14results about How to "Lower conditions" patented technology

The invention relates to the technical field of computer deep learning, and relates to an equipment fault diagnosis network model training method based on multi-source domain knowledge joint migration, and the method comprises the steps: constructing a training sample set, a verification set and a test set, and training a pre-constructed equipment fault diagnosis network model through the training sample set, optimizing parameters of the equipment fault diagnosis network model to obtain a trained equipment fault diagnosis network model; verifying the trained equipment fault diagnosis network model by adopting a verification set, evaluating the diagnosis performance of the trained equipment fault diagnosis network model, and selecting an optimal equipment fault diagnosis network model; and testing by adopting the test set optimal equipment fault diagnosis network model, and evaluating the performance of the optimal equipment fault diagnosis network model. According to the method, multi-source-domain cooperative training is carried out on the model by utilizing a collected multi-source-domain data set which is composed of a plurality of labeled source-domain data sets and unlabeled source-domain data sets and contains a small number of labels, domain invariant features in fault samples are learned, and shared diagnosis knowledge is migrated to a target domain from labeled data and unlabeled data together; therefore, the trained equipment fault diagnosis network model can complete a cross-domain fault diagnosis task without obtaining a target sample in advance.

The invention relates to the technical field of direct current motors, and particularly discloses a direct current brushless motor driving method. A central electric signal, a first electric signal, a second electric signal and a third electric signal of a motor stator winding are analyzed by using a signal processing and analysis algorithm based on deep learning, so that implicit features in each electric signal are captured; and after difference calculation is carried out on the center electric signal feature and other electric signal features, query code representation of the rotor rotation position is obtained in a feature query matching mode, so that the rotor rotation position is determined. Therefore, accurate judgment on the rotation position of the rotor can be realized through artificial intelligence and a deep learning algorithm, and the influence of noise interference and external condition change is reduced not only through a hardware component mode, so that the flexibility and generalization ability are improved through a more intelligent direct current brushless motor driving mode.

The invention relates to a Halton sequence optimization method and system based on RISC-V vector extension and application. The Halton sequence optimization method comprises the following steps: 1) identifying mathematical characteristics generated by a Halton sequence; a Halton sequence is generated; after continuous index values are partitioned and grouped, simultaneous processing of the multiple index values is achieved through a parallelized grouping calculation method in combination with vectorization operation; 2) carrying out vectorization optimization by using an RISC-V vector instruction; in a Halton sequence generation process, carrying out parallel processing on the grouped index values by using an RISC-V vector extension instruction; 3) packaging into a dynamic link library; and 4) integration and calling with a Hadoop framework. According to the Halton sequence generation method, the number of loop iterations is remarkably reduced, and the Halton sequence generation efficiency is greatly improved. According to the method, resource waste in traditional serial computing is avoided, meanwhile, branch jump and condition judgment expenses are reduced, and the utilization rate of hardware computing resources is increased.

The invention relates to the fields of preparation of a composite functional aerogel carbon material and antibiotic wastewater purification, in particular to a method for creating a functional aerogel carbon high-long-acting purification material based on a waste disposable mask as a carbon source. Comprising the following steps: preparing a precursor solution taking a waste disposable mask as a carbon source, carrying out metal grafting on a precursor to obtain a base material, freeze-drying the base material to prepare metal-grafted functional aerogel, uniformly dispersing the product at the bottom of a porcelain boat, placing the porcelain boat in a tubular furnace, carrying out high-temperature pyrolysis in an argon atmosphere, and naturally cooling to room temperature to obtain the metal-grafted functional aerogel. The functional carbon aerogel with the high and long-acting purification effect is obtained. According to the material, polypropylene serving as a main component of a middle layer of a waste disposable medical mask serves as a carbon source, a metal polyphenol network is constructed by waxberry tannin and magnesium element to form the biomass carbon composite material, synthesis steps are simple and easy to implement, reaction conditions are easy to control, raw material components needed for preparation are low in price, and environmental benefits are achieved. The prepared carbon aerogel material activates peroxydisulfate (PDS), so that rapid degradation and purification of various types of antibiotics represented by oxytetracycline can be efficiently realized.

