26results about How to "Optimize data processing" patented technology

The invention discloses a water quality prediction method based on multi-source data, and constructs a water quality prediction model based on a long short-term memory network (LSTM) and a graph neural network (GNN) of multi-source data (surface water monitoring data, meteorological data, hydrological data and pollution source on-line monitoring data), so that short-term real-time on-line prediction of surface water quality factors can be realized. According to the method, on the basis of multi-source data such as section water quality monitoring data, historical meteorological data, forecast meteorological data, hydrological monitoring data, pollution source online monitoring data and upstream and downstream relations, multiple main water quality influence factors such as water quality, meteorology, hydrology, pollution sources and upstream and downstream section water quality are comprehensively considered; the LSTM or the graph neural network is adopted to establish a water quality prediction model, and the comprehensive influence of various influence factors and the time-space relationship on the water quality is simulated, so that the simulation result is more accurate and reliable.

The invention provides a method for measuring plasma generated by electro-chemical coupling explosion, which adopts a device for measuring plasma generated by electro-chemical coupling explosion, the device comprises an explosion cavity and an oscilloscope, and a Langmuir three-probe is arranged in the explosion cavity; and the Langmuir three-probe is connected with an oscilloscope. The Langmuir three-probe comprises a probe P1, a probe P2 and a probe P3. The device provided by the invention has the characteristics of being suitable for transient plasma diagnosis based on Langmuir three probes, simple in structure and convenient in data processing, voltage signals measured by a probe circuit are acquired and are converted into plasma electron temperature and density after being analyzed and calculated, and the electron density ne of the plasma is calculated according to the electron density ne of the plasma. Therefore, the plasma generated by the electro-chemical coupling explosion can be measured.

This invention belongs to the field of impurity detection technology for ethanol solutions, and particularly relates to a method for detecting trace impurities in ethanol solutions based on near-infrared spectroscopy, comprising the following steps: (1) examining the standard deviation (RSD) value and calculating the required sample size N; (2) acquiring samples; (3) outlier removal and spectral preprocessing; (4) dividing the dataset; (5) using the difference spectrum method to screen feature signals; (6) establishing a "background silence" discrimination criterion; and (7) using an external prediction set for discrimination. The detection method model described in this invention has a wide range of applications. It establishes a model based on the background system, effectively identifying normal samples. For impurity samples or abnormal situations that are inconsistent with the near-infrared absorption characteristics of the background system, as long as they cause changes in the background system, they can be effectively detected. Compared with traditional PLS, PLSDA and other modeling methods, background silence discrimination only requires calculation using relevant statistical methods, resulting in a smaller overall computational load and more convenient data processing.

The present invention provides a monitoring method for steel bar management at a construction site, which relates to the technical field of steel bar management, and aims to achieve more accurate, timely and efficient steel bar management, including using colored wireframes to divide the steel bar storage area in a steel bar warehouse, and setting a type mark for each steel bar storage area to calibrate the steel bar type of the corresponding steel bar storage area; arranging multiple image acquisition devices to acquire images of each steel bar storage area; identifying the placement position, quantity and type of steel bars in each steel bar stacking area through the top view and side view of the acquired image; judging whether there are abnormal conditions, and the abnormal conditions include the placement position of the steel bar exceeding the preset range, the wrong area for the steel bar placement and the number of steel bars of a certain type being lower than the corresponding quantity threshold. The present invention has the advantages of intelligent, efficient, high-quality and safer management of steel bars.

The invention discloses a side slope tiny deformation monitoring system and method based on wireless optical communication, and belongs to the technical field of side slope deformation detection.The side slope tiny deformation monitoring system comprises a power module, a shielding module, an optical signal coding module, a laser transmitting module, a laser receiving module, an optical signal decoding module and a wireless communication module; the micro deformation degree of the side slope is judged according to the optical signal receiving deviation degree of the laser transmitting module and the laser receiving module, micro deformation monitoring of the side slope is achieved, the monitoring result of the micro deformation of the side slope is uploaded to an external upper computer through the wireless communication module for data storage, and the shielding module is used for shielding the micro deformation of the side slope. The laser transmitting module and the laser receiving module are covered, and interference of the external environment on optical communication is reduced. According to the invention, based on wireless optical communication, the micro deformation monitoring result of the slope can be timely and directly sent to the upper computer for statistical storage, the data volume transmission pressure is small, the data processing is convenient, different deformation grades can be divided, and a manual inspection strategy is convenient to formulate.

