54 results about "Time processing" patented technology

The invention discloses a power equipment anomaly detection method and device, equipment and a storage medium. According to the dynamic graph division method based on computational load awareness, partition layout of load balance is achieved, the problem of load imbalance between processing nodes is remarkably reduced, hotspot bottlenecks caused by high-frequency equipment concentration are avoided, the overall throughput and parallel processing capacity of a system are improved, and the performance requirement for real-time processing of high-frequency data is met. And a constructed partition-unit-device multi-level anomaly detection mechanism triggers the detection task of each level as required, so that the system resource overhead is effectively reduced, and the overall detection efficiency is improved. By analyzing the abnormal propagation path in the electrical topology and combining the spatial position information of the equipment, the abnormal region boundary expression is generated, so that the conversion from point-level identification to chain-level analysis and region-level visualization is realized, the operation and maintenance personnel can quickly position and respond, and the interpretability of the abnormal result and the practical value of scheduling are improved.

The invention provides an optical module and a link optimization method and system. The method comprises the following steps that: the microcontroller issues a gain value, so that the continuous time linear equalizer performs equalization processing on an input voltage signal; the time processing module is used for sampling a voltage signal output by the continuous time linear equalizer to obtain sampling data; and the microcontroller determines the gain configuration of the continuous time linear equalizer based on the sampling data under different gain values. Compared with the prior art, the power consumption and the time delay of the module are equal to those of a traditional LPO, and meanwhile, the self-adaptive capability which is only achieved by a DSP scheme in the past is obtained. The application scene and deployment flexibility of the LPO technology are expanded; and meanwhile, the link performance can be always maintained near the optimal point, so that the risk that the performance is continuously deteriorated until error codes occur is fundamentally avoided, and intelligent maintenance of the link state is realized.

The invention discloses a complex flexible automatic material carrying system which is composed of a dispatching subsystem, a carrying subsystem, a transfer subsystem, a truss connection subsystem and a positioning and clamping subsystem. A dispatching subsystem in the complex flexible automatic material carrying system serves as a brain, stable data communication is established with all subsystems and automatic machining equipment, the working state of the equipment is collected, and demand information and machining progress of parts to be machined can be obtained in real time; the carrying subsystem, the transfer subsystem and the truss connection subsystem can be commanded to work cooperatively according to the machining progress, and bidirectional automatic transfer of metal parts in a production preparation area and automatic machining equipment is achieved. The problem that in the machining process, experience and skills of operators are highly relied on is solved, and automatic measurement, automatic compensation and unmanned high-quality and high-efficiency machining in the part machining process are achieved.

A method for carrying a plurality of substrates to be continuously processed from a carrying section to a processing section in a processing system provided with at least one processing section for performing a desired process on a substrate and the carrying section for carrying the substrate to the processing section, in which method an adjustment value for arbitrarily changing a processing time for each of the plurality of substrates is assigned to the substrate in advance, the method comprising the steps of: acquiring the adjustment value assigned to a first substrate for this time processing; acquiring a reference adjustment value assigned to a reference substrate processed before the first substrate; acquiring an actual processing time, i.e., an actual time, for processing the reference substrate; calculating a predicted processing time for the first substrate by reflecting a difference between the adjustment value assigned to the first substrate and the reference adjustment value into the actual time; and adjusting a carrying timing of a second substrate processed after the first substrate based on the calculated predicted processing time.

According to the real-time multi-level tile map synthesis method provided by the invention, five-level processing pipelines are not simply parallel, and independent segmentation factor level design, lock-free cross-level data channels and three-level synchronous barrier architecture are carried out; a dynamic memory release mechanism driven by a global tile counting dictionary and a boundary tile divide-conquer synthesis algorithm are used. Through global tile counting dictionary monitoring, the memory is released once the tiles are completed, and accumulation and occupation of the memory are avoided; a boundary adaptive threshold value avoids memory retention caused by the fact that boundary tiles wait to be filled up; five layers of independent treatment pipelines are designed, and the actually measured treatment speed is increased by 4-5 times compared with that of a single-stage serial system; synchronous barriers are arranged in the three stages of initialization, real-time processing and termination, and data consistency is ensured; 1: 1 to 1: 64 times of dynamic scaling is supported through five-level segmentation factors, original features of the image are kept while scaling is carried out by using a nearest neighbor interpolation algorithm, and coordinate range inspection is carried out.

