779results about How to "Improve compression efficiency" patented technology

The invention discloses an audio and video joint coding and decoding method based on generative artificial intelligence. The coding comprises the following steps: extracting various modal features from an audio signal and a video; fusion is carried out in cross-modal attention; task identification: firstly identifying a current task type, determining the task type, and analyzing specific requirements of the task by a system; dynamic self-adaptive weight distribution is carried out; and fusing the features, namely fusing the multi-modal features distributed with different weights. The audio and video joint coding method has the advantages that audio and video feature extraction, video feature extraction and AI-based generation technologies are applied to audio and video joint coding for the first time, and the problems that when video coding and decoding are conducted through a traditional method, compression efficiency is low, and the pursuit of higher quality cannot be met are solved. Meanwhile, on the basis of a generation type coding and decoding mode, the style and quality can be flexibly adjusted according to the personal requirements of the user.

The invention discloses a high-compression-ratio image compression method based on optimal transmission mapping, which is suitable for application scenes such as network transmission, image storage and image transmission, and can remarkably improve the image transmission efficiency and save network bandwidth and storage resources. Compression can be carried out based on generative adversarial learning or a diffusion model, and the generative adversarial learning is utilized by the generative adversarial learning to train an image compression model based on optimal transmission mapping. The model comprises a feature extraction layer, a mapping layer, a quantization coding layer and a decoding reconstruction layer. The mapping layer realizes mapping and optimization of image features through optimal transmission mapping based on convex mapping; an image compression model of the latter comprises a feature extraction layer, a mapping layer, a quantization coding layer and a decoding reconstruction layer, the feature extraction layer is responsible for coding the preprocessed image into low-dimensional feature representation, quantized features are restored into image features through a denoising network of a diffusion model, and the decoding reconstruction layer is responsible for decoding the image. And decoding the image into a high-quality compressed image close to the original image.

The invention relates to the technical field of data storage, and discloses a lossless compression algorithm-based data storage method, which comprises the following steps of: receiving to-be-stored data through a data interface, automatically identifying a data format by using a data analysis tool, and performing feature analysis to obtain the size, the type and the complexity of the data; through deep analysis of data features, the method can flexibly select a proper Huffman coding processing mode, and optimizes a compression process according to different data types and complexity. In addition, a context modeling optimization mechanism is introduced, the coding mode is dynamically adjusted, and the compression ratio and the storage efficiency are further improved; efficient storage and reliability verification of data are ensured through a block storage strategy in combination with metadata management; the problem that an existing compression algorithm is low in efficiency is solved, the integrity and reliability of data storage are improved, and the method is suitable for storage requirements of large-scale data and diversified data.

The invention discloses a method for generating a three-dimensional building GLTF file based on index compression. The method comprises the following steps: S1, collecting three-dimensional coordinate data of a building; s2, grouping and classifying the data according to floors to form a classification index structure based on a hash table; s3, selecting a reference model and recording Mesh data and vertex coordinates of the reference model; s4, calculating a translation matrix T of the polyhedral structure, and performing coordinate transformation; s5, generating Mesh data of other polyhedrons based on index compression, and reducing redundant surface data by adopting a topology preserving surface optimization algorithm; s6, independently processing the geometric data of each floor, and generating corresponding Mesh data and Node nodes; and S7, combining all floor data to generate a complete GLTF file, and performing compression by using a dynamic Huffman coding algorithm. Through the improved index compression and dynamic Huffman coding technology, the file size is remarkably reduced, the transmission efficiency is improved, and the geometric and topological integrity of the model is ensured.

The invention discloses a data compression method and device and a data decompression method and device.In the compression method, data to be compressed are processed according to a Huffman coding mode to obtain a first data table, then the first data table is standardized to obtain a second data table, and the second data table is compressed according to the Huffman coding mode. Obtaining a hierarchical table according to the second data table, obtaining serial numbers of all leaf nodes through a formula on the basis of the hierarchical table, outputting codes corresponding to the characters according to the serial numbers and depth of the leaf nodes, and compressing the data according to the codes; in the decompression method, decompression can be carried out only by acquiring the coding table or the weight table generated in the compression process of the data to be decompressed; and the Hoffman tree does not need to be traversed in the compression and decompression processes, so that the compression and decompression efficiency of the data can be improved.

