30 results about "Abnormal Indicator" patented technology

The invention discloses an anti-electricity-stealing precise localization online monitoring method. Models and anomaly screening rules about line loss anomaly indexes, electricity utilization anomaly indexes, metering device failure and anomaly alarming indexes, user historical business handling condition indexes, user historical electricity utilization service indexes and electricity price executing indexes are established through a known electricity stealing user electricity utilization data rule, a marketing business application system, an electric energy collecting system, a 95598 service complaint and customer basis file information are adopted as customer data sources, and suspected electricity stealing users are monitored in real time. Electricity utilization anomaly customers are investigated through an anti-electricity-stealing online monitoring platform, the loads, electricity quantity and other abnormal conditions of the customers are tracked in real time, the problem of difficult stealing investigation and evidence obtaining is fundamentally solved, anti-electricity-stealing working efficiency is effectively improved, and enterprise benefits are guaranteed.

The embodiment of the invention discloses a method and a system for determining a fault root cause and a computer readable storage medium. According to the method, fault source information is analyzedfrom the three dimensions of multi-time-sequence correlation, data stream correlation and event correlation, and a first fault index and an anomaly index set are acquired; a Pearson-grey correlationcombination method is utilized to calculate the correlation degree between the first fault index and each anomaly index in the corresponding anomaly index set; the anomaly indexes corresponding to thecorrelation degrees meeting a preset threshold are used as a correlation result set; a pre-established fault diagnosis set is queried, a historical diagnosis result set corresponding to the first fault index is acquired; and an intersection of the correlation result set and the historical diagnosis result set is calculated, and the index contained in the intersection is the fault root cause of the first fault index. According to the technical scheme, automatic and intelligent mining and positioning of the root cause of a fault in an e-commerce system are realized, and the problem solving speed of development, operation and maintenance personnel is effectively increased.

The invention discloses an equipment fault prediction method based on factor-event correlation recognition. The method includes: acquiring normal running historical information and fault historical information of equipment, and storing running information and ambient information related to an equipment fault moment in a data sheet to form an equipment fault data set; forming a normal equipment running data set through the running information and ambient information when the equipment normally runs; statistically analyzing equipment fault parameters online, recognizing an equipment running abnormality indicator to quickly recognize a grid equipment fault hazard, and giving an early warning to provide scheduling and shipping inspectors with decision basis. The method has the advantages that fault criterions can be provided, fault factors and a fault indicator range can be selected, a clear warning indicator is provided, and a scientific method of warning is provided.

The invention provides an abnormal index detection method and an abnormal index detection device. The abnormal index detection comprises the steps of: respectively acquiring a sequence of indexes to be detected of each host from N hosts; dividing a target time interval into M unit time periods; calculating a mean value of instantaneous values of each sequence among sequences of N indexes to be detected at corresponding moment in each unit time period, and regarding sum of the mean values in the unit time period as a target value of the unit time period; ranking the target values of the unit time periods according to time sequence to obtain a target sequence; and generating a status value based on the numerical values in the target sequence, and determining that an abnormal index is detected if the status value does not satisfy a preset condition. Therefore, the method and the device provided by the embodiment reduce the dimensions of the N sequences of the indexes to be detected to the target sequence, and reduce the dimensions of the target sequence to the status value, so as to determine whether the indexes are abnormal according to the status value, thus the method for determining whether the indexes are abnormal according to the status value is simpler.

The invention discloses a microquake multi-parameter early warning method of a rock burst in a high-stress concentration area. Microquake signals are recorded by use of a microquake monitoring system, and a microseismicity S value, a microseismic time information entropy Qt value, a microquake accumulation impact index E value and a microseismic activity abnormal index |Z| value are calculated and analyzed; after obtained data is analyzed, evolution graphs of the four indexes are respectively drafted; according to the drafted evolution graphs, whether the phenomena occurs in the same time period is analyzed that the microseismicity S value is firstly decreased within seven days and then is rapidly increased at a rate greater than a decreasing rate, the microseismic time information entropy Qt value is continuously decreased within four days, the microquake accumulation impact index E value is greater than a critical value Em and the microseismic activity abnormal index |Z| is greater than three, if the two to four from four indexes occur in the same time period, it is determined that a rock burst is about to take place. According to the invention, an early warning of the impact burst is given in an integrated mode by use of multiple parameter indexes, and thus the early warning accuracy can be effectively improved.

