49 results about "Code space" patented technology

The invention relates to the technical field of entity relationships, and discloses a multi-feature fused entity relationship extraction optimization model construction method and system, and the method comprises the steps: obtaining an input text sequence and a relationship label set, and carrying out the coding processing, and obtaining a text embedding vector and a relationship embedding vector; calculating the similarity between the text embedding vector and the relation embedding vector, screening in combination with a similarity threshold to obtain a candidate relation subset, and fusing the relation embedding vector and the text embedding vector in the candidate relation subset to generate a relation enhancement vector; processing the relation enhancement vector through a mixed attention mechanism to obtain a semantic enhancement vector; constructing a three-dimensional marking matrix based on the semantic enhancement vector, and marking the three-dimensional marking matrix by adopting a diagonal marking strategy; and carrying out decoding processing on the three-dimensional mark matrix, and generating a structured entity relationship triple by adopting a constraint decoding strategy. The interactive fusion of the text and the relation label can be accurately processed in a unified coding space.

The invention discloses a column storage-based big data compression and query optimization method, which relates to the technical field of big data compression and query optimization, and comprises the following steps of: performing sliding window division on original data of column storage to obtain a plurality of data windows; calculating a feature vector based on the value distribution characteristics in the multi-data window, wherein the feature vector is used for representing a local statistical rule of the data; performing dynamic merging according to the similarity of the feature vectors of the adjacent data windows to form a compressed block; selecting a corresponding compression coding mode based on the data type and the distribution characteristic of the compression block, and generating a metadata index containing a minimum value, a maximum value, a coding type and a compression size; after receiving a query request, mapping a predicate condition to a compressed coding space, and executing non-decompressed filtering judgment on a compressed block by utilizing the metadata index and a compressed coding type; and determining a decompression range based on a filtering result of the compressed blocks, and only performing local decompression and data reduction on the possibly hit compressed blocks.

The invention discloses a programmable metasurface fault rapid diagnosis method based on orthogonal coding space-time modulation. The method comprises the following steps: step 1, applying independent orthogonal coding space-time modulation to each metasurface unit on a programmable metasurface to be diagnosed by adopting a time-varying signal based on orthogonal coding; 2, irradiating the programmable metasurface to be diagnosed by using a single-frequency plane wave; 3, receiving a reflection signal of the programmable metasurface to be diagnosed, and recovering each orthogonal coding channel energy from the reflection signal; step 4, according to the magnitude of the recovered orthogonal coding channel energy, determining a malfunctioning metasurface unit; when a certain unit breaks down, preset orthogonal coding modulation cannot be normally executed, so that a corresponding coding channel in a transmitting signal is lost, and therefore whether the unit corresponding to each coding channel breaks down or not can be judged by recovering energy distribution of each coding channel in a receiving signal, and accurate and efficient fault diagnosis is achieved.

The invention discloses a multi-mode joint information source channel coding system for satellite-ground semantic communication. The multi-mode joint information source channel coding system comprises a joint information source channel coder and a decoder, the encoder is used for sequentially performing feature extraction, feature fusion, data cutting and phase modulation operation on input multi-modal data to generate a transmitting signal, and transmitting the transmitting signal to a ground base station through a channel; and the decoder is used for sequentially performing real and virtual part separation, data expansion, feature extraction and modal data recovery operation on the received signal so as to reconstruct multi-modal data. According to the system, public semantic information among multi-modal data can be mined, the time-varying low-signal-to-noise-ratio channel characteristics of a satellite downlink are combined, the information bottleneck theory highly related to data reconstruction quality is used as guidance to optimize a coding space, complex field transmission signals with the high compression ratio are generated in a self-adaptive mode, and the multi-modal multi-domain transmission signals are obtained. The reconstruction quality of the multi-modal data can be ensured, and the bandwidth and the energy consumption overhead of satellite communication can be remarkably reduced.

The invention belongs to the technical field of optical transport networks (OTN), and particularly relates to a resource identifier storage and reading method for network management system data acquisition of OTN and WDM communication equipment, which comprises the following steps of: when the network management system data acquisition and reading are performed on the OTN and WDM communication equipment, performing bidirectional transcoding conversion between a resource identifier in a five-section layered form and an rmUID (Radio Mode Unified Identifier) identifier; a database static mapping table is prevented from being introduced, disk IO is reduced, the processing process is carried out in a memory, and the conversion efficiency is effectively improved; meanwhile, the 36-system is fully used for encoding each encoding segment in the rmUID, and under the encoding limiting condition that the longest bit of the rmUID limits 16 bits, the data encoding space is increased by about 10000 times compared with a 35-system and separator scheme, so that the utilization rate of the encoding space is expanded and increased to the maximum extent; the problems that in the prior art, conversion efficiency is poor, and the utilization rate of coding space is poor are effectively solved, and the method has good technical application prospects.