The invention discloses an end-to-end video coding method based on a scale-spatial stream and hierarchical hyper-prior, and the method employs a hierarchical hyper-prior coding and decoding network to introduce hyper-prior information to assist the generation of entropy model parameters, thereby enabling an entropy model to obtain more accurate estimation probability distribution, and improving the compression efficiency. And meanwhile, the motion information of the video is better estimated in combination with a scale-spatial stream, and the video coding performance is improved by estimating a more accurate entropy model and motion information. Experimental results show that when SSIM and MS-SSIM are respectively adopted as evaluation standards, compared with an HEVC (High Efficiency Video Coding) standard, the coding method provided by the invention has the advantage that the average code rates are respectively saved by 16.40% and 15.63% under the same distortion condition for video sequences with different resolutions. Compared with a traditional video compression method, the quality of the compressed low-resolution video can be effectively improved, and a good visual effect can be obtained through the method provided by the invention.

The invention relates to the technical field of intelligent garbage cans, in particular to an intelligent classification garbage can based on screw drive, which comprises a main body frame, the top of the main body frame is provided with a top cover, the top cover is provided with a garbage throwing port, and the front side surface of the main body frame is provided with a liquid crystal display controller; a spiral conveying mechanism is arranged below the garbage throwing opening and used for achieving garbage separation. A synchronous belt and a roller mechanism are arranged below the spiral conveying mechanism and are used for realizing garbage conveying; a storage mechanism for receiving garbage is arranged below the synchronous belt and the roller mechanism, and a rotary chassis mechanism is arranged below the storage mechanism; a battery is arranged on one side of the synchronous belt and the roller mechanism, and a compression mechanism is arranged on the other side of the synchronous belt and the roller mechanism and used for compressing the recyclable garbage. The garbage classification efficiency can be effectively improved, the intelligent degree of the garbage can is improved, and the difficulty of later garbage centralized classification treatment work is reduced.

The invention provides a deep learning-driven data processing and compression method and system, and belongs to the technical field of cloud computing, and the deep learning-driven data processing and compression method and system comprises a data acquisition and preprocessing module which is responsible for obtaining original data from different sources, including images, videos, audios or sensor data and the like; the data is subjected to preliminary cleaning, format conversion and standardization processing, it is ensured that the data quality meets subsequent processing requirements, the system can dynamically adjust a compression strategy and model parameters according to real-time changes of data content through the optimization and self-adaptive control module, it is ensured that the optimal compression effect and the resource utilization rate can be achieved in different scenes, and the system reliability is improved. The module also realizes model compression and optimization technologies, such as quantification, network pruning and knowledge distillation, which effectively reduce the memory usage and calculation cost of the model, and further improve the efficiency of data processing and compression.

The invention relates to the technical field of data storage, in particular to a construction engineering measurement data storage method and system.The construction engineering measurement data storage method comprises the steps that the overall character frequency and the stage character frequency are obtained by analyzing the occurrence frequency of characters in each piece of measurement data in the measurement data; analyzing key data in the measurement data based on the stage character frequency to obtain the key data representation degree of each character; the change degree of the stage character frequency of each character in different construction stages is analyzed, the change degree of the total data amount of the measurement data in different construction stages is analyzed, and the future change trend degree of each character is obtained; according to the future change trend degree and the key data representation degree, the coding priority of each character is obtained in combination with the overall character frequency; and according to the coding priority, endowing each character with a coding length to complete the compression and storage of the data. The compression efficiency can be effectively improved, and the subsequent access efficiency of key data can be taken into account at the same time.

The invention relates to the technical field of data processing, in particular to a data compression and block storage processing method based on deep learning. The method comprises the following steps: acquiring integrated data to be compressed; analyzing the effective to-be-compressed integrated analysis data according to the to-be-compressed integrated data; constructing a heterogeneous data feature analysis tree model; extracting to-be-compressed feature data of the effective to-be-compressed integrated data through the heterogeneous data feature analysis tree model; designing a recursive sparse coefficient evaluation objective function based on the to-be-compressed feature data; performing adaptive sparse compression processing on the effective to-be-compressed integrated data based on the recursive compression sparse coefficient evaluation objective function to obtain compressed data; performing block processing on the compressed data to generate block compressed data; and performing compressed data block storage optimization processing on the partitioned compressed data to generate an optimized storage compressed data block. According to the method, data features are analyzed through a deep learning algorithm, so that efficient processing of data compression and block storage is realized.