The invention discloses a high-concurrency work order system distribution mode automatic switching method, system and device and a medium, through intelligent configuration routing, a real-time processing mode or an asynchronous queue processing mode is dynamically selected for work order APIs with different characteristics according to a preset strategy, and therefore the low delay requirement and the system stability are both considered; moreover, by adopting an independent mode switching monitoring module, when the message queue is abnormal, second-level sensing can be realized, and the mode is automatically and seamlessly switched to a real-time processing degradation mode, so that when the message queue is unavailable, the core work order service can still run continuously, the robustness of the system is improved, and the system performance is improved. The continuity of the core service of the system under the component fault is ensured, and the real high availability is realized.

The application relates to the field of mechanical processing, in particular to a workpiece parameter monitoring system and method for cycloidal rotation division processing, which comprises the following steps: collecting temperature data of a cutter and load data of a driving part in a cycloidal rotation division processing process in real time; collecting historical processing data when workpiece errors exist under various processing parameters; extracting the temperature data of the cutter, the load data of the driving part and corresponding workpiece errors from the historical processing data; establishing a relationship function of the processing parameters, error temperature change intervals, error load change intervals and the workpiece errors; obtaining real-time processing parameters and verifying real-time temperature change intervals and real-time load change intervals based on the relationship function; and judging the workpiece errors. According to the application, the temperature and load data of the cutter are collected based on the cycloidal rotation division processing principle, and the workpiece parameter errors can be monitored in real time.

Systems and methods may include a processor to receive time-series presence data from at least one presence sensing device associated with an area, including instances of presence detected in the area, and times associated with the instances. The processor may determine an occupancy metric in each time slot of the area based on the instances of presence and the times. The processor may generate an occupancy schedule for the area based on: the occupancy metric in each time slot and a history of occupancy metrics. The occupancy schedule represents a prediction of a level of occupancy of the area during each subsequent time slot in subsequent weeks. The processor determines a comfort system actuator in the area and communicates the occupancy schedule to the comfort system actuator to cause the comfort system actuator to actuate based on the prediction of the level of occupancy of the area.

The invention provides a marshalling station resource application plan compiling method and device, equipment, a medium and a product, and the method comprises the steps: determining a plurality of processing modules needing to be called according to the type of a to-be-processed train, and adding the to-be-processed train into a to-be-processed queue of the first processing module; each processing module determines resources occupied by the train or the train set, the start occupation time and the end occupation time; when the train or the train set starts to occupy resources, the train or the train set is moved from the to-be-processed queue to the in-processing set, and the current resource occupation state, the occupation starting time and the previous resource occupation ending time are updated. And after the processing is completed, judging whether the train or the train group has a next processing module, if so, adding the next module to-be-processed queue, and otherwise, ending the processing. According to the method, resource allocation is optimized through queue management, occupied resources, occupied starting time and occupied ending time of each train are determined, marshalling station resource occupation conflicts in a plan are effectively avoided, and the utilization rate of marshalling station resources is increased.

The invention discloses a vehicle trajectory prediction method based on an improved HTM, and the method comprises the steps: compressing an original code into a short code through multi-dimensional feature fusion, carrying out the feature extraction of a space pool through an SPLSN (micro-column self-recommendation space pool module), and achieving the time pool time sequence modeling through a TPLLAA (position sensing time pool module). And multi-path input expansion is realized by introducing a sequence caching mechanism. According to the multi-dimensional compression coding method, the sparse distribution representation is generated by fusing grid, time period and category coding, so that the data redundancy can be reduced, and the calculation complexity can be reduced; graded activation and synaptic protection can be realized by combining a micro-column self-thinning space pool module with a bearing degree and an overlapping value, and the efficiency and the accuracy are improved; tPLLA is utilized, position information is introduced to optimize cell selection, and an active set is reduced to inhibit historical interference; and by utilizing an SSCM (sequence state cache) mechanism, multi-track parallel processing and quick context retrieval can be supported, and the real-time processing capability is improved.