The invention discloses a discrete dung beetle optimized adaptive scanning VMama image denoising method, and relates to the field of image processing. In order to solve the problems of computation redundancy and denoising detail loss caused by a fixed scanning path of an existing VMama network, a hybrid coding space containing the number of network layers, state dimensions and binary scanning masks is constructed. According to the method, an S-type transfer function is introduced to improve a discrete dung beetle algorithm, an optimal architecture is adaptively searched by using behaviors such as rolling and dancing of a dung beetle population, a scanning path of an SS2D module is dynamically pruned according to a binary mask, performance is evaluated by fusing a fitness function of PSNR and FLOPs, and finally, a de-noised image is output based on the optimal architecture. According to the method, the balance between the denoising quality and the reasoning speed is effectively realized, and the model calculation amount is reduced.

The invention provides a character string coding and mapping method, system and device, a medium and a program product. The method comprises the steps that a to-be-coded character string is calculated through a self-defined coding polynomial to obtain a coding value corresponding to the character string; for each character string, allocating an index address to store a storage path corresponding to the character string in a storage space of a preset specification indicated by the index address, and storing the corresponding character string in a storage space indicated by the storage path; and storing the coded value of each character string and the corresponding index address in a lookup table by taking the coded value as an index so as to indicate a mapping relationship among the character string, the coded value, the index address and the storage path. The character string is coded through the polynomial, the prime number with the good hash characteristic serves as the polynomial cardinal number, the distribution uniformity of coded values is improved, and therefore the hash conflict probability is reduced; the realization of unique coding of the character string under the condition that the coding space is limited is ensured, and the system stability and the retrieval accuracy are improved.

A language model training method and apparatus (900). The method comprises: acquiring a training data set (401); respectively performing feature extraction on speech sample data and text sample data to obtain a first feature representation corresponding to the speech sample data and a second feature representation corresponding to the text sample data, wherein the first feature representation and the second feature representation belong to the same representation space (402); mapping the first feature representation and the second feature representation to a discrete coding space to obtain first discrete codes corresponding to the speech sample data and second discrete codes corresponding to the text sample data (403); and on the basis of the first discrete codes and the second discrete codes of a plurality of speech-text pairs, training an LLM to be trained (404). According to the method, speech sample data and text sample data which are not paired are expressed in the same representation space, so that multi-modal data of the speech sample data and the text sample data is used to train language models, thereby reducing the model training cost and improving the model training effect.

The present application relates to the technical field of network protocol testing, in particular to a double information perception network protocol fuzzy testing method and system based on state variables, which performs static analysis on network protocol source code and identifies state variables in the source code; the change of network protocol state variables is tracked and detected by plugging the state variables, the process state in the network protocol is acquired, and a state machine is constructed according to the process state to map the state space and the code space; the key state of the network protocol is selected according to the state weight, the message pool of the key state is constructed, and the messages are selected, replaced and cross-compiled in the message pool according to the state and the message perception to obtain message variation, the message sequence for generating test cases is generated according to the message variation, and the key state of the network protocol is tested by using the test cases. The present application can obtain higher edge coverage, more crash triggers and faster first crash trigger, and has good application prospect.

The invention discloses an aircraft rotating frame detection method and system based on cyclic angle coding, and relates to the technical field of image processing, and the method comprises the steps: obtaining a target image of a to-be-detected aircraft; performing cyclic angle coding on the angle domain to obtain a cyclic angle coded value; performing angle prediction on the target image based on the cyclic angle coded value to obtain an angle initial coded value and an angle residual coded value of the to-be-detected aircraft; generating a target angle coded value of the to-be-detected aircraft according to the angle initial coded value and the angle residual coded value; decoding the target angle coded value into a target angle value; and carrying out rotation constraint on the sampling frame based on the target angle value to obtain a target frame, and carrying out feature extraction on the target image based on the target frame. According to the invention, the coding space and the physical angle space are strictly isomorphic in the topological structure, and the problem of boundary fracture is avoided; and the feature space alignment precision during rotation of the aircraft can be improved, so that the rotating frame of the aircraft can be detected more accurately.

