605 results about "Exception handling" patented technology

The invention discloses a dynamic multi-modal data fusion and real-time analysis method, and particularly relates to the technical field of data analysis. Carrying out standardization and time alignment on the multi-modal data, evaluating the stability of each modal in the current scene, and calculating a stability score; extracting features by using a deep neural network, fusing the features, detecting abnormal synchronization offset between modes in real time, and calculating collaborative offset intensity; based on the combined feedback of the stability score and the offset intensity, soft shielding processing is executed on the suspected abnormal mode; the future fusion risk is further evaluated through a time sequence prediction algorithm, and the model execution process is interrupted and an exception handling mechanism is triggered when necessary, so that the reliability and the safety of the multi-modal system in a complex environment are remarkably improved.

The invention relates to the technical field of information, and discloses a ciphertext execution exception handling method and system for a privacy computing algorithm, which quantifies the data query sensitivity of each tenant by collecting differential privacy query parameters of a plurality of tenants, and performs time sequence analysis on the sensitivity quantification result by using an ARIMA model to predict the future trend of the tenant, so as to improve the accuracy of the ciphertext execution exception handling of the privacy computing algorithm. The residual error between the actual sensitivity and the predicted sensitivity is calculated to identify abnormal tenants; a sliding window method is adopted to extract statistical features of the abnormal tenants to construct a feature set, and clustering analysis is carried out on the feature set to identify abnormal modes and abnormal fingerprint feature clusters corresponding to the abnormal tenants; and training a model based on the positive and abnormal fingerprint feature clusters of the abnormal tenants, and quantifying the influence degree of each abnormal mode on the privacy protection level of the abnormal tenants by using the model, so as to adjust and execute the privacy budget allocation proportion of each abnormal tenant according to the obtained quantitative analysis result. And therefore, the exception in the ciphertext execution of the privacy calculation algorithm can be effectively processed.

The invention relates to the technical field of process management, and discloses a lightweight process management method, which comprises the following steps of: defining a business process and analyzing the business process through a process engine; a graphical process design interface is provided, and a user can dynamically configure business process nodes through dragging and clicking operations; the business process is disassembled into a plurality of task nodes, and each task node is packaged into an independent function module through modularization design; the task nodes are combined according to needs and executed in parallel on different processors, and efficient execution of the task nodes is ensured; the execution state of the business process is monitored in real time, and potential problems are found and processed in time through log recording and an exception processing mechanism. According to the technical scheme of supporting dynamic adjustment of the task nodes and optimizing parameters based on the historical abnormal mode, execution parameters of the task nodes are dynamically corrected, association logic between the nodes is adjusted in real time, and the effects that process management is flexible and adapts to complex service scenes, and operation stability is improved are achieved.

The invention provides a large model agent collaborative scheduling method and system oriented to complex tasks, relates to the technical field of artificial intelligence, and comprises the steps of task decomposition, feature extraction, agent matching, dynamic scoring, scheduling scheme generation and optimization, execution monitoring, exception handling and the like to realize efficient collaboration of large model agents. According to the method, accurate matching can be carried out according to task characteristics and intelligent agent capabilities, the task completion efficiency and quality are improved, meanwhile, the dynamic adjustment capability is achieved, abnormal conditions in the execution process are effectively handled, and the system robustness is enhanced.

The invention relates to the technical field of equipment abnormity control, and discloses an equipment abnormity self-closed-loop control system. An anomaly detection engine of the system collects operation state data of target equipment in real time, and performs preliminary anomaly marking according to a preset anomaly judgment rule; the dynamic analysis unit receives the preliminary anomaly marks, generates anomaly feature vectors in combination with historical operation data, and inputs the anomaly feature vectors into a multi-dimensional evaluation model to divide anomaly levels; a strategy generator is matched with a preset repair strategy library according to the abnormal grade division result, and a corresponding repair instruction sequence is generated; the execution control module analyzes the repair instruction sequence, and dispatches hardware resources to execute repair operation according to a preset execution priority; and the feedback verification unit collects the running state data again after restoration, and compares the running state data with the initial abnormal mark to generate a restoration verification result. The system realizes full-process automatic processing of equipment exceptions, and improves exception processing efficiency and equipment operation stability.

