38 results about "Inductive analysis" patented technology

The invention provides a water pollution treatment facility monitoring system and a water pollution treatment facility monitoring method based on the Internet, and belongs to the technical field of sewage monitoring. The problem that sewage supervision is difficult in the prior art is solved. The water pollution treatment facility monitoring system based on the Internet is composed of a cloud data center, a plurality of sewage monitoring terminals, and a remote monitoring center. Each sewage monitoring terminal comprises a data acquisition unit and a data identification unit connected with the data acquisition unit. The cloud data center is responsible for real-time data reception and data exchange. The remote monitoring center exchanges data with the cloud data center in real time through the Internet, acquires the operation parameters and states of the sewage monitoring terminals, and displays, does statistics of and reports the operation parameters and states in real time. The invention further provides the water pollution treatment facility monitoring method based on the Internet. A regional water environment pollution treatment strategy is formed through inductive analysis of big data of the cloud data center. Through the monitoring system and the monitoring method, the difficulty in sewage discharge supervision can be reduced.

The invention discloses a work correction system and method, and the system comprises an obtaining module which is used for obtaining a to-be-corrected work and importing the to-be-corrected work into electronic equipment in a format of images; a correction module which is used for correcting the imported work and storing the correction result; and a remark module which is used for the call of the remarks in a remark database for the remarking of the corrected work. The method is implemented in the correction system. The system and method can achieve a purpose of replacing manual correction with electronic correction. A teacher can obtain the experience like conventional manual correction under the condition of reducing the workload. The teacher also can remark the errors in the work timely, and carries out concluding and analyzing. Meanwhile, the correction feedback list generated during correction can provide a tool for arranging and correcting work errors for a student, and enables the arrangement and correction of the errors of the students, so the method and system are convenient and effective.

The invention discloses a workshop-level manufacturing capability oriented dynamic comprehensive assessment method. The method includes the steps that at first, composition elements of the workshop-level manufacturing capability are concluded and analyzed, an index system of workshop-level manufacturing capability dynamic comprehensive assessment is established, then a mathematical model of the workshop-level manufacturing capability dynamic comprehensive assessment is set up, and the manufacturing capability is assessed aiming at the mathematical model by means of combination of an entropy time empowerment and an analytic hierarchy process. According to the method, historical manufacturing data are used as the basis, an dynamic accurate assessment is conducted on the workshop-level manufacturing capability mainly for real-time workshop manufacturing data collected through the sensor technology, the radio frequency identification technology and other technologies with comprehensive consideration of manufacturing data in different manufacturing time periods, and support is provided for workshop production scheduling optimization and cooperation of enterprises.

The invention provides a method for assessing an immersed tunnel operation phase health state. The method comprises steps that inductive analysis on the historical disease data of built immersed tunnels at home and abroad is carried out, and a health state assessment index system is established; a health state assessment model of an assessed immersed tunnel is established by utilizing a hierarchical analytical method; an improved hierarchical analytical method is employed to determine the relative weight of each factor and the weight of each assessment index contained in each factor relative to the factor; fuzzy comprehensive assessment ideas are integrated, and grade comprehensive assessment on the built immersed tunnel health state assessment model is carried out on the basis of preset tunnel health state assessment standards. According to the method, factors such as the environment factor of the immersed tunnel, structural stress, strain and cracks are comprehensively considered, quantitative comprehensive assessment on the immersed tunnel health state in an operation process is realized, and effective support is provided for operation maintenance and decision of the immersed tunnel.

The invention discloses a multi-class safety service combinable safety network construction method and device. The method includes conducting inductive analysis on safety business to obtain the safety business class; searching a safety resource database to obtain the quantity of corresponding network safety resources; searching a network topological graph to obtain candidate node sets meeting the requirement; building a network topological structure according to the connection relation and the construction rule of the candidate node sets; distributing and combining the safety resources according to a node resource distribution and combination function and building a combinable safety network; detecting safety business requirement change, evaluating the surplus condition of the safety resources and marking nodes not meeting the changed resource requirement as key nodes; recombining and reconstructing the safety network containing the key nodes. The method and device can improve supporting flexibility and adaptability of network safety service to the safety application business, effectively and reasonably utilizes the network safety resources to achieve multi-class safety and meets the requirement of the combinable safety network.