The invention belongs to the field of chemical engineering, and particularly relates to a method for recycling and preparing methyl acetoacetate. The method comprises the following steps: mixing the tower kettle residual liquid of a crude product diethyl methyl ester finished product tower with methanol by taking methanol as an extracting agent, keeping the temperature, stirring, and standing for layering; and taking the upper-layer methyl diethyl ester methanol solution for rectification, and stopping discharging when the kettle temperature rises to 56-60 DEG C to finally obtain methyl diethyl ester. The content of the prepared and recovered diethyl methyl ester is 95.23 to 96.53 percent, and the molar recovery rate of the diethyl methyl ester is 82.99 to 88.21 percent through calculation. According to the method, the loss of the diethyl methyl ester is reduced, the recovery rate of the diethyl methyl ester and the quality of a finished product are improved, meanwhile, harmless treatment is carried out on the tower kettle raffinate, the environmental pollution is reduced, and the waste treatment cost is reduced for chemical enterprises.

The invention provides a method and device for measuring the cuttable property of rock and a tunneling machine, and relates to the technical field of rock tunneling, and the method comprises the following steps: obtaining the invasion force and the invasion depth of the rock to be measured; obtaining a rock invasion change curve according to the invasion force and the invasion depth; and calculating according to the rock invasion change curve to obtain cutting force and cutting specific energy consumption, and determining the cuttable property of the rock to be tested according to the cutting force and the cutting specific energy consumption. According to the method, more accurate rock strength parameters can be obtained by measuring the invasion force and the invasion depth of the rock, meanwhile, the cutting force and the cutting specific energy consumption are directly predicted based on the rock strength parameters through an established mathematical model and an empirical formula, the influence of personal errors and experimental conditions is reduced to a certain extent, and the method is suitable for large-scale popularization and application. Therefore, the test speed is improved. By accurately calculating the two parameters of the cutting force and the cutting specific energy consumption, the cutting performance of the rock can be more accurately tested, and the test accuracy is effectively improved.

This invention provides a method for preparing transparent polycrystalline diamond nanoparticles at low temperatures, comprising the following steps: S1: Mixing: Using hydrogen-modified carbon nanospheres as raw materials, the raw materials are mixed after removing moisture and impurities; S2: Pressing: The mixed raw materials are pressed into cylindrical shapes according to the size of the synthesis chamber using a hydraulic press; S3: Assembly: The cylindrical raw materials are placed into a heating container and then assembled in the synthesis chamber; S4: Synthesis: The pressure is controlled at 9.0-15 GPa, the temperature at 1250-2300℃, and the holding time is 1-15 min, to synthesize the raw materials assembled in step S3 to obtain the product; S5: Cooling and depressurization: After the product synthesized in step S4 is cooled and depressurized, transparent polycrystalline diamond nanoparticles are obtained. This invention provides a low-cost and relatively simple method for preparing transparent polycrystalline diamond nanoparticles at low temperatures, which has high commercial and promotional value.

The application provides a polyethylene gas pipeline risk analysis and early warning method and system based on a knowledge graph, and relates to the technical field of urban gas safety risk assessment.The existing technology has the problems of dispersed representation of the evaluation method of the gas pipeline risk, difficulty in uniformly organizing accident cases, operation data, specification requirements and management experience, unclear expression of the cause-effect relationship between indexes, difficulty in describing the risk propagation path, high dependence on expert subjective valuation, difficulty in realizing consistent dynamic updating of the evaluation results, and inaccurate prediction results.The mapping mechanism from the knowledge graph to the fuzzy Bayesian network automatically maps the entity hierarchy and the relationship type defined in the knowledge graph into the Bayesian network nodes and the directed edges, so that the network structure construction no longer completely depends on manual analysis, the influence of subjective experience on the model structure is reduced, the modeling efficiency is greatly improved, and the social and economic safety is protected.

The invention belongs to the technical field of ammonia decomposition, and particularly relates to a method for simulating ammonia decomposition in a catalytic channel based on COMSOL simulation software. By utilizing simulation of software, part of orthogonal experiments and condition exploration can be reduced, the time and experiment cost can be reduced, researchers can clearly observe the reaction condition of an ammonia catalytic decomposition reaction area, the reaction performance and structural rationality of the catalyst can be evaluated through information such as concentration distribution of reaction substances, and the method has the advantages of simple operation and low cost. Researchers can analyze the ammonia catalytic decomposition process more conveniently, and powerful guidance is provided for experimental condition modification or structure optimization and the like of the catalyst in the next stage.