The invention provides a software code defect detection method and system based on program code feature fusion, and the method comprises the steps: carrying out the grammar and structure inspection of a code through a static analysis tool, and extracting defect features related to control flow chaos, exception handling and resource leakage; running a preset test case through a dynamic analysis tool, capturing an execution path and an abnormal behavior in a runtime state, and obtaining defect features which are not covered by static analysis; if the output result of the decision tree model is that defects exist, grouping comprehensive defect feature vectors by adopting a density-based clustering algorithm, determining the types and distribution ranges of the defects, and selecting the density clustering algorithm to process defect features in non-spherical distribution; and according to a clustering result, generating a defect repairing suggestion, combining code logic and execution path information, and determining a specific position and an influence range of the defect. According to the method, the stealth defect in the code can be effectively identified and positioned, the software quality and reliability are improved, and timely and accurate defect repairing guidance is provided for developers.

The invention discloses a dynamic script compiling and hot updating system based on Grouping and an implementation method of the dynamic script compiling and hot updating system. The system comprises a script source code management module, a dynamic compiling engine, an intelligent cache manager, an exception handling and recovery system and a hot update controller. And the script source code management module receives and preprocesses the Grouping script to generate a unique identifier for subsequent management. And the dynamic compilation engine executes compilation operation according to the identifier to ensure that a compilation result accords with a specification. And the intelligent cache manager efficiently stores and retrieves the compiling result, so that the repeated compiling cost is reduced. And the exception handling and recovery system monitors the execution state in real time, and automatically starts a recovery process in case of exception to guarantee stable operation of the system. The hot update controller realizes seamless update and version switching of scripts, and ensures service continuity. Through cooperative work of the modules, high-reliability, high-performance and zero-shutdown deployment is realized.

The invention relates to the field of industrial automation testing, discloses a multifunctional testing tool and method for an EUROMAP interface of an injection molding machine, and achieves the crossing from single function verification to system-level compliance evaluation. A test network is constructed through a controller, and deep compliance verification, coverage data interaction, exception handling and cross-layer response consistency are realized. The test tool integrates the functions of protocol analysis, signal simulation, fault injection and the like, supports dynamic generation of boundary value test scenes and abnormal injection of signal delay, CRC errors and the like, and verifies the time sequence / logic consistency of a protocol instruction and an execution mechanism response through a hardware-level timestamp alignment technology. According to the method, an evaluation report including compliance rating, fault diagnosis and optimization suggestions is automatically generated, the problems of single coverage dimension, insufficient abnormal simulation, cross-layer verification deficiency and the like of a traditional test are solved, the intelligence and standardization level of the injection molding machine interface test is remarkably improved, and the equipment interconnection and intercommunication performance is guaranteed.

The invention relates to the technical field of storage, in particular to a test method, device, equipment, system, medium and product, and the method comprises the steps: obtaining a test management command of an input and output management command representing error injection in a real working environment of a disk array controller chip; the command is analyzed to obtain the error injection test type and the corresponding related parameters, and the error processing mode is changed according to the error injection test type, so that the exception is only reported and not processed when encountering the exception in the test, the interference of exception processing on the test process is avoided, and the test can be smoothly carried out according to the preset error injection scene; and according to the error injection test type and the related parameters, constructing analog input and output and injecting the analog input and output into the target hardware unit to perform an execution behavior test, thereby realizing accurate test of the specific hardware unit in a specific error scene in an environment of performing input and output test based on a read-write input and output test program, so that the test is more comprehensive, and the test efficiency is improved. And the test precision is higher.

The invention discloses a scheduling instruction real-time monitoring system for streaming data processing, which relates to the technical field of streaming data processing and comprises a data access module, an instruction analysis module, a dynamic scheduling strategy module, a real-time monitoring module, a scheduling execution module, a visual monitoring interface, an exception handling module and an extension module. The data access module is used for receiving a multi-source heterogeneous data stream in real time and carrying out protocol analysis and priority marking on input data, and the instruction analysis module is connected with the data access module and is used for extracting a scheduling instruction in the data stream and converting the scheduling instruction into executable operation; and the dynamic scheduling strategy module generates a dynamic scheduling strategy based on the real-time data traffic, the system load and a preset rule. Through the dynamic scheduling strategy module and real-time monitoring feedback, the system can automatically adjust resource allocation according to real-time load prediction, and dynamic balance of high resource utilization rate and low delay is achieved.

