3439 results about "Current time" patented technology

The invention discloses an electric connector fault prediction method, and the method comprises the steps: synchronously obtaining multiple types of time series data of a contact area of a target electric connector in a preset time window based on a preset data collection device, and the time series data comprise temperature spatial and temporal distribution time series data, contact resistance transient time series data and a surface image sequence; performing feature analysis on the multi-source time sequence data by using a preset time sequence coupling sign extraction mechanism to obtain a multi-source phase change feature vector of the target electric connector in the current time window; inputting the multi-source phase change feature vector into a pre-trained electric connector health state prediction model, and outputting a prediction result of the health state of the target connector at the current moment, including a health state index; and performing differential early warning based on the predicted health state index of the target connector. Therefore, early and quantitative accurate prediction of the state of the electric connector is realized.

The present application relates to a waveform file conversion method and apparatus for chip testing, and a computer readable storage medium. The method comprises: performing content analysis on a waveform file to be converted, to acquire period information, pin information, and state information of pins in each period of said waveform file; generating a PAT-format digital signal waveform file; and on the basis of a mapping relationship between pins and ATE channels, converting the PAT-format digital signal waveform file into a binary vector file for ATE testing. A waveform file in any format is converted into a PAT-format digital signal waveform file which uses periods as rows and pins as columns, so that each row vector not only contains current time information but also contains a logical state of each pin; in addition, to facilitate understanding, the PAT-format digital signal waveform file is further converted into a binary vector for ATE testing, so that efficient processing of waveform files in a plurality of different formats can be realized, thereby improving the universality of conversion.

The invention relates to a scraper chain tension dynamic optimization method based on real-time load feedback, and belongs to the technical field of scraper chain control. The method comprises the following steps: acquiring load data of a scraper chain in various operation states; carrying out standardization processing on the load data of various operation states and then extracting features to obtain load time sequence features; carrying out time attention mechanism processing on the load time sequence characteristics and the load data of the multiple operation states to obtain importance weights; a tension value is calculated according to the load data of each operation state and the importance weight of the load data; calculating a real-time working condition coefficient of the current time node, and dynamically adjusting a preset safety tension range to obtain a real-time safety tension range of the current time node; comparing the tension value with a real-time safe tension range, and generating a control instruction according to a comparison result; and executing the control instruction. The tension control method of the scraper chain is optimized, and the control precision of the tension of the scraper chain is improved.

The invention relates to the technical field of baby diapers, in particular to an intelligent baby diaper replacement reminding system integrated with hydrogen sulfide detection, which is used for determining a reference acquisition frequency of each time interval in a time period based on historical multi-dimensional monitoring data of a target user; then determining the necessity of hydrogen sulfide detection at the current acquisition moment based on the multi-dimensional monitoring data in the backtracking time window at the current acquisition moment, and then adjusting the reference acquisition frequency of the current time interval based on the necessity of hydrogen sulfide detection at the current acquisition moment to obtain a final acquisition frequency; acquiring multi-dimensional monitoring data based on the final acquisition frequency in the remaining time interval in the current time interval; and finally, based on the multi-dimensional monitoring data acquired in real time, generating a diaper replacement reminding signal.

The invention discloses a quick data traceability method and system based on multi-source log analysis, and relates to a data processing system or method specially suitable for administrative, commercial, financial, management, supervision or prediction.The method comprises the steps that firstly, the system responds to a service instruction to generate a transaction receipt containing a unique serial number and service attribute parameters; and establishing an association relationship between the two records and generating a to-be-confirmed record and a timestamp. And sending a service message containing the service attribute parameters to a receiving end. When an ownership right reverse search request of a receiving end is received, the system calculates an effective time interval based on current time and a preset time delay threshold value, and screens out a target to-be-confirmed record which is matched with a service attribute parameter and generates a timestamp in the interval. And finally, extracting the unique serial number from the target record, generating a confirmation receipt and sending the confirmation receipt to a receiving end system. The method is used for reducing the calculation overhead and false alarm rate of accurately positioning specific abnormal transactions in massive logs by a system, and improving the confidence and timeliness of an automatic traceability result.