The invention discloses an anomaly detection method and device applied to an oil gas and pipe network site, and relates to the field of oil gas and pipe networks. The method comprises the following steps: acquiring operation data in an oil gas and pipe network site; under the condition that the operation data meets the preset abnormal condition, the operation data are sent to an operation and maintenance center in real time; under the condition that the operation data does not meet the preset abnormal condition, storing the operation data to a data queue; under the condition that the data queue meets the preset idle condition, the operation data in the data queue is sent to the operation and maintenance center, so that frequent data sending to the operation and maintenance center is avoided, the network transmission burden and the instant processing pressure of the operation and maintenance center are reduced, the operation and maintenance center can centralize resources to instantly process key data, and the user experience is improved. The processing delay caused by data redundancy is reduced, and the instantaneity of anomaly detection is improved.

The application belongs to the technical field of digital twinning, and particularly discloses a rough and fine grinding integrated machine virtual-real collaborative control method based on digital twinning, which comprises the following steps: S1, collecting real-time processing parameters of a rough grinding unit and a fine grinding unit, and constructing a grinding digital twinning body synchronized with an actual processing process; S2, constructing a long short-term memory network model to predict the state evolution trend of each unit in a future processing process; S3, performing process parameter optimization of a rough grinding to fine grinding whole process in the grinding digital twinning body; S4, searching for an optimal process parameter combination in the grinding digital twinning body environment by using a snake swarm optimization algorithm; S5, driving actual rough grinding and fine grinding process execution; and S6, if a processing abnormality or deviation is detected, automatically triggering re-optimization and correction control. The application combines a snake swarm optimization algorithm, a long short-term memory network model and an industrial field bus control technology, and realizes virtual-real collaborative grinding control of a full-automatic rough and fine grinding integrated machine based on digital twinning.

A sheet detecting device detects each sheet fed by a feeding process at a detection position on a downstream side of a feeding rotating body in a sheet feeding direction. A timing device measures an elapsed time from a time when the feeding process for each sheet is started to a time when each sheet is detected by the sheet detecting device. A processing device derives a target feeding time required for a target sheet to be fed from an initial reference position to the detection position based on a target measurement time measured by the timing device for the target sheet fed by the feeding process. The processing device counts a delay count that is a number of times the target feeding time exceeds a delay determination time. The processing device determines a deterioration state of a feeding mechanism based on the delay count.

The invention discloses an intelligent sensor signal processing method based on artificial intelligence. The method comprises the following steps: acquiring an original data stream related to the operation state of production equipment from at least one sensor; executing real-time processing based on a first preset parameter group on the original data stream, and outputting an operation instruction for controlling the production equipment; performing data analysis on the original data stream and / or the generated intermediate data based on a time sequence to obtain interference factors influencing data quality; dynamically adjusting the first preset parameter group through an adjustment strategy according to the interference factor; optimizing the operation instruction according to the output of the adjustment strategy; in this way, the key processing parameter set is seamlessly updated through parameter reconstruction. Therefore, the automatic control system can adaptively cope with various abnormal conditions and changes, and the automation degree of the automatic control system is improved.