The invention provides a test analysis report generation method and a test analysis report generation device, wherein the test analysis report generation method comprises the following steps: obtaining test data; carrying out statistics on the test data according to various statistics items of a test analysis report; and correspondingly filling the test analysis report with statistics results of various statistics items to generate a test analysis report file. By utilizing the technical scheme of the test analysis report generation method and the test analysis report generation device, test procedure data are subjected to extraction, conclusion and analysis according to unified requirements and format, and the test analysis report file is automatically generated to solve the problems of high writing threshold, large workload, low efficiency, low accuracy and the like existing in a generation process of a conventional test analysis report.

The invention discloses a water dispenser monitoring system and method with a filter cartridge monitoring function. The water dispenser monitoring system comprises a first TDS detector, a second TDS detector, a flow sensor, a processor, a communication module and a service terminal, wherein TDS detection is performed by the first TDS detector and the second TDS detector, the first TDS detector detects water quality before filtering, the second TDS detector detects water quality after filtering, third water quality data is obtained by comparing two groups of water quality data, flow data is acquired by the flow sensor, the third water quality data and the flow data are subjected to inductive analysis with default, and an alarm signal is produced according to an analysis result; the processor transmits the alarm signal to the service terminal through the communication module, and the service terminal performs alarm and display. The water dispenser monitoring system and method monitors a filter cartridge of a water dispenser precisely, a user is reminded timely to replace the filter cartridge when the filter cartridge of the water dispenser is abnormal, misoperation made during anomaly of single detection data is avoided, and drinking water safety is guaranteed.

The invention discloses a Johnson-Copula model-based power demand total amount related factor analysis system and method. The system comprises an input module, an index module, an analysis module andan output module which are sequentially connected. The index module obtains a correlation evaluation index data value from the input module, concludes and analyzes the historical statistical data of the input module, and establishes a correlation evaluation index system; the analysis module comprises a sample distribution verification sub-module, a Johnson distribution curve family calculation sub-module, a Copula joint distribution sub-module and a correlation analysis sub-module which are used for analyzing the correlation evaluation index system established by the index module; and the output module is used for outputting a power demand related factor analysis result. The method and the system have the advantages that the accuracy is good, and the diffusion and conduction effects of a power demand structure and power demand fluctuation can be revealed; the adaptability is strong, and the power grid enterprises are beneficial to comprehensively grasp the change rule of the total social power demand at different development stages.

The invention relates to a fire propagation reason analysis system. The fire propagation reason analysis system comprises a hardware part and a software part, wherein the software part comprises an event-reason logic relation module and a GUI online analysis module. The software part is built by using a GUI in a MATLAB, the event-reason logic relation module is used for building the correspondingrelations between basic events and fire propagation reasons, and the building process comprises the specific steps that according to a fire case database, the basic events happening in a fire are found out one by one and induced into a basic event database; the fire propagation reasons are found out one by one, and a fire propagation reason database is built; the logic relations between the basicevents and the fire propagation reasons are built by using a statistical induction method. The GUI online analysis module comprises a basic event selecting unit, an output unit for outputting the firepropagation reasons corresponding to an event, and an induction analysis unit used for inducing the fire propagation reasons corresponding to the selected basic event. The system can be used for quickly analyzing the reasons for a fire, the system is simple and convenient to use, and time and labor are saved.

The invention discloses a data analysis-based real-time monitoring system and method for the primary frequency modulation capability of a power grid. The method comprises the steps as follows: a signal collector module transmits collected real-time load values of units to first function setting modules, comparator modules and second function setting modules; output of each first function setting module is connected to a first input end of a first selector module; the output of each second function setting module is connected to the first input end of a second selector module; the output of each comparator module is connected to set terminals of the corresponding first selector module and second selector module separately; real-time primary frequency modulation upper limit values output by the first selector modules of all grid-connected frequency modulation units are summated; and real-time primary frequency modulation lower limit values output by the second selector modules of all grid-connected frequency modulation units are summated. Summary and analysis of the primary frequency modulation capability of each unit in various load intervals are achieved through a disturbance test; the primary frequency modulation conditions of the grid-connected frequency modulation units can be effectively monitored; and effective supervision and management are achieved.