The invention relates to the technical field of hearth coking monitoring, and discloses a monitoring method for judging a hearth coking state, which comprises the following steps of: acquiring basic data of six heating surfaces in a boiler operation combustion state; calculating operation heat transfer coefficients of the six heating surfaces; initial data of the boiler in a healthy state are collected, and an optimal heat transfer coefficient prediction model is trained; boiler operation parameters in the boiler operation combustion state are obtained, and the trained optimal heat transfer coefficient prediction model is adopted to obtain the optimal heat transfer coefficient in the boiler operation combustion state; and comparing the operation heat transfer coefficient with the optimal heat transfer coefficient to determine whether the hearth of the boiler is coked or not. According to the method, the whole boiler is divided into six heating surfaces, whether adjustment or optimization such as coking or soot blowing needs to be carried out or not is judged through the optimal heat transfer coefficient prediction model according to the six coking surface heat transfer coefficients, boiler shutdown is not needed, the coking condition of the boiler is found in time, power generation losses are reduced, and the operation health state and the operation efficiency of a combustion hearth are improved.

The invention discloses a blade rotating speed debugging method and system for an automobile engine cylinder cover test, computer equipment and a storage medium. The method comprises the following steps that the blade rotating speed is collected; filtering and averaging the blade rotating speed data to obtain a rotating speed average value; carrying out interval recalibration on the processed rotating speed mean value data; and outputting and displaying the calibrated blade rotating speed. According to the invention, the rotation speed fluctuation in unit time can be reduced, invalid values in the blade rotation speed are filtered out, the rotation speed is calibrated in different intervals, the influence of the blade rotation speed fluctuation on the test result is eliminated to the greatest extent, and the output rotation speed precision is improved, so that the accuracy of the test result is improved.

The invention relates to a petrochemical engineering emergency early warning method and device based on large model data distillation. The method comprises the steps of obtaining original data, preprocessing and standardizing the original data, and constructing a data set. The method comprises the following steps: mapping a data set from a high-dimensional space to a low-dimensional space through linear transformation, and performing eigenvalue decomposition on a covariance matrix of data in the data set to obtain eigenvalues and eigenvectors; and sorting the feature vectors according to the feature values from large to small, selecting the feature vectors of which the feature value ranking is not lower than a first threshold value to form a new feature space, and extracting important features from the feature space through LASSO regression. And calling a CNN deep learning model to extract key features from the important features, distilling representative features in the original data, and outputting a feature set after distillation. And performing anomaly detection on the petrochemical engineering system through a clustering algorithm according to the feature set after distillation, and triggering early warning when a detection result does not meet a preset condition.

The invention discloses a data real-time compression and transmission system and method based on a thinning algorithm, and relates to the technical field of data processing. The system comprises a data acquisition module, a data preprocessing module, a thinning algorithm module, a data compression module, a real-time display module and a data transmission module. The system uses 3D laser scanning to obtain three-dimensional point cloud data, and the data are preprocessed, denoised and partitioned. The thinning algorithm module recognizes and retains feature points, carries out thinning on non-feature points, and keeps data integrity and details. The compression module reduces the data volume, and the real-time display module dynamically loads the data blocks by using a graphics library, so that the display efficiency is improved. And finally, the data transmission module transmits the processed data to a client or a server through a network, and supports efficient data transmission and reception. The whole system integrates all links of data processing, and efficient and real-time data compression and transmission are achieved.

The embodiment of the present invention discloses a data transmission system, method and medium based on the Internet of Things and big data. The system includes: a collection unit, which is used for diverse data collection; a preprocessing unit, which is used to package the data collected by the collection unit according to a preset period to form a data packet, and process the data in each data packet to obtain a corresponding data change rate and data correlation index; a marking unit, which is used to compare the obtained data change rate and data correlation index with a preset threshold value, and mark the data packet corresponding to the data exceeding the threshold value; a transmission unit, which is used to give priority to the transmission of the marked data packet; the beneficial effect is: by acquiring the data change rate and data correlation index in each collected data packet, marking the data packet exceeding the threshold value, so that data with larger differences are transmitted first, which is beneficial to subsequent data processing and improves the performance of data fusion.

