CN109445306B - Automatic associated parameter interpretation method and system based on rule configuration analysis - Google Patents
Automatic associated parameter interpretation method and system based on rule configuration analysis Download PDFInfo
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Abstract
The invention discloses a method for automatically interpreting associated parameters based on rule configuration analysis, which comprises the following steps: adopting a definable grammar to construct a parameter interpretation rule to be judged in a character string form; updating and perfecting a feature extraction method related to an interpretation rule in a feature library; loading interpretation rules of the parameters to be interpreted, and carrying out semantic analysis on the interpretation rules by combining the feature library; and loading the parameter data associated with the interpretation rule, and interpreting the parameter data by using the interpretation rule after semantic analysis. The technical scheme provided by the invention overcomes the defects of low manual parameter interpretation efficiency, slow evidence collection and the like, is suitable for occasions where a large number of parameters are quickly and accurately interpreted, is particularly suitable for interpretation of complex associated parameters, and has good application prospect in the fields of industrial automation test and intelligent fault diagnosis. The invention also provides a system for automatically interpreting the associated parameters based on rule configuration analysis, and the system has the beneficial effects.
Description
Technical Field
The invention relates to the field of data processing application, in particular to an automatic interpretation method and system for associated parameters based on rule configuration analysis.
Background
With the rapid development of fieldbus technology and modern sensor technology, more and more parameters are detectable by industrial control processes. Most of the parameters are time sequence data, the correlation is strong, and the upper and lower limit ranges of the parameters and the time sequence characteristics thereof are closely related to the system working state. Therefore, how to interpret and analyze the parameters is very important for evaluating whether the system works normally or not.
At present, the parameter interpretation is mainly finished by means of manual interpretation of experts through naked eyes, which is time-consuming and labor-consuming and has low interpretation efficiency. For the occasions where a large number of parameters are quickly and accurately interpreted, such as a large-scale system with thousands of test parameters like a space rocket, the parameter interpretation not only needs a plurality of experts, but also needs to be repeatedly exchanged to correctly interpret the associated characteristics, so that quick evidence support cannot be provided for decision-makers, and the interpretation of complex associated parameters causes great waste of human resources.
The patent number of the Chinese space technology research institute is CN201410617252.9, and the patent named as 'curve data automatic interpretation method' describes an automatic interpretation method for satellite test data, and the method establishes an interpretation criterion by classifying curves and quantitatively analyzing the characteristics of the curves and adopts Lua script language to realize an interpretation algorithm. For one interpretation rule, the invention only supports a single feature, cannot adapt to the condition of logic combination of a plurality of features, and does not consider the condition that associated features exist in the rule. Therefore, the method of the present invention is not suitable for complex rule situations such as multiple association parameter combinations and timing associations.
The method described in "design of automatic interpretation system for space camera simulation test data" (computer measurement and control, 2010, vol. 18, No. 6) is used for a space camera ground simulation test system, wherein the interpretation method involved divides interpretation rules into three types to be respectively and specifically realized, the interpretation rules only support a logic and combination form, an interpretation algorithm module needs to be adaptively changed along with the change of the interpretation rules, and the rules cannot be uniformly analyzed by an intelligent algorithm.
Therefore, how to realize fast and accurate interpretation of complex correlation parameters is a technical problem which needs to be solved by those skilled in the art at present.
Disclosure of Invention
The invention aims to provide a method, a system and equipment for automatically interpreting associated parameters based on rule configuration and analysis and a computer readable storage medium, which are used for realizing the rapid and accurate interpretation of complex associated parameters.
In order to solve the above technical problem, the present invention provides a method for automatically interpreting associated parameters based on rule configuration analysis, which comprises:
constructing an interpretation rule of the parameter to be interpreted in the form of a character string; wherein the interpretation rule comprises a rule formed by multi-parameter feature association coupling;
updating and perfecting the feature extraction method related to the interpretation rule in a feature library;
loading the interpretation rule of the parameter to be interpreted, and carrying out semantic analysis on the interpretation rule by combining the feature library;
and loading the parameter data associated with the interpretation rule, and automatically interpreting the parameter data by using the interpretation rule after semantic analysis.