The invention discloses an intelligent device gesture recognition control method based on image recognition, and the method comprises the steps: 1), capturing a user image through a camera, and recognizing the identity of a user and the general position of a hand based on OpenCV2; 2) graying and binarizing the image information of the rectangular part of the hand, solving the center distance of the hand graph to judge the palm center position, and analyzing the position coordinates of the key points of the hand by adopting a CNN model; (3) comparing and judging the hand key point position coordinates obtained in the step (2) with an operation gesture preset by a user by using a cosine similarity method by calculating a two-dimensional angle relation and other motion information of the hand key point position coordinates, so as to realize gesture analysis; 4, according to the analyzed gestures, a control instruction is sent to the equipment according to control logic set by a user, and the equipment is operated across the air through the gestures. According to the method, the neural network is used for recognizing the hand positions and gestures, inductive analysis on the gestures is introduced, and the intelligent equipment is rapidly controlled through the recognition result.

The invention relates to a quality control method and system, a server and a storage medium. The method comprises the following steps that: the identification information of each quality control product and quality control detection data which are obtained after detection is completed are acquired in a wireless/wired network transmission mode, and are transmitted to a cloud server; according to the identification information, the cloud server performs inductive analysis on the quality control detection data according to preset rules; and if the quality control detection data are abnormal, quality control feature data corresponding to the quality control detection data are inputted into a corresponding neural network, and after the quality control feature data are processed by the neural network, reason data causing quality control abnormalities, and/or solution data are outputted. With the quality control method and system, the server and the storage medium provided by the embodimentsof the invention adopted, the automatic judgment of quality control data, data transmission, the automatic analysis of quality control abnormal reasons and the automatic pushing of corresponding solutions can be realized, and thus the efficiency of quality control detection and the reliability of a quality control result are improved.

The invention provides a sewage discharge on-line monitoring system. The sewage discharge on-line monitoring system comprises a sampling device, a sample separation device, a detection device, and a control device which is connected with the sampling device, the sample separation device and the detection device separately. The sewage discharge on-line monitoring system is characterized by furthercomprising a cloud data center and a remote monitoring system; the output end of the sampling device is connected with the input end of the sample separation device, and the output end of the sample separation device is connected with the input end of the detection device; the control device is connected with the sampling device, the sample separation device and the detection device and controls the operation of the sampling device, the sample separation device and the detection device according to control instructions, the detection device uploads detected data to the cloud data center, and aremote control center performs inductive analysis based on the data of the cloud data center to obtain integrated data of water pollution environment management in a certain area.

The invention discloses an optimization method for anti-corrosion measures for a petroleum and natural gas industrial device. The optimization method comprises the following steps: optimizing material anti-corrosion measures, reasonably determining materials of key corroded parts between equipment and a pipeline according to the content of corrosive mediums in process mediums of the device, corrosive damage manners of the corrosive mediums to the equipment and the pipeline and an actual corrosion rate threshold value; optimizing process anti-corrosion measures, carrying out standard process operation according to real-time monitoring of the key corroded parts of the device, enhancing the sampling analysis to the corrosive mediums, effectively controlling the processing quality of the process mediums, and efficiently utilizing a corrosion inhibitor; optimizing corrosion detection measures, and finishing the setting of the number and positions of online corrosion rate monitoring points on the key corroded parts of the equipment and the pipeline and setting of the number and positions of offline fixed point thickness measurement points; concluding and analyzing corrosion failure cases, establishing a corrosion failure case database, and carrying out conclusion and analysis, thereby guaranteeing the smooth operation of the petroleum and natural gas industrial device.

The invention discloses a multi-station data acquisition and processing system of a flow assembly line, and relates to the technical field of data acquisition. The system comprises a station monitoring module, a data accumulation module, a data temporary storage unit, a self-analysis unit, a processor, a storage unit, a display unit, a suggestion generation unit and a management unit. The stationmonitoring module is used for monitoring a plurality of flow assembly lines with the same operation at the same time, and the self-analysis unit is used for carrying out self-analysis processing on asingle-piece man-hour group Gj of the data temporary storage unit to obtain tedious stations. According to the invention, inductive analysis is carried out on the condition of each station to obtain individual stations with relatively long occupied time, and the stations with relatively long occupied time are positioned and are suggested to be split so that the overall stations are reasonably planned, the condition of unreasonable station procedure arrangement is avoided, and intelligent management is realized; and the system is simple, effective, easy and practical.