The invention discloses a multi-core real-time processing method, device and equipment and a storage medium, relates to the technical field of multi-core processors, and is applied to a multi-core real-time processing system.The method comprises the steps that an interrupt event is obtained; and distributing the interrupt event to a corresponding real-time processor through a multi-core cluster interrupt distribution unit and / or an internal interrupt source shared by a multi-core cluster, so that the corresponding real-time processor processes the interrupt event, according to the method and the device, the interrupt event can be allocated to the corresponding real-time processor through the multi-core cluster interrupt allocation unit and / or the internal interrupt source shared by the multi-core cluster, so that the corresponding real-time processor processes the interrupt event, and the real-time interrupt event and the multi-core interrupt event can be processed at the same time; the real-time performance can be improved, the resource distribution is optimized, and the interrupt event management operation is simplified.

The application discloses a kind of dynamic adjustment method and terminal of task memory, monitor and calculate the average task processing rate of each subtask of pending task under historical condition;When the real-time execution data of pending task is obtained, if pending task has not been set fast task label, whether the current pending task exceeds the average task processing rate of preset proportion subtask, if yes, set fast task label for pending task;If pending task has been set fast task label, then increase the memory threshold of pending task according to preset proportion. In this way, the real-time processing rate of a task can be compared with the historical average processing rate to identify tasks that can improve processing speed by expanding memory, and dynamically configure appropriate memory threshold for the task. The dynamic adjustment of task memory can improve task processing speed and efficiency.

The embodiment of the invention provides a work order processing method and device based on a large model, equipment, a medium and a product. The method comprises the following steps: converting call voice corresponding to a to-be-processed work order into a to-be-processed text; a cue word is constructed, the cue word is used for indicating the large model to execute work order processing on the to-be-processed text, and work order processing comprises at least one of element extraction, work order classification and work order summarization; and calling the large model, inputting the cue word into the large model, so that the large model performs corresponding processing on the to-be-processed text based on the cue word to obtain a work order processing result, and through combination of voice-to-text processing and large model processing, the processing period of a single work order is greatly shortened, the processing efficiency of the work order is improved, and nearly real-time processing capability is realized. Therefore, the throughput of the whole customer service or operation and maintenance system is remarkably improved, the large model is guided through the elaborately designed cue words, standardization and normalization of the processing process can be ensured, and the accuracy of work order processing is improved.

This invention relates to the field of coating production line control technology, and particularly to a time-series linkage control method and system for a coating production line. The method includes the following steps: calculating the congestion level of each workstation; identifying the workstation with the highest congestion level as the bottleneck workstation; calculating the upstream supply segment disturbance index of the bottleneck workstation; obtaining a target time horizon based on the upstream supply segment disturbance index and a preset time horizon; obtaining a buffer target value based on the target time horizon and the real-time processing rate of the bottleneck workstation, wherein the buffer target value is positively correlated with the target time horizon; and updating the buffer capacity in the DBR scheduling algorithm using the buffer target value to control the material input at the beginning of the production line, effectively improving the efficiency of the time-series linkage control of the coating production line.

The invention provides a time processing method, a vehicle and a storage medium, and relates to the technical field of data processing. The method can comprise the steps of obtaining target data; wherein the target data comprises at least one of inertial measurement data and navigation positioning data; obtaining a target duration corresponding to the target data; wherein the target duration comprises at least one of the following items: resolving duration and transmission duration; based on the current time of the control module and the target duration, adding a target timestamp to the target data; wherein the target timestamp is used for representing the generation time of the target data. According to the technical scheme provided by the invention, the problem of how to carry out accurate time service on inertial measurement data and navigation positioning data for a domain controller integrated with an inertial measurement module and a navigation positioning module in related technologies can be solved.

The invention is suitable for the technical field of copper alloy wire production, and particularly relates to a real-time data processing method, device and equipment in the copper alloy wire production process, and the method comprises the following steps: firstly, obtaining process parameters, design parameters and operation parameters of a copper alloy wire in process nodes of wire drawing equipment; secondly, based on the operation parameters of the process nodes and the positions of the process nodes in the process flow, obtaining an operation parameter vector set; generating a plurality of deviation diameter data based on the actually measured diameter and the preset diameter of the mold; based on the deviation diameter data and the operation parameter vector set, fine tuning operation data are obtained; and the input parameters of the wire drawing equipment are adjusted in real time. And the operation parameters of each process node are regulated and controlled in real time, so that process errors are reduced, the tolerance of the product is finally reduced, and the superior product rate is improved.