The present disclosure provides a method and device for determining power characteristics of a wind turbine. The method comprises: obtaining first operating data of the wind turbine before applying a predetermined control strategy and second operating data of the wind turbine after applying the predetermined control strategy, the first operating data comprising first environmental data and first output power data, and the second operating data comprising second environmental data and second output power data; determining an environmental space intersection of the first operating data and the second operating data by performing environmental space matching on the first operating data and the second operating data according to the first environmental data and the second environmental data; predicting a first predicted power of the wind turbine before applying the predetermined control strategy and a second predicted power of the wind turbine after applying the predetermined control strategy based on the environmental space intersection; and determining a power characteristic difference of the wind turbine before and after applying the predetermined control strategy according to the first predicted power and the second predicted power.

The application discloses a rubber track finished product longitudinal tension testing device, which comprises a testing machine body, a track fixing device and a fixing device lifting guide rail, wherein the track fixing device is connected with the testing machine body through the fixing device lifting guide rail, and the track fixing device comprises a fixing base, a fixing wheel, a carrier wheel, a hydraulic oil cylinder, a supporting wheel and a pressure sensor. The testing device makes the testing steps simpler, reduces the testing cost and shortens the testing period.

The invention discloses a digital wind tunnel balance with temperature and inertia compensation elements, and belongs to the technical field of wind tunnel balance design. The digital wind tunnel balance comprises a body, a force measuring module, a temperature measuring module and a three-axis acceleration and angular velocity measuring module, so that the surface temperature, the three-axis acceleration and the angular velocity of the balance can be measured on the basis of measuring aerodynamic force and moment; accurate information is provided for temperature compensation for static calibration and inertia compensation for dynamic calibration of the balance, so that the balance load measurement error is reduced.

The invention discloses an enterprise data element governance method and device based on big data, and the method comprises the steps: determining a target enterprise needing data element governance, and collecting the public data information of the target enterprise; dividing the public data information into a plurality of data classifications according to data correlation; determining a weight coefficient corresponding to each data classification according to the enterprise type of the target enterprise; determining a mapping relationship between the data classification and the data element tag according to the historical data classification and the historical data element tag, and determining a target data tag of the target enterprise according to the mapping relationship; and according to the target data label and the weight coefficient, generating a target enterprise portrait to complete data element treatment of the target enterprise. According to the method, the data can be classified, weight analysis is carried out by utilizing the multi-dimensional data, specific labels can be conveniently marked on each type of data, the enterprise portraits are generated according to the labels and the corresponding weight coefficients, and convenience is provided for subsequent data processing.

The invention discloses a heterogeneous information conversion method and device. The method comprises the following steps: if an upper computer and a plurality of devices exist in a ground control vehicle of the unmanned aerial vehicle, each device interface is different in type, and when the upper computer is different from each device interface in type, each device interface and an upper computer interface are initialized; when the data of each device is uploaded to the upper computer and the data of the upper computer is issued to each device, whether data update exists in a receiving cache region of each device and an interface of the upper computer or not is detected at the same time; processing the data of the receiving cache region of each equipment interface, putting the data into a network sending cache region, and sending the data to an upper computer; and processing the data of the receiving cache region of the upper computer interface, putting the data into the data cache region of each equipment interface, and sending the data to each equipment. According to the invention, the technical problems of multiple interface types, complex interface protocol and inconvenient communication among various devices in the ground control vehicle of the unmanned aerial vehicle are solved.

The utility model provides an AMT gearbox and gear shifting execution mechanism control system of a new energy mine truck, which comprises a TCU master control module, a sensor unit, an execution unit, an MCU and a power supply module, the sensor unit is used for collecting signals, and the collected signals comprise motor rotating speed, vehicle speed, gear data and gear displacement signals; the signals are transmitted to the TCU main control module through the sensor signal processing module; the execution unit comprises a gear electromagnetic valve and a speed sensing electromagnetic valve. Signals such as motor rotating speed, vehicle speed, gear data, gear displacement and the like can be collected through the sensor unit, analysis of the TCU master control module is facilitated, a gear electromagnetic valve and a speed induction electromagnetic valve of the execution unit are used for adjusting a gear shifting execution motor, and accelerator, motor rotating speed and brake signals can be transmitted to the TCU master control module through the MCU. Data processing is facilitated, the motor efficiency is improved, and the economical efficiency of the whole vehicle is improved.

