CN-121979321-A - Impact machine temperature control method with multi-standard dynamic mapping and scene perception

CN121979321ACN 121979321 ACN121979321 ACN 121979321ACN-121979321-A

Abstract

The invention relates to a multi-standard dynamic mapping and scene-aware temperature control method of an impact machine. The method comprises the steps of obtaining original temperature data of a tested device through a preset temperature acquisition device with thermal, electric and magnetic three-in-one isolation, constructing a standard adaptation rule base based on dynamic mapping of the original temperature data, and obtaining a result of matching multi-source data conversion with a target format through a standard factor algorithm. The method comprises the steps of adopting multi-scale anomaly detection and cross-standard verification to carry out standardized verification on data, analyzing test interface characteristics through a scene recognition module, generating scene recognition results, driving a mode switching rule, outputting scene-adaptive temperature control adjustment data, generating a dynamic temperature control instruction based on a self-adaptive strategy, driving a heat flow module to carry out standard temperature control on a tested device through a multi-mode actuator, generating a multi-standard diagnosis result through an anomaly diagnosis engine, dynamically adjusting temperature control strategy parameters through an online updating mechanism, and realizing closed-loop control on a temperature control device.

Inventors

GU JIA
Wu sai

Assignees

上海世纪保德集成科技有限公司

Dates

Publication Date: 20260505
Application Date: 20251231

Claims (12)