The invention discloses a monitoring and warning method and system. The method comprises the following steps: 1, determining abnormal indexes in a plurality of monitored indexes of one or more runningmodules, and recording information of the determined abnormal indexes; 2, determining an index correlated with one abnormal index on the basis of information of the abnormal index, and determining acause leading to the abnormal index on the basis of the abnormal index and the correlated index; and 3, performing corresponding warning on the basis of the determined cause leading to the abnormal index. Through adoption of the method and the system, the cause and influence range of a problem can be rapidly located.

The invention relates to the field of data analysis, in particular to a financial data analysis early warning method and device, computer equipment and a storage medium. The method comprises the stepsof obtaining financial data to be analyzed; obtaining a trained abnormal index identification model; inputting the to-be-analyzed financial data into the abnormal index identification model to identify a current abnormal index existing in the to-be-analyzed financial data; and obtaining a trained financial health degree model, inputting the current abnormal index into the financial health degreemodel to obtain a default probability corresponding to the financial data to be analyzed, and outputting early warning information when the default probability of the financial data to be analyzed ishigher than a preset value. By adopting the method, the financial data analysis and early warning accuracy can be improved.

The invention discloses an air-space-ground integrated measurement and control method for tailings reservoir risk in the technical field of mine safety risk monitoring, the steps including follows: 1.remote sensing satellite photos of different time periods in a mine area are obtained, and then normal libraries and suspected abnormal libraries are screened out, and difference point areas of the suspected abnormal libraries are found out; 2. according to starting threshold condition of unmanned aerial vehicle, the unmanned aerial vehicle is started to conduct low-altitude aerial survey of thesuspected abnormal libraries to obtain two-dimensional spatial data information; 3. according to starting threshold condition of three-dimensional laser, the three-dimensional laser is started to measure the suspected abnormal libraries to obtain three-dimensional spatial data information and establish a three-dimensional spatial model; 4. when the parameters index of the three-dimensional spatialdata information reaches the threshold range, real-time monitoring is started; 5. abnormal indicators are monitored in real time and early alert is issued. The air-space-ground integrated measurement and control method for the tailings reservoir risk realizes the multi-level monitoring of tailings reservoir in a wide range, and obtains the parameters data of the tailings reservoir in time, quantitatively and at low cost, and can alert the risk.

The invention provides a network fault early warning method and device, and the method comprises the steps: collecting network fault data and network sensing index data; analyzing the correlation between the network fault data and the network sensing index data, and determining related indexes; predicting whether the related index is abnormal or not by utilizing a time sequence prediction algorithm, and if so, determining that the related index is an abnormal index; and for each piece of user-level network equipment, collecting abnormal index data, and if the preset number of abnormal indexesare abnormal, determining that the user-level network equipment has a network fault. According to the invention, the faulted user-level network equipment can be accurately positioned, and the index data used by the network fault early warning of each user-level network equipment is unified, so that the whole network can be covered.

The invention discloses a social security incident monitoring and tracing method. The social security incident monitoring and tracing method comprises the steps of establishing a forecasting and early warning database, a case database, a preplan database and an expert evaluation database; setting index data of an emergency security incident; performing model calculation on data newly transferred into the forecasting and early warning database, analyzing and forecasting the trend of social security incidents, and displaying a forecasting result by adopting a diagram; generating an early warning level according to the forecast trend of the social security incidents, and providing an assistant decision for a decision maker. The social security incident monitoring and tracing method can perform big data analysis on emergency mass incidents, serious criminal cases and emergency public health incidents, and carry out modeling and early warning on the analyzed data, thereby forecasting the trend of the social public security, labeling and paying close attention to abnormal indicators, and being capable of providing an early warning display and assistant decision-making scheme for the decision-making personnel.

The invention provides an automatic interpretation method, system and device for a hospital inspection report, and the method comprises the step: performing OCR identification of a hospital inspectionreport file uploaded by a user, and further comprises the steps: capturing the anomaly index information; generating electronic inspection report information; combining with a knowledge base to automatically generate recommendation information; and generating an interpretation file of the hospital inspection report according to the recommendation information. The invention provides the automaticinterpretation method, system and device for the hospital inspection report, and the method and system use the automatic extraction rule to interpret the information in the report based on the OCR recognition and the authoritative knowledge base, and give the user corresponding explanation and health guidance.