A time series data prediction method and apparatus, and a storage medium are provided. The method includes: obtaining current time series data collected in a current time window that is adjacent to and precedes a prediction time window in a current time period, and obtaining a plurality of groups of historical time series data separately collected in a same target time window of a plurality of historical time periods; encoding the plurality of groups of historical time series data by using a plurality of encoders respectively, to obtain a plurality of historical time series features, where each historical time series feature represents relative location information and change trend information of each group of historical time series data in the target time window; and determining, predicted time series data corresponding to a target object in the prediction time window.

The invention discloses a multi-energy fusion system cooperative scheduling method and device in a port dynamic scene, and relates to the field of port energy system optimization scheduling, and the method comprises the steps: constructing a dynamic coupling relation model according to port data; according to the energy system power of each area at the current time point, a multi-objective optimization model is constructed, and objective functions of the multi-objective optimization model include operation cost minimization, total carbon emission minimization, energy storage equipment service life maximization, energy storage equipment power optimization and energy storage equipment power optimization. The constraint conditions of the multi-objective optimization model are power balance, energy storage charge state, electric hydrogen equipment capacity, berth distribution continuity and load demand priority; according to the multi-target optimization model and the port data of each region at the current time point, determining a target collaborative scheduling operation strategy of each region at the current time point, the target collaborative scheduling operation strategy comprising a multi-energy output distribution scheme, a load response instruction and an equipment operation parameter; and executing the target collaborative scheduling operation strategy of each region at the current time point.

The invention provides a resource scheduling processing method, device and system, a medium and a product. The method is applied to a cloud desktop management system, and comprises the following steps: according to obtained historical data of a cloud desktop instance running on each computing node in a to-be-scheduled cloud pool, calculating and obtaining a use probability of the cloud desktop instance on each computing node in a next time period of a current time period; for each computing node, according to the use probability of the computing node, predicting the increased or reduced resource overhead of the computing node in the next time period of the current time period, and according to the resource overhead, computing the resource load of the computing node in the next time period of the current time period; and determining a to-be-migrated computing node and a target computing node according to the resource load of each computing node and a pre-configured resource use threshold, obtaining a first target cloud desktop instance on the to-be-migrated computing node based on a pre-configured migration strategy, and migrating the first target cloud desktop instance to the target computing node. According to the method provided by the invention, the resource utilization rate of each computing node in the cloud pool is effectively improved, so that the normal use of the cloud desktop is ensured.

The invention provides a SaaS service security verification method and system under a zero-trust architecture. The method comprises the following steps: a client sends a login request to a server; the server side verifies the login request and returns a dynamic key, a coding rule table and a shuffling rule to the client side based on the login request and a current time window; the client generates a first password table corresponding to the dynamic key, hashing data of the service request according to a coding rule table, embedding the data into the first password table, performing shuffling processing of various different schemes on the first password table according to a shuffling rule to obtain a client request signature, and sending the service request and the client request signature to the server; and the server side obtains the server side request signature according to the same logic, verifies the client side request signature based on the server side request signature, and returns a response result corresponding to the service request to the client side after the verification is passed. According to the method, the end-to-end data integrity and security in the communication process of the client and the server can be remarkably improved.

The invention relates to the technical field of data processing, in particular to an electric energy meter fault detection method based on multi-sensor data fusion, and the method comprises the steps: judging whether an electric energy meter generates data drift abnormity or not in a current time period according to the data change trend of each monitoring index in the current time period; if the data drift abnormity of the electric energy meter occurs in the current time period, acquiring historical abnormal data of the data drift abnormity of each monitoring index, and acquiring the historical abnormal data influenced by the temperature under each monitoring index according to the own performance of each piece of historical abnormal data; according to the method, the relation curve of the temperature and the historical abnormal data influenced by the temperature under each monitoring index and the real-time data performance of each monitoring index in the current time period are integrated, the reason of the data drift abnormity of the electric energy meter in the current time period is determined, then fault detection is carried out on the electric energy meter, and the maintenance efficiency of the electric energy meter is improved.

