16 results about "Full cycle" patented technology

The invention discloses a full-period operation and maintenance guarantee method and system for a direct current system, and the method comprises the steps: collecting system state data in real time through a multi-source sensor network, and carrying out the synchronization and normalization processing, and then generating a standardized time series data set; utilizing the pre-trained fault prediction neural network model to carry out probabilistic evaluation on future fault risks; when the risk exceeds a threshold value, an isolation decision engine is triggered to generate an optimal isolation instruction according to system topology and a real-time state, and a solid-state switch and a mechanical mechanism in the intelligent execution unit cooperate to complete millisecond-level rapid isolation; after isolation, a closed-loop feedback module collects steady-state parameters and compares the steady-state parameters with expected values, and online self-adaptively optimizes a prediction model and decision parameters; during normal operation of the system, the preventive maintenance module automatically generates a digital list based on the equipment health score. According to the method, full-period intelligent operation and maintenance of the direct current system from passive response to active prediction, automatic disposal and continuous optimization are realized, and the reliability and the safety of the system are remarkably improved.

This invention discloses an intelligent data synchronization system and method for voltage monitoring instruments, relating to the field of intelligent data synchronization technology. The method includes the following steps: acquiring the original sampling sequence; constructing a preset step-size sliding window; generating filter coefficients based on the statistical characteristics of sampling points within each window and performing weighted calculations to obtain the filtered output value at the window center point, forming a preprocessed sequence; detecting the sign change of adjacent sampling points in the sequence; marking valid zero-crossing points; extracting an integer number of complete cycle sampling data as a cycle data block; calculating the theoretical number of sampling points based on the rated frequency and sampling rate and setting a tolerance range; comparing the actual number of points to preliminarily determine the synchronization effectiveness; calculating the actual frequency from the preliminarily valid data block; verifying the rated frequency deviation to confirm synchronization; simultaneously calculating its effective value; comparing it with a preset voltage threshold to determine whether the data is valid. This invention achieves intelligent synchronization of sampling data.

A joint sensing method for an orthogonal frequency domain multiplexing (OFDM) communication system includes transmitting a plurality of reference signal (RS) resource elements (RE) from a set of staggering comb patterns to a sensing terminal; and determining the plurality of RS resource elements to perform either a full cycle of staggering, a partial cycle of staggering, or a combination of the full cycle and the partial cycle of staggering.

The application discloses a kind of management systems and implementation methods of full life cycle operation and maintenance, it is related to full life cycle technical field.Constructs full cycle initial dynamic operation and maintenance hypergraph;Generation represents the dynamic hypergraph time sequence evolution sequence of system topology evolution along with life cycle;Generation full cycle space-time fusion operation and maintenance representation;Output the multidimensional abnormal risk prediction distribution atlas of the future operation trend of representation system;Based on the full life cycle management library, the corresponding resource degradation, isolation or expansion strategy is matched, and the adaptive operation and maintenance scheduling execution instruction set for directly intervening target system is generated.The application makes that when processing the full cycle long sequence data of mass node scale, the time axis resolution of operation and maintenance characteristics is significantly improved, especially in the correlation tracing of long-range latent fault.

The application discloses a kind of based on nesting block genetic's super large scale network operation method and system, the method includes: obtaining asset network data, constructs infrastructure operation planning physical mathematical model;With the parent individual representing different complete cycle planning scheme, constraint-aware annual plan exchange crossover is carried out;Asset block and nesting;Block maintenance strategy exchange and hierarchical variation between blocks;Block level linear programming guided adaptive optimization.The system includes: including physical modeling module, annual plan exchange crossover module, block nesting module, sub-block processing module and adaptive optimization module.Through using the application, the calculation bottleneck under the scale of huge assets can be solved, and an efficient and scalable decision support scheme is provided for the fine management of complex infrastructure systems such as roads and bridges.The application can be widely applied in the technical field of infrastructure management.

