1891 results about "Mirror image" patented technology

The invention discloses an ERP (Enterprise Resource Planning) data intelligent supervision method based on the Internet of Things, which relates to the technical field of enterprise informatization, and comprises the following steps: constructing a time sequence integrity observation layer in an Internet of Things data acquisition link, embedding a mirror image time anchor in each sensor sampling point, recording electromagnetic interference, time service offset and queuing delay, generating a phase fingerprint time baseline, and obtaining a phase fingerprint time baseline; constructing a unified time reference framework; operating a causal coherent analysis mechanism based on a unified time reference frame, comparing instantaneous offsets of a mirror time anchor and a real-time timestamp, identifying a phase inversion region, extracting information of a corresponding sampling node, a production line position and an energy consumption unit, generating a high-risk time slice list, and determining a time correction boundary. According to the method, a time sequence observation layer and a time reference frame are constructed, phase abnormity is identified, a data trend is reconstructed, a regulation and control instruction draft is generated, sampling time sequence recovery and scheduling convergence are realized through time inversion control, data consistency and decision accuracy are improved, and a closed-loop control system is constructed.

The invention relates to the technical field of optical network operation and maintenance, and particularly provides an optical network fault prediction method and system based on MEMS characteristic embedding and digital twinning, and the method comprises the steps: collecting multi-physics field coupling parameters of optical network operation in real time through an MEMS multi-physics field coupling sensing unit which is disposed at an optical network key node and is embedded in a physical layer device; constructing an optical network cross-scale digital twin, inputting parameters to realize real-time synchronization and fault rehearsal of a physical entity and a virtual mirror image, and outputting a rehearsal result; constructing a fault prediction model based on an optical network physical mechanism, inputting parameters and rehearsal results to complete feature fusion and trend analysis, and outputting a fault prediction result; an intervention strategy is generated and subjected to twinborn virtual simulation verification; and after the verification is passed, driving the physical layer to execute intervention, and feeding back effect data to dynamically update twin model parameters. A closed loop of perception, modeling, prediction, intervention and feedback is formed, and the problems of prediction lag and low operation and maintenance efficiency in the prior art are solved.

A method of brain imaging detection includes: dividing a brain image into a left brain medical image and a right brain medical image and obtaining the grayscale values of multiple pixels thereof, respectively; mirror-flipping one of the left and right brain medical images; performing a grayscale value subtraction with the mirror-flipped medical image and the other medical image to obtain a plurality of grayscale differences of the pixels; determining whether the grayscale difference of each pixel exceeds a grayscale difference threshold and whether a number of the pixels having the grayscale different exceeding the grayscale difference threshold is greater than or equal to a pixel number threshold; and when the number of the pixels having the grayscale difference exceeding the grayscale difference threshold is greater than or equal to the pixel number threshold, determining that the brain image is abnormal.

The invention discloses an atmospheric and vacuum distillation unit intelligent optimization method and system based on deep reinforcement learning, and relates to the field of oil refining and chemical engineering, and the method comprises the steps: collecting historical operation data from a distributed control unit and a real-time database of an atmospheric and vacuum distillation unit, and carrying out the preprocessing, and obtaining a preprocessed historical data set; constructing a process mechanism feature network through a graph neural network by using the preprocessed historical data set, mining an association relationship among equipment parts, extracting abstract features representing a process principle, and constructing a digital twin environment; in a digital twin environment, a meta-reinforcement learning algorithm is adopted to train a deep reinforcement learning agent, so that the deep reinforcement learning agent obtains meta-strategies adapted to different crude oil properties. According to the method, safe, stable and efficient intelligent optimization control is realized through a closed-loop operation mechanism of safe mirror image drilling and credibility driving, and the problem of optimization response lag caused by manual model adjustment due to crude oil property change in a traditional optimization technology is solved.

