invention discloses a venue building fire automatic early warning construction integrated device and a using method. The venue building fire automatic early warning construction integrated device comprises a mounting base, a shell is arranged at the lower end of the mounting base, an air inlet cover is arranged in the center of the lower end of the shell, a filter screen is fixedly mounted at the position, close to the bottom, of the surface of the air inlet cover, and the upper end of the air inlet cover penetrates into the shell. According to the automatic early warning construction integrated device for the venue building fire, through the scheme of the mounting base, the rotating column, a second gear, a third gear, a threaded rod, a threaded plate, a clamping plate, a connecting block, a clamping groove, a clamping block and a rotating button, an operator rotates the rotating button, and then the second gear can be meshed with the second gear to drive the threaded rod to rotate; the two threaded plates can horizontally move oppositely or oppositely, so that the clamping blocks on the clamping plates are driven to be tightly combined with or separated from the clamping grooves, the mounting and dismounting steps are simplified, and the complexity caused by a traditional screw fixing mode is avoided.

The invention discloses a feature information reconstruction industrial defect detection method based on multi-dimensional feature fusion, and relates to the technical field of defect detection. Compared with a previous defect detection method, the defect detection method solves the problems that a traditional defect detection method is sensitive to environmental changes and poor in generalization ability; the real-time requirement cannot be met; the reconstruction performance effect is poor; and the generalization performance of the system is not high. A cutting type auto-encoder AE is introduced to complete reconstruction of normal feature information of a defect sample, and the parameter quantity and the calculation quantity of the network are reduced. And the embedding module is used for replacing an editing part, system performance is maintained, feature information of a normal image is increased, and the reconstruction function of the reconstruction module is completed. An MFF module is introduced to reutilize the encoder module feature information in the AE reconstruction module; and an information correction mechanism is additionally introduced into the MFF module, so that the problem of reconstruction performance reduction caused by leakage of abnormal information is prevented, and normal feature information of the teacher network is utilized to guide correct use of multi-dimensional feature information.

The invention discloses a large-scale data consistency method and device based on a multi-level tree structure cluster, and the method comprises the steps: constructing the multi-level tree structure cluster, distributing an i-level cluster for a follower in an i-1-level cluster as a corresponding subtree, and enabling a leader in the i-level cluster to be the follower in the i-1-level cluster; the i-level leader triggers own data collection according to the heartbeat detection message, and feeds back the collected data to the i-1-level leader; the (i-1)-level leader carries out consistency comparison on the collected data, if the collected data are not consistent, consistent data construction is carried out, a synchronization log of the constructed data is sent to the i-level leader, and the i-level leader carries out log synchronization after verification; and the i-level leader sends a log copy message to the i-level follower in the sub-tree where the i-level leader is located, and the i-level follower executes log synchronization after verification. The method has relatively low election performance loss, and realizes the capability of adapting to a large-scale distributed system.

The utility model relates to the technical field of control cabinets, discloses a weak current intelligent control cabinet with a heat dissipation structure, and solves the problems that only a fan is used in the prior art, the heat dissipation effect is poor, and a dustproof net is inconvenient to overhaul. A weak current intelligent control cabinet with a heat dissipation structure comprises a device body, a cabinet door is hinged to the device body, dust screens are arranged in the middle of the top end of the device body and on the side walls of the left end and the right end of the device body, heat dissipation holes are formed under the dust screens, and a mounting frame used for mounting electrical components is fixedly connected into the device body. According to the weak current intelligent control cabinet with the heat dissipation structure, it can be ensured that the temperature in the control cabinet is always kept within a proper range, performance reduction or damage, caused by overheating, of electric appliance elements is avoided, the operation stability of the electric appliance elements is improved, and the service life of the electric appliance elements is prolonged. And meanwhile, the dustproof net is convenient to clean and maintain, and the flexibility of equipment is improved.