The application relates to the technical field of archive management, in particular to an archive intelligent question-answering and automatic recording method and system based on a large language model. The method encodes archive business rules and original data into rule vectors and data vectors, and establishes a bijective mapping relationship to generate a reciprocal coding space. By encoding the query request into a query tensor, the tensor contraction operation is used to constrain the reasoning path, and the reconstruction is triggered when the rule is violated to generate the reasoning result. Then, the semantic gradient is calculated to identify and correct the recording field, and the correction is propagated in the association graph, and the rule is used to make a decision when there is a conflict. Finally, the field difference set is calculated, marked, merged and written to generate a recording version chain. The application realizes the intelligent linkage of question-answering and recording, and improves the automation degree and data consistency of archive processing.

The invention provides a malicious code detection method and system based on semantic analysis, and the method comprises the steps: determining a space where a suspicious code is located based on a monitoring behavior record of security software in a terminal, extracting a target code in the space, and reducing a subsequent malicious code detection interval range; based on the semantic feature extraction model and the text semantic classification model, generating a word sequence containing semantic information corresponding to the target code, and correcting the word sequence; analyzing the corrected word sequence based on a deep text classification model to obtain global text semantics of the target code so as to calibrate malicious code snippets in the target code, and performing code change operation on the space based on distribution characteristics of the malicious code snippets to obtain the target code. And meanwhile, global recognition is performed on the codes by utilizing a semantic feature extraction model and a text semantic classification model, efficient and accurate analysis of code semantics is considered, semantic information of the codes is comprehensively extracted, malicious code components are recognized and positioned in massive codes, and the working accuracy and reliability of security software are improved.

The invention relates to a data retrieval method based on adaptive space division and hash coding, and relates to the technical field of data retrieval. The method comprises the following steps: extracting feature vectors of original data and to-be-queried data; dividing a feature space Rd formed by the feature vectors based on a preset adaptive space division method, and repeating T times to generate T groups of feature space subunits of the Rd; distributing the data points of the Rd to the feature space subunits of the Rd; coding the T psi-bit vector sets H (x) based on a preset Hash coding mechanism, and connecting to generate an L-bit binary Hash code of each data point; and calculating the distance between the original data and the L-bit binary hash code of the to-be-queried data, and taking the original data corresponding to the minimum distance as a target retrieval result. The compact binary code is generated, and rapid similarity retrieval is realized in the binary code space, so that the problems of complex data coding, high calculation cost, low retrieval efficiency and high memory occupation in the prior art are solved.

The invention discloses a knowledge decision supervision method for watershed flood prevention, and relates to the technical field of watershed flood prevention, and the method comprises the steps: obtaining watershed flood prevention data and real-time meteorological data of a target region; performing knowledge extraction on the flood prevention data of the drainage basin to obtain spatial element information and non-spatial element information; coding the space element information according to a preset identity coding rule to obtain coded space element information; performing spatial topological relation construction on the encoded spatial element information by utilizing a geographic information system, and constructing a knowledge relation of a root primitive according to the constructed spatial topological relation to obtain a spatial element knowledge relation; fusing the non-spatial element information and the spatial element knowledge relationship, and converting a fusion result into a knowledge graph to obtain a fused knowledge graph; and inputting the meteorological data and the fused knowledge graph into a preset knowledge aided decision-making model, and outputting a decision-making result. According to the invention, the decision-making precision, the response speed and the early warning response efficiency are improved.

The invention discloses a built environment space friendliness evaluation method based on deep learning. The campus space is discretized into independent units, static space attributes, dynamic environment states and child behavior response data are integrated, and a unified space-time diagram structure is constructed. A topological relation between space units is captured through a graph convolutional network, a time sequence dynamic change is modeled by using a gating cycle unit, a fusion representation of a simultaneous coding space structure, environment fluctuation and behavior feedback is generated, and deep collaborative analysis of cross-modal information is realized. And on the basis of the fused spatial-temporal characteristics, a shared underlying network and a multi-branch output layer structure are adopted to synchronously predict a comprehensive spatial friendliness score and sub-dimension scores such as diversity and openness, and scientific decision support is provided for spatial layout transformation and optimization improvement of the campus.