An illumination device, system, and method are provided herein for emulating sunlight along a daytime or nighttime locus. Color temperature is determined using a first color temperature curve that includes data representative of a first color temperature as a function of a time of day. In response to a request to a change in brightness of one or more LED chains, a target color temperature output as a function of the current time of day is determined using a second color temperature curve based on the requested change in brightness. The second color temperature curve includes the target color temperature corresponding to the determined current time of day. The target color temperature output includes a lesser change in color temperature at solar noon than the change in color temperature at sunrise and sunset.

The invention relates to the technical field of Internet of Things, in particular to a high-speed rail environment monitoring method based on a multi-mode sensor, which comprises the following steps: acquiring measurement data of the multi-mode sensor for temperature, vibration and air pressure in real time, and constructing a state observation vector at the current moment; generating an initial parameter matrix of multi-modal dynamic Kalman filtering by using a generative adversarial network; correcting the state observation vector at the current moment based on improved multi-modal dynamic Kalman filtering to obtain a target state vector; and calculating an environment score according to the state value of each modal sensor in the target state vector at the current moment, evaluating the high-speed rail environment at the current moment, and taking corresponding response measures. According to the method, multi-modal sensor data can be integrated in a complex scene of high-speed running of the high-speed rail, quantified environment scores are output in real time, the running risk level is visually reflected, a reliable basis is provided for train dispatching, fault pre-judgment and emergency decision making, and the running safety and the operation and maintenance efficiency of the high-speed rail are remarkably improved.

The invention relates to the technical field of power distribution networks, in particular to a real-time monitoring method and system for multi-mode industrial Internet of Things data. The method comprises the following steps: acquiring the operation influence degree of each node on any other node at the current moment according to the fluctuation association degree of power indexes of each node and any other node in a monitoring time period in a virtual power plant and the similarity between the electric appliance connection tightness and the production state of the corresponding two nodes; according to the power index deviation degree and deviation time of each node in the virtual power plant relative to the state similar moment and the operation influence degree, obtaining the blocking resistance influence degree of each node at the current moment, and obtaining the response priority of each node in the virtual power plant at the current moment in combination with the power supply and consumption capacity; and determining the sequence of executing the virtual power plant dispatching instruction by each node. According to the method, line impedance influence and mutual influence between equipment are considered, so that the response priority is more reliable, and the operation toughness, safety and stability of the industrial park power distribution network are enhanced.

The invention relates to the technical field of data processing, and particularly provides a power supply health monitoring method, system and device and a storage medium, and the method comprises the steps: obtaining the real-time state data of a power supply; evaluating a health degree score of the battery according to the real-time state data; arranging the health degree scores generated in the current time window into a health degree score sequence; and utilizing a prediction model to predict the remaining service life of the battery according to the health degree. According to the method, the health degree score is constructed into the sequential sequence, and the prediction model is adopted for analysis, so that the prediction precision is improved, the working condition adaptability is enhanced, and the maintenance cost is optimized.

The invention provides a real-time scheduling method for a wireless network based on a large language model, the wireless network comprises a scheduling node and a plurality of user nodes, and the scheduling node is provided with a scheduling agent, a historical memory pool, an reflection agent and a suggestion buffer area. The method comprises the following steps executed in each time slot: step S1, the scheduling node acquires global information of a wireless network under the current time slot and calculates states of all data streams under the current time slot according to a preset calculation rule; and S2, the scheduling agent generates a scheduling decision of the current time slot according to a preset scheduling prompt word by using a large language model configured by the scheduling agent based on the states of all data streams under the current time slot and decision suggestions stored in the suggestion buffer area and by taking a maximized reward as a target. According to the technical scheme of the invention, by introducing the large language model, the problem of insufficient adaptability in a dynamic network environment in the prior art is solved.

The invention provides a robot control method, a robot and electronic equipment, and the method comprises the steps: planning an initial action sequence of the robot according to the environment information of the robot, correcting a part of action sequences in the initial action sequence according to a target action state of the robot at a current moment, and obtaining a target action sequence; and finally, the robot is controlled according to the target action sequence, the collection moment of the environment information is before the current moment, the initial action sequence comprises initial action states of the robot at multiple moments after the collection moment, and the partial action sequence is the action sequence located after the current moment in the initial action sequence. According to the method, the two steps of planning the action sequence and executing the action sequence can be executed at the same time, and the control efficiency is ensured.