1. The multi-standard dynamic mapping and scene-aware impactor temperature control method is characterized by comprising the following steps of: s1, acquiring original temperature data of a tested device through a preset temperature acquisition device with thermal, electric and magnetic three-in-one isolation; S2, obtaining an adaptation rule base of standard temperature data based on the original temperature data through dynamic mapping, converting the temperature data of corresponding standards based on the rule base by using a standard factor conversion algorithm to obtain a conversion result of the original temperature data, matching the conversion result of the original temperature data with a target format to obtain a matching result of the original data to the target format, carrying out multidimensional anomaly screening on the matching result by using a multiscale anomaly detection assembly, calling a preset anomaly judgment threshold value by using a cross validation engine, and carrying out cross-standard consistency check on the screened anomaly data to obtain checked temperature data; S3, obtaining a scene recognition result by using a test connection interface of a scene recognition module based on the temperature data, converting a temperature control mode type and a parameter adjustment dimension under a corresponding scene by using a mode switching rule based on the scene recognition result to obtain scene-adaptive temperature control adjustment data, generating a dynamic temperature control instruction by using a temperature control strategy self-adaptive generation module through the temperature control adjustment data, and controlling an impact machine heat flow module to execute the dynamic temperature control instruction by using a multi-mode actuator driving module to perform standard state temperature control on the tested device to obtain an impact machine temperature controller; S4, intelligently monitoring the temperature control device through standard state temperature control of the impact machine to obtain monitoring data of the temperature control device, generating a multi-standard diagnosis result of failure cause analysis by utilizing an abnormality diagnosis and root cause analysis engine, generating a parameter compensation instruction through a self-adaptive correction strategy library based on the diagnosis result, dynamically adjusting temperature control strategy parameters of a target device of the impact machine through an online updating mechanism based on the compensation instruction, and obtaining the temperature control device under a corresponding temperature control strategy.
2. The method of claim 1, wherein the original temperature is obtained by performing corresponding environmental isolation through a multilayer circuit, attaching a composite contact of a graphene heat conducting film to a device to be tested, constructing a low thermal resistance interface by using high thermal conductivity of graphene to obtain the actual temperature of the device to be tested, and performing adaptation operation with a chip packaging device through die compatibility based on the actual temperature to obtain original temperature data.
3. The method of claim 1, wherein the specific process of obtaining the adaptation rule base of the standard temperature data comprises the steps of carrying out structural analysis on a text of a target standard based on a rule template and a semantic analyzer, and extracting parameter definitions, measurement units, test conditions and tolerance requirements in the standard to obtain a standard metadata set; Based on the standard metadata set, establishing a mapping relation pair between corresponding standard terms through a similarity matching algorithm of keyword weight and context association degree; And generating a conversion rule set between standards through a deterministic rule engine and an interpolation function library based on the mapping relation pair and the systematic deviation, and constructing a standard temperature data adaptation rule library.
4. The method of claim 1, wherein the conversion data of the original temperature is characterized by comprising the specific processes of converting a measurement unit, a sampling frequency and an accuracy level of multi-source heterogeneous temperature data to a standard frame of a target standard through a dimension normalization engine and a statistical caliber alignment algorithm based on a standard mapping relation and systematic deviation stored in the adaptation rule base, and carrying out standardized reconstruction on the dimension, scale and distribution characteristics of the original temperature data through a standard factor matrix and a linear transformation model based on the standard frame and obtaining a conversion data set of the original temperature through data consistency verification.
5. The method according to claim 1, wherein the process of matching the original data to the target standard format comprises the steps of extracting data field definitions, data type constraints, data hierarchy relationships and verification rules of the target standard by a format template parsing engine based on a structured format specification of the target standard, and generating a standard format template; Based on the standard format template and the original temperature conversion data, performing intelligent matching and mapping on the data elements according to field names, semantic similarity and data types through a field mapping algorithm and a data structure adapter, and establishing a corresponding relation from an original data field to a target standard field; Based on the corresponding relation, the data type conversion, the unit unification, the precision adjustment and the logic verification are executed through the data format converter and the verification rule engine, standardized temperature data which meets the requirements of the target standard format and passes the validity verification is generated, and the automatic matching of the original data to the target standard format is obtained.
6. The method according to claim 1, wherein the multi-dimensional anomaly screening comprises the steps of decomposing the converted temperature signal on a time scale by an adaptive sliding window mechanism, and extracting multi-scale statistical feature vectors; Based on a predefined expert knowledge rule base and a statistical process control model, respectively carrying out abnormal pattern matching and deviation calculation on the feature vectors under the corresponding scale, and identifying point abnormality, context abnormality and trend abnormality; And generating an abnormality screening report based on the multisource evidence fusion strategy and the abnormality judgment result of the corresponding scale.
7. The method of claim 1, wherein the verified temperature data comprises multiple rule verification of standard compliance of abnormal data through a protocol compliance verification engine based on a multi-standard protocol compatibility rule base, compliance arbitration of fuzzy abnormal data under standard boundary conditions through a dynamic tolerance matching algorithm, and generation of verified temperature data through a data restoration and marking mechanism based on the arbitration result.
8. The method of claim 1, wherein the obtaining the scene recognition result by using the corresponding matching algorithm comprises extracting connector type, pin definition and communication protocol stack characteristics by an interface characteristic analysis engine based on physical characteristics and electrical parameters of a test connection interface, generating an interface characteristic vector, extracting an instruction sequence mode, a parameter configuration template and operation flow characteristics by an instruction characteristic analysis engine based on sequential logic and semantic structures of a test instruction, generating an instruction characteristic vector, and calculating matching degree with a predefined scene template by a multi-characteristic weighted fusion algorithm and a rule reasoning mechanism based on the interface characteristic vector and the instruction characteristic vector to obtain the scene recognition result.
9. The method of claim 1, wherein the specific process of converting the temperature control mode type and the parameter adjustment dimension under the corresponding scene comprises the steps of matching a predefined temperature control mode template library through a rule engine and a fuzzy reasoning mechanism based on scene type identification and feature weight in scene identification results, obtaining a basic temperature control mode type, dynamically adjusting the temperature control parameter dimension through a multi-objective optimization algorithm based on scene feature vectors and a history optimization record, generating a parameter optimization set, and carrying out online correction on the parameter set through an adaptive compensation mechanism based on real-time system state feedback, so as to obtain temperature control adjustment data matched with a test scene.
10. The method of claim 1, wherein the generation of the dynamic temperature control instruction comprises the steps of obtaining a control quantity through multi-objective optimization based on mode configuration and parameter sets in the temperature control adjustment data, dynamically compensating the control quantity through a feed-forward and feedback composite control algorithm based on real-time system state feedback and environment disturbance observation, and generating the dynamic temperature control instruction by utilizing a boundary protection and smoothing filter mechanism of an instruction safety constraint library.
11. The method of claim 1, wherein the generating the parameter compensation command comprises matching a predefined correction strategy template through a fault strategy mapping and rule reasoning mechanism based on fault type, positioning information and confidence data in the multi-standard diagnosis result, dynamically generating a parameter adjustment scheme based on a historical correction effect database and a real-time system state by using a compensation calculation model, and carrying out feasibility verification on the adjustment scheme to obtain a parameter compensation command set.
12. The method of claim 1, wherein dynamically adjusting the temperature control strategy parameters of the target device of the impactor comprises updating codes based on the parameter compensation instruction set by using a hot patch loading technology and a dual memory area switching mechanism, dynamically calculating parameter correction amounts by an incremental parameter adjustment algorithm and a rolling optimization window based on real-time system state monitoring data, and performing feasibility verification on the adjusted parameter set by using a formal verification method to generate a temperature control strategy parameter updating scheme.