The invention relates to a pixel antenna multi-objective optimization method based on a BPSO-MLP algorithm, and is applied to the technical field of wireless communication antennas. Global search is carried out in a high-dimensional discrete coding space of a pixel antenna through an improved binary particle swarm optimization algorithm, a dynamic temperature parameter is introduced to adjust the shape of a Sigmoid mapping function, and a probability-driven variation mechanism is adopted to effectively balance exploration and development capabilities; a performance prediction model is established through the designed multilayer perceptron neural network, and rapid and accurate prediction of key performance indexes such as bandwidth, gain and radiation pattern of a candidate antenna structure is realized; and submitting the predicted and screened high-potential solution to full-wave electromagnetic simulation through an intelligent optimization mechanism, feeding back a simulation result to an optimization algorithm, and dynamically updating a prediction model. According to the method, the problems of high-dimensional discrete search, high simulation cost and multi-performance index coordination in pixel antenna multi-target optimization are effectively solved, and an efficient solution is provided for reconfigurable antenna design of a new-generation communication system.

The invention discloses a method, system and equipment for optimizing SSD log records and a medium, and relates to the technical field of solid state disk log management.The method comprises the steps that description characters and formatted character strings in an original log printing function are removed, key parameters are reserved, and meanwhile retrieval fields are added; printing the simplified log containing the retrieval fields and the key parameters; establishing a mapping relationship among the description characters, the formatted character strings and the retrieval fields, and generating a log retrieval table; and based on the log retrieval table, analyzing the simplified log through a tool or a script, and restoring the real log to print. Only the key parameters are printed during printing, and other description characters (including formatted character strings) are omitted, so that the effect of not compiling the description characters in the compiling stage is achieved, the code space of an executable file after compiling is reduced, the consumption of a log function on the code space is reduced, the utilization rate of the log space is improved, and the user experience is improved. And meanwhile, the logs are compressed and restored without damage.

The invention discloses a stratum fracture pressure prediction method of a multi-input depth operator network with double embedding of physical information. Comprising the following steps: acquiring logging data and engineering parameter data of a to-be-predicted well section, then executing target perception mutual information grouping, calculating an input feature mutual information matrix, constructing a mutual information fingerprint vector, weighting and clustering according to the correlation between the mutual information fingerprint vector and fracture pressure, obtaining feature subsets, and respectively inputting the feature subsets into a multi-branch sub-network; a depth operator network is constructed, a backbone network takes well depth as input coding space dependence, a multi-branch sub-network extracts grouping features, an attention module performs adaptive weighted fusion on each branch representation, and adaptive physical constraint is performed through a physical layer; according to the method, the prediction curve of the fracture pressure changing along with the well depth can be output through the physical information double-embedded multi-input depth operator network, the prediction accuracy, the physical consistency and the cross-well-section generalization ability are improved, and the method is suitable for well wall stability analysis and fracturing parameter optimization.

The application discloses a kind of distributed mixed flow water workshop scheduling optimization methods based on greedy workpiece insertion, comprising: obtaining current scheduling solution, identifying key factory and key workpiece;Select the non-key factory with the minimum completion time as the target factory;From the first process of key workpiece, sequentially insert each process into the best insertion position of the corresponding processing stage of target factory to make the longest path length through the process minimum;After insertion, update the head length of affected process, obtain new scheduling solution.The present application is based on the longest path length minimization criterion of solution space, greedily inserts each process of key workpiece into the best position one by one and updates the head length in real time, realizes the accurate disturbance of critical path and the rapid evaluation of neighborhood solution, significantly improves the search accuracy and calculation efficiency of neighborhood movement between factories, solves the technical problems of poor controllability, low precision and long time caused by extensive movement and global re-encoding in the coding space.

The application relates to the technical field of remote collaborative embedded development, and discloses a remote collaborative embedded development system and method, wherein the remote collaborative embedded development method comprises the following steps: receiving developer editing behavior data, constructing a multi-dimensional intention vector field, obtaining an intention vector representation, reading embedded source code, performing code structure topology mapping, forming a code structure topology representation, fusing the two to create a unified intention-code space model, calculating a conflict entropy distribution to generate a distribution diagram, adopting a self-organizing optimization method to generate an optimal code merging scheme, and constructing an intention visual interface to form a collaboration environment; the application effectively solves the core technical problem of remote collaborative development, improves development efficiency and code quality, enhances conflict management capability, promotes the formation of collective intelligence, and accelerates the integration of new members.