The invention discloses a variable frequency phase shift control DAB type single-stage inverter reactive power control method, system and device and a medium, and belongs to the technical field of power electronic converter control, and the method comprises the steps: setting a reactive power instruction as zero; when the reactive power instruction changes, the active power instruction and the reactive power instruction at the current moment are decomposed into a direct-axis current reference value and a quadrature-axis current reference value respectively; comparing the reference value with an actual sampling value, calculating an error compensation amount by using a PI controller, and determining the amplitude and phase of the AC side current according to the compensation amount; according to the amplitude and the phase of the voltage and the current, a DAB frequency conversion phase shift control curve is calculated; and generating a PWM (Pulse Width Modulation) signal according to the frequency conversion phase shift control curve obtained by calculation, wherein the PWM signal is used for driving a DAB inverter to carry out power transmission. According to the invention, on the premise that no extra hardware circuit is introduced, dynamic adjustment and accurate control of the instantaneous reactive power of the AC output side can be realized.

The invention discloses an event flow assisted link self-adaption method and system oriented to the Internet of Vehicles, and belongs to the field of link self-adaption of the Internet of Vehicles, and the method comprises the steps: obtaining event flow data; inputting the event stream data into the trained depth estimation model to obtain the environment depth under the current time step; calculating the distance between the base station and the user equipment based on the event stream data and the environment depth under the current time step; and based on the distance between the base station and the user equipment, estimating a channel state and calculating a coding rate under the current time step so as to complete link self-adaption. According to the invention, dynamic sensing of the distance between the BS and the UE is realized by using the space-time correlation of the event stream, the time delay defect of a traditional feedback mechanism is overcome, the problem of inaccurate channel acquisition caused by traditional outdated feedback information is solved through visual information, the model calculation complexity is reduced, the coding rate performance is improved, and the spectrum efficiency is further improved.

The invention relates to the technical field of intelligent cables, in particular to an automatic sensing and monitoring intelligent cable and a control method, and the method comprises the steps: collecting the temperature data of a cable, processing the temperature data in time and space based on the temperature values of all positions and all times in the temperature data of the cable, and constructing a temperature space-time matrix of the cable; performing prediction according to the temperature space-time matrix of the cable to obtain a temperature space-time matrix containing a plurality of moments after the current moment, and taking the temperature space-time matrix as a predicted temperature space-time matrix of the current moment; determining a cooling regulation and control coefficient by using the temperature change and distribution condition in the predicted temperature space-time matrix at the current moment; and performing temperature regulation and control on the cable based on the cooling regulation and control coefficient. According to the invention, the conversion from passive cooling to active prevention is realized, faults and fire risks caused by overheating are effectively prevented, and the distribution and utilization efficiency of cooling resources is optimized at the same time.

The invention relates to an identity authentication and key negotiation method, gateway equipment and a terminal. The method is applied to gateway equipment and comprises the following steps: receiving an equipment certificate sent by a terminal and digital signature information based on first timestamp information; verifying the validity and legality of the device certificate, the validity of the first timestamp information and the validity of the digital signature information; when the verification is passed, randomly generating a session key, and setting a calculation initial value and current time; sending a first encryption result of the calculation initial value and the current time and a second encryption result of the session key to the terminal; and receiving a ciphertext which is sent by the terminal and encrypted by the session key, and determining that terminal identity authentication and key negotiation are successful under the condition that the result of decrypting the ciphertext is a target value which is the sum of the calculation initial value and the preset change value. By adopting the method, the security and reliability of communication between the terminal and the gateway equipment can be improved.

A computing system, a method and a computer program product for presenting a determined optimal duration of video recap of media content. The method includes detecting, via a processor of a computing system, selection of a current episode of media content for playback. In response to detecting selection of the current episode of the media content for playback, the method includes determining a first time difference between a current time and a previous viewing time of prior episodes. The method includes determining, based on the first time difference, a first time duration for a first video recap of the prior episodes of the media content. The method includes streaming the first time duration of the first video recap of the media content for presentation on an electronic device as a preview presented prior to streaming the current episode of the media content for presentation on the electronic device.