The invention relates to the technical field of video coding, in particular to a power system monitoring video rapid coding optimization method and system, and the method comprises the steps: extracting a plurality of maximum coding units of a power system monitoring video frame; a quantization parameter is introduced, and a deep learning-based adaptive multi-scale space prediction network is used to predict the maximum coding units to obtain an optimal sub-coding block division mode of each maximum coding unit; dividing the maximum coding unit according to the optimal sub-coding block division mode to obtain sub-coding blocks to be coded; performing mode prediction on the sub-coding block by using a texture sensing network to obtain an optimal intra-frame coding mode of the sub-coding block; and coding the sub-coding blocks of the monitoring video of the power system according to the optimal intra-frame coding mode to obtain coded video stream data. According to the method, the intra-frame prediction process is optimized by combining the adaptive multi-scale space prediction network and the texture sensing network, the coding complexity is reduced, and the video coding speed is remarkably improved while the image quality is ensured.

The invention discloses a cryogenic reliquefaction device utilizing natural gas cold energy. The cryogenic reliquefaction device comprises a compressor, an expansion machine and a motor used for driving the compressor and the expansion machine to rotate. The compressor is sequentially connected with the water cooler, the backheating heat exchanger, the expansion machine and the supercooling heat exchanger through pipelines to form a cooling loop; a cooled loop is formed between the supercooling heat exchanger and the liquefied natural gas storage device; at least one refrigerant side inlet of the backheating heat exchanger is communicated with the liquefied natural gas storage device, and an outlet of the backheating heat exchanger is communicated with the boil-off gas collecting facility. When the reliquefaction device works, natural gas cold energy can be fully utilized, part of heat exchange loss of the heat exchanger is offset, the inlet and outlet temperature of the compressor is improved, the compression efficiency is greatly improved, meanwhile, the use amount of cooling water can be reduced, and therefore the comprehensive efficiency of the reliquefaction device is improved. And the device has high economic and practical values in occasions where natural gas is needed.

The invention provides a video compression method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the frame-by-frame disassembly of a source video uploaded by a user, and generating a continuous frame sequence; performing image semantic recognition on each video frame in the frame sequence to obtain a semantic word set corresponding to each video frame; according to the semantic word sets, key frames and non-key frames in each video frame are judged frame by frame, the semantic word sets corresponding to the key frames are compared, and repeated frames identical to the key frames are determined; and deleting the non-key frames and the repeated frames, and generating a compressed video to complete compression of the source video. Compared with the prior art, the content of each frame can be analyzed in detail; key information in the video can be identified, non-key frames and repeated frames can be deleted, and redundant information in the video can be remarkably reduced; therefore, the video compression efficiency can be improved, and the video compression quality can be optimized.

The invention relates to a multiplier based on radix-4Booth coding and an improved Wallace compression tree, and the multiplier comprises a partial product generation module which recodes an input multiplier into a plurality of partial products through employing a Radix-4Booth algorithm, and forms a compact partial product array; the partial product compression module is used for quickly compressing the partial product through two compressors by utilizing an improved Wallace tree compression structure, and reducing the calculation path delay; and the final summation module is used for summing the compressed partial product by using a high-speed summator to obtain a final multiplication result. According to the invention, a radix-4Booth coding algorithm is adopted, so that a partial product array is regularly arranged, the circuit area is reduced, a new tree type compression structure in which a 3-2 compressor and a 4-2 compressor are mixed is adopted to realize a Wallace tree, the compression efficiency is improved, and the key delay is reduced.

The invention relates to the technical field of digital model storage, in particular to a digital model storage method for a multi-material 3D printing denture, and the method comprises the steps: determining a local complexity index based on point cloud data and the smoothness and complexity of all point cloud data in a neighborhood of the point cloud data at corresponding positions on a fitting curved surface, determining neighborhood complexity by combining the distances from each point cloud data and all the point cloud data in the neighborhood to the fitting curved surface and the distances from each point cloud data to all the point cloud data in the neighborhood; and determining a comprehensive complexity index of each point cloud data based on each point cloud data and an included angle between the normal vectors of all the point cloud data in the neighborhood of the point cloud data on the fitting curved surface in combination with the neighborhood complexity, and storing the denture digital model. According to the method, the resource waste in the storage process of the digital model of the 3D printing false tooth is reduced by analyzing the complexity of the digital model of the false tooth.

