52results about How to "Quantitative precision" patented technology

The invention discloses a GIS-based pipe network geographic information integrated management system, and relates to the technical field of geographic information, a pipe network information acquisition module can accurately extract detailed attribute information of graphic elements in each layer from a GIS management system, and generates feature vectors through preprocessing to build a data basis for subsequent analysis. The layer display module can determine the overlapping rate of graphic elements between layers through a rigorous calculation process, analyzes the overall overlapping distribution condition, and then judges whether a visual conflict hot spot area exists or not. On the basis, the interlayer interference analysis module quantitatively calculates a visual conflict measurement coefficient and a logic correlation coefficient from the perspective of representation and internal correlation and deeply analyzes the multi-dimensional relation between layers, and the comprehensive analysis module utilizes deep learning to construct a model, integrates the coefficients and outputs a comprehensive conflict measurement index. And overall coordination performance among the layers is comprehensively evaluated.

The invention provides a memory and an optimization method thereof, and the memory is characterized in that a main control unit receives different test instructions of a processor, analyzes the test instructions, and generates corresponding control instructions; the flash memory unit is used for executing different operations according to the control instruction; the main control monitoring unit is used for recording the delay duration of the main control unit in processing different test instructions; the flash memory monitoring unit is used for recording delay durations when the flash memory unit executes different operations; wherein the main control unit judges whether the sum of the delay durations is greater than a preset total duration or not; if yes, firmware is optimized; otherwise, firmware does not need to be optimized. According to the memory and the optimization method thereof provided by the invention, the delay of the memory during execution of each operation can be quickly tested so as to carry out optimization.

The invention discloses a product full life cycle carbon emission tracking method, which is embedded in a product carbon footprint management service platform, and specifically comprises the following steps: S1, formulating a product definition boundary and a truncation standard based on a carbon emission calculation formula; s2, data acquisition and accounting are completed according to local conditions, and real-time monitoring and data acquisition are carried out on all links in the product production process. According to the method, the total emission amount of greenhouse gases directly or indirectly generated by a product in the whole life cycle of the product is calculated, including the emission in the extraction, production, transportation, use and waste processes of raw materials, so that the calculation and result traceability of the carbon footprint in the whole life cycle of the product are realized. Accurate carbon emission data are provided for enterprises, the green level of the production process and technical equipment is improved, and the transformation of the enterprises and the society to low-carbon economy is promoted.

The invention discloses a day-ahead electricity price probability prediction method and device based on deep learning, and the method comprises the steps: obtaining the meteorological state data of a to-be-predicted region and the power generation data of a power generator, and constructing prediction parameters; inputting the prediction parameter into a pre-trained day-ahead electricity price probability prediction model for prediction to obtain a day-ahead electricity price probability; the training method comprises the following steps: collecting meteorological state data of a region and power generation data of a generator, and constructing a historical data set; performing visual analysis and data preprocessing on the historical data set to obtain a prediction feature parameter set; and taking the prediction characteristic parameter set as input, taking a deep neural network (DDNN) as a basic model for training, adding hyper-parameter optimization in the training process, and carrying out probability prediction on the day-ahead electricity price by using an output probability distribution parameter. According to the method, the possible fluctuation range of the predicted value can be provided, the uncertainty level of the predicted result is reflected, and information and basis are provided for decision making such as planning prediction and operation of a power system.

The invention discloses a method for identifying the occurrence state of water in urban sludge by using extracellular polymeric substances, relates to a method for identifying the occurrence state of water in sludge, and aims to solve the technical problem that the existing method for testing the distribution of water in sludge is poor in accuracy, and the method comprises the following steps of: extracting an extracellular polymeric substance solution of urban sludge, and testing the total organic carbon content in the extracellular polymeric substance solution; or the ratio of the hydrophobic organic matter to the hydrophilic organic matter, or the content of protein, or the content of polysaccharide, or the content of humic acid, or the fluorescence intensity value of tryptophan protein, or the fluorescence intensity value of tyrosine protein, or the proportion of alpha-helix of a protein secondary structure, or the proportion of beta-corner, or the proportion of beta-helix of a protein secondary structure; the content of the free water, the chemical bound water and the mechanical bound water is calculated according to the relation curve between the parameters and the free water and the chemical bound water, the quantification precision is high, the detection precision of the sludge dewatering performance is improved, and support is provided for the sludge dewatering process.