The invention discloses a polarization code belief propagation decoding method for correcting insertion and deletion errors, and relates to the field of digital communication error control coding. The method comprises the following steps: mixing information bits with the length of 1 and all-zero frozen bits with the length of 1 according to position indexes of preset information bits and fixed bits to obtain a bit sequence; encoding the bit sequence to obtain a sending sequence with the length of 1; the sending sequence is transmitted through an IDS channel to obtain a receiving sequence with the length of the IDS channel; and carrying out insertion and deletion error correction processing on the receiving sequence through a BP decoder based on a weighted Lelwstein distance, and outputting an information sequence estimated value. According to the method, the drift distance is introduced, and the weighted Levinstein distance is adopted as probability measurement, so that the problem that insertion and deletion errors cannot be corrected by a traditional BP decoding algorithm is solved. The inherent problem of an SC framework is also avoided, and the error correction capability is improved; and through parallel operation, the decoding time delay is reduced, and the unit time processing capacity is improved.

The invention discloses a loan real-time processing method, device and equipment, a medium and a product, relates to the technical field of data processing, and can be used in the field of financial science and technology. The method comprises the steps of obtaining a target configuration parameter in response to a deduction configuration operation of a website; wherein the target configuration parameters comprise an effective date, a loan product code and an overdue duration; synchronizing the target configuration parameter to a real-time deduction parameter table; according to the real-time deduction parameter table, obtaining a full quantity list and a monitoring list from a loan business system; according to the monitoring list, obtaining account dynamic account messages from a monitoring message queue, and screening the account dynamic account messages to obtain a list of messages to be deducted; performing analysis screening and processing state marking on the to-be-deducted message list to obtain a message processing result; and deducting money according to the message processing result to obtain a money deducting result. According to the technical scheme, the real-time performance of loan deduction can be improved.

The invention discloses a Manchester code efficient decoding method for an electromagnetic flaw detection logger, which comprises the following steps: step 1, Manchester code single-ended signal acquisition and underground pretreatment, step 2, single-ended signal conditioning, step 3, double-edge interruption triggering and composite synchronous head identification, step 4, pulse width timing recording, and step 5, pulse width decoding. Step 6, decoding based on pulse width; step 6, verifying and outputting decoded data; by adopting a double-edge triggering interruption mode, interruption can be triggered at the rising edge and the falling edge of a Manchester code single-end signal, and compared with traditional single-edge triggering interruption, the interruption waiting time is shortened. Meanwhile, the pulse width is recorded in real time through the timer module, decoding is directly carried out based on the pulse width, complex clock synchronization and signal sampling processing processes are not needed, the decoding process is greatly simplified, the decoding efficiency is effectively improved, and the requirement of electromagnetic flaw detection logging operation for data real-time processing can be met.

The invention provides an ultra-thin box bottom mirror image milling method based on an overcut prediction model, which comprises the following steps: carrying out primary rough machining on a box bottom according to a set first machining layer, and carrying out scanning reverse reconstruction on the inner shape surface of the roughly machined box bottom; the method comprises the following steps: acquiring machining data during rough machining under different partitions, performing data preprocessing on the machining data, inputting the preprocessed machining data into a pre-trained overcut prediction model to predict and output machining data at the next moment, and performing evaluation and judgment according to a preset evaluation index; if the judgment requirement is met, secondary finish machining is carried out on the box bottom according to the set second machining layer; and iterating the number of processing layers until the box body is milled to the target thickness. According to the method, the overcutting condition of the next time sequence can be predicted and alarmed in the machining process, and the phenomenon of mirror image milling overcutting of the ultra-thin box bottom is reduced.

