24results about How to "Reduce analysis error" patented technology

The embodiment of the invention discloses a bridge bolt monitoring image recognition method and system based on deep learning, and belongs to the technical field of bridge image processing. The method comprises the following steps: acquiring a multi-angle monitoring image set of a bridge bolt part through an image acquisition device, and preprocessing the monitoring image set to generate a standardized target image sequence; positioning a bolt monitoring area for each image frame in the target image sequence based on a pre-trained positioning model, and generating an area coordinate set containing bolt position information; inputting the region coordinate set into a state recognition model, extracting structural state features of each bolt monitoring region, and generating a looseness degree prediction result of the bolt part according to the structural state features; according to a matching result of the looseness degree prediction result and a preset safety threshold range, a bolt state abnormity alarm signal is output; and associating the bolt state abnormity alarm signal to the corresponding monitoring image frame, and generating a monitoring report containing a visual mark.

The invention discloses a Beidou-based slope monitoring and early warning system evaluation method, particularly relates to the technical field of system monitoring, and is used for solving the problem that a fault of an existing slope monitoring and early warning system is not found in time. Analyzing a time synchronization function of the Beidou system to realize data synchronization between the target sensors and analyzing automatic calibration conditions of the target sensors; on the basis that the data synchronism is normal and the sensor is reliable to use, the consistency of data fusion is further analyzed through an entropy theory, vibration influence evaluation and adaptability evaluation caused by a vehicle are analyzed, key monitoring is conducted for a high-risk time period, and through comprehensive analysis, the accuracy of data fusion is improved. The system can generate detailed early warning information for a specific monitoring scene, the safety of slope monitoring and the accuracy of early warning are enhanced, the data processing efficiency is improved through the staged processing flow, and disasters and accidents caused by inaccurate data or improper analysis are effectively prevented.

The invention relates to the field of fault early warning, in particular to a fault early warning method for a tailing paste filling system. Comprising the steps of monitoring and storing parameters in real time to form a parameter matrix; a sliding time window technology is introduced, standardization processing is carried out on the parameters at each moment, and standardized parameter values are obtained; on the basis of the standardized parameter values, a dynamic feature extraction algorithm is adopted for processing to obtain feature values; based on the characteristic value, a fault probability value is calculated through a dynamic gain adjustment fault probability calculation algorithm, the fault probability value is compared with a fault threshold value, and a fault judgment result is obtained; according to the characteristic value and the fault judgment result, a saliency score is calculated through a fault positioning algorithm, and a fault source is determined according to the saliency score; and performing fault early warning based on the fault source. The technical problems that in a tailing paste filling system, multiple monitoring points exist, so that real-time data processing becomes complex, and unified comparison and analysis are difficult to conduct are solved.

The invention relates to the technical field of environmental analysis, and discloses a new pollutant identification method and device, computer equipment and a storage medium, and the method comprises the steps: determining a target execution strategy through determining the application sequence of each non-target analysis method and each computational toxicology method in a high-throughput fusion method; the method can be realized by reasonably selecting and switching execution strategies whether searching corresponding chemical substances from the toxic effect or evaluating the toxic effect of the chemical substances from the found chemical substances. Furthermore, a target execution strategy is utilized to perform new pollutant risk assessment and calculate a plurality of risk values, various characteristics of the new pollutants and performance in an actual environment are comprehensively considered, and the potential risk of the new pollutants can be quantitatively reflected from different angles. And finally, multiple target new pollutants are further determined in combination with multiple risk values, and objects which have great threats to the environment and human health and need to be managed and controlled preferentially are screened out from numerous possible new pollutants.

The invention provides a mud-phase shale component quantitative analysis and calculation method, which relates to the technical field of geological mineral exploration and mainly comprises the steps of sample collection and pretreatment, X-ray diffraction pattern acquisition, pattern analysis and mineral component determination, quantitative calculation based on an innovative model, result correction and evaluation and the like. Through an innovative quantitative analysis model and a strict sample processing flow, the content of various mineral components in the mud-phase shale can be more accurately determined, analysis errors are reduced, more reliable data support is provided for geological research and resource exploration, and compared with a traditional method, the method has the advantages that operation steps are simplified, analysis efficiency is improved, and the method is suitable for popularization and application. According to the method, the quantitative analysis of the mud-phase shale components can be completed in a shorter time, the progress of research and exploration is accelerated, the dependence on complex and expensive chemical analysis equipment is reduced, the experiment cost and the human input are reduced, and meanwhile the utilization efficiency of resources is improved.