The invention discloses a game controller dynamic configuration system, and relates to the technical field of computers. The system comprises a controller end and a host end. The controller end adopts a heterogeneous equipment hybrid communication protocol stack to realize bidirectional data synchronization between the host end and the controller end; the controller end comprises a trigger, a selector, an interceptor, a switch assembly, a dynamic resource configuration unit and a firmware upgrading interface; the host end comprises an equipment dynamic identification and registration module, a game semantic analysis module, a dynamic mapping strategy generation model, a user adaptive learning unit, a multi-modal feedback fusion unit and a security verification and exception handling unit. According to the method, the mapping relation library of the controller hardware features and the game scene parameters is established, the physical state data of the controller is collected in real time through the sensor group, and the dynamic matching rule is generated in combination with the role action threshold in the game scene, so that the controller configuration difficulty is reduced, and the controller configuration efficiency is improved.

The invention discloses an intelligent timed task configuration and multi-mode feedback system based on natural language interaction, and relates to the field of industrial automation control, enterprise-level task scheduling management and instant messaging. The system comprises a natural language interaction module, a user natural language instruction is converted into structured semantic information through a BERT + BiLSTM + CRF mixed architecture, and lightweight processing is achieved in combination with TinyBERT distillation; the dynamic task arrangement module completes task creation, modification and the like based on structured information, completes missing parameters through historical task mode matching, and supports multi-session real-time synchronization; the rich media report generation module generates a multi-mode report containing charts, tables and the like, and the RAG technology and large model interpretation are combined; and the multi-channel pushing adaptation module adapts multiple platforms by adopting a strategy and factory mode. According to the system, the task configuration efficiency and flexibility are improved, the feedback form is enriched, the information pushing accuracy is guaranteed, and the exception handling capacity is enhanced.

The invention discloses an exception handling method and device for an embedded system, equipment and a storage medium, and relates to the technical field of embedding. The method comprises the steps of determining a current operation mode of a target processor according to a program state register of the target processor under the condition that abnormal codes appear in the operation process of the target processor in a target embedded system; according to the program state register, switching the current operation mode into a target operation mode, and obtaining a stack pointer value of a stack pointer register of the target processor in the target operation mode; and determining a target function address of a target function to which the abnormal code belongs and a call chain of the target function according to the stack pointer value. According to the technical scheme, the target function address is determined according to the stack pointer register, and before the target function address is determined, the target processor is switched to the target operation module and the interrupt is closed, so that interruption in the exception handling process can be effectively avoided, and the exception handling reliability can be improved.

The invention relates to an operating system startup exception processing method and device, equipment, a medium and a program. The method comprises the steps that when an operating system is started, a loading program is guided to load an external initramfs file into a memory, and an initial address of the external initramfs file is transmitted to a kernel of the operating system; performing Hash verification on the external initramfs file by executing the Hash verification function to obtain a Hash value of the external initramfs file; the operating system kernel decompresses the external initramfs file into a root file system according to the initial address; and when it is determined that the external initramfs file cannot be normally decompressed, determining a decompression failure reason according to a comparison result of the hash value of the external initramfs file and an expected hash value. And reporting the decompression failure problem to the corresponding processing object according to the decompression failure reason. By adopting the method, the decompression failure reason can be quickly and accurately positioned, the decompression failure problem can be pointedly processed, and resource waste is avoided.

The embodiment of the invention provides an application log exception processing method and device, equipment and a storage medium, and the method comprises the steps: extracting exception information corresponding to an application identifier from original log data, and determining a target keyword and a target time range based on a preset alarm rule and the exception information; determining candidate log data from the original log data according to the target time range and the target keyword, and filtering the candidate log data to obtain target log data; inputting the target log data and a set prompt text into the target network model to obtain a problem description text and a solution description text; and determining a manual processing description text associated with the problem description text from a stored manual processing record corresponding to the application identifier, fusing the solution description text and the manual processing description text to obtain a target scheme description text, and feeding back the target scheme description text to the background server. According to the scheme, the log exception processing efficiency can be improved.