The invention discloses a BMC firmware starting method and device, equipment, a medium and a program product, and relates to the technical field of server management.The BMC firmware starting method comprises the steps that when a main mirror image file is damaged, BMC firmware is restarted on the basis of a standby mirror image file, if starting fails, the BMC firmware is restarted on the basis of a latest mirror image file of a remote server, and if starting fails, the BMC firmware is restarted on the basis of the latest mirror image file of the remote server; if the BMC firmware is started abnormally, the BMC firmware is restarted based on the local minimum mirror image file, so that the problem that a double-mirror image backup mechanism still faces system paralysis can be solved, a multi-stage mirror image file recovery mechanism is constructed through the multiple pre-deployed mirror image files, when the BMC firmware is started abnormally, the system is recovered step by step according to the multi-stage mirror image file recovery mechanism, and the system recovery efficiency is improved. The technical effects of ensuring the minimum availability of the system and improving the reliability and safety of the system are achieved.

The invention discloses a millimeter wave barrier gate radar multipath interference suppression method and device, and belongs to the field of millimeter wave radar signal processing. The method comprises the following steps: S1, generating an RD image by an echo signal, and executing 2D-CFAR detection to obtain a candidate target unit; s2, eliminating ground reflection (GB) through an RD domain multipath sensitive area mask (MVZ); s3, converting the candidate target unit into a Cartesian coordinate system point cloud; s4, through point cloud domain mirror symmetry verification, removing a pole side mirror image (PSR); s5, clustering the reserved point cloud to obtain a target cluster; s6, through vehicle contour modeling, constructing a rear suppression area to reject vehicle-brake box multiple reflections (VBR); and S7, outputting effective target information after tracking processing. The device comprises a radar radio frequency front end, a signal processing unit, a point cloud post-processing unit, a tracking and control unit and an embedded processing platform. Through a three-layer cooperative inhibition mechanism, three types of main multipath interferences of a barrier gate scene are comprehensively covered, the detection accuracy is improved, static targets are prevented from being mistakenly eliminated, the engineering practicability is high, and safe and reliable barrier gate control can be ensured.

The invention discloses a dual-hybrid robot mirror image processing equipment trajectory planning method, which comprises the following steps of: defining a dual-machine tool nose point position path and a same point position path on a tool shaft in a Cartesian coordinate system; performing fitting fairing on the paths of double tool nose points and double tool axis points of the double-hybrid robot, the paths of the tool nose points of the four robots and the path of the same point on the tool axis by adopting spline curves, introducing a fitting error evaluation method, reducing fitting errors by adjusting control points, and determining a final double-robot four-Nurbs curve; a cubic B spline is adopted to represent a double-machine speed curve, synchronous coordination machining constraint, joint constraint, cutter shaft constraint and cutter point speed, acceleration and jump threshold values are introduced, an improved iterative optimization algorithm is adopted to obtain double-machine speed curve control points, and it is ensured that the speed curve meets various constraints. According to the method, the trajectory planning process of the double-hybrid robot mirror image processing equipment is realized, time optimization is taken as a target function, the processing efficiency is greatly improved, and the precision requirement is met.

The invention relates to an urban green land high-resolution remote sensing monitoring method. The method comprises the following steps: data acquisition and preprocessing: synchronously acquiring point cloud data, hyperspectral data and multi-temporal remote sensing data; feature engineering: constructing a multi-dimensional feature space, and optimizing the multi-dimensional feature space through feature selection; model training: on the basis of the optimized multi-dimensional feature space, performing filling, differential normalization processing and regularization improvement on a U-net + model through pixel values of the edges of mirror images in sequence for urban green land features, and establishing the urban green land-oriented and multi-dimensional feature-based U-net + model, so that the urban green land-oriented and multi-dimensional feature-based U-net + model is obtained; adding the multi-dimensional feature data of the training sample into the U-net + model for training, predicting the spatial distribution of the urban green land after the training is completed, obtaining a prediction result of the U-net + model, and combining a mixed loss function with an adaptive training strategy; and post-processing and result generation: applying adaptive CRFs to optimize a U-net + model prediction result, generating a high-resolution urban green land distribution map, and outputting a precision evaluation report.

