11results about How to "Avoid troubleshooting" patented technology

The invention provides a distribution line fault judgment method and system. The distribution line fault judgment method comprises the steps that S1, a plurality of detection points are arranged on a distribution line to be detected, and three-phase current is collected; s2, converting the three-phase current of the plurality of detection points into a plurality of zero-sequence currents through an intelligent fusion terminal; s3, collecting a plurality of zero-sequence currents, and analyzing the plurality of zero-sequence currents respectively; and S4, when the distribution line to be detected has a fault, calculating the occurrence duration of the corresponding zero-sequence current. According to the method, maintenance processing in different modes can be performed in a targeted manner when a fault occurs, tedious troubleshooting and maintenance processes under an instantaneous fault are avoided, the operation efficiency and reliability of the power distribution network are improved, the maintenance cost is greatly reduced, and in addition, compared with a conventional detection mode at the present stage, the maintenance cost is greatly reduced. The method has the remarkable advantages of being convenient to operate, wide in application range, high in detection precision, high in response speed and the like, and a new thought is provided for power distribution maintenance engineering.

The invention relates to the technical field of process engines, in particular to a custom code execution method and device of a process engine, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: newly adding a user-defined task node in a front-end design module of an Activiti process engine, and setting a user-defined event monitor for the user-defined task node; starting a process virtual machine to execute the custom event monitor; according to the user-defined event monitor, a JavaScript user-defined code is compiled in the NapornSandBox sandbox environment, and the JavaScript user-defined code is executed; and obtaining an execution result of the JavaScript custom code, and recording the execution result in a log record table of the Activiti process engine. By adopting the method, the flexibility of process design and the participation degree of users can be improved in the aspects of customizing and modifying the business process.

The present invention relates to the field of chip manufacturing, and proposes a method and system for realizing the preparation of semiconductor memory chips, the method comprising: first obtaining chip parameters, selecting semiconductor materials and pre-processing, determining the area to be deposited, and then depositing insulating layers and conductive layers to build a multi-layer structure framework, and then determining the optimal thickness and layout of each layer and calculating the expected reading and writing values, then determining the performance indicators according to the expected reading and writing values, evaluating the feasibility of preparation to obtain preparation evaluation data, querying the influencing factors to calculate the influence degree value, and then configuring the packaging materials according to the influence degree value to build a curing environment, monitoring the curing process state and tracing the abnormality, and finally analyzing the target concentrated in the abnormal source, identifying the abnormal storage factor, and generating a chip preparation plan based on this monitoring feedback data. The present invention can improve the preparation stability of semiconductor memory chips.

The present invention belongs to the technical field of air tightness monitoring, and discloses an artificial intelligence-based transformer oil storage cabinet capsule air tightness monitoring system, the system comprising a temperature information acquisition module, a pressure information acquisition module, a temperature anomaly analysis module, a gas flow anomaly analysis module, an air tightness analysis module, an air tightness change trend identification module, a monitoring result display module and a data storage library. The present invention analyzes the capsule air tightness index by analyzing the temperature anomaly and gas flow anomaly of the transformer oil storage cabinet capsule, and evaluates whether the capsule air tightness meets the standard based on the capsule air tightness index, and analyzes the air tightness change trend of the capsule for the situation where the air tightness does not meet the standard, effectively improving the efficiency of capsule air tightness monitoring, improving the authenticity and effectiveness of the monitoring results, avoiding possible safety accidents during the monitoring process, optimizing the accuracy and scientificity of the monitoring results, and at the same time improving the efficiency and accuracy of maintenance.

The utility model provides a kind of circuit board fault rapid detection system, including monitoring and data acquisition comparison system, detection module, XYZ three-axis displacement system, pose adjustment system and motion control system, pose adjustment system is fixed on the X motion component of XYZ three-axis displacement system, to be measured circuit board is fixed in pose adjustment system top, detection module is fixed in the Z axis motion component bottom of XYZ three-axis displacement system.Detection module is used to measure the voltage value between each pin on to be measured circuit board and to be measured circuit board GND end;Motion control system controls XYZ three-axis displacement system movement to adjust the position of detection module, and there is perfect same type circuit board pin volt-ampere characteristic database in monitoring and data acquisition comparison system.The utility model system can realize to be measured circuit board in situ fault detection, will not cause damage to circuit board, and can accurately position circuit fault area, detection efficiency is high and cost is low.

The invention discloses an archive data storage system and method based on cloud computing, and relates to the technical field of archive data analysis, and the system comprises a warehousing scanning unit, an archive data analysis module, a label data analysis module, and an archive maintenance module. The warehousing scanning unit is used for recording standard image information during distribution of the visual coding labels and scanning paper archives and visual coding label images during warehousing and returning of borrowers; the archive data analysis module calculates a paper archive data detection rate, and constructs an archive damage prediction model in combination with environment influence parameters in a storage environment and a paper archive damage rate marking result; the label data analysis module calculates the identification degree and the comprehensive identification degree of each coding color block image of the visual coding label image, and performs fitting to obtain a prediction curve of the identification degree of each coding color block image; and the archive maintenance module is used for predicting storable time of the paper archive and the visual coding label and setting an archive maintenance period to which the paper archive belongs.