The invention relates to a data screening method and particularly discloses an abnormal business data screening method for an anti-money laundering system. The method comprises steps that business data is received; abnormal indexes triggered by the business data are acquired through screening; abnormal models triggered by the triggered abnormal indexes are calculated; business data contained by each triggered abnormal index contained by each triggered abnormal model is derived, and the abnormal business data is acquired. According to the method, the abnormal index and abnormal model screening method is employed, namely combination of the screening method and business scenes, the multiple abnormal indexes satisfying abnormal model triggering conditions are screened in a triggering mode, abnormal transaction possibility of the screened-out business data is substantially enhanced, and the abnormal business data can be more effectively screened. The method is advantaged in that flexible configuration and strong portability are realized, and the method can be applied to different data analysis type systems.

The embodiments of the present invention disclose a feature grouping-based electric energy metering abnormality diagnosis method and system. The invention aims to solve the technical problems of vulnerability of judgment results to subjective effects, lack of theoretical basis and long judgment and identification time which are caused by a condition that judgment on the failure abnormality modes of an electric energy metering device mainly relies on the experience of technicians of field maintenance processing. According to the implementations of the invention, the method includes the following steps that: an initial database is constructed according to obtained electric energy metering abnormality types, judgment criteria of the electric energy metering abnormality types and a corresponding data source; the data of the data source of the initial database is transformed according to the judgment criteria of the electric energy metering abnormality types, so that an initial metering abnormality indicator set is formed; indicator feature grouping is performed on the initial metering abnormality indicator set, so that a plurality of indicator groups are formed; multi-classifier training is performed on the indicator groups, so that a plurality of different classification models can be obtained; and the different classification models are fused, so that an electric energy metering abnormality recognition result can be obtained.

The invention discloses an elevator running state active checking method. The method comprises the following steps that an anomaly index data set is collected by a failure prediction system and transmitted to an active checking system; the active checking system calculates information identification codes according to the anomaly index data set; the active checking system searches an elevator failure historical database for a similar index data set and detailed data set according to the information identification codes, and a detailed data collection request needing to be collected is determined; the active checking system sends the detailed data collection request to an elevator control system; the elevator control system sends the detailed data set to the active checking system; the active checking system carries out prediction result analysis on the detailed data set; and the active checking system stores the anomaly index data set, the detailed data set and the information identification codes corresponding to the anomaly index data set and the detailed data set into the elevator failure historical database. During system running, only anomaly index data are subjected to detailed data extraction, and the pressure of a data collection, real-time transmission and analysis system is effectively reduced.

The invention discloses an SDN abnormal flow detection method based on a re-marking range method, and belongs to the technical field of computer network security. The method comprises the following steps: collecting the number of normal network flow packets of each node (including a controller and each user terminal) of the SDN, and respectively calculating the Hurst index of the normal network flow packets; storing and taking as a network normal index, and setting a threshold value of a normal state; collecting the number of network flow packets with certain known exception of each node, andcalculating the Hurst index of each node as the index of the exception; intercepting a forward sequence by using a window function and calculating a Hurst index of the forward sequence, and if a normal index is finally changed into a certain abnormal index, determining that the abnormality of the mode occurs and determining an abnormality occurrence time point. And if only the index change deviates from the normal value, but the similar abnormal index cannot be found, an exception except the known mode occurs, and an exception time point can be determined. According to the method, the flow state can be detected in real time, whether the flow is abnormal is judged, the abnormality occurrence time can be detected, and the security of the SDN network system is enhanced.

The invention discloses a monitoring method and a monitoring device for an application program of a train display system. The method comprises the following steps: acquiring a monitoring process identifier according to the application program of the train display system; starting the monitoring process and monitoring the application program of the train display system according to the acquired monitoring process identifier; acquiring the state information of an application program index of the train display system and treating the abnormal index state information. The monitoring method and the monitoring device for the application program of the train display system, disclosed by the invention, can be used for realizing the monitoring for any application programs of the train display system. When the monitored application program of the train display system is abnormal, the train display system can automatically repair the fault and display the fault information, the train display system can provide a solution for the driver and passengers, all the abnormal information are recorded and a data basis is supplied for the subsequent fault analysis.