The invention relates to the technical field of bridge engineering detection and life evaluation, and discloses a bridge deck residual fatigue life prediction method and system based on real-time image information. The objective of the invention is to solve the problems of low subjective efficiency, time-consuming numerical simulation, low automation and intelligence level and poor generalization ability of the existing in-service bridge RC deck residual fatigue life evaluation means. According to the scheme, an evaluation system including image acquisition, physical simulation data set generation, deep learning evaluation model and result output is constructed; generating a bridge deck crack image-residual fatigue life pairing data set covering mirror symmetry and extreme crack modes by using a high-fidelity physical simulation platform, and training an end-to-end deep convolutional neural network regression model; a bridge floor image is collected on site and preprocessed, the residual fatigue life is directly output by an input model, and finally a visual evaluation report is generated.

The invention discloses a substrate management controller firmware integrity verification method and electronic equipment, and relates to the technical field of server management, and the method comprises the steps: building a tree structure layered according to a storage path prefix through obtaining the storage path and content data of each function module, the full-coverage verification of all functional modules of the firmware of the baseboard management controller is realized; according to the method, the security level labels in the structured description information are screened, and the verification path is determined for the target function module, so that the redundant operation of full firmware mirror image hash calculation is avoided, and the calculation amount and time consumption in the verification process are reduced; hash is recalculated based on the target function module and path consistency is verified, whether the target function module is tampered or not can be rapidly judged, all firmware data does not need to be traversed, verification comprehensiveness and efficiency are both considered, and bandwidth resource consumption is reduced; all function modules are associated through a storage path and content data, tree structure verification logic is combined, and refinement of firmware verification from a full mirror image level to a function module level is achieved.

The invention discloses a transformer substation abnormity intelligent diagnosis method based on a self-attention mechanism, and relates to the technical field of transformer substation abnormity identification, and the method comprises the following steps: S2, employing a computer vision technology, a sensor, an ultrasonic detector, and a current and voltage detector to collect the electrical parameters of equipment, and completing the collection of multi-source data; s3, realizing a virtual mirror image of the physical equipment by using a digital twinning technology; and S5, analyzing and processing the important information in the database through a self-attention mechanism, and predicting the health trend, risk point and service life of the substation equipment. According to the method, image information and equipment parameters of substation equipment are collected in real time, an attention weight matrix of data is obtained through calculation, multi-source data are associated, the fault probability is output, then a regression device is used, key parameter values of multiple time points in the future and the remaining service life are output, and the service life of the substation equipment is calculated. And predicting the health trend, the risk point and the service life of the substation equipment.

The invention discloses a Linux system quick starting method and device based on dormancy mechanism optimization. The method comprises the following steps: in response to detection of shutdown, executing the following dormancy operations: actively releasing a memory cache and temporary data, setting the size of a dormancy mirror image as a preset lower limit value, and generating the dormancy mirror image with the corresponding size; and in response to detecting that the system is powered on, executing the following wake-up operation: directly starting by the clipped boot kernel, and after the clipped boot kernel is started and before the initial memory disk is initialized, reading the sleep mirror image and restoring the system state. According to the Linux system quick starting method based on dormancy mechanism optimization, the starting speed of the Linux system can be remarkably increased by optimizing the core process of the dormancy mechanism.

The invention relates to a hot update control method and system for an industrial PLC (Programmable Logic Controller) of a microkernel operating system, belonging to the field of industrial controllers. A shadow instance is created by an isolated address space and is bound with a shadow I / O (Input / Output) mirror image and a shadow communication stack; capturing a containment point in the scanning period, wherein the containment point is located between input sampling completion and output submission; acquiring running state information from the current network instance, converting the running state information, and transmitting the converted running state information to the shadow instance; pre-operating the shadow instance in the isolation channel in an accelerated or constant-speed manner, and switching the I / O channel from the current network instance to a shadow I / O mirror image of the shadow instance at the next restraint point if the verification is passed; and continuing to run in parallel for a certain period, unloading the old instance if the continuous running is qualified, and executing rollback if an exception occurs. Depending on a microkernel operating system, shadow instances are drilled and switched under the controlled priority, the real-time performance and certainty are met, the time delay defect of periodic gap switching is overcome, and updating and switching are completed in a single scanning period or a plurality of scanning periods in an atomic mode.