The invention provides a self-adaptive control system and method for a machining path of an electric spark cutting machine tool, and the method comprises the steps: obtaining initial data of the electric spark cutting machine tool and operation state data in a real-time machining process, and carrying out the initial correction of a preset theoretical machining path based on initial offset data in the initial data, obtaining an initial processing path; on the basis of the operation state data and state data in the initial machining path, real-time dynamic change data is determined, matching is conducted on the basis of the real-time dynamic change data in combination with a preset error type library, and a current error type and a corresponding error magnitude are obtained; and performing fuzzy reasoning based on the current error type and the error magnitude to obtain a target path compensation parameter, and adjusting a corresponding parameter of the initial processing path based on the path compensation parameter to obtain a target processing path. The technical problem that the machining precision is insufficient due to the fact that the machining path is only based on theoretical parameters and does not consider inherent errors and dynamic accumulative errors is effectively solved.

The application provides a kind of thin-walled cabin inner cavity self-compensation processing method and system, comprising: (1) preparing metal blank with uniform physical properties everywhere; (2) reasonable installation and positioning of thin-walled cabin on equipment; (3) processing zero point setting and tool length compensation; (4) pre-optimization of tool position path; (5) automatic induction of wall thickness of cooling liquid containing carbon nanotubes; (6) real-time ball tool angle self-induction of thin-walled metal wall thickness of cooling liquid containing carbon nanotubes; (7) error calculation of product induction wall thickness and theoretical wall thickness; (8) automatic compensation and correction of pre-planned tool position data; (9) thin-walled inner cavity traversal processing inner surface. The application can realize real-time and effective processing of each point of thin-walled inner cavity, and provides technical support for obtaining qualified thin-walled cabin through one-time processing.

The invention relates to the field of computing, and particularly provides a time processing method and computing device.The time processing method comprises the steps that an atomic variable is set, and the initial value of the atomic variable is 0; starting to cyclically run the timer at the starting moment of the system; when it is detected that the timer runs once, adding 1 to the value of the atomic variable; determining at least one target object of which the running time needs to be monitored; the variable quantity of the atom variable in the target object running period is collected, and the variable quantity corresponding to the at least one target object is obtained; and determining running time corresponding to the at least one target object according to the variable quantity corresponding to the at least one target object in combination with the timing duration of the timer.

The invention relates to the technical field of industrial control, and discloses a control system of a screw processing machine table based on terminal cloud collaboration. Comprising a parameter acquisition module which is used for splicing a control period and acquiring real-time processing parameters; the model identification module is used for identifying standard processing parameters through a deep learning model; the control analysis module is used for drawing a stable curve graph and judging whether a cooperative control mode is executed or not; the cooperative control module is used for performing cooperative control operation on the screw processing machine table; according to the invention, by splicing the control period with the period units distributed at intervals, the evaluation process of thread rolling processing of the screw processing machine can be divided at intervals and circularly, and reasonable redundant buffer time is reserved for data transmission and interaction between the mechanical end and the cloud end; the interaction of data between the mechanical end and the cloud end is improved, the phenomena of data discretization and confusion are avoided, and safety guarantee is provided for end-cloud cooperative control.

The application discloses a covariance matrix inversion method and device based on beat sample updating, and the method comprises the following steps: initializing the inverse covariance matrix as a weighted unit matrix and an initial beat time k=0; at the next beat time k=k+1, calculating a projection vector based on the array signal vector received at the current beat and the inverse covariance matrix at the last time, updating the inverse covariance matrix through matrix multiplication by using the projection vector and the inverse covariance matrix at the last time, and repeating the operation until the specified sample beat number of the covariance matrix estimation is processed; and correcting the output inverse covariance matrix at the final beat time to obtain the final inverse covariance matrix of the specified beat number. The application does not need to perform matrix inversion operation, has high calculation stability, reduces the bit width limitation of FPGA implementation, can adopt a streaming data processing mechanism, does not need the full beat data buffer required by the traditional block processing method, and is convenient for FPGA real-time processing of the sample input through the sample-by-sample calculation mechanism.