Included is the steps of providing a plurality of standard solutions containing amyloid β-related peptide and a surfactant and having different concentrations of the amyloid β-related peptide; mixing a solution containing internal standard peptide with each of the plurality of standard solutions; performing immunoprecipitation and mass spectrometry on a plurality of calibration curve solutions; standardizing signal intensity (A) in the amyloid β-related peptide with the signal intensity (B) in the internal standard peptide for each of the plurality of calibration curve solutions; and calculating a regression equation of a calibration curve based on a plurality of normalized intensities and the concentration of the amyloid β-related peptide.

The application discloses a kind of emotion evaluation and intervention method and system based on multi-modal data.Through terminal synchronous acquisition voice, face, screen tremor and so on multi-modal data;Reaction mode vector is generated based on context information and data verification fusion;The composite emotional state of user is determined using emotional emergence model.At the same time, personalized emotional causal diagram is constructed and updated, and the enhanced state vector is generated by extracting key causal path features.The vector is input into the intervention agent to output intervention actions;After execution, the emotional state is evaluated again and the reward is calculated, and the system model is updated online.The application realizes accurate emotion evaluation and closed-loop adaptive intervention that strikes the root.

The present application relates to the technical field of agricultural product processing, and discloses a plum kernel-meat separation chute conveying device and method, which obtains real-time rotation state of double excitation vibrators and extracts dynamic phase error, obtains instantaneous angular velocity deviation through filtering processing, calculates parasitic lateral disturbance force induced by error, introduces an experience forgetting factor to perform state-decay discrete quadratic integration on the disturbance force to obtain lateral slip accumulation displacement, performs nonlinear coupling on accumulated shrinkage of the chute opening degree in a limited time window and the lateral displacement to calculate dynamic jam risk margin, and finally extracts one-way deterioration gain as an adaptive weight according to the risk margin to generate an instantaneous frequency compensation instruction for feedforward control of a lagging side excitation vibrator. The device comprises a memory and a processor, and the above method program is executed by the processor. The present application realizes dynamic prediction and active feedforward inhibition of jam risk, and greatly improves the stability and production efficiency of the conveying system.

The present invention relates to the technical field of drought remote sensing monitoring, and specifically discloses a drought remote sensing monitoring method and system integrating multi-source remote sensing data, the method comprising: dividing the area to be measured into a plurality of position units; obtaining the temperature, altitude and air pressure data of each position unit in the area to be measured, and calculating the saturated water vapor pressure difference of each position unit; simultaneously obtaining the soil moisture and sunlight-induced chlorophyll fluorescence data of each position unit in the area to be measured; performing data normalization; selecting the driest position unit as the reference position unit, comprehensively calculating the saturated water vapor pressure difference, soil moisture and sunlight-induced chlorophyll fluorescence dimensions, calculating the distance between other position units and the reference position unit, and obtaining the drought index of each position unit; and using the drought index to realize drought monitoring of different positions in the area to be measured. The present invention can more accurately quantify the degree of drought, comprehensively extract the comprehensive information of drought events, and has good reliability and accuracy.

The invention provides a flower quality grading quality inspection method and system based on AI and image processing, and belongs to the technical field of computer vision and pattern recognizing.The method comprises the steps that an original image of the surface of a flower is collected through high-resolution imaging equipment, and high-frequency sub-band data representing tiny physical characteristics are extracted through multistage discrete wavelet transform; meanwhile, a sliding window is adopted to traverse the image, the color information entropy of a local area is calculated, and a color entropy graph is constructed. And after vectoring and splicing the two types of features, inputting the two types of features into a deep belief network model based on a multilayer restricted Boltzmann machine, and extracting deep abnormal feature codes. And finally, performing linear discriminant analysis on the code by utilizing a classification projection vector based on inter-class and intra-class distance optimization to generate an insect attack infection index, and realizing automatic grading quality inspection of the flower quality according to the insect attack infection index. According to the method, precise recognition and quantitative grading of tiny insect pests and recessive lesions on the surfaces of the fresh flowers are realized.