The invention discloses a preparation method and application of an infantile anorexia animal model, and belongs to the technical field of medicines. The model can be used for screening, pharmacological research and efficacy evaluation of medicines for treating child anorexia. A modeling method of erythromycin gradient increment intragastric administration is creatively adopted for the first time, and the child anorexia animal model is successfully established. Compared with a conventional high-fat and high-protein-fat feed feeding and central operation modeling mode, the modeling method has the following advantages that the modeling time is shortened, and the modeling time cost is reduced by two weeks compared with other modeling modes; compared with expensive high-fat and high-protein feed, the cost of erythromycin medicine is 1 / 10 of that of the high-fat and high-protein feed, and the time cost is shortened, so that the animal feeding cost is also reduced; the operation technology is simple and convenient; compared with preparation of a high-precision central anorexia animal model, the experiment operation technology is simple; the conditions for laboratory instruments and equipment are relatively low; the requirements of experimenters are reduced, and the labor cost is reduced.

The invention provides an automatic detection method and device for cerebral cortex micro-infarction (CMIs). According to the method and the device, the CMIs of a patient are intelligently identified and judged by using an artificial intelligence (AI) model in combination with a clinical diagnosis standard of the CMIs, and the method and the device aim at eliminating errors and low efficiency possibly caused by subjective judgment of a doctor, so that rapid, objective and accurate evaluation of the CMIs is realized. According to the method, on the basis of a magnetic resonance (MRI) image, cerebral cortex signal characteristics of a patient under a T1 sequence, a liquid attenuation inversion recovery (FLAIR) sequence and a double inversion recovery (DIR) sequence are intelligently analyzed through an AI model, rapid clinical diagnosis support can be provided for doctors, dependence on professional skills and clinical experience is reduced, the diagnosis efficiency of CMIs is remarkably improved, and the diagnosis accuracy of the CMIs is improved. The related research progress and clinical application are accelerated.

The application discloses a prompt sound statistical method, device, equipment and readable storage medium. The prompt sound statistical method comprises the following steps: obtaining square wave data corresponding to an envelope line of collected audio data; determining a time period corresponding to an a-th wave band in the square wave data; obtaining audio corresponding to the time period from the audio data to obtain a target audio segment; calculating the similarity between the target audio segment and each collected segment in the audio data; determining a first target peak point and a target threshold in a cross-correlation function; determining at least one second target peak point in the plurality of similarities; and determining the playing information of the prompt sound in the audio data according to the total number of the first target peak point and the second target peak point and the time interval between the first target peak point and the second target peak point. According to the embodiment of the application, the accuracy of determining the playing number or frequency of the prompt sound can be effectively improved, and the reliability of the test result of the device outputting the prompt sound is improved.

The application belongs to the technical field of natural product extraction and nanometer material preparation, and specifically discloses an enzyme-assisted green extraction and nanometer modification method of active polysaccharide of traditional Chinese medicinal materials. In the extraction stage, a three-stage biomimetic gradient layering degradation strategy is adopted to target the wall breaking, and subcritical water extraction is coupled to realize efficient release of polysaccharide, so that the extraction rate reaches 18-25%, and the purity is 85-95%. In the nanometer stage, the polysaccharide, chitosan, sodium alginate and tea polyphenol are constructed into core-shell type nanoparticles (50-200 nm) through ultrasonic driving layer-by-layer self-assembly, the water solubility of the polysaccharide is increased by 3-5 times, the thermal stability is increased by 30-45 DEG C, and the oral absorption rate is increased by more than 2 times.

The present invention relates to a synthesis process of a dapagliflozin intermediate, belonging to the technical field of drug synthesis. In order to solve the problem of high production cost, a synthesis process of a dapagliflozin intermediate is provided, the method comprising: in an organic solvent, acylation reaction of p-bromophenol and 4-ethoxybenzonitrile under the catalysis of Lewis acid to generate 5-bromo-2-hydroxy-4'-ethoxybenzophenone, reduction reaction of 5-bromo-2-hydroxy-4'-ethoxybenzophenone to generate 5-bromo-2-hydroxy-4'-ethoxydiphenylmethane, halogenation of 5-bromo-2-hydroxy-4'-ethoxydiphenylmethane to obtain the final product 5-bromo-2-chloro-4'-ethoxydiphenylmethane in an organic solvent; the present invention as a whole has the advantages of low production cost, high product yield, and environmental friendliness.