The invention discloses a power distribution network scheduling method and device based on approximate dynamic programming and load aggregation and electronic equipment, and belongs to the technical field of power system scheduling, and the method comprises the steps: obtaining parameters such as the line, cost, topology and load prediction of a power distribution network, and the operation constraint of distributed loads; constructing an aggregation feasible region of the adjustable load cluster; establishing an optimal dispatching model of the power distribution network by taking minimization of the operation cost as a target; reconstructing the power distribution network optimization scheduling model into a Markov decision model; and solving the Markov decision model period by period under the aggregation feasible region and the physical constraint of the power grid. And in each time period, constructing a post-decision state value function by using the current state and a preset fixed slope parameter, solving an optimal scheduling scheme of the current time period, updating the state of the next time period, generating an all-day optimal scheduling scheme, and executing the all-day optimal scheduling scheme. By implementing the method and the device, the technical problem of poor practical operability of dispatching of the power distribution network in the prior art can be solved.

The invention relates to an electromagnetic radiation interference resisting method and device of a touch key and computer equipment. The method comprises the following steps: acquiring touch sensing data input through a plurality of touch keys in a current time period; determining a touch sensing reference value corresponding to each touch key, and obtaining a touch sensing deviation value corresponding to each touch key based on the difference between the touch sensing reference value corresponding to each touch key and the touch sensing data; obtaining an interference intensity statistical result based on the touch sensing deviation value corresponding to each touch key, and if the interference intensity statistical result meets a strong electromagnetic radiation interference judgment condition, indicating that the touch key integrated equipment is in a strong electromagnetic radiation interference environment; and adjusting the key-out threshold value of each touch key in the strong electromagnetic radiation interference environment based on the strict key-out rule to obtain a key-out threshold value adjustment result of each touch key. By adopting the method, the anti-interference stability of the touch key integrated equipment in a complex electromagnetic environment can be improved.

The invention relates to the technical field of conveyor regulation and control, in particular to a pipe chain conveyor operation regulation and control method suitable for bulk material conveying. Obtaining time sequence data of motor working states and monitoring point running states of the pipe chain conveyor in a preset time period and a historical time period, and screening out historical reference time most matched with working conditions at all moments in the preset time period by comparing difference characteristics of the motor working states in the historical time period and the preset time period; carrying out multi-dimensional operation state characteristic comparison on the material blocking probability and each moment in a preset time period, dynamically calculating the material blocking probability, and screening material blocking moments; the material blocking probability difference of all the monitoring points at the material blocking moment and the time relation of the material blocking moment are analyzed, an abnormal transmission chain is constructed, and a material blocking propagation path is revealed; on the basis, feature vectors are constructed, misjudgment is reduced in combination with a neural network, and a refreshed abnormal transmission chain is obtained; and finally, calculating the self-adaptive regulation and control intensity at the current moment based on the refreshed abnormal transmission chain to realize closed-loop optimization of a regulation and control strategy.

The invention provides a power distribution network evaluation method and system, and relates to the technical field of power system operation control, and the method comprises the steps: obtaining an extreme event index of a power distribution network in a current time period according to a measurement data flow, and judging whether an extreme event exists in the power distribution network or not according to the extreme event index; the measurement data streams are classified through a data quality grading mechanism, and then an observation weight matrix of the extreme events is constructed; supplementing missing data for the missing data segment according to the observation weight matrix, dynamically updating topological information of the power distribution network in combination with the supplemented missing data, and obtaining a real-time network model corresponding to the extreme event according to the topological information; and according to the real-time network model and the extreme event index, obtaining a state evaluation result of the power distribution network in the current time period. According to the invention, the evaluation precision of the power distribution network under extreme conditions is improved.