The invention relates to the technical field of nondestructive testing, in particular to a copper bar coating lower substrate defect nondestructive testing device based on terahertz waves, which comprises a terahertz scanning acquisition module used for controlling a transmitting and receiving unit to perform two-dimensional scanning so as to acquire an original waveform; the flight time dynamic correction module is used for resolving the local coating thickness and carrying out dynamic time axis alignment; the substrate roughness deconvolution module is used for calling the reference model to carry out deconvolution filtering so as to strip background scattering noise; the interface dielectric feature analysis module is used for extracting a dielectric feature vector reflecting an interface dielectric constant mutation state; the defect risk assessment imaging module is used for constructing a three-dimensional chromatography map and outputting a detection result; according to the method, the physical characteristic decoupling of the signal source is realized, the coating thickness fluctuation and the real defect are effectively distinguished, the misjudgment rate is obviously reduced, and the evaluation accuracy is ensured.

The invention discloses an energy consumption optimization calculation method in an industrial enterprise intelligent supply chain, and belongs to the technical field of industrial enterprise energy consumption management. The purpose of collaborative improvement of energy consumption and efficiency of industrial enterprises is achieved. The method comprises the steps of collecting 6 types of basic data based on an existing digital system of an industrial enterprise intelligent supply chain, and performing energy consumption data fusion and calibration to obtain energy efficiency indexes of the 6 types of basic data; a cross-link energy consumption synergistic effect of a logistics link, a storage link and a production link is considered, and a smart supply chain collaborative energy consumption coupling factor is calculated; order fluctuation data and inventory turnover data are introduced for elastic correction, and a corrected dynamic energy consumption factor is obtained; and considering the energy-saving technology of the intelligent supply chain, calculating an energy-saving cost balance factor based on the corrected dynamic energy consumption factor, introducing a carbon emission reduction coefficient and the equipment scheduling elasticity of the intelligent supply chain, calculating the optimal power consumption target value of the future one month, and directly applying the finally output kilowatt-hour level target value to the real-time scheduling decision of the intelligent supply chain.

The invention discloses a crop growth drought stress detection system and method, belonging to the technical field of facility agriculture biological information detection. The system comprises an acquisition platform, a multi-spectral polarization imaging system, a power supply system, a control module, a whiteboard automatic correction device, a USB signal receiver, a signal reading circuit, a storage module and a processing module. By developing a portable multi-spectral polarization imaging system, optimizing data processing and fusion algorithms, the state of plant drought stress can be obtained in time, and accurate data support can be provided for agricultural production.

The invention provides a wake wave-based thick plate structure grain size quantification method, and belongs to the field of thick plate structure grain size quantification, and the method comprises the steps: S1, carrying out the pulse signal excitation of a thick plate structure, and collecting a wake wave signal; s2, obtaining a preliminary noise reduction signal based on the collected wake wave signal; s3, variational mode decomposition is carried out on the preliminary noise reduction signal, and a limited bandwidth signal with a specific frequency is extracted; s4, fitting the attenuation coefficient by using the average power envelope of the limited bandwidth signal; and S5, obtaining a grain size quantification result considering uncertainty by using a logarithmic linear quantification model. According to the method, accurate and rapid grain size quantification can be carried out on a thick plate structure with a relatively large frequency thickness product by utilizing the characteristics of wake waves; the overall energy attenuation rule of the signal related to the grain size is effectively described through the average power envelope, the obtained wake wave attenuation coefficient can be used for accurately and reliably quantifying the grain size of the thick plate structure, and the accuracy of the prediction result is ensured.

The invention relates to a device and a method for detecting surface defects of an optical element, in particular to a device and a method for detecting surface defects of a large-aperture optical element, which are used for solving the problem that quantitative evaluation standards exist or cannot be provided when an existing detection method is used for detecting damage of the large-aperture optical element. Or the efficiency is low, the large-range detection requirement is difficult to effectively meet, or the three-dimensional shape information of the defect cannot be obtained. According to the surface defect detection device for the large-aperture optical element, the diffraction characteristic of the binary deformation diffraction grating is utilized, a plurality of diffraction spots with different diffraction orders are acquired by a camera at a time, and the surface phase of the large-aperture optical element is calculated through a phase recovery algorithm; and the whole surface of the large-aperture optical element is scanned by the laser beam in combination with the two-dimensional translation stage, so that the surface defect detection of the large-aperture optical element is realized.