The invention discloses a building full life cycle monitoring management system and method, and relates to the technical field of engineering management, and the method comprises the steps: constructing a digital thread topology, building an object passport and an object identifier, and forming a digital thread topology table; when a business document is formed in an engineering business link, uniformly packaging a thread event shell and associating the digital thread topology table to form a thread event flow, and updating object passport information at the same time; and according to the thread event flow, maintaining a full-cycle state record table compiled according to the object identifier, and executing permission check and precondition check to generate an instruction list and a gap exception list. According to the method, the full-cycle state record table is generated through the thread event flow, the ready item field and the event track field are compared and verified, the instruction list or the gap exception list is formed in combination with permission verification and precondition verification, and the certainty and interpretability of process propulsion are achieved.

The invention discloses a full-period operation and maintenance guarantee method and system for a direct-current system, and relates to the technical field of operation and maintenance of power systems. The method comprises the following steps: S1, acquiring a multi-dimensional operation state data stream through multiple types of sensors; s2, generating a standardized time sequence data set through synchronous alignment and normalization processing; s3, calling a pre-trained fault prediction neural network model to evaluate a future fault risk; s4, when the fault probability exceeds a threshold value, a fault isolation decision engine is triggered; s5, the intelligent execution unit executes millisecond-level isolation operation; s6, the closed-loop feedback evaluation module calculates parameter deviation; s7, on-line fine adjustment of model and algorithm parameters is carried out; and S8, periodically generating a preventive maintenance work order. The system correspondingly comprises a multi-source state sensing layer, a data preprocessing layer and other functional layers. According to the method, full-period intelligent closed-loop operation and maintenance of'prediction-isolation-feedback-optimization 'are realized, the traditional manual dependence bottleneck is broken through, the reliability and safety of a direct current system are remarkably improved, and the method is suitable for the fields of electric power, data centers and the like.

The invention discloses a super-large scale network operation and maintenance method and system based on nested block heredity, and the method comprises the steps: obtaining asset network data, and constructing an infrastructure operation and maintenance planning physical mathematical model; performing annual plan exchange crossover of constraint perception on parent individuals representing different complete cycle planning schemes; blocking and nesting assets; maintaining strategy exchange and hierarchy variation among the blocks; and adaptive optimization guided by block-level linear programming. The system comprises a physical modeling module, an annual plan exchange cross module, a block nesting module, a sub-block processing module and a self-adaptive optimization module. By using the method, the calculation bottleneck under a huge asset scale can be solved, and an efficient and extensible decision support scheme is provided for fine management of complex infrastructure systems such as roads, bridges and the like. The method can be widely applied to the technical field of infrastructure management.

The application discloses an instruction processing system and method for a quantum computer and the quantum computer, and is used for outputting waveform data of a pulse signal for manipulating a spin quantum bit. The instruction processing system comprises a state starting module configured to send a data output request according to waveform parameter instructions sent by an upper computer; wherein the waveform parameter instructions comprise waveform coefficients of a pulse signal waveform; and a data generation module configured to generate waveform data of a complete cycle of the pulse signal waveform and output the waveform data in response to the data output request and according to the waveform coefficients. The application generates the waveform data of the pulse signal by using the waveform coefficients in the lower computer, and can solve the problems that the waveform data of the pulse signal is large, the waveform data is sent to the lower computer to occupy the memory, and the slow transmission affects the computing efficiency of the quantum computing, and can greatly improve the computing efficiency of the quantum computing.

The application discloses a kind of FPGA implementation TDLAS-WMS gas signal enhancement method based on periodic average algorithm, belong to gas detection technical field.For trace gas detection, due to the target gas concentration is extremely low, the second harmonic signal obtained by demodulation is easy to be submerged by random noise, leading to signal identification difficulty, affect the accuracy and stability of detection system, the application provides a kind of signal enhancement method based on periodic average algorithm, by corresponding sampling point in multiple cycles is averaged, effectively suppress random noise, significantly improve the signal-to-noise ratio of weak signal, especially suitable for FPGA implementation TDLAS-WMS trace gas detection system.The method of the application utilizes the multiple relationship of read-write clock frequency, after BRAM stores complete cycle data, quickly completes cycle alignment, average operation and real-time output, improves system signal quality and processing efficiency.