The invention provides an underwater surveying and mapping system and method based on a rotary scanning type three-dimensional imaging sonar. The surveying and mapping system comprises a water surface moving platform (unmanned ship), an underwater scanning unit (three-dimensional imaging sonar), a pose and coordinate measuring unit (RTK / IMU), a data processing and converting unit and a remote display and control unit. The surveying and mapping method specifically comprises the following steps: controlling the unmanned ship to move to the center of each sub-region; a sonar is started to plot the sub-regions to obtain underwater three-dimensional point clouds of the underwater terrain and the underwater creatures; based on the position information and the attitude information of the underwater surveying and mapping system, the coordinates of the underwater three-dimensional point cloud are converted into an east-north-sky rectangular coordinate system, and the final coordinates of the underwater three-dimensional point cloud are obtained; and on the basis of the underwater three-dimensional point clouds of the sub-regions, a complete underwater three-dimensional point cloud of the region to be measured is generated through fusion. The method is suitable for underwater topographic surveying and mapping and dynamic target monitoring of rivers, lakes and offshore waters, the measurement efficiency is high, data processing is convenient, and the method does not depend on platform tracks and measuring lines.

The invention discloses a double-shaft multi-angle wind tunnel test supporting device, and relates to the technical field of wind tunnel tests. The device comprises a stand column, the bottom of the stand column is connected with a test section pivotal bearing, the top of the stand column is connected with a bearing seat, the bearing seat is rotatably connected with a transmission supporting rod, one end of the transmission supporting rod is connected with a driving mechanism, and the other end of the transmission supporting rod is connected with a fixed base. The mounting seat interface is mounted at the end part of the transmission support rod, the spherical hinge is arranged on the mounting seat interface, and the central round hole of the model mounting seat is matched and connected with the spherical part of the spherical hinge. The supporting device provided by the invention adopts a structural form of the main support and the axial extension rod, and the possibility of resonance with a wind tunnel foundation is avoided due to fixed bottom, stable structure and relatively high frequency; and the structural design is small and light, and each part is provided with a hoisting hole, so that transfer transportation and test installation are facilitated, and compared with a traditional supporting structure, the adaptability is wider.

The present invention provides a fire monitoring system based on GNSS-R, including a GNSS satellite that transmits a direct signal and a temperature sensing device, a GNSS-R receiver, a data storage system, a data discrimination system and an alarm system that are connected in sequence; the temperature sensing device receives a first reflected signal and obtains the peak value and signal-to-noise ratio data of a delayed Doppler waveform; the GNSS-R receiver receives the data, the direct signal and the second reflected signal; the data storage system extracts position information and time information from the direct signal; the data discrimination system receives the above data and information, and makes a judgment based on the peak value and signal-to-noise ratio data of the delayed Doppler waveform; the alarm system sounds an alarm in the area judged to be a fire occurrence area based on the judgment result. The present invention also provides a monitoring method. The present invention utilizes the direct signal and reflected signal of GNSS and adopts a temperature sensing device that is extremely sensitive to forest temperature, so that forest fires can be judged in real time.

The invention provides a grabbing control method, system and device for a dexterous hand, and the method comprises the steps: controlling the dexterous hand to move to a target object, and obtaining the pressure information between the dexterous hand and the target object; acquiring forward pressure data based on the pressure information; the forward pressure data is compared with preset grabbing force data, and the stress change state of the dexterous hand when the target object is grabbed is determined; the stress change state of the dexterous hand comprises a deformation state, an offset state and a sliding state; and a control instruction is generated based on the stress change state of the dexterous hand, and the grabbing force of the dexterous hand on the target object is adjusted according to the control instruction. The pressure sensing precision and the response speed can be improved, and the dexterous hand can more accurately sense the contact force and make corresponding adjustment.