The invention provides a storage space management method, device and equipment of an intelligent card, and is applied to the technical field of intelligent cards, the storage space of the intelligent card comprises a code area and a data area, and the method comprises the following steps: extracting a code to be released from COS codes based on a preset code extraction strategy; the to-be-released code is a code which is only executed for a preset number of times before the smart card is only in the personalization stage. And compiling the to-be-released code to the to-be-released code area by using a compiling tool, and calculating the storage space occupied by the to-be-released code. The to-be-released code area is located at the tail of the data area. And performing space release on the to-be-released code area based on a space release instruction sent by the upper computer. And distributing the released to-be-released code area to a data area of the storage space. The problem that the code space saved by an existing method for optimizing the storage space of the intelligent card is limited can be solved.

The invention relates to the technical field of industrial robot and mechanical arm motion control, in particular to a mechanical arm multi-target motion path planning method and system. The method comprises the following steps: firstly, constructing a scene graph state structure containing geometric, topological and real-time states by integrating multi-source data; constructing a multi-objective cost function fusing time, energy consumption, risk and collaborative constraint based on the structure, and coding by using a graph neural network; carrying out state construction and strategy training on the coding space by applying reinforcement learning, and generating a candidate path set of cooperation of multiple mechanical arms; and finally, performing collision detection, optimization screening and smoothing processing on the candidate paths through digital twinborn simulation, configuring a local re-planning mechanism, and finally generating a control instruction. According to the method, the path planning collaboration, safety and comprehensive efficiency of the multi-mechanical-arm system in a complex scene are effectively improved.

The invention discloses a video compression method based on motion estimation and affine transformation substitution. The method comprises the following steps of: 1, performing feature analysis and initial coding on an image to realize initial compression of an original video frame, and establishing spatial geometric association between adjacent frames; 2, mapping high-resolution homography to a low-resolution coding space by using a down-sampling matrix based on spatial geometric correlation to obtain a down-sampling homography matrix; step 3, according to the mask region of the moment coding data obtained by calculation in the step 2, separating to obtain a code of a cutting background, namely a code of an increment background, and realizing differential compression; and 4, according to the codes of the incremental background obtained in the step 3, the decoding end combines the stored codes at the T-1 moment to splice and fuse reconstructed coding data at the T moment, and then video frames are decoded. According to the invention, the adaptive compression coding capability for different regions in the video compression process is effectively improved.

This invention discloses a spectral coding optimization method and imaging system based on the minimum distance in the coding space. The core of this invention lies in proposing a design criterion that maximizes the minimum Euclidean distance between the corresponding vectors of any two different spectral samples in the coding response space. This directly improves the separability of different spectra at the detector end from a geometric perspective, thereby enhancing the system's robustness to noise and disturbances. To efficiently solve this non-convex optimization problem, this invention proposes a global-local joint optimization strategy. The spectral encoder structural parameters optimized based on this method can be applied to computational spectral imaging systems. This system, through encoder modulation, signal detection, and sparse reconstruction, ultimately outputs a spatial-spectral three-dimensional data cube of the target object. This invention effectively overcomes the shortcomings of traditional design criteria that do not directly consider geometric separability and the tendency of single optimization methods to get trapped in local optima, significantly improving the system's reconstruction accuracy and stability.

The invention belongs to the technical field of mixing test design, and particularly relates to a mixing test method and system with a limited test space, and the method comprises the steps: obtaining a test space based on response variables, test factors, and equality constraints and lower bound constraints among the test factors in a mixing test; obtaining a transformation relation between coordinates of any point in the test space and a natural space and a coding space; based on the transformation relation, obtaining distribution of test points and a test scheme by adopting a simplex gravity center design method; performing a mixing test based on the distribution of the test points and the test scheme, collecting test data, and constructing a regression model; and obtaining the optimal combination proportion of each mixing component based on the regression model. According to the method, the accurate mixing test regression model can still be efficiently established under the condition of extremely limited test times, and optimization of key performance indexes and cooperative control of component cost are achieved.