The invention discloses an intelligent slub yarn parameter acquisition device, and relates to the technical field of slub yarn detection. The device comprises a device body, supporting legs are arranged at the corners of the bottom of the device body, an intelligent collector is arranged on the front face of the device body, an L-shaped frame is arranged on the back of the device body, a take-up roller is arranged in the L-shaped frame, a main shaft roller is arranged on the left side of the bottom of the inner wall of the device body, and two auxiliary wire rollers are symmetrically arranged at the bottom of the inner wall of the device body; a driving assembly is arranged at the bottom in the device body. According to the invention, the distance between the acquisition assembly and the slub yarn can be continuously changed, the appearance and detail drawings of the slub yarn at different distances are acquired by the acquisition assembly, and the acquired data are intelligently analyzed by the intelligent acquisition device, so that the acquired sample contains detailed data such as details and overall appearance, and the detection accuracy is improved. The reduction of the detection and analysis accuracy of the whole parameters of the slub yarn is avoided.

The invention belongs to the technical field of metal material preparation, and particularly relates to a method for preparing an irradiated metal micro-nano mechanical sample. Comprising the following steps: providing a metal block material, and performing ion irradiation on the metal block material to obtain an initial sample; fixing the initial sample, determining the grain orientation of the initial sample, marking oriented grains, and preparing the sample to obtain an original rectangular sheet sample; removing a part of irradiation layer on the surface of the original rectangular sheet sample, and trimming to obtain a crenel-shaped rough blank with a continuous concave-convex structure in an irradiation area and a non-irradiation area under the same grain orientation; and thinning to obtain the micro-nano mechanical sample. In the same crystal grain of the irradiated metal block sample, irradiated and non-irradiated single crystal in-situ mechanical samples with the same orientation are obtained, the situation that an irradiated area and a non-irradiated area with the same orientation are found in a plurality of samples is avoided, analysis errors caused by data acquisition in different areas are reduced, and the analysis accuracy is improved. Therefore, high-efficiency preparation of the single crystal in-situ mechanical sample under the transmission electron microscope is realized.

The utility model relates to a chloroacetic acid production device for processing glycine, which is characterized in that an interlayer is arranged in the outer wall of a chlorination kettle, the side end is connected with a liquid level meter a, and a discharge pipe is arranged on the lower surface; a radar liquid level instrument, a chlorine feeding pipe, an on-line component analyzer, an on-line thermometer, an on-line hydrometer, a condensation pipe, a catalyst filling pipe and an acetic acid feeding pipe are sequentially arranged on the upper surface, the lower end of the chlorine feeding pipe is connected with a gas distributor, and the condensation pipe is externally connected with a condenser; the catalyst filling pipe is externally connected with a catalyst metering tank; a liquid level meter b is connected to the side end of the kettle body, a discharging pipe is arranged on the lower surface of the kettle body, a water supplementing pipeline is connected to the right side of the upper surface of the kettle body, a liquid inlet pipe and an online moisture measuring device are arranged on the left side of the upper surface of the kettle body, and the liquid inlet pipe is communicated with the discharging pipe; the upper end of the stirrer is connected with a stirring motor, and the lower end is connected with a frame-type stirring paddle; the utility model has the advantages of reasonable structural design and good use effect.

This invention discloses an AI-powered big data-based enterprise management data visualization and analysis system. The system includes a multi-source management data acquisition module, used to collect revenue, cost, profit, cash flow, inventory, procurement, orders, customers, projects, human resources, and supplier performance data from enterprise financial systems, ERP systems, CRM systems, inventory systems, procurement systems, contract systems, project management systems, and human resource systems. This invention relates to the field of enterprise management data processing technology. This AI-powered big data-based enterprise management data visualization and analysis system, when abnormal result indicators occur, can trace intermediate transmission indicators and cause indicators backward along the operational causal chain, and delete pseudo-correlation paths based on business rule verification values ​​and time sequence verification values, solving the problem that existing visualization systems can only display abnormal results but cannot explain the root causes of anomalies.