Disclosed in the present invention are a method and apparatus for performing full-link reconciliation on the basis of a snowflake algorithm, and a device and a medium. The method comprises: responding to a cross-border business reconciliation request, and acquiring bill source data from a business terminal; parsing the acquired bill source data, and converting same into target bill data; calling a reconciliation rule engine to acquire a corresponding reconciliation rule and select a corresponding reconciliation algorithm, and executing a full-link reconciliation task for the target bill data, so as to obtain a reconciliation result; transmitting reconciliation imbalance data to a corresponding exception handling system for checking processing of abnormal data; and on the basis of an optimized snowflake algorithm, generating a unique target ID to associate a corresponding bill with the reconciliation result, automatically penetrating full-link data of an information flow and a fund flow on the basis of the corresponding unique target ID in the reconciliation result, and on the basis of the unique target ID, tracing the whole process of the circulation of a corresponding bill between the fund flow and the information flow, so as to achieve a complete reconciliation closed loop. In this way, the reconciliation working efficiency and data accuracy of the full-link reconciliation of a cross-border business are improved.

The invention provides a control method, device and equipment for an FMS production line warehouse system based on fault warning and elimination verification and a storage medium. The control method comprises the steps that material attribute information is acquired, a classification model based on machine learning is adopted to conduct classification and recognition on materials, a unique material identification code is generated and bound with an electronic tag, and a real-time material tracking system is established; a storage position distribution model based on multi-objective optimization is constructed, material relevance, use frequency and warehouse constraint conditions are considered, a material storage position distribution scheme is generated, and a corresponding carrying equipment control instruction is generated; a real-time monitoring and exception handling mechanism is established, and when it is detected that the actual state of the material does not accord with the system record, a fault warning process is triggered, an exception handling control instruction is generated, and a correction action is executed; the material demand prediction is carried out based on the neural network model, the replenishment control instruction is generated according to the prediction result, the accuracy of the execution result is ensured through a secondary verification mechanism, and the reliability of the warehouse system is improved.

The invention discloses a verification method for a second-level cache interface protocol, which belongs to the technical field of multi-core verification, and comprises the following steps of: setting verification targets, including function correctness, performance standard, compatibility and exception handling capacity; establishing a verification environment, wherein the verification environment comprises a hardware platform and a test tool; function verification, including read-write operation verification, cache line state transition verification and consistency verification; performance verification including delay testing and bandwidth testing; the compatibility verification comprises the compatibility with a first-level cache and the compatibility with a processor core; the abnormal condition verification comprises interrupt processing verification and error injection verification; and analyzing a test result. According to the verification method for the second-level cache interface protocol, the second-level cache interface protocol can be comprehensively and deeply verified, the function correctness, the performance standard reaching performance and the compatibility with other components of the second-level cache interface protocol are ensured, and a solid guarantee is provided for stable operation of a high-performance computer system.

The invention discloses an agent assisted testing method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring demand information of a Web system to be tested; analyzing the demand information and generating a test case set; performing hierarchical labeling on the test case set to form a hierarchical case set containing the basic operation type case, the data verification type case and the complex logic type case; distributing the basic operation type use case to an execution module of the agent system, distributing the data verification type use case to an interface automation test module, and distributing the complex logic type use case to an artificial interaction terminal; and when the execution module or the interface automatic test module monitors that the case execution fails or the state is abnormal, an exception processing strategy is matched according to an exception type and an exception source, corresponding processing operation is executed, and feedback information used for optimizing the layered case set is generated. According to the method, the test tasks can be intelligently allocated and accurately executed, and automatic adaptation and optimization can be performed when an exception occurs, so that an efficient man-machine collaborative test is formed.