The utility model discloses a kind of gas production assemblies suitable for non-pressure type fire extinguishing device, including plug, plug left side screwing fixed with high-pressure gas cylinder, plug right side screwing fixed with screw sleeve, spring is provided in screw sleeve inside, ejector pin passes through spring and is placed in spring inside, screw sleeve right side is also connected with starting component, still including starting component is composed of screw plug, after hot initiation line and electric ignition wire are inserted into silica gel cover, fixed at screw plug end, the other end of electric ignition wire is connected to wiring harness connector, the utility model has electric, two kinds of starting mode, electric starting mode consumes small energy, and need not continuous power supply;Hot starting can be through the mode of extending hot initiation line, fixed-point protection is carried out to protection area, two kinds of mode are used in combination, can satisfy the actual use demand of user to the maximum, and repeated use function can be realized by replacing high-pressure gas cylinder and starting component.

The present invention relates to the field of coking coal blending, and more specifically, the present invention relates to a method and system for controlling coal coking coal blending based on artificial intelligence. The method comprises: collecting a plurality of pre-processed coal coke block grayscale images, constructing a grayscale matching matrix of the coal coke block grayscale images; calculating the importance of each element in the grayscale matching matrix, calculating the coal coke block loss value after each experiment according to the element value and importance, and taking the ratio of the coal coke block loss values ​​of two adjacent experiments as the coal coke block stability; inputting the coal coke block loss value and the coal coke block stability into a preset neural network to obtain a coal bonding index; constructing a historical coal blending sample, clustering all historical coal blending samples, and coking coal blending according to the blending ratio in the clustering result. Through the technical solution of the present invention, the accuracy of the coking coal blending results can be improved, and the quality and characteristics of the final coke can be guaranteed.

The invention relates to a large lake region polder displacement and nitrogen and phosphorus into-river / lake contribution accounting method, model improvement is realized by introducing a polder pit-pond suspended matter transportation module into PHPS and PHNS models, the improved model is utilized to simulate the polder displacement and nitrogen and phosphorus output, and the on-way degradation amount is estimated in combination with the nitrogen and phosphorus into-river / lake contribution accounting method. And finally obtaining the contribution of nitrogen and phosphorus entering the river / lake. The method can be applied to a large lake region polder, and the hydrological flux of the polder and the contribution of nitrogen and phosphorus into the lake are more accurately quantified by combining the improved model.

The present invention relates to the technical field of motor heat dissipation, and specifically to a phase change heat dissipation method and system for a propulsion motor. The invention analyzes the data distribution of multiple curve segments in the temperature curve of each position, obtains the degree of fluctuation of each curve segment, and obtains the local heat dissipation degree of each curve segment corresponding to each position; screens out abnormal heat dissipation curve segments; obtains the overall heat dissipation degree of each position according to the time characteristics of the abnormal heat dissipation curve segments corresponding to each position, and the distribution of the local heat dissipation degree; obtains multiple heat dissipation similar position groups according to the difference in the overall heat dissipation degree between adjacent positions; obtains the flow rate control coefficient of each position at each moment, regulates the initial output power of the flow rate control device, and obtains the corresponding regulated output power; assists the propulsion motor in phase change heat dissipation. The present invention assists the phase change structure in more effective motor heat dissipation by appropriately adjusting the flow rate control device of the cooling liquid corresponding to each position.