The present invention discloses a water well tuning method based on digital modeling results, relates to the technical field of digital modeling results, and is used to solve the problem of water well productivity decline caused by the wrong guidance analysis of the extraction degree on the water well productivity. The method comprises the following steps: using the MAD algorithm to screen data and then calculating the corresponding threshold to analyze the degree of water well productivity decline; using the support vector machine to construct an extraction impact assessment model through extraction data; analyzing the degree of influence of extraction on water well productivity according to the results of the extraction impact assessment model; using fuzzy reasoning to evaluate the adjustment level based on the degree of water well productivity decline and the degree of influence of extraction on water well productivity; implementing different adjustment operations for different adjustment levels; collecting extraction adjustment feedback data for the water wells adjusted by extraction; using the logistic regression algorithm to analyze the degree of water well productivity recovery according to the extraction adjustment feedback data; and performing fracturing operations on the water wells with low recovery degrees. Thus, the analysis error caused by the extraction degree is reduced, and the water well productivity guarantee is enhanced.

The utility model relates to a low-temperature ammoniation kettle for producing glycine, which is characterized in that the side end of a kettle body is connected with a liquid level meter, an interlayer is arranged in the outer wall, a discharging pipe is arranged at the bottom, and a radar liquid level meter, a liquid ammonia feeding pipe, an on-line component analyzer, an on-line thermometer, an on-line PH meter, an emptying pipe and a chlorination liquid feeding pipe are sequentially arranged at the top; two sides of the interlayer are respectively connected with a cooling water inlet pipe and a cooling water outlet pipe, the lower end of the liquid ammonia feeding pipe is positioned at the bottom of the kettle body and is connected with a uniform distribution disc, and the emptying pipe is externally connected with a tail gas treatment system; the upper end of the stirring shaft is externally connected with a stirring motor, and the lower end of the stirring shaft is connected with a stirring paddle; the cooling coil pipe is spirally arranged inside the kettle body, the liquid inlet end of the cooling coil pipe is connected with a frozen saline water inlet pipe, the liquid outlet end of the cooling coil pipe is connected with a frozen saline water outlet pipe, and the frozen saline water inlet pipe, the cooling water inlet pipe, the liquid ammonia feeding pipe, the discharging pipe and the chlorination liquid feeding pipe are all provided with control valves and flow meters; the device has the advantages of being good in cooling effect and safe and accurate in detection.

The application discloses a waste miscellaneous aluminum classification and rapid identification method and relates to the field of waste miscellaneous aluminum classification and rapid identification. S1, grading pretreatment: through a conveying belt, the waste miscellaneous aluminum to be sorted is conveyed into a three-layer vibrating screen machine to be graded and screened, and waste miscellaneous aluminum of different sizes is sorted out; S2, separation of impurities: the graded waste miscellaneous aluminum is conveyed into a drum-type magnetic separator respectively to remove magnetic impurities, then the waste miscellaneous aluminum after magnetic separation is conveyed into an air flow sorting machine to separate light non-metallic impurities, and then a conveying belt conveys the waste miscellaneous aluminum onto a loading platform, full-process automatic processing reduces manual dependence, and the work load of a single production line of sorting workers can be reduced; the classification cost is reduced, compared with manual sorting, the waste product rate of recycled aluminum alloy can be effectively reduced due to accurate classification, and economic benefits are significantly improved.

The application discloses a kind of IES multi-objective dynamic optimization scheduling method considering multi-energy flow constraint, including the following steps: IES steady-state MEF modeling;Based on the calculation of MEF using Newton-Raphson method, the steady-state energy flow distribution of IES is obtained;IES multi-objective optimization scheduling model considering MEF constraint is constructed;The model constructed in step c is solved using NSGA-II based on normal distribution crossover operator, and the Pareto optimal solution set of IES multi-objective dynamic optimization scheduling is obtained.To ensure the operation safety and reduce the analysis error, the IES multi-objective dynamic optimization scheduling model considering MEF constraint is established, with the minimum operation cost and pollutant emission external cost as the target, and the process of solving the model using NSGA-II based on normal distribution crossover operator is given.The effect of the method is good through test.

The utility model provides a chromatographic column with high separation efficiency, which comprises a chromatographic tube, and a separation flange is arranged at the lower part of a screening groove. According to the chromatographic column with the high separation efficiency, the sample injection needle can be accurately and stably inserted into the chromatographic column through guiding of the sample injection needle, deviation or shaking in the sample injection process is avoided, and therefore accurate introduction of a sample is ensured, the experiment accuracy can be kept, experiment errors caused by misoperation can be reduced, and the separation efficiency of the chromatographic column is improved. Through the insertion of the sample injection needle, an introduced sample enters the liquid inlet pipeline through the material pushing piston, the amount of the sample entering the chromatographic column can be accurately controlled through the material pushing piston, and the sample can be ensured not to leak in the sample injection process through the tight connection between the material pushing piston and the liquid inlet pipeline; the sealing performance is favorable for keeping the purity of a sample and preventing external impurities or air from entering to influence the accuracy of chromatographic analysis, thereby being favorable for improving the separation effect of the chromatographic column.