The invention relates to the technical field of live broadcast systems, and discloses a multi-scene live broadcast system, which comprises an acquisition module, an encoding module, a transmission module, a processing module, a storage module, a playing module and an interaction module, and is characterized in that the acquisition module, the encoding module, the transmission module, the processing module, the storage module, the playing module and the interaction module are arranged; the system can meet the requirements of various scenes such as live broadcast with goods, online education, entertainment live broadcast and the like, provides more flexible and diversified live broadcast services, adopts advanced coding technologies such as an AAC encoder and an H.264 encoder, carries out quantization processing, improves the compression efficiency and transmission stability of audio and video data, improves the quality of live broadcast pictures and sounds, and improves the user experience. The problems of jamming, distortion and the like are reduced; the interactive experience can be enhanced, the interactive experience between the users is enhanced through the arrangement of the interactive module, the users can participate in live broadcast through various interactive modes, and the participation sense and the satisfaction degree of the users are improved.

The invention provides a memory management method and device, equipment, a storage medium, a program product and a chip. The method relates to the technical field of mobile terminals. Comprising the steps of starting an asynchronous compression process under the condition that a current idle memory is lower than a waterline value; and traversing the plurality of memory control groups, and allocating a thread to each memory control group through an asynchronous compression process so as to compress the anonymous page in each memory control group. According to the method provided by the invention, the compression efficiency is improved by asynchronizing the anonymous page compression part in the memory recovery process, creating the thread pool and performing parallel compression according to the memcg memory control group, and meanwhile, the asynchronous memory compression process does not influence the main recovery process.

The invention provides a quadratic screw pitch double-screw rotor and a vacuum pump, and belongs to the technical field of vacuum pumps, the quadratic screw pitch double-screw rotor comprises a male rotor and a female rotor which are meshed with each other, the male rotor and the female rotor are rotationally meshed in opposite directions, the screw pitch of the male rotor and the female rotor is reduced from a suction end to an exhaust end in the circumferential direction, and the screw pitch changes along with a rotation angle in a quadratic relation; and a quadratic screw pitch design is adopted, so that the screw pitch of the screw is allowed to be decreased in a quadratic manner in the axial direction, the suction volume is further increased, and energy consumption and gas leakage are effectively reduced. The method is suitable for application scenes of high compression ratio and deep vacuum, compression efficiency can be effectively improved, energy loss is reduced, reliability of equipment is improved, and the service life of the equipment is prolonged.

The utility model discloses a compression mechanism hydraulic system of a garbage collection vehicle and a working method of the compression mechanism hydraulic system in the field of hydraulic systems, which comprises a push plate oil cylinder, a scraper oil cylinder and a sliding plate oil cylinder, and a compression valve block, a back pressure valve block and a plurality of reversing valves are arranged corresponding to the push plate oil cylinder, the scraper oil cylinder and the sliding plate oil cylinder. The hydraulic oil tank supplies oil to the push plate oil cylinder, the scraper oil cylinder and the sliding plate oil cylinder through the duplex hydraulic pump, the reversing valves, the compression valve block and the back pressure valve block. The garbage compression device can improve the garbage compression rate and compression efficiency, plays a role in protecting the compression mechanism, and is convenient for personnel to maintain.

The embodiment of the invention discloses a data storage method and device, equipment, a medium and a program product. The method comprises the steps of obtaining to-be-stored target data; based on multiple first compression modes, performing parallel compression processing on the target data, and based on the actual compression speed of each first compression mode, determining a target first compression mode corresponding to the target data and a first compressed file compressed based on the target first compression mode; determining a first index value corresponding to the first compressed file, wherein the first index value comprises identification information of a first storage bucket allocated at the time; and based on the first index value, storing the first compressed file into a first storage bucket in the object storage service, establishing a target mapping relationship between the first index value and the identification information of the target data, and storing the target mapping relationship into a database. Through the technical scheme of the embodiment of the invention, the data storage cost can be effectively reduced, and the data storage efficiency and management convenience are improved.