The application discloses a method for recognizing distraction driving behavior based on an improved DCH neural network, which comprises the following steps: constructing a hyper-dimensional calculation model; firstly, constructing an improved DCH neural network; replacing an ADAM optimizer in the DCH model with an improved artificial traveling mouse optimizer; then, using the improved DCH neural network to perform hyper-dimensional vector coding; in a hash code space, the Hamming distance of hash codes of semantically similar images is close, and the Hamming distance of semantically dissimilar images is far; finally, classifying image information of the same category to form a category hyper-dimensional vector; constructing an AdaptHD retraining model; using the model to calculate a classification accuracy rate, and calculating the similarity between all training samples and the category hyper-dimensional vector again; training the model, testing a data set by using the trained model; and outputting a test result; and the application improves the efficiency of the algorithm within an acceptable range of detection precision, reduces the time for training the model, and no longer depends on high-performance edge computing devices.

The invention discloses a pedestrian detection-oriented physical adversarial patch generation and migration method, and belongs to the field of computer vision and artificial intelligence security. The invention provides a shape-texture two-stage layered optimization and Min-Max robust migration framework aiming at the problems of abrupt patch shape, difficulty in reproduction of pixel-level noise and poor environmental adaptability in the existing physical countermeasure attack. The method comprises the following steps: firstly, constructing a smooth patch contour by using a centripetal Catmull-Rom spline curve, and optimizing an anchor point coordinate through a differential evolution algorithm so as to lock an effective receptive field which is most sensitive to a model; secondly, constructing a discrete texture coding space based on a physical adhesive tape, and searching an optimal stripe texture formed by the color, width and direction of a standard adhesive tape in a fixed shape; meanwhile, a Min-Max robust optimization strategy is introduced, and the anti-interference capability of the patch is improved by minimizing the maximum confidence coefficient under the worst illumination transformation; and finally, a physical mapping strategy based on vector reconstruction is adopted, a precise transformation model from pixels to millimeters is established, and an SVG vector manufacturing file irrelevant to resolution is output. According to the method, precise closed loop of the anti-patch from digital algorithm optimization to physical object manufacturing is realized, and the method has the advantages of high physical realizability, natural and hidden shape, high environmental robustness and the like.

This application provides a method, apparatus, and device for managing the storage space of a smart card, applicable to the field of smart card technology. The storage space of the smart card includes a code area and a data area. The method includes extracting code to be released from the COS code based on a preset code extraction strategy. The code to be released is code that will only be executed a preset number of times before the smart card is personalized. A compilation tool is used to compile the code to be released into the code to be released area, and the storage space occupied by the code to be released is calculated. The code to be released area is located at the end of the data area. The space to be released is released based on a space release command sent by a host computer. The released code to be released area is allocated to the data area of ​​the storage space. This method can solve the problem of limited code space savings in current methods for optimizing the storage space of smart cards.

The present invention discloses a virtual machine scheduling heuristic function optimization method based on a large language model, which realizes optimization and efficiency improvement in online virtual machine scheduling by integrating the two ideas of discovery strategy and discovery reflection. Specifically, it includes: designing and constructing an online virtual machine scheduling simulator including a virtual environment engine and a scheduling allocation system, which is used to simulate the virtual machine scheduling process in a cloud computing environment; through a policy mining module, the generation and reasoning capabilities of the large language model are used to generate an initial scheduling strategy, and the strategy is optimized through a code space reinforcement learning method to improve scheduling efficiency; combined with the optimization history, the reflection mining module is used to analyze the previous optimization path, extract effective strategy parameters and generate optimization guidance to avoid repeated invalid exploration, thereby optimizing the global scheduling strategy. The present invention shows higher adaptability, flexibility and global optimal strategy search capabilities in complex cloud computing environments, and has broad application prospects.

The invention discloses an electric power secondary equipment code memory change detection positioning system and method. The system comprises upper computer detection software, a device management plug-in and a monitored core processing plug-in, wherein the device management plug-in and the monitored core processing plug-in communicate with the upper computer detection software; the method comprises the following steps: configuring a CPU memory code segment; the upper computer obtains CPU code space distribution of the device; forming a code memory space configuration file; the upper computer software sequentially obtains the normal code memory space of each plug-in; the device performs code memory change detection and alarm; and the upper computer software reads the memory space value of the abnormal operation code of the alarm CPU, and the upper computer locates the memory change position. According to the method, the dependence on the resources of the processor is effectively reduced, a method for accurately positioning the fault is provided, and the situation that the operation needs to be quitted for maintenance due to function failure caused by a single fault in the equipment engineering operation process is reduced.