The invention relates to the technical field of retail management, in particular to a retail end online management method and system based on concurrency control, and the method comprises the steps: constructing a retail knowledge graph based on historical transaction logs through employing a space-time interaction entropy weighting algorithm; calculating a local topology edge density increment by applying a streaming dense subgraph increment mining algorithm, and determining a topology aggregation state of a target node; if the state is the mixed concurrent state, constructing an inventory time slice mirror image containing a reference inventory domain and a dynamic increment domain; and writing the request into the lock-free annular buffer during checking, and merging data by adopting a time sequence alignment algorithm after checking to carry out atomized updating. According to the method, static inventory and dynamic sales are physically isolated by constructing the inventory time slice mirroring and lock-free buffer mechanism, the read-write conflict in the scene of inventory while sales is solved, and zero-blocking hybrid concurrence is realized while the final consistency of inventory data is guaranteed.

The invention discloses a hip replacement lower limb equal-length control system and method based on individualized three-dimensional modeling. The hip replacement lower limb equal-length control system comprises a data preprocessing module, a medical image processing module, a dynamic implantation simulation module, a biomechanical analysis module, a guide plate generation module and a postoperative evaluation module. The method comprises the following steps: acquiring bilateral lower limb CT data and carrying out multi-modal registration; segmenting a skeleton structure by using a deep learning model, and constructing a three-dimensional model; reconstructing a complete sphere through affected side femoral head multi-plane fitting, and determining a target femoral head center in combination with uninjured side mirror image data; dynamically adjusting the space posture of the prosthesis to enable the center of the prosthesis head to coincide with the center of the target; performing finite element analysis to optimize stress distribution; and generating a 3D printing file of the individualized osteotomy guide plate and the positioning pointer. According to the method, preoperative accurate planning, intraoperative real-time control and postoperative quantitative evaluation are achieved, the operation precision is effectively improved, and complications of unequal lengths of lower limbs are avoided.

The invention discloses a mirror image rejection method and device based on spectrum entropy, and belongs to the technical field of radio frequency signal processing. Multiple groups of frequency spectrums are collected by moving a local oscillator, the frequency spectrums are mapped to a unified reference frequency axis to achieve frequency alignment, a spectrum entropy sequence of the same frequency point after alignment is calculated, and the problem that the spectrum entropy fluctuation of the same frequency point is large due to nonlinear deviation of the local oscillator frequency of a mirror image signal is solved. And accurate identification and suppression of the mirror image signal are realized due to the difference of spectrum entropy stability caused by linear offset of the useful signal. According to the method, multiple groups of frequency spectrums are mapped to a unified reference axis through frequency alignment, high-precision mirror image suppression is effectively realized by utilizing the characteristics of large fluctuation of mirror image signals and stable useful signals in a spectrum entropy sequence of the same frequency point, the distinguishing capability in a complex scene is improved, and the problems of high cost and insufficient robustness of an existing mirror image suppression method are solved.

The invention discloses a power grid active constraint optimization method and device based on deep reinforcement learning, and the method comprises the steps: building a mirror image simulation environment, and generating different power flow operation condition data sets; training the initial system sensitivity model by using the data set to obtain a system sensitivity model; a sensitive regulation and control unit is screened, and an optimal active adjustment strategy is obtained through reinforcement learning training in a mirror image environment; and verifying strategy performance in a mirror image environment, and deploying in a power grid after the strategy performance reaches the standard. According to the power grid active constraint optimization method and device based on deep reinforcement learning, offline processing is realized through a mirror image simulation environment, key units are screened by using a system sensitivity model to reduce dimensions, and the complexity and time consumption of online calculation can be reduced by combining a reinforcement learning training strategy and offline verification; effective control of the power grid is achieved, and the problems that an existing active correction control technology is complex in solution, long in time consumption and difficult to meet the real-time decision-making requirement of the power grid can be solved.