The application relates to the technical field of data processing, and particularly discloses an online time sequence reserved rain flow counting method, which comprises the following steps: S1, acquiring an original overload sequence; S2, reading four continuous data points in the original overload sequence into a new data set, judging whether a full cycle exists in the new data set, if the full cycle exists, deleting the full cycle from the new data set and recording the full cycle into a cycle result list, and then supplementing two new data points from the original overload sequence into the new data set; if the full cycle does not exist, supplementing one new data point from the original overload sequence into the end of the new data set; S3, taking the last four data points in the new data set as the input of the next round, and repeatedly executing S2 until all data points in the original overload sequence are read and no full cycle exists in the new data set; and S4, arranging all full cycles in the cycle result list of the latest round in time sequence. The application can more efficiently and completely identify and extract the full cycle.

The embodiment of the invention provides a topology management method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of software and information security. The method comprises the steps that in response to starting of a topological graph management assembly, a topology editing page is generated, the topology editing page comprises a plurality of node assemblies, in response to editing of the node assemblies, topology nodes are generated, connecting edges corresponding to the topology nodes are determined, the topology nodes are marked with corresponding risk information, and the risk information is generated based on the topology nodes and the connecting edges. And generating a target topological graph, displaying the target topological graph and risk information corresponding to the topological nodes, traversing all the topological nodes in response to a saving instruction, converting a traversing result and original graph data of the target topological graph into data in a predetermined format, and uploading the data to a server. According to the embodiment of the invention, the topology drawing efficiency is improved by setting the topology editing page, the topology and risk information is visually displayed and reliably stored, the complete cycle management of the topology information is realized, and the efficiency of topology management is improved.

The invention discloses a process memory allocation method and electronic equipment, is applied to the technical field of communication, and aims to solve the problem of poor reliability caused by the fact that a key process cannot use a mirror image memory in a full cycle in the related technology. Determining a key process according to the entity file name of the loaded process; a mirror image memory identifier is set and used for the key process; and in the process of allocating the memory by the process, if the to-be-allocated process has the identifier of using the mirror image memory, allocating the mirror image memory for the to-be-allocated process. According to the method and the device, key process identification and mirror image memory allocation of the key process can be realized in the process loading process, and the mirror image memory can be used when the process starts to run, so that the key process is ensured to use the mirror image memory in a full cycle, and the reliability of the key process is improved.

The invention discloses a CAN signal data dynamic backtracking and hierarchical drawing processing system based on LOD and LTTB, which comprises a message acquisition unit, a message analysis unit, a message storage unit, a signal processing unit and a display rendering unit, and also discloses a processing method of the CAN signal data dynamic backtracking and hierarchical drawing processing system. Comprising the following steps: starting a system and starting to receive message data, constructing 0-level data, calculating the level of LOD, and drawing an image. Full data life cycle traceability can be realized, and a complete data basis is provided for deep fault diagnosis; repeated calculation delay is eliminated; maintaining visual features of the signals; full-cycle data backtracking is achieved, limitation of a traditional tool is broken through, dynamic signal adding and complete historical data loading in the analysis stage are supported, fault diagnosis flexibility and analysis efficiency are improved, and test repetition caused by signal missing is avoided; and super-large-scale data processing is supported, memory-level access performance is realized with hard disk-level storage cost, and a common computer is supported to process 10 billion-level data points.

The invention provides a teaching virtual simulation full-period management system and method, and belongs to the technical field of simulation management, and the method comprises the steps: obtaining a user virtual simulation operation log, and extracting a behavior pattern matrix which comprises a space-time coordinate sequence of a task completion path, a clustering tag sequence of an error type, and a timestamp sequence of response time delay; the cognitive demand feature vector is an optimal path length, an actual path length, a key error number, a total operand and a Shannon entropy of a response time delay sequence, and the three components respectively correspond to an efficiency factor, a precision factor and attention stability; a simulation scene is dynamically generated by extracting cognitive feature vectors (efficiency, precision and attention stability) of a user operation log and combining a piezerger cognitive stage theory, so that scene complexity is accurately matched with user cognitive ability, and learning motivation is maintained while learning efficiency is improved.

Disclosed is an AI / ML verification method performed by a first communication node including a communication unit and a processor. The disclosed method comprises the steps of: transmitting, to a second communication node, life cycle management (LCM) configuration information for AI / ML full cycle management; in the case of an AI / ML verification environment, applying an LCM lock mode by locking a portion of LCM functions for to-be-verified AI / ML; and verifying the to-be-verified AI / ML in the LCM lock mode.