The invention relates to an automatic interface test management method and device, equipment and a medium, and the method comprises the steps: obtaining an interface document of a to-be-tested interface, carrying out the analysis of the interface document, generating interface case data containing the primary configuration content of an interface case, and transmitting the interface case data to a server; performing execution grouping on the interface cases configured with the input parameter value set, generating a case execution group based on interface grouping information and a preset test execution strategy, setting an execution sequence and an exception handling rule for the case execution group, and generating a corresponding execution link at the same time; calling an execution link based on the trigger request to sequentially use each group of request content execution cases in the input parameter value set to execute the interface cases in the group, and generating corresponding case execution results; high automation and intelligentization are achieved in the whole interface test process, manual intervention is remarkably reduced, the test coverage rate is increased, the problem response speed is increased, and therefore the working efficiency of testers is effectively improved, and the human error risk is reduced.

The invention relates to a service orchestration method based on a multi-tenant micro-service architecture, in particular to the field of distributed systems, comprising the steps of creating a thread pool and defining a private final pipeline, creating a pipeline builder and appointing each stage in the pipeline, generating a pipeline execution class, and initializing a pipeline processing overall business process. The method comprises the following steps: establishing a pipeline object, packaging into different processors, creating a pipeline object, effectively processing concurrent tasks, carrying out reasonable processing under an overtime condition, avoiding waste and blockage of system resources, adding each processor into a pipeline and inserting an interceptor into the pipeline, enhancing expandability and flexibility of a system, and improving system performance. The output results of the processors are combined into a final result, exception handling and rollback operation are carried out, the steps of the whole business process are divided into a plurality of sub-tasks, parallel execution and serial execution sub-task groups are formed, the execution sequence is determined, and the response speed and the concurrent processing capacity of the system are improved.

The invention provides an exception handling method and an exception handling module, and relates to the technical field of processors, in particular to the technical field of processor exception handling. According to the specific implementation scheme, under the condition that a first processing component in a plurality of processing components is abnormal, a target thread where the first processing component is located is determined, and the target thread is one of a plurality of parallel threads; at least one second processing component occupied by the target thread is determined, and the at least one second processing component comprises the first processing component; and sending a pause control signal to the at least one second processing unit, the pause control signal being used for the at least one second processing unit to pause the operation.

The invention provides an automatic learning engine device based on a packaging large model training platform, and the device comprises a unified access specification module which carries out the standardized training and reasoning parameter configuration through a YAML configuration template file; the multi-device support and parallel computing framework module is compatible with three hardware devices including a CPU (Central Processing Unit), a GPU (Graphic Processing Unit) and an NPU (Network Processing Unit), and supports two parallel computing frameworks including Accelerate and DeepSpeed; the training engine module adopts a three-layer architecture to realize task allocation, state monitoring and exception handling; and the training algorithm framework module is used for analyzing the running configuration file, carrying out data set splitting and data format conversion, supporting various fine tuning training methods and evaluating the model. According to the overall scheme, the technical threshold of large model fine adjustment is lowered, non-professional personnel can complete complex model training tasks through simple configuration, and popularization and application of the large model technology are promoted.

The invention discloses a power embedded RTOS-oriented clock management method and related equipment, and the method comprises the steps: collecting the current clock data of a power embedded RTOS system, carrying out the feature extraction of the current clock data, constructing a clock feature library, and constructing a clock data model in a normal clock operation state, generating normal clock data according to the clock data model; the frequency stability, the clock jitter rate and the clock drift rate of the current clock data are calculated, and whether the deviation between the current clock data and the normal clock data exceeds a clock threshold value or not is judged; and when the deviation exceeds the clock threshold value, executing a corresponding exception handling flow according to the frequency stability, the clock jitter rate and the clock drift rate, and dynamically adjusting the range of the clock threshold value. According to the embodiment of the invention, combined judgment and dynamic adjustment can be carried out by combining drift, jitter and frequency stability thresholds, and accurate monitoring and anomaly detection of the clock are realized. The method can be widely applied to the technical field of clock management.

The invention relates to the technical field of internet-of-things control management, in particular to an intelligent internet-of-things control management system based on commercial operation, which comprises a data acquisition and alignment module, a strategy generation and authority module and an instruction execution and exception handling module. The data acquisition and alignment module is used for acquiring an equipment state, an environment parameter and a user instruction, and completing standardized processing and space-time alignment to generate a unified data set; the strategy generation and permission module generates a control strategy according to a service rule, divides permissions according to user roles, and generates a role instruction set; and the instruction execution and exception handling module issues an instruction to the equipment, monitors an execution state, and triggers rollback, work order generation and permission verification mechanisms when an exception occurs. According to the invention, high-precision sensing, intelligent control and safe and efficient Internet of Things equipment management are realized.