The invention is a multifunctional monitoring device, comprising a monitoring system body, a camera, an infrared sensor, a processing module and a signal receiving module, wherein the monitoring system body is composed of the camera, a monitoring host and an abnormal alarm device; the camera is fixedly installed in the middle of the upper side of the monitoring system body, the infrared sensor isfixedly disposed below the camera, and the infrared sensor is fixedly connected to the right end of a collection module. The multifunctional monitoring device can shoot the portrait through the set camera and infrared sensor, process the portrait through the acquisition module and the processing module, control through the monitoring host, store through the storage module, feedback the abnormal situation of the monitoring system by the setting of the power supply and abnormal alarm device, observe through the abnormal indicator light provided, control the abnormality indicator light by the transmission conductor and the power supply, and is convenient for observation through the display screen provided.

The invention discloses a pharmaceutical composition for treating II-type diabetes and a preparation method of pharmaceutical composition. The pharmaceutical composition comprises the following ingredients in parts by weight: 80-150 parts of a crude fiber mixture, 60-90 parts of phycocyanobilin, 50-80 parts of patuletin, 38-76 parts of diosgenin, 35-70 parts of rutin, 16-30 parts of polyethylene glycol, 15-24 parts of pyridoxine, 12-18 parts of flavonoid glycosides, 10-16 parts of linoleic acid, 10-15 parts of sciadopitysin, 8-13 parts of kaempferol, 8-12 parts of quercetin, 7-11 parts of glutamic acid, 6-10 parts of lysine, 5-10 parts of tannin, 5-8 parts of flunarizine, 4-7 parts of thiamine and 2-6 parts of mixed enzyme. The pharmaceutical composition disclosed by the invention is a combination of traditional Chinese medicine and western medicines, effectively reduces the blood sugar and improves the glucose tolerance level of a muscle body on the basis of regulating the normal diet, regulates various abnormal indicators of the muscle body, enhances the tolerance of long-term drug use of a diabetic patient and reduces drug side effects. The pharmaceutical composition disclosed by the invention is simple in preparation process and convenient to use and has good clinical popularization significance.

The embodiment of the invention relates to the technical field of communication, in particular to an abnormity positioning method, a server and a storage medium. The abnormity positioning method comprises the following steps: acquiring abnormity indexes of a client; according to the abnormity index and a preset abnormity detection model, acquiring an abnormity level corresponding to the abnormityindex in a content distribution network and the time when the abnormity index occurs in the abnormity level, wherein the abnormity detection model is obtained through historical client index training;and determining the occurrence position of an abnormal event according to the abnormity index, the abnormity level and the time when the abnormity index occurs in the abnormity level. By adopting theembodiment of the invention, the occurrence position of the abnormal event occurring in the content distribution network can be quickly determined, and the efficiency of solving the abnormal event can be improved.

The invention discloses an automation-based meter reading business data analysis and processing method and system. A meter reading work quality normal evaluation mechanism throughout the province is established and a meter reading business management and control data analysis model is researched and developed based on the established complete business management and control system of "province-city-county" three-level supervision. A fair, open and transparent work quality evaluation system is established, evaluation mainly depends on a performance appraisal indicator system and a peer-to-peerbenchmark indicator system with focus on the peer-to-peer benchmark indicators, the business performance indicators are refined, the business abnormal indicators are identified, the meter reading related business is comprehensively standardized and the risk of complaint is strictly controlled so that all-business, whole-course and all-indicator monitoring of the meter reading work indicators and work quality can be realized, field investigation of the prominent problems of meter reading is completely covered, and thus the method and the system have the advantages of high data processing efficiency, accurate diagnosis result, comprehensive analysis and simple and convenient implementation of the method.

The invention belongs to the field of aquiculture and discloses an automatic fishpond monitoring system which comprises a controller, monitoring equipment, adjusting equipment, an operating panel, a high-voltage power source, a low-voltage power source and relays. The monitoring equipment, the operating panel, the low-voltage power source and the relays are all connected with the controller, and the relays are connected with the adjusting equipment which is connected with the high-voltage power source. The automatic fishpond monitoring system can automatically monitor pH value, temperature and dissolved oxygen content of a water body in a fishpond and can automatically adjust abnormal indicators, and integration and automation of monitoring and adjusting of the water body in the fishpond are realized.