Description

Impact machine temperature control method with multi-standard dynamic mapping and scene perception Technical Field The invention belongs to the field of industrial automation and intelligent control, and particularly relates to a multi-standard dynamic mapping and scene-aware impact machine temperature control method. Background The contact type high-low temperature impact machine still has the following to be improved: The conventional contact type high-low temperature impact machine has obvious limitation on a multi-standard adaptation surface, the measurement dimension and the statistical caliber of temperature data under different test standards are large in difference, and a unified conversion rule and an adaptation mechanism are lacked, so that the multi-source heterogeneous data are difficult to realize effective comparison, and the universality and the accuracy of a test result are affected. The temperature acquisition link is easy to be interfered by the outside, the existing equipment lacks perfect thermal, electric and magnetic three-in-one isolation design, the temperature coupling and electromagnetic interference of a peripheral circuit can directly influence the accuracy of acquired data, meanwhile, the compatibility of different types of tested devices such as bare chips, packaged chips and the like is insufficient, and the acquisition requirements of diversified test scenes cannot be met flexibly. The scene suitability of control by temperature change mode is relatively poor, and current equipment adopts fixed control by temperature change strategy more, is difficult to be according to test connection interface characteristic, instruction logic etc. dynamic identification test scene, leads to control by temperature change mode type and parameter adjustment dimension unable accurate matching actual test demand, has the control by temperature change response hysteresis, parameter adjustment irrational problem. The closed loop optimization capability of the temperature control system is insufficient, a real-time intelligent monitoring and failure attribution analysis mechanism for the temperature control effect is lacking, when temperature control deviation or device failure occurs, root factors cannot be rapidly positioned, a specific parameter compensation instruction is generated, and the temperature control strategy parameters are difficult to realize dynamic adjustment through online updating, so that the stability and reliability of long-term use of equipment are affected. Disclosure of Invention In order to solve the problems in the prior art, the invention provides a multi-standard dynamic mapping and scene-aware temperature control method of an impact machine. The aim of the invention can be achieved by the following technical scheme: s1, acquiring original temperature data of a tested device through a preset temperature acquisition device with thermal, electric and magnetic three-in-one isolation; S2, obtaining an adaptation rule base of standard temperature data based on the original temperature data through dynamic mapping, converting the temperature data of corresponding standards based on the rule base by using a standard factor conversion algorithm to obtain a conversion result of the original temperature data, matching the conversion result of the original temperature data with a target format to obtain a matching result of the original data to the target format, carrying out multidimensional anomaly screening on the matching result by using a multiscale anomaly detection assembly, calling a preset anomaly judgment threshold value by using a cross validation engine, and carrying out cross-standard consistency check on the screened anomaly data to obtain checked temperature data; S3, obtaining a scene recognition result by using a test connection interface of a scene recognition module based on the temperature data, converting a temperature control mode type and a parameter adjustment dimension under a corresponding scene by using a mode switching rule based on the scene recognition result to obtain scene-adaptive temperature control adjustment data, generating a dynamic temperature control instruction by using a temperature control strategy self-adaptive generation module through the temperature control adjustment data, and controlling an impact machine heat flow module to execute the dynamic temperature control instruction by using a multi-mode actuator driving module to perform standard state temperature control on the tested device to obtain an impact machine temperature controller; S4, intelligently monitoring the temperature control device through standard state temperature control of the impact machine to obtain monitoring data of the temperature control device, generating a multi-standard diagnosis result of failure cause analysis by utilizing an abnormality diagnosis and root cause analysis engine, generating a parameter compensation instruction through a self-adaptive c