The embodiment of the invention provides a hyperspectral image coding method, a hyperspectral image decoding method and related equipment, and the coding method comprises the steps: firstly, dividing a hyperspectral image into a basic image and an additional image, the basic image comprising anchoring wave band data, and the additional image comprising non-anchoring wave band data; then, spectral interpolation processing is carried out on anchoring wave band data in the basic image, and an interpolation basic image containing non-anchoring wave band data is obtained; next, based on a difference value between the additional image and the interpolation basic image, obtaining an actual residual image; then, inputting the basic image into a spectral super-resolution network to generate a predicted residual image, and obtaining an optimized network parameter based on a difference value between the actual residual image and the predicted residual image; and finally, obtaining image coding data of the hyperspectral image based on the optimized network parameters and the basic image, thereby effectively improving the coding compression efficiency of the hyperspectral image.

The utility model relates to kitchen waste compression equipment which comprises a compression box, the top of the compression box is fixedly connected with a smashing box, the top of the smashing box is fixedly connected with a feeding port, a smashing structure is fixedly arranged in the smashing box, and an ultraviolet lamp is fixedly connected in the compression box. The inner side wall of the compression box is fixedly connected with an electric heating pipe. According to the kitchen waste compression equipment, by arranging the smashing structure, material residues can be automatically removed, fall and discharged along with rotation of the grinding rollers, the material residues are effectively prevented from being accumulated on the inner wall of the smashing box or all parts, and meanwhile the problem that due to the fact that the material residues are accumulated on the inner wall of the smashing box, other workpieces of the equipment break down is solved; meanwhile, bacteria and viruses in the kitchen waste can be killed, peculiar smells generated during compression of the kitchen waste are reduced, the scientific and reasonable requirements are met, a large amount of kitchen waste can be continuously spin-dried and compressed, and the compression efficiency of the kitchen waste is improved.

The invention relates to an index prefix compression processing method and device, computer equipment, a computer readable storage medium and a computer program product, and relates to the technical field of databases. According to the method, intelligent compression of the index prefix can be realized, the compression efficiency is improved, the space occupation is reduced, and the storage overhead of the index is reduced. The method comprises the following steps: generating a prefix symbol for simplifying and representing a corresponding repeated prefix part according to the repeated prefix part of each original index through a symbol generation model; the symbol generation model generates a prefix symbol corresponding to the original index based on the use condition of a historical index containing a historical prefix symbol and / or the use condition of an index sample containing a prefix symbol sample; registering each prefix symbol corresponding to each repeated prefix part in a prefix symbol table; and for the target index, replacing the repeated prefix part of the target index with the corresponding prefix symbol according to the prefix symbol registered in the prefix symbol table.

The invention relates to the technical field of compressed air energy storage, in particular to an industrial waste heat coupling isothermal non-afterburning compressed air energy storage system which comprises an isothermal compression energy storage module, an isothermal compression heat recovery module, an industrial waste heat conversion module and an expansion power generation module. The isothermal compression energy storage module achieves multi-section compression of air and stores compressed air through electric energy in the valley period, and the isothermal compression heat recovery module is used for collecting compression heat generated by the isothermal compression energy storage module during multi-section compression of the air. The expansion power generation module receives the industrial waste heat stored by the industrial waste heat conversion module and is used for compressed gas expansion power generation; the isothermal compressor technology is adopted for compressing air, the compressed air energy storage efficiency is improved, the compression power consumption is reduced, meanwhile, industrial waste heat is fully utilized for heating the compressed air in the expansion stage, the problem that compression heat is insufficient in the isothermal compression process is solved, and the energy storage efficiency and the energy-saving effect are higher.

The invention relates to the technical field of aviation, in particular to a variable-geometric-axis symmetric supersonic air inlet channel, an aircraft and a control method, and aims to solve the problem that in the prior art, due to the movement distance of a center cone, a molded surface with variable-geometric-axis symmetric supersonic speed dramatic change easily induces flow separation. The variable geometric axis symmetric supersonic air inlet channel is applied to an engine and comprises a center cone, an outer casing, a supporting assembly and a drainage ring, the center cone is located in the outer casing, the head end of the center cone is in sliding connection with the inner side wall of the air inlet end of the outer casing, and the supporting assembly is fixed to the air outlet end of the outer casing; the tail end of the center cone is fixed to the inner side wall of the air outlet end of the outer casing through a supporting assembly, a plurality of drainage grooves allowing fluid to flow in are formed in the head end of the center cone, and the drainage rings are arranged at the drainage grooves. The variable geometric axisymmetric supersonic air inlet channel, the aircraft and the control method are used for design of aero-engines.