The invention discloses a remote video monitoring data transmission method, and the method comprises the steps: collecting visual video information through a robot camera, and transmitting the visual video information to a remote power plant monitoring center through a HDMI interface, an encoder, a 5G-CPE, a decoder and other links. The 5G-CPE uses MEC, 5G slicing and SRT technologies to adjust resource allocation according to network conditions and requirements, and defines configuration slices and priorities. A network monitoring component is deployed to monitor slice loads in real time, a load threshold value is set for each slice, and a resource adjustment strategy is triggered when the loads exceed the threshold values. And resources are dynamically reallocated after analysis and evaluation, so that sufficient and optimized utilization of high-load slice resources is ensured. Performance is continuously monitored and feedback adjustment is performed, network adaptability and flexibility are improved, key video streams are ensured to be transmitted preferentially, and power plant inspection requirements are met.

The invention relates to a container environment safety protection method and device based on CVE, and the method comprises the steps: building an App service and an Agent service, and separating front and rear end management; constructing a CVE library, and according to the CVE library, performing security scanning on the container mirror image through an App service and an Agent service; monitoring the environment in the container in real time through the Agent service monitoring container; according to the CVE library, performing baseline compliance scanning on the Docker and Kubernetes components through an App service and an Agent service; the security scanning result, the real-time monitoring result and the baseline compliance scanning result are sent to Kafka; and processing the container environment according to the data in the Kafka, and storing the processed data into a CVE library for subsequent analysis and query. Compared with the prior art, the safety protection of the container environment is realized by constructing the own CVE library, and the distributed processing of the scanning tasks is realized by allocating the scanning tasks to different services, so that the cost is reduced while the overall scanning efficiency is improved.

The invention discloses a traveling wave electric curtain lunar dust conveying device based on three-dimensional electrodes, and relates to the field of lunar dust conveying. In order to solve the problems of low utilization rate of an electric field, easy abrasion of equipment and high energy consumption in the existing lunar dust transportation work in the prior art, the technical scheme provided by the invention is as follows: the traveling wave electric curtain lunar dust transportation device based on the three-dimensional electrode comprises a substrate; the wedge-shaped microstructure is arranged on the upper surface of the substrate, and the wedge-shaped microstructure is in a triangular prism shape; and the electrodes are arranged on the side walls of the wedge-shaped microstructures and used for generating electrodes and transporting lunar dust particles. The invention also provides a traveling wave electric curtain lunar dust transportation method based on the three-dimensional electrode, the method is realized based on the device, and the method comprises the following steps: collecting the motion state of lunar dust particles; a step of adjusting a driving voltage according to the motion state; and driving the electrode according to the adjusted driving voltage. The lunar dust conveying device is suitable for lunar dust conveying work.

The utility model discloses in-mold insert and popcorn foaming particle integrated forming sole equipment, which relates to the technical field of sole foaming forming and comprises a frame body, a fixed mold frame capable of translating is arranged in the frame body, and a movable mold frame capable of getting close to or away from the fixed mold frame is arranged above the fixed mold frame by taking the translating direction of the fixed mold frame in the frame body as the left-right direction. A fixed mold and a movable mold are installed in the fixed mold frame and the movable mold frame correspondingly and are integrally formed through 3D printing, and a plurality of nanoscale holes which are formed in a penetrating mode and can allow steam or water flow to enter are formed in the inner circumferential wall of the top of a mold cavity of the fixed mold and the inner circumferential wall of the top of a mold cavity of the movable mold correspondingly. A plurality of elastic telescopic positioning pieces used for fixing a carbon plate are arranged in die cavities of the fixed die and the movable die, a feeding port used for feeding and a plurality of air holes used for steam to pass through are formed in the bottom of the die cavity of the fixed die, and a vacuumizing assembly is further arranged on one side of the frame body. According to the scheme, the sole and the carbon plate can be integrally formed, and the carbon plate of the formed sole cannot be subjected to performance reduction or damage.

The invention discloses a high-voltage line safety distance prediction method based on electric field intensity and probe speed change, and relates to the technical field of electric field safety, and the safety distance prediction method comprises the steps of early-stage preparation, input parameter acquisition, data processing, prediction model construction, alarm and feedback, and later-stage maintenance. The method has the advantages that the actual distance between the probe and the high-voltage line can be predicted more accurately by integrating multivariate data such as the electric field intensity, the change trend of the electric field intensity and the movement speed and direction of the probe, training a prediction model in combination with a neural network algorithm and calculating a loss function value by using a formula; according to the method, false alarms and alarm distance errors caused by changes of environmental factors are reduced, the precision and reliability of high-voltage line safety distance prediction are improved, and alarm mechanisms of different levels can be triggered by comparing the prediction result output by the prediction model with the preset safety distance threshold value.