The invention discloses a battery in-situ test system based on a product gravity-buoyancy grading mechanism, and belongs to the technical field of electrochemical energy storage and conversion. The system comprises a special-shaped cross section reaction kettle main body, an anode feeding driving mechanism, a modularized cathode interface assembly and a peripheral fluid and sensing circulation loop. The special-shaped section reaction kettle main body is provided with a top gas phase guide area, a middle electrochemical reaction area and a bottom solid phase settlement area, and in-situ separation and collection of gas, liquid and solid three-phase products are realized by utilizing gravity and buoyancy. And the anode feeding driving mechanism is used for realizing axial feeding of the anode and maintaining a constant inter-electrode distance. The modular cathode interface assembly is used for realizing quick assembly, reliable sealing and efficient current collection of an air cathode. And the peripheral fluid and sensing circulation loop is used for realizing field-liquid separation type monitoring. The problems that in the prior art, bubbles are shielded, mechanically peeled products are difficult to quantify, the polar distance cannot be changed, and monitoring interference is large are solved.

The application discloses a CDC shock absorber whole vehicle abnormal sound quantification method, device, equipment and medium, relates to the automobile NVH test and diagnosis technical field, and the method comprises the following steps: obtaining subjective evaluation based on abnormal sound perception, vibration signals and sound signals measured by sensors under different driving conditions; obtaining vibration characteristic values based on the vibration signals, obtaining sound characteristic values based on the sound signals, and converting the subjective evaluation into standardized subjective score values; calculating standardized vibration values and standardized sound values, and calculating an abnormal sound comprehensive quantification index in combination with the standardized subjective score values; dividing the abnormal sound levels based on the abnormal sound comprehensive quantification index, combining the divided abnormal sound levels and the vibration characteristic values, and outputting adjustment suggestions for the CDC shock absorber. The application realizes objective and accurate quantification of the abnormal sound degree through multi-source data fusion and characteristic frequency analysis.

The present disclosure provides a method for detecting a biomolecule. The method includes providing an electrode 101 and an aptamer 102 that specifically binds to a target biomolecule and has a charge, the aptamer 102 being disposed near the electrode 101; introducing a cationic mediator 113 having a charge opposite to the charge of the aptamer 102 to the electrode 101 at which the aptamer 102 is disposed; bringing a solution containing the target biomolecule into contact with the aptamer 102 to cause the aptamer 102 to bind to the biomolecule; and measuring an electrical signal that is produced at the electrode 101 in association with the cationic mediator 113.

The invention discloses a metal ion detection method based on a three-color fluorescent carbon dot sensing array, and belongs to the technical field of ion detection. According to the method, glutathione, formamide, manganese perchlorate hexahydrate and zinc chloride are used as raw materials, naked carbon dots (CDs), manganese-doped carbon dots (Mn-CDs) and zinc-doped carbon dots (Zn-CDs) are obtained through a one-step solvothermal method, and three kinds of carbon dot solutions are mixed with different kinds of metal ion standard solutions respectively for fluorescence detection. A fluorescent sensing array and a database of a single metal ion solution and a composite metal ion solution are constructed, and qualitative and quantitative detection of a to-be-detected solution is realized. The array sensor constructed by the method disclosed by the invention has high sensitivity and high selectivity, can distinguish and identify as many as 10 metal ions, also realizes quantitative detection on 5 metal ions, and has the capability of accurately identifying and quantifying the metal ions in an actual sample.

An object is to provide a diluent for a calibration sample and a sample that is less likely to cause a carryover of the TARC antigen. The object can be solved by a composition including (A) TARC (Thymus and activation-regulated chemokine) and (B) one or more components selected from the group consisting of acidic amino acids, basic amino acids, acidic polymers having an average molecular weight of 4,000 to 1,200,000, and salts thereof, and being in liquid form.

The invention relates to the technical field of non-woven fabric production line control, in particular to a non-woven fabric production line control method and system, and the method comprises the steps: collecting videos before and after a uniform fiber web on a working production line enters a needling machine, and obtaining a needling raw material video and a needling effect video; performing frame extraction on the acupuncture effect video according to a first time interval to obtain acupuncture effect images, and inputting the preprocessed acupuncture effect images into a pricking needle state classification model for classification; if the blunt needle production image is recognized, calculating the total number of the blunt needle images within specified time to obtain a first number; if the first number exceeds a preset threshold value, the current parameter is adjusted to be a corresponding stage optimal control parameter; and if the damaged needle production image is identified, calculating the total number of damaged needle images within a specified time to obtain a second number, and if the second number exceeds a preset threshold, replacing the needle. According to the method, the stability of the product quality is improved through precise production line control parameter regulation and control.