The invention discloses a method for building an apparent pollution classification model of a landscape water body and an apparent pollution classification method of the landscape water body. The method for building the landscape water body apparent pollution classification model comprises the following steps: firstly, defining different apparent pollution types; selecting sampling points according to definition and carrying out water sample collection and determination as well as data accumulation; performing inductive analysis on accumulated data quantity by adopting a statistical method based on various index theory analysis; identifying different apparent pollution type characteristic indexes or characteristic values; determining the different apparent pollution type characteristic indexes and ranges of thresholds of the indexes; secondly, building the classification method of the landscape water body apparent pollution according to the characteristic indexes and the ranges of thresholds of the indexes; and finally, repeatedly selecting different sampling points to collect the data so as to perform coincidence ratio verification and threshold correction on building of the apparent pollution classification method until the coincidence ratio is up to 90 percent or above; primarily completing the building of the apparent pollution classification method; and dividing apparent pollution of the landscape water body into an organic dominant type, an inorganic dominant type, a nutritional dominant type and a mixed type.

The invention relates to a forward additive manufacturing control method based on physical model drive of a material. The method comprises the following steps: constructing an integral service life analyzing module based on a physical model of a microstructure of the material; searching and settling microstructure databases of the material in an additive manufacturing equipment range and carryingout summary and analysis to obtain a standard microstructure parameter combination of the material; establishing a corresponding relationship between a manufacturing control parameter group and a standard microstructure parameter combination of the material by using an artificial neural network; constructing an integral service life database of the material based on the physical model of the microstructure according to the standard microstructure parameter combination of the material for different materials; and constructing a forward driven additive manufacturing logic module by using the artificial neural network according to the integral service life database of the material, the standard microstructure parameter combination of the material, and the corresponding relationship between the manufacturing control parameter group and the standard microstructure parameter combination of the material, wherein the additive manufacturing logic module determines the priority of a manufacturing plan comprehensively.

The invention discloses a one-stop service system for intellectual property. According to the system, an information acquisition module acquires user information and transmits the acquired informationto a big data processing unit; the big data processing unit comprises a query module and an information analysis module; the query module queries relevant data information in a big data storage unitthrough a big data acquisition unit; the information analysis module analyzes the information queried by the query module; a service unit generates a service scheme of a user according to the data information transmitted by the big data processing unit. User information is acquired by the information acquisition module, the queried data information is summarized and analyzed by the big data processing unit, and the service unit is used for generating a professional intellectual property service scheme and/or a litigation service scheme, so that the user can solve the problems of application, management and litigation of the intellectual property through the service unit, all problems of the user are solved in one stop, and service efficiency is improved.

The invention belongs to the technical field of drinking water monitoring, and particularly relates to a system and a method for testing urban drinking water safety. The system comprises a monitoringmanagement center, a data center and multiple drinking water monitoring terminals, and the monitoring management center is in data communication with the drinking water monitoring terminals through the data center. The system is characterized in that each drinking water monitoring terminal comprises an information collection unit and an information recognition unit, and the monitoring management center acquires running state data collected by and result data recognized by each drinking water monitoring terminal, summarizes and analyzes the running state data to acquire comprehensive data of water quality monitoring management in a certain area and summarizes and analyzes the recognized result data to acquire comprehensive data indicating whether each drinking water treatment device has failure or not. Data acquired by detection are sent to terminal facilities, so that difficulty of management personnel in troubleshooting drinking water purifying equipment is lowered, and the managementpersonnel is enabled to timely find and deal with equipment failure.

The invention relates to a syndrome input RS code decoding method based on deep learning, comprising the following steps: generating a data set: calculating a syndrome S by using a receiving sequencey, and dividing the syndrome into a training set and a test set; calculating an error polynomial corresponding to the training set syndrome, and taking an error polynomial value as a deep learning training label; training a neural network: selecting a multi-layer perceptron (MLP) neural network structure, taking the syndrome S and the error polynomial E obtained in the step (1) as a data set of neural network training, and performing effective learning by using a back propagation algorithm; obtaining a neural network weight and bias with high decoding accuracy through training of a certain amount of data and algebra; when the number of the code word errors is within the decoding radius, performing inductive analysis on the neural network to obtain a correct corresponding relationship; andwhen the number of the code word errors is beyond the decoding radius, the neural network obtains the corresponding relation with the maximum possibility.