The embodiment of the invention provides a root cause positioning method and device, electronic equipment and a computer storage medium. The method comprises the steps: determining at least one abnormal index in an abnormal event when the abnormal event of a transaction occurs; determining an abnormal transaction flow corresponding to each abnormal index in the at least one abnormal index; constructing a transaction calling chain corresponding to each abnormal transaction flow, the transaction calling chain comprising nodes called by the abnormal transaction flow; determining a root cause nodecorresponding to each abnormal transaction flow in the transaction call chain corresponding to each abnormal transaction flow according to the abnormal type of the abnormal event; and determining theroot cause node of the abnormal event according to the root cause node corresponding to each abnormal transaction flow.

The embodiment of the present invention discloses a method, system and computer-readable storage medium for determining the root cause of a fault, which analyzes the fault source information from three dimensions of multi-sequence correlation, data stream correlation and event correlation, and obtains the first fault index Abnormal index set; use the Pearson-gray correlation combination method to calculate the degree of correlation between the first fault index and each abnormal index in the corresponding abnormal index set; use the abnormal index corresponding to the correlation degree that meets the preset threshold as the association Result set; query the pre-established fault diagnosis set to obtain the historical diagnosis result set corresponding to the first fault index; calculate the intersection of the association result set and the historical diagnosis result set, and the index contained in the intersection is the fault of the first fault index Root cause. According to this technical solution, the automatic and intelligent mining and locating of the root causes of faults in the e-commerce system are realized, and the speed of problem solving by development and operation and maintenance personnel is effectively improved.

The invention discloses a surge protection device which is in coupling connection with a live wire, a neutral wire and a ground wire of a three wire type power supply. The surge protection device comprises a first surge protection unit, a second surge protection unit, a third surge protection unit, a first optical coupling unit and a second optical coupling unit; the first surge protection unit comprises a voltage dependent resistor and a fuse; the second surge protection unit comprises a voltage dependent resistor and a fuse; the third surge protection unit comprises a voltage dependent resistor and a fuse; a normal indicator signal is output from an emitter end of the second optical coupling unit during normal operation of the plurality of fuses of the first surge protection unit, the second surge protection unit and the third surge protection unit; an abnormal indicator signal is output from the emitter end of the second optical coupling unit when one of the plurality of fuses of the first surge protection unit, the second surge protection unit and the third surge protection unit is fused. According to the surge protection device, the complexity of the design is reduced.

The invention relates to a high-precision indicator diagram production metering correction statistical method, which belongs to the technical field of automatic oil extraction and is characterized bycomprising the following steps of: counting the operation time of an oil well; extracting all indicator diagrams in the running time of the oil well; removing the abnormal indicator diagrams from allindicator diagrams in the oil well operation time to obtain residual indicator diagrams; determining the effective operation time of the oil well corresponding to the residual indicator diagram; and summarizing the yield corresponding to each period of time in the effective operation time to complete high-precision indicator diagram production statistics. The method mainly comprises the steps of oil well startup and shutdown time confirmation; eliminating the abnormal indicator diagram in the startup time period; determining the time length represented by each remaining work map; according tothe high-precision indicator diagram production counting correction statistical method, carrying out daily production statistics according to the timeliness of each indicator diagram. Precision is high, and better and wider adaptability is achieved.

The invention discloses a microquake multi-parameter early warning method of a rock burst in a high-stress concentration area. Microquake signals are recorded by use of a microquake monitoring system, and a microseismicity S value, a microseismic time information entropy Qt value, a microquake accumulation impact index E value and a microseismic activity abnormal index |Z| value are calculated and analyzed; after obtained data is analyzed, evolution graphs of the four indexes are respectively drafted; according to the drafted evolution graphs, whether the phenomena occurs in the same time period is analyzed that the microseismicity S value is firstly decreased within seven days and then is rapidly increased at a rate greater than a decreasing rate, the microseismic time information entropy Qt value is continuously decreased within four days, the microquake accumulation impact index E value is greater than a critical value Em and the microseismic activity abnormal index |Z| is greater than three, if the two to four from four indexes occur in the same time period, it is determined that a rock burst is about to take place. According to the invention, an early warning of the impact burst is given in an integrated mode by use of multiple parameter indexes, and thus the early warning accuracy can be effectively improved.