The invention discloses an equipment exception handling method and device, equipment, a medium and a product. The method comprises the following steps: in response to an exception handling request for target equipment, determining an alarm text sent by a secondary master station system, and extracting exception alarm information in the alarm text to generate corresponding structured data; according to the structured data, performing matching in a preset case library to obtain a target case, and determining a processing effect evaluation value corresponding to the target case; and according to the structured data, the target case, the processing effect evaluation value of the target case and the current operation data, determining an exception handling decision and a decision priority of the target equipment, so as to perform exception handling on the target equipment. According to the technical scheme, intelligent and automatic decision support of the secondary equipment of the converter station can be realized, and related personnel can be helped to make decisions quickly and accurately, so that the reliability and the operation and maintenance efficiency of the equipment and the stability of a power grid are improved.

The invention discloses an OTA upgrade process customizing method and system adaptable to multiple vehicle types, and relates to the technical field of OTA upgrade.The OTA upgrade process customizing system comprises an OTA upgrade process customizing layer, is compatible with an existing OTA network architecture, and mainly relates to upgrade strategy management, dependency management, task scheduling and exception handling technologies; a user can customize upgrading paths of different vehicle types through the upgrading strategy management module; dynamically distributing upgrading tasks through an upgrading task scheduling module; analyzing the dependency relationship of the software component through a dependency relationship management module; the user-defined upgrading process is executed through an OTA upgrading execution module; and a log recording and exception handling mechanism is provided through the exception handling and log management module. Therefore, by the adoption of the OTA upgrading process self-defining method and system capable of adapting to the multiple vehicle types, OTA upgrading optimization of the different vehicle types can be achieved, the success rate is increased, and the maintenance cost is reduced.

The invention relates to the technical field of Internet of Things, in particular to a decision-making method for computing power balanced allocation between Internet of Things devices, which comprises a task allocation module, a resource management module, a dynamic adjustment module and a priority regulation and control module. The task distribution module decomposes tasks and generates a preliminary distribution scheme; the resource management module monitors equipment performance and classifies the equipment performance; the dynamic adjustment module optimizes an allocation strategy by using a particle swarm optimization algorithm; and the priority regulation and control module regulates the task sequence according to the weight and ensures the high-priority task resource demand. The system stability is enhanced through the exception handling unit and the load prediction unit, the computing power distribution efficiency and the resource utilization rate are improved, and efficient and flexible task execution is achieved.

The invention discloses a system exception handling method, device and equipment, a medium and a product. The method comprises the steps of determining a current model file and a current program version corresponding to target equipment in the substation secondary system in response to an anomaly detection request for the substation secondary system; according to the current program version, determining a standard model file from a preset standard database, and based on a preset text analysis model, respectively determining a standard semantic vector and a current semantic vector corresponding to the standard model file and the current model file; and performing feature fine-grained matching interaction on the standard semantic vector and the current semantic vector to obtain a semantic generality vector, and determining a difference semantic vector and a corresponding exception level according to the semantic generality vector and the current semantic vector to perform exception processing. According to the technical scheme, the file of the transformer substation system can be analyzed and compared through the text analysis model so as to carry out anomaly detection on the system, and therefore targeted anomaly processing is facilitated.

The invention relates to the technical field of equipment exception handling, and discloses an equipment exception handling system based on multi-modal data linkage, which comprises a sensor, a multi-modal exception detection and trigger module, a lightweight AI model and the like, the invention further provides an equipment exception handling method based on multi-modal data linkage, and the method comprises the following steps: S1, parameter monitoring: collecting operation parameter data and position information data of equipment through a sensor; compared with a traditional system which needs to separately collect equipment data and video data from multiple sources for analysis and response, the method has the advantages that the whole process from abnormal triggering to data analysis to control completion is greatly accelerated, and meanwhile, the false alarm rate can be greatly reduced through multi-modal data fusion; the root cause analysis accuracy is greatly optimized compared with that of a traditional analysis method.