The invention relates to the technical field of voice interaction, in particular to a dialogue type AI low-delay response control method and system based on semantic analysis. The method comprises the following steps: firstly, generating a driving intensity correlation factor of a current time window according to the change of CAN bus data; further monitoring the output of the NLU, analyzing the acoustic intonation raising characteristics, and obtaining an interaction suppression coefficient in combination with the driving intensity correlation factor; further acquiring a time pressure coefficient based on the mute duration after the user stops sounding; further comparing the interaction suppression coefficient and the time pressure coefficient of the current time window to obtain a response judgment value; further analyzing the change trend of the interaction inhibition coefficient, and updating an environment improvement flag bit; and finally, according to the driving intensity correlation factor, the environment improvement flag bit and the response decision value of the current time window, carrying out multi-level response decision control, and carrying out selective reset of an interaction state, thereby solving the problems of wrong truncation and response delay of voice interaction under dynamic driving.

The invention relates to the technical field of power system safety, and discloses a safety early warning method and system for a power system data center. The method comprises the steps that a safety monitoring period threshold value is set, when the continuous operation duration of the data center reaches the standard, historical and real-time safety state summaries are synchronously obtained, the historical operation duration comprises historical operation duration and configuration parameters, and the real-time safety state summaries comprise current operation duration and configuration parameters. And searching a security data fluctuation set by calculating security difference measurement of corresponding parameters of the two types of summary. And when the set variation degree is greater than or equal to a variation threshold value, taking the time distance ratio between the data storage starting point and the historical acquisition point as well as between the data storage starting point and the current time point as an early warning trigger factor, and starting a safety data early warning response from the data storage starting point according to the factor. According to the method, historical and real-time data comparison is combined, accurate monitoring of the safety state is achieved, timely risk identification is assisted, and a safety barrier is built for operation of the data center.

The invention discloses an intelligent autonomous networking monitoring method and system based on optimal channel selection, and a medium, a gateway selects an optimal channel from a plurality of communication channels as a data channel, and divides each time slot of the data channel into a communication segment and a broadcast segment; performing data communication with the networked monitoring node corresponding to the current time slot in the communication section; broadcast information of non-networking monitoring nodes is received in a broadcast segment, and a networking information packet is generated and replied; after being powered on, each monitoring node is switched to a default broadcast channel to send broadcast information to a gateway to request networking, and after receiving a networking information packet, the monitoring nodes which are not networked analyze the networking information packet to obtain networking information, calculate the next wake-up time of the monitoring nodes according to the networking information, and wake up the monitoring nodes when the monitoring nodes sleep to the next wake-up time; the networked monitoring nodes are switched to a data channel to perform data communication with the gateway after being awakened, and the nodes are timed and synchronously awakened with the gateway through a dynamic channel selection algorithm and a time-sharing synchronous communication mechanism, so that the power consumption is reduced.

An accelerator offload device (100) includes: a data processing amount acquisition part (110) that acquires a data processing amount that is a data processing amount at the current time of offload target processing being performed and / or a predicted data processing amount; an operation destination determination part (120) that determines whether to perform an operation by a CPU (11) or offload the operation to an ACC (12) based on the data processing amount of an APL (1), and when a change is necessary, changes an offload destination of an operation processing offload part (130); and an operation processing offload part (130) that receives a request of operation processing from the APL (1), stores data to be processed and a processing instruction in a shared memory, and causes the CPU (11) or the ACC (12) to execute pertinent processing.

The invention relates to the technical field of data processing, in particular to a mining disc brake abrasion detection method based on an intelligent sensor, and the method comprises the steps: respectively obtaining the detection abrasion loss of a brake under the conditions of thickness, vibration signals and temperature, so as to comprehensively reflect the abrasion state of the brake; according to the pressure stability of the brake disc in the current time period, the thickness confidence coefficient is obtained; according to the vibration signal difference of the brake between the reference time period with the lowest noise and the current time period, the vibration confidence coefficient is obtained; according to the amplitude characteristics and temperature changes of the acoustic emission signals of the brake disc in the current time period, the temperature confidence coefficient is obtained; according to the thickness confidence coefficient, the vibration confidence coefficient and the temperature confidence coefficient, the detection abrasion loss of the brake under the thickness, the vibration signal and the temperature is subjected to weighted fusion, the final abrasion loss is obtained, then the abrasion state of the brake is judged, and the accuracy of abrasion detection on the brake is improved.