The invention relates to the technical field of novel photoelectric detection, in particular to a balanced photoelectric detector based on a differential technology. Comprising a photoelectric conversion circuit, a first-stage operational amplifier circuit, a second-stage operational amplifier circuit and a power supply circuit, the photoelectric conversion circuit comprises two photodiodes which are connected in series, and a grounding resistor is arranged between the two photodiodes, so that a bias circuit is formed to provide bias voltage for the photodiodes; the output end of the primary operational amplifier circuit is connected with the input end of the secondary operational amplifier circuit to form a differential amplifier circuit; the power supply circuit comprises a 12v-to-5v power supply circuit and a 5v-to-5v power supply circuit. A magnetic bead filter, a pi-type low-pass filter circuit and a shunt capacitor filter circuit are arranged between the 12v-to-5v power supply circuit and the 5v-to-5v power supply circuit. According to the invention, the dark counting influence caused by the adoption of a single-ended phototube in the weak signal extraction process can be avoided, and the measurement precision and reliability are improved.

The invention discloses a biological environment monitoring data management system based on the Internet of Things, and relates to the technical field of monitoring data management. Comprising the steps that a data cleaning module collects original data through the Internet of Things, and primary data is obtained after data cleaning; the demand screening module obtains data demands of users and deletes completely useless elementary data to obtain medium data; the truth judgment module extracts biological environment information according to the medium data, judges whether the medium data is truth or not, and obtains a truth judgment result; the traceability judgment module obtains the importance degree of medium data and judges whether data traceability is carried out or not in combination with a real judgment result; the data tracing module performs data tracing on the medium data, and performs screening and deletion after tracing to obtain high-level data; and the data storage module stores the higher data to obtain a biological environment monitoring database. According to the invention, the accuracy of biological environment monitoring data management based on the Internet of Things is improved.

The invention provides an intelligent credit line evaluation method and system based on multi-dimensional enterprise data, electronic equipment and a storage medium, and relates to the field of financial science and technology and data processing. The system adopts a four-layer architecture, and automatically collects enterprise invoices, industry and commerce and judicial data through an interface. And the data processing layer constructs quantitative indexes by using a cleaning engine and feature engineering. The decision engine layer adopts a multi-dimensional scoring model and a quota checking algorithm based on linear regression, the quota checking model introduces a natural logarithmic function to process the invoicing amount, and the credit line is dynamically calculated in combination with the downstream customer growth rate and the special invoice rate. According to the method, through multi-source data fusion and real-time calculation, the problems of data lag, single dimension and low decision-making efficiency of a traditional model are solved, accurate quantitative evaluation of enterprise operation conditions is realized, and risk identification accuracy and approval efficiency are remarkably improved.

The invention relates to a CVT operation error evaluation method and device, electronic equipment and a storage medium, and belongs to the technical field of power monitoring, and the CVT operation error evaluation method comprises the steps: determining an error evaluation index of a target CVT based on the real-time secondary voltage data of the target CVT; inputting the error evaluation index of the target CVT into an error evaluation model, and taking the output of the error evaluation model as the operation error evaluation result of the target CVT; wherein the error evaluation model performs error evaluation based on the SCN network, and the bias and the input weight of the hidden layer node of the SCN network are configured based on normal distribution. According to the method, the error evaluation accuracy is ensured, the complexity of an error evaluation model is reduced, and the iteration speed of the model is improved.

The present application relates to a basketball sports auxiliary system, the system comprising: a net sensor, arranged on a net, for collecting a user's shooting data; a wearable device, for collecting the user's basketball behavior information; a first terminal, respectively connected to the net sensor and the wearable device for communication, for obtaining the user's shooting data and basketball sports data obtained from the user's basketball behavior information, and outputting the user's shooting data and basketball sports data, wherein the basketball sports data includes one or more of physiological information and motion data. This method does not require manual recording of the user's shooting data and basketball sports data, saves human resources, avoids erroneous data caused by manual recording, improves the accuracy of shooting data and basketball sports data, and improves the efficiency of data collation. The present application also relates to a basketball sports auxiliary method.

The invention provides a method for measuring the sound reflection coefficient of a large-sample underwater acoustic material based on a sound pressure hydrophone array, and the method comprises the steps: employing a CW pulse (continuous wave pulse) as a transmitting signal form, and receiving a signal through a sound pressure hydrophone array disposed near the surface of a sample; then separation of the direct sound and the reflected sound is attributed to a mathematical problem of solving an equation set by utilizing known prior information of measurement system parameters, the direct sound and the reflected sound are separated, and then the sound reflection coefficient of the sample can be rapidly obtained through simple calculation.