The invention discloses an aluminum sulfate quality analysis method based on multi-index determination. The method comprises the following steps: S1, appearance and character; s2, measuring the content of aluminum sulfate; s3, determining the iron content; s4, determining the content of water insoluble substances; s5, determining the pH value; s6, heavy metal content determination; and S7, judging: integrating the measurement results of the indexes in the steps S1-S6, and judging whether the aluminum sulfate sample meets the related quality standard or not. The aluminum sulfate quality analysis method based on multi-index determination is simple, convenient, rapid and accurate to operate, can comprehensively evaluate the quality of aluminum sulfate, and can effectively control the product quality of aluminum sulfate by determining the indexes such as the aluminum sulfate content, the iron content, the water insoluble content, the pH value and the heavy metal content; the guarantee is provided for the application of the method in the field of water treatment.

The invention provides an EL and I-V integrated acquisition system and method and a defect detection system and method, which can be applied to the technical field of photovoltaic power generation. The acquisition system comprises an EL imaging device, an I-V acquisition device, a bidirectional program control direct current power supply module and a synchronous control module. The bidirectional program-controlled direct-current power supply module is configured to serve as a power supply to provide original current for the synchronous control module in an EL mode and serve as an electronic load to obtain current output by the object to be detected in an I-V mode; the synchronous control module is configured to output a controlled modulation excitation signal to a to-be-detected object in an EL mode and control the EL imaging device to work so as to obtain an EL image; and the control device is configured to control the I-V acquisition device to work in the I-V mode so as to acquire the I-V data of the to-be-tested object. According to the invention, the EL-I-V integrated efficient detection of the photovoltaic module can be realized in the daytime environment, and the accuracy and timeliness of defect detection are greatly improved.

The present application relates to the technical field of wind power equipment health monitoring and fault prediction, and discloses a wind power blade recession trend monitoring and prediction method based on digital twinning and optical fiber strain driving, which comprises the following steps: determining a damage monitoring key area based on global point cloud data, and constructing a mechanical twinning model of the wind power blade in combination with sensor measured data; correcting the boundary conditions of the mechanical twinning model through strain data, and establishing a dynamic correlation mechanism between the strain data and the wind power blade; constructing a spatial continuous deformation mode based on the strain data to implement initial parameterization setting of the mechanical twinning model, and establishing a model inversion iteration mechanism to locate and evaluate the damage degree of the wind power blade; constructing a recession trend comprehensive index to determine a trend prediction quantitative basis of the wind power blade; and constructing a prediction model based on the trend prediction quantitative basis and strain time series data to calculate the recession trend of the wind power blade at a future time. The present application can accurately locate the damage position and evaluate the damage degree.

The invention provides a dynamic simulation analysis method and a debugging mode for a high-speed ball bearing retainer. Belongs to the technical field of ball bearing dynamics simulation analysis. The method comprises the following steps: establishing a bearing three-dimensional model; carrying out linear perturbation modal analysis on the retainer under stress stiffening and rotation effects in finite element analysis software, and generating a modal neutral file; calculating the equivalent contact stiffness under the coupling action of multiple factors such as a bearing clearance, a contact angle and an oil film, solving load-deformation distribution of each rolling body by combining geometric equations between the rolling bodies and inner and outer rings and a force balance equation, and calculating equivalent contact parameters under the lubrication working condition; constructing a rigid-flexible coupling dynamic analysis model of the retainer; by constructing the rigid-flexible coupling analysis model of the high-speed ball bearing retainer and integrating the equivalent contact parameters under the multi-factor coupling effect, the analysis error caused by model simplification is reduced, the problems of high cost and long period of a traditional test method are avoided, and the analysis efficiency and precision are improved.

The invention relates to the technical field of concrete performance testing, and discloses a concrete performance improvement method based on temperature rise character monitoring and analysis, which comprises the following steps: receiving a concrete performance testing instruction, starting a performance detection device, taking an equilateral cylindrical concrete sample in a solidified state, performing pre-test cleaning treatment on the concrete sample, and then performing temperature rise character monitoring and analysis on the concrete sample. After processing, uniformly spraying speckle paint on a middle scale distance section of the concrete sample, fixing the middle scale distance section, adjusting high-speed camera equipment, shooting the speckle section of the sample to obtain an original speckle image set, then carrying out step-by-step loading and stretching on the concrete sample until the concrete sample is fractured, and meanwhile, collecting a deformed speckle image set before and after the fracture; and recording temperature change data in the process before and after fracture, combining with the analysis to obtain a performance test result of the concrete sample, formulating targeted performance improvement measures, and completing concrete performance improvement based on temperature rise character monitoring and analysis. According to the invention, the accuracy of concrete performance testing can be improved.