The present invention belongs to the technical field of material machining, and relates to a die-free mirror-image-based fiber placement method and a die-free mirror-image-based fiber placement system, which place fibers in a mirror symmetry manner without requiring dies, thereby improving the flexibility and efficiency of production. The method comprises: acquiring in real time the temperature and pressure of fibers; by using a temperature difference and a pressure difference, calculating the output power of a heater and a modified value of a path of a fiber placement tail end movement mechanism; and optimizing controller parameters by means of reinforcement learning, so as to realize stable control over the temperature and pressure. The system comprises a hardware portion and a control system, wherein the hardware portion includes components such as a pressure component and a heat source, and the control system performs adjustment on the basis of real-time feedback, thereby ensuring the quality of fiber placement. The present invention solves the problem of it being difficult to accurately control the temperature and pressure during die-free mirror-image-based fiber placement, and improves the performance of composite products.

The invention discloses a smart city monitoring and simulation deduction method based on a digital twinborn model, and belongs to the field of electric digital data processing.The smart city monitoring and simulation deduction method based on the digital twinborn model comprises the following steps that dynamic data are continuously accessed, static data are obtained at the same time, a digital twinborn body with a timestamp is constructed, and the digital twinborn body is constructed; forming a virtual mirror image of the physical state of the city; on the basis of real-time indexes in a digital twinborn body, hydrological model parameters are corrected in real time, the short-term rainfall prediction precision is improved by fusing an LSTM model, and a twinborn driving model matched with the current reality is generated; compared with the prior art, the method has the advantages that dynamic data and static data of a city are collected in real time, a digital twinborn model for analyzing city drainage is constructed, the ponding risk level can be rapidly evaluated, differentiated emergency plans are automatically generated according to different risk levels, and the method has the advantages of being high in prediction precision and high in response speed.

The invention discloses a building fire safety management and control method based on a digital twinborn technology, and the method comprises the steps: constructing sensor-middle platform-model bidirectional mapping, and reconstructing a dynamic scene through employing a neural radiation field technology; fusing the cross-domain desensitization data based on federal transfer learning, and constructing a building total-factor dynamic digital mirror image; through a spectrum analysis algorithm, a fire source is positioned in real time, and a flame spreading track is predicted; performing fire simulation in linkage with a total-factor dynamic digital mirror image, and optimizing a fire-fighting resource scheduling path through a multi-target particle swarm optimization algorithm; a multi-target rescue scheme is generated, an asynchronous block chain is used for evidence storage of a fire-fighting decision instruction, a rescue key area is plotted, and an optimal evacuation route is planned; and converging federal node data to quantify the data contribution degree, reproducing a historical fire behavior and deducing a new scene to carry out iterative optimization. According to the method, the problems of data sensing fragmentation, difficulty in cross-domain fusion, fire prediction lag, underscientific resource scheduling, slow drill scheme iteration and the like in traditional management and control are solved.

A mannequin model video real-person clothing display system based on a diffusion model comprises a data acquisition unit used for acquiring a mannequin model video and a target identity image; and the video generation unit is used for converting the mannequin model video into a real person video with a target identity feature. The video generation unit comprises a feature encoder used for encoding a high-dimensional image and a video into a low-dimensional hidden space; the dynamic posture sensing head encoder is used for fusing the facial appearance features of the target identity image, the facial key point postures of the target identity image and the human body posture sequence features corresponding to the mannequin model video so as to generate posture sensing identity embedding features; the distribution perception adapter is used for carrying out distribution alignment on the identity embedding characteristics and the clothing characteristics; the diffusion video generation network based on the hidden space is used for de-noising reasoning; and the mirror image loss calculation module is used for generating a face region of the video and calculating pixel-level reconstruction loss and perception loss.