The present invention relates to an error compensation method and system for a GPS / INS integrated navigation system, wherein the method comprises: obtaining navigation data of GPS and INS, calculating and tracking the difference between the navigation data of GPS and INS to generate error data; constructing an error prediction model, inputting the error data into the error prediction model for training, and performing error prediction; when the GPS signal is in a lost-lock stage, obtaining real-time navigation data in the signal lost-lock stage according to the navigation data of INS in the signal lost-lock stage and the navigation data of GPS at the start time; performing error compensation on the real-time navigation data in the GPS signal lost-lock stage according to the error prediction data output by the error prediction model. The present invention significantly improves the accuracy, stability and adaptability of the navigation system by accurately tracking and quantifying errors, performing error prediction using a KAN network, and performing error compensation on real-time navigation data when the GPS signal is lost-lock.

The invention provides a single-sample HRD state evaluation method, device and system and a storage medium, and relates to the technical field of bioinformatics. The method comprises the following steps: constructing a control negative library according to a normal negative sample, and respectively calculating the coverage depth of each SNP site of a target sample to be detected and the control negative library; determining similar change region fragments and calculating to obtain a fragment average comparison rate; determining a total copy number and calculating to obtain an allele copy number; calculating to obtain an LOH characteristic value, a TAI characteristic value and an LST characteristic value; calculating to obtain a homologous recombination defect result; the BRCA1 gene variation and the BRCA2 gene variation are analyzed, and a BRCA mutation state result is obtained; and obtaining an HRD state according to a homologous recombination defect result and a BRCA mutation state result.

A nano cantilever beam array and a preparation method thereof, and a resonant array gas sensor, the nano cantilever beam array comprising a substrate and a cantilever beam array, each cantilever beam of the cantilever beam array comprising: a support layer, arranged on the substrate, one end in contact with the substrate forming a U-shaped cantilever beam support arm, the end of the support layer away from the U-shaped cantilever beam support arm being suspended on the substrate; a metal conductive layer, arranged on the support layer; and a sensitive layer, arranged on the metal conductive layer away from the U-shaped cantilever beam support arm, on which a sensitive unit is arranged. The present invention adopts a cantilever beam structure with double arm support, which can effectively improve the sensitivity of the sensor; the cantilever beam array with a double arm support structure has multiple sensitive units, which can respond to a variety of chemical gases quickly and sensitively.

The invention discloses a target classification method and device based on image analysis and electronic equipment, and relates to the field of image recognition. The method comprises the following steps: acquiring a target image containing a to-be-identified bottle; performing target detection on the target image to obtain a target bottle, and extracting a boundary contour of the target bottle; determining the angle and gradient of the target bottle based on the boundary contour; according to the angle and the gradient, correcting the target bottle to reach a preset standard angle and a preset standard gradient, and obtaining a corrected standard image; based on the target bottle, carrying out characteristic extraction on the standard image to obtain a target characteristic; and if it is determined that the similarity between the target feature and the target bottom library feature is greater than or equal to a preset similarity threshold, determining a target bottle category corresponding to the target bottom library feature, and taking the target bottle category as a bottle category corresponding to the to-be-identified bottle. By implementing the technical scheme provided by the invention, the accuracy of bottle classification is improved by performing standardization processing on the target image.

The embodiment of the invention provides an evaluation set determination method and device, a storage medium and electronic equipment, and the method comprises the steps: determining an index set for evaluating the power generation performance of a wind turbine generator, and obtaining an index value corresponding to each index in the index set; the degradation degree corresponding to each index is determined according to the index value corresponding to each index, an evaluation set used for evaluating the power generation performance of the wind turbine generator set is determined, and the evaluation set comprises a plurality of evaluation elements; a membership degree set corresponding to each index is determined according to the deterioration degree and a membership degree function, and the membership degree set is used for indicating the membership degree of each index to each evaluation element; an evaluation set of the power generation performance of the wind turbine generator is determined according to the membership degree set, and each element in the evaluation set is used for indicating the membership degree of the power generation performance of the wind turbine generator belonging to each evaluation element.