The invention discloses a project cost analysis method and system, a storage medium and electronic equipment, and the method comprises the steps: determining a power distribution network cost informatization list protocol according to the standard design and typical construction content of a distribution network; according to the power distribution network cost informatization list specification and the power distribution network project investment estimation index, determining initial construction engineering cost and installation engineering cost; according to the material price information, the difference adjustment price information and the determined initial construction engineering cost and the installation engineering cost, determining the engineering cost; and performing normative detection on the power distribution network engineering project according to the detection standard of the power grid engineering project. According to the invention, intelligent management of the construction cost of the power distribution network project is realized, the efficiency and accuracy of analysis of the construction cost of the power distribution network project are improved, errors of manual calculation and analysis are reduced, and a reliable basis is provided for project management and investment decision.

The invention provides a method for determining the content of acetate in a compound sodium acetate-glucose injection, and belongs to the technical field of medicine component analysis, the content of acetate is determined by adopting a high performance liquid chromatography (HPLC) technology, high-sensitivity and high-resolution separation and detection can be realized, and the detection accuracy is high. According to the method, chromatographic conditions (such as chromatographic column temperature, mobile phase composition, flow velocity, detection wavelength and the like) are accurately set, operation steps are standardized, a reference substance solution is reasonably selected, a hydrogen-type sulfonated cross-linked styrene-divinyl benzene copolymer is adopted as a chromatographic column filling agent, and ultrasonic degassing treatment is introduced; the accuracy and the reliability of determination are improved, so that the method is more accurate, higher in efficiency and better in stability when being used for detecting the content of acetate.

The utility model discloses a continuous desolventizing device for glyphosate production, which comprises a first-stage desolventizing device, a second-stage desolventizing device and a third-stage desolventizing device which are sequentially connected in series and respectively perform step-by-step desolventizing at different temperatures, the first-stage desolventizing device, the second-stage desolventizing device and the third-stage desolventizing device adopt desolventizing kettles with the same structure to carry out desolventizing work; the first-stage desolventizing device, the second-stage desolventizing device and the third-stage desolventizing device are respectively connected with a first-stage condenser, a second-stage condenser and a third-stage condenser; the first-stage condenser, the second-stage condenser and the third-stage condenser are connected with a tail gas absorbing device and a collecting tank; a methylal online analyzer is arranged on the primary desolventizing device, and a methanol online analyzer is arranged on the secondary desolventizing device; generally, the glyphosate desolventizing device has the advantages of high desolventizing efficiency, high automatic detection and analysis degree, reduction of side reactions and improvement of glyphosate product quality.

The application relates to the technical field of intelligent control, and discloses an unmanned water sample automatic analysis system and method based on artificial intelligence and a computer storage medium, which comprises a water sample access device, a water sample storage device, a water sample separation device and a water sample analysis device. Through the cooperative linkage of the water sample access device, the water sample storage device, the water sample separation device and the water sample analysis device, the system realizes the whole-process unmanned operation from water sample access, identification, control, storage, separation pretreatment to water quality analysis and result synthesis. It can be seen that the system described in the application can realize the full-automatic control and analysis monitoring of a plurality of water samples, and is favorable for improving the water quality analysis monitoring efficiency and the water quality analysis monitoring reliability.

The invention discloses a carrier rocket sub-level wreckage landing area automatic off-line analysis method and a carrier rocket sub-level wreckage landing area automatic off-line analysis system. The carrier rocket sub-level wreckage landing area automatic off-line analysis method comprises the following steps of performing data reading; determining an administrative region of the sub-level wreckage drop point according to the read data; after the administrative region of the sub-level wreckage drop point is determined, the administrative region of the sub-level wreckage drop point is determined; and according to the determined administrative region of the sub-level wreckage falling region, determining an administrative unit covered by the sub-level wreckage falling region. According to the method, automatic output of the administrative region where the sub-level wreckage drop point is located, the administrative region where the drop region is located and the administrative unit covered by the drop region is achieved, manual analysis of trajectory designers is not needed, and the manual operation intensity is greatly reduced.