The invention relates to the technical field of carbon fiber plate detection, and discloses a carbon fiber processing quality detection device and a detection method.The carbon fiber processing quality detection device comprises a workbench, the upper surface of the workbench is provided with two detection piece bearing assemblies which are used for placing a carbon fiber plate needing to be detected in a side-standing mode, and the two detection piece bearing assemblies are arranged in a mirror image mode; an extrusion unit is arranged on the upper surface of the workbench and located on one side of the two detection piece bearing assemblies and used for extruding the side edge of the carbon fiber plate, and a bending degree detection unit is arranged on the upper surface of the workbench and located on the other side of the two detection piece bearing assemblies and used for detecting the resilience degree of the extruded carbon fiber plate. According to the invention, through the arrangement of the detection piece bearing assembly, a carbon fiber plate to be detected can be placed on the device in a side-standing manner, so that the error of an experiment result caused by the weight of the carbon fiber plate when the carbon fiber plate lies flat is effectively reduced.

The invention belongs to the technical field of cigarette production, and provides a cigarette three-dimensional shape reconstruction method and system based on laser three-dimensional scanning and application, and the method comprises the steps: collecting three-dimensional point cloud data of the whole surface of a cigarette based on a laser triangular reflection principle; preprocessing the three-dimensional point cloud data by adopting a multi-stage filtering algorithm strategy to obtain reference data; the method comprises the following steps of: dispersing reference data into a plurality of two-dimensional sections along the axial direction of a cigarette, synchronously extracting upper and lower semicircular feature points of the cigarette in different two-dimensional sections by adopting a multi-thread technology, performing offset vector calculation and mirror image translation transformation so as to reconstruct a plurality of continuous two-dimensional reference sections in a virtual space, and performing curved surface reconstruction on the continuous two-dimensional reference sections, obtaining a three-dimensional shape model of the cigarette; based on the three-dimensional shape model, the perimeter and the length of the cigarette are extracted through a mixed measurement model. The cigarette shape detection efficiency can be improved, and the detection accuracy and the data accuracy are improved.

The invention discloses a traffic anomaly detection method based on a space-time double-flow network and multi-modal feature fusion, relates to the technical field of intelligent video analysis and traffic behavior recognition, and is used for solving the problem of high false detection rate of existing traffic anomaly detection in a complex environment. A video image sequence is extracted through a fixed and dynamic combined frame sampling strategy, and motion features are constructed. And in combination with the direction consistency coefficient and the perturbation evolution trend, repairing direction perception distortion by using a mirror image mapping mechanism. Target appearance features are extracted through spatial branches, behavior evolution trajectories are extracted through time branches, and meanwhile, a modal weight dynamic adjustment mechanism is introduced to enhance the adaptability to complex scenes. The multi-target interaction relation is quantified based on a graph structure modeling mode, an adjacent structure is reconstructed through a graph self-encoder, and local behavior mutation is recognized. And finally realizing high-confidence anomaly marking by combining state transition analysis and spatial aggregation characteristics. The method has the advantages of high real-time performance, high robustness and wide scene adaptability.

The invention belongs to the technical field of material processing, and relates to a composite mirror image fiber placement method and a system capable of realizing stable pressure control. The mirror image fiber placement method for the composite material comprises the following steps: laying two fiber ribbons in a mirror image symmetry manner without using a mold, and repeating the fiber placement process for multiple times; and real silk ribbon pressure is obtained in real time in the silk placement process, the pressure difference is calculated in real time, the modified value of the silk placement tail end movement mechanism path is calculated in real time according to the pressure difference, and the silk placement tail end movement mechanism path is updated in real time. The system capable of realizing stable pressure control comprises a hardware part and a control system, the hardware part comprises a fiber placement tail end movement mechanism and a pressure sensor; the control system comprises a pressure stability control subsystem, a control instruction generation subsystem and a fiber placement tail end movement mechanism control subsystem. The problem that the pressure is difficult to accurately control in the mold-free mirror image fiber placement process is solved, and the performance of a composite product is improved.