The invention relates to the technical field of data processing, in particular to a rail train fusion host-oriented data integration method, which comprises the following steps of: acquiring and preprocessing multi-dimensional time sequence data when a rail train runs; determining a target dimension between a target shift and a non-target shift based on the preprocessed multi-dimensional time series data, obtaining corresponding specificity through the target dimension, constructing a target dimension set, obtaining a weight of each dimension of the target shift, and determining a non-standard factor of the target shift; determining a first attention degree and a second attention degree of each initial time period based on the non-standard factors and the multi-dimensional time sequence data, and constructing an attention degree sequence of the target shift from the starting point to the end point by combining the first attention degrees and the second attention degrees to obtain a plurality of optimal time periods and corresponding attention degrees; and carrying out parallel coding on all dimension time sequence data corresponding to the optimal time period, and taking the attention corresponding to the optimal time period as a label to complete data integration.

The invention provides a large model cue word compression method based on dynamic budget allocation. The method aims at optimizing the cue word length of a large language model so as to improve the calculation efficiency of the model and reduce the calculation cost. Through cooperative work of the dynamic budget distributor and the vocabulary selector, the cue words can be compressed on the premise of ensuring semantic integrity. Firstly, a dynamic budget distributor dynamically distributes a vocabulary retention budget of each sentence based on the correlation between each sentence and a question; then, the vocabulary selector calculates the retention probability of each vocabulary through the strategy network, and key vocabularies are preferentially retained; and evaluating loyalty and similarity of compression prompts through a reward function module, and guiding a strategy gradient to update network parameters. According to the method, the performance of the large language model is remarkably improved, and the method is suitable for prompt optimization in scenes such as multi-round dialogues and long text analysis.

The invention discloses a streaming error bounded floating point type data compression method. The method comprises the following steps: acquiring an original time sequence of a floating point type to be compressed; the quantization-based streaming error bounded floating point compression method comprises the following steps of: quantizing a floating point value in an original time sequence into an integer quantized value; encoding the quantized value to generate a compressed bit stream as a compression time sequence; the invention discloses a streaming error bounded floating point compression method based on XOR operation. The method comprises the following steps: displacing a floating point value in an original time sequence to obtain a displacement value; converting the displacement value into an approximate value; performing exclusive-or operation on each approximate value and the previous approximate value to obtain an exclusive-or value; and encoding the XOR value to generate a compressed bit stream as a compression time sequence. According to the method, the streaming error bounded floating point compression method based on quantization and XOR operation is designed to realize the streaming floating point compression with the error bounded, and the compression requirements of streaming time series data of the Internet of Things and the like can be better met.

The invention relates to the field of air compressors, and particularly discloses an air compressor air inflow adjusting device which comprises a supporting frame, a compression mechanism is arranged on the supporting frame, an air storage cylinder communicated with the compression mechanism is arranged on the supporting frame, the air storage cylinder is communicated with working equipment, and a driving mechanism is arranged on the supporting frame. The driving mechanism is used for driving the compression mechanism to move so that the compression mechanism can compress air. The standard pressure of the compressed air in the air storage cylinder and the actual pressure of the compressed air of the compression mechanism can be utilized, different adjustment degrees of the upper communication assembly and the lower communication assembly are achieved, the purpose of adjusting and controlling the air inlet amount of the air inlet adjusting assembly is achieved, and therefore the air inlet amount of the compressed air of the compression mechanism is adjusted; the air pressure in the compression mechanism is adjusted, air pressure balance of the air compressor is facilitated, the compression efficiency of the air compressor is improved, and the service life of the air compressor is prolonged.

The invention relates to the technical field of compressor maintenance, and discloses a compressor cooling health management system and method, and the system comprises a collection module which is used for collecting, storing and classifying the temperature and voltage data of a compressor, and a processing module which is used for carrying out the cleaning, normalization processing and feature extraction of the collected data, and building a compressor parameter monitoring model. The analysis module is used for carrying out fault diagnosis and performance evaluation on the compressor cooling system, the feedback control module is used for formulating a control strategy of the compressor cooling system and executing and adjusting the control strategy, and the parameter report is generated and displayed through a visual screen. Emergency shutdown caused by sudden failures is avoided, and the maintenance cost and the production loss are reduced.