The invention discloses a multivariate data fusion-based engine oil abnormal consumption diagnosis method, which adopts an innovative diagnosis scheme of multivariate data fusion, dynamic model and multistage judgment, and comprises the following steps of: generating a dynamic reference model of engine oil consumption through a neural network model through fusion analysis of working condition parameters and engine oil consumption data; according to the system and the method, engine oil abnormal consumption can be accurately detected in real time in advance, the abnormal judgment of the liquid level-oil consumption change ratio is calculated, a matched intelligent diagnosis system is synchronously developed, and the intelligent diagnosis system comprises a data acquisition module, a sensor, an edge gateway, a visual instrument terminal and a cloud platform. And efficient technical support is provided for engine operation and maintenance.

The present invention relates to the field of grain storage monitoring technology, and specifically to a method and system for monitoring grain conditions in a wharf granary. The method comprises the following steps: obtaining data on the environmental characteristics of the wharf granary and the grain pile size characteristics, temperature characteristics, humidity characteristics, and gas concentration characteristics; constructing a spatiotemporal feature model based on the data, the spatiotemporal feature model comprising a temperature spatiotemporal feature model, a humidity spatiotemporal feature model, and a gas concentration spatiotemporal feature model; obtaining spatiotemporal feature data according to the spatiotemporal feature model; processing the spatiotemporal feature data to obtain optimized spatiotemporal feature data; constructing a food security risk assessment model through the optimized spatiotemporal feature data; and monitoring the grain conditions in the wharf granary according to the food security risk assessment model. The present invention greatly reduces the monitoring cost and achieves high-precision assessment of food security risks by performing internal sensorless monitoring of the temperature, humidity, and concentration of infinite space points inside the grain pile.

The invention discloses an archive data storage system and method based on cloud computing, and relates to the technical field of archive data analysis. The system comprises: a storage scanning unit, an archive data analysis module, a label data analysis module, and an archive maintenance module; the storage scanning unit records standard image information when visual coding labels are allocated, and scans paper archives and visual coding label images when they are stored and returned by borrowers; the archive data analysis module calculates the detection rate of paper archive data, and constructs an archive damage prediction model in combination with environmental impact parameters in the storage environment and paper archive damage rate annotation results; the label data analysis module calculates the image recognition and comprehensive recognition of each coded color block of the visual coding label image, and obtains the recognition prediction curve of each coded color block by fitting; the archive maintenance module is used to predict the storage time of paper archives and visual coding labels, and set the archive maintenance cycle to which the paper archive belongs.

The invention provides a vehicle door and shielding door linkage fault diagnosis and analysis method and system, and belongs to the technical field of urban rail transit, and the method comprises the steps: judging whether the linkage state of a vehicle door and a shielding door has a fault or not based on the vehicle-mounted log data of a vehicle; when the linkage state of the vehicle door and the shielding door has a fault, the fault type is determined; establishing a fault tree model corresponding to the fault type; state confirmation is conducted on top events and sub-events in the fault tree model layer by layer, fault causes are obtained, the top events are linkage faults of the vehicle door and the shielding door, and the sub-events comprise control instruction problems and communication connection problems related to the vehicle door and the shielding door. The linkage state of the vehicle door and the shielding door is monitored in real time through the vehicle-mounted log data, the fault types are automatically classified, and the node state is diagnosed layer by layer based on the fault tree model, so that the linkage fault of the vehicle door and the shielding door is accurately detected and diagnosed, and the fault processing efficiency is improved.

The invention discloses an electrostatic monitoring method and system for faults of a heavy-duty gas turbine, relates to the technical field of gas turbines, and is mainly used for solving the problem that the monitoring accuracy of the faults of the gas turbine caused by static electricity is relatively low. The method mainly comprises the following steps: in the fault monitoring process of the heavy duty gas turbine, acquiring fault monitoring target data in real time, and performing fault monitoring on the fault monitoring target data based on configured fault monitoring standard data; when it is determined that the heavy duty gas turbine breaks down based on the fault monitoring standard data, electric signals collected by electrostatic monitor sets installed at at least two electrostatic monitoring positions are obtained; determining a target monitoring position of a maximum electric signal in the electric signals, and determining an associated electric signal of at least one associated position based on a monitoring network constructed by the electrostatic monitor group; if the electric distance value between the associated electric signal and the maximum electric signal is larger than a preset electric distance threshold value, it is determined that the heavy duty gas turbine is in an electrostatic fault.