The invention discloses a protocol message tamper-proofing method and system based on symmetric encryption and a medium, and relates to the technical field of industrial automation Ethernet time synchronization. According to the method, mirror image monitoring is carried out on the message receiving and sending process in the protocol processing process of time synchronization equipment, a protocol message is obtained and analyzed, and the protocol message tamper-proofing effect is achieved; a message abstract and encrypted verification data thereof are generated at a sending end, and a corresponding abstract is obtained through decryption at a receiving end; consistency comparison is carried out on the sending side abstract and the receiving side abstract based on the time window, and a tamper-proof consistency coefficient is calculated to judge the integrity of the protocol message; on the basis that the integrity is qualified, performing difference analysis on an encryption verification result, and calculating an encryption credibility coefficient to evaluate the credibility state of the symmetric encryption link; and further performing coupling calculation to obtain a time synchronization security coupling coefficient, comprehensively evaluating the influence of tamper-proofing and symmetric encryption on the time synchronization operation security, and implementing a security regulation and control strategy according to the influence, thereby improving the security and stability of the time synchronization system.

The invention discloses a block chain technology and big data-based data synchronous scheduling management and control system, and relates to the technical field of data synchronous scheduling management and control. Comprising a cross-level dynamic observation module, a causal coherent decomposition module, an anti-fact playback construction module, a double-mirror-image time scale rearrangement module, a time-varying virtual impedance regulation and control module and a time reversal phase traction module. And the cross-level dynamic observation module constructs a cross-level cache link dynamic observation layer, collects cache pressure fluctuation data and link delay pulsation data of each node in the block chain network in real time, and generates a coupling feature baseline for representing a relationship between cache pressure and link delay. According to the invention, through multi-layer time sequence observation and time baseline correction, accurate control of cross-node data synchronization is realized, and repeated confirmation and account book bifurcation are prevented; and resonance energy is absorbed through the time-varying virtual impedance and the energy buffer zone, so that self-balancing and self-repairing of the system are realized, and global consistency and scheduling stability of the block chain are ensured.

The embodiment of the invention provides a software development environment construction method and device, equipment, a medium and a program product, and relates to the technical field of software development. The method comprises the following steps: acquiring a software development kit on a target architecture host machine; creating a file structure of the container mirror image, and copying the software development kit into the file structure; in any host machine, setting a prefabricated basic mirror image, and copying contents in the file structure into the basic mirror image in a layering manner through a file structure copying instruction to obtain a container file of the container mirror image; and constructing a container mirror image based on the container file, wherein an environment provided by the container mirror image is used for developing software of the target architecture. By the adoption of the method, a software development environment based on the basic mirror image can be constructed, the purposes of cross compiling, automatic compiling and testing can be achieved in a cross-framework mode, the software development difficulty can be lowered, and the software development efficiency can be improved.

1. The name of the design product: hearing aid (H6). 2. The use of the design product: for helping people with impaired hearing or hearing impairment to improve their hearing ability. 3. The design points of the design product: in shape. 4. The picture or photo that best shows the design points: assembly state diagram. 5. Other circumstances that need to be explained: component 1 is for right ear wearing, component 3 is for left ear hearing aid, component 3 and component 1 are mirror image symmetric design, so the six view and perspective of component 3 are omitted.

The invention discloses an intelligent operation and maintenance management system and method based on digital twinning, and relates to the technical field of intelligent operation and maintenance management. The system comprises a parameter acquisition and anomaly identification module, a digital twin mirror image module, a fault trajectory generation module, a non-dominant fault positioning module and a closed loop verification module. The parameter acquisition and anomaly recognition module acquires data and recognizes anomaly based on a composite judgment threshold value; the fault trajectory generation module drives digital twin mirror image backtracking to generate fault time sequence trajectory data; the non-dominant fault positioning module constructs a reference scene and compares, analyzes and identifies non-dominant associated fault points; and the closed-loop verification module generates a verification instruction, and the verification instruction is verified by the physical device and then fed back to the digital twin mirror image to complete closed loop and confirm the fault root cause. According to the method, fault full-time-sequence tracing and hidden fault accurate identification are realized, and the operation and maintenance reliability and accuracy are improved.