The invention provides a high-water-resistance optical film and a polarizing plate comprising the same. The high-water-resistance optical film comprises a base film, a water-resistance layer and an adhesive layer, the structure of the high-water-resistance optical film comprises a water-resistance layer, a first adhesive layer, a base film and a second adhesive layer which are stacked in sequence, or the water-resistance layer, the base film and the second adhesive layer which are stacked in sequence, the surface of the waterproof layer is provided with nanometer protrusions and micropore structures which are uniformly and orderly arranged. The high-water-resistance optical film has excellent hydrophobicity, the water-resistance layer can efficiently absorb ultraviolet radiation, the problems of aging, yellowing, embrittlement and the like of the optical film caused by ultraviolet radiation are effectively prevented, the high-water-resistance optical film can be applied to a polarizing plate, and the service life of the polarizing plate is greatly prolonged.

The invention discloses an anti-static polyether-ether-ketone composite film as well as a preparation method and application thereof, relates to the technical field of electrostatic protection materials, and solves the problem of poor dispersity of single-form conductive fibers in a polyether-ether-ketone material in the prior art. The In2O3SnO2 (at) CF composite material with the multilayer porous structure and the superfine hollow structure is prepared through a spinning method and a solvothermal method, the specific surface area of the material is increased, and the conductivity is remarkably improved. The anti-static polyether-ether-ketone composite film is prepared by utilizing a method that indium and tin metal ions in the In2O3SnO2 (at) CF composite material can form stable coordinate bonds with amino groups and carboxyl groups in polyether-ether-ketone containing amino groups and carboxyl side groups, so that the interface bonding capacity between the In2O3SnO2 (at) CF composite material and the anti-static polyether-ether-ketone composite film is remarkably enhanced; the stability and the durability of the anti-static polyether-ether-ketone composite film are further improved. The anti-static film can be applied to preparation of anti-static films of integrated circuit chips and sensors in mobile phones or small electronic equipment.

The invention relates to the technical field of high-density packaged chips, in particular to a high-density packaged chip and a packaging structure, the high-density packaged chip comprises a mounting shell, a cover plate, a positioning mechanism and a circuit connecting mechanism, a substrate is arranged in the mounting shell, a mounting groove is formed in the substrate, and a chip is placed in the mounting groove; the cover plate is arranged at the top of the mounting shell; a silver paste bonding layer is arranged in the mounting groove and is used for fixing the chip; a heat-conducting plate is arranged at the top of the chip; the positioning mechanism comprises a positioning plate, a positioning bolt and a clamping block; the positioning plate is arranged above the heat conducting plate, the clamping blocks are arranged at the two ends of the positioning plate, and the inner walls of the ends, extending out of the mounting shell, of the clamping blocks are clamped with the outer side wall of the mounting shell; a positioning hole is formed in the base plate; a positioning bolt is arranged at the bottom of the positioning plate; a plurality of welding spots are arranged on the two sides of the top of the heat conducting plate and connected with the circuit connecting mechanism. The packaging structure provided by the invention has good thermal conductivity, and provides enough space for integration of other elements while ensuring stable installation of the chip.

The present invention discloses an L-band extended hybrid fiber amplifier, which belongs to the technical field of broadband fiber amplifiers. The system includes a first amplifying module and a second amplifying module; the first amplifying module is used to amplify the signal power of a conventional signal band; the second amplifying module is provided with an erbium-doped fiber, which is used to eliminate the backward ASE generated by the first amplifying module and amplify the signal power of an extended wavelength band. The present invention connects a section of highly-absorbent thulium-doped fiber to the front end of the first amplifying module including an erbium-doped fiber and a wavelength division multiplexer, and utilizes its absorption and emission characteristics in the C+L band to eliminate the backward 1.5μmASE generated in the system, thereby improving the L-band extended band amplification performance. The system of the present invention has a simple structure, high cost-effectiveness, and high efficiency, and at the same time meets the urgent demand for communication capacity of the current optical fiber communication system.