Optionally, the constructing the interpretation rule of all the parameters to be interpreted includes:
determining the relational expressions of all parameters to be judged based on the feature library, the time sequence instruction list and expert knowledge by adopting a definable grammar; the relational expression is composed of a time expression and a characteristic expression;
and combining the relational expressions through logic conditions to construct interpretation rules of all the parameters to be interpreted.
Optionally, when the feature extraction method related in the interpretation rule does not exist in the feature library, the method further includes:
expanding a corresponding new feature extraction method in the feature library according to the received new feature expansion instruction;
and modifying the corresponding feature extraction method in the feature library according to the received feature modification instruction.
Optionally, performing semantic analysis on the interpretation rule of the parameter, including:
analyzing the interpretation rule to obtain a group of relational expressions;
segmenting each relational expression to obtain a plurality of groups of characteristic expressions;
the interpreting the parameter data by using the interpreting rule after the semantic analysis correspondingly comprises the following steps:
loading parameter data related to the parameters to be judged, and calling corresponding feature extraction methods in the feature library to evaluate the multiple groups of feature expressions;
and calculating the values of the relational expressions according to the values of the multiple groups of characteristic expressions, calculating the logic value of the interpretation rule according to the values of the relational expressions, and judging whether the parameters are normal or not according to the logic value.
Optionally, calculating the value of each relational expression according to the values of the multiple sets of feature expressions, and calculating the logical value of the interpretation rule according to the value of each relational expression, includes:
sequentially evaluating the feature expression, the relational expression and the interpretation rule from bottom to top by adopting a three-level stack algorithm;
when each level of expression is solved, establishing an operator stack and an expression stack, pressing a logic operator or a relational operator in the expression into the operator stack from left to right, and sequentially pressing a next level of expression related to the level of expression into the expression stack;
evaluating each element in the current-level expression stack according to the parameter data associated with the parameter to be judged;
evaluating all expressions of the current level by respectively adopting a stack algorithm, repeatedly operating each expression according to the priority in the operator stack until the operator stack is empty during evaluation, and determining that the top element of the expression stack is the expression value of the current level;
and replacing the expression item of the current level in the expression of the previous level by the expression value of the current level, circularly evaluating the expression of the previous level until the rule level is calculated, and determining that the stack top element is the interpretation rule logical value.
Optionally, the evaluating the feature expression, the relational expression, and the interpretation rule sequentially by using a three-level stack algorithm from bottom to top includes:
respectively calculating a plurality of groups of feature expression values by adopting a stack algorithm, and replacing feature expressions in relational expressions associated with the feature expressions by the plurality of groups of feature expression values to obtain a group of relational expressions;
respectively calculating the value of each relational expression by adopting a stack algorithm, and replacing the corresponding relational expression in the interpretation rule with the value of the relational expression to obtain an interpretation rule consisting of numerical values and logical operators;
calculating the value of the interpretation rule by adopting a stack algorithm, wherein if the value of the interpretation rule is FALSE, the parameter to be interpreted is abnormal; if the value of the interpretation rule is TRUE, the parameter to be interpreted is normal;
and storing the interpretation result and the abnormal reason of the parameter to be judged in a database.
The invention also provides a system for automatically interpreting the associated parameters based on rule configuration analysis, which comprises the following steps:
the construction module is used for constructing an interpretation rule of the parameter to be interpreted in the form of a character string; wherein the interpretation rule comprises a rule formed by multi-parameter feature association coupling;
the updating module is used for updating and perfecting the feature extraction method related to the interpretation rule in a feature library;
the semantic analysis module is used for loading the interpretation rule of the parameter to be interpreted and carrying out semantic analysis on the interpretation rule by combining the feature library;
and the interpretation module is used for loading the parameter data associated with the interpretation rule and automatically interpreting the parameter data by using the interpretation rule after semantic analysis.
Optionally, the building module includes:
the determining submodule is used for determining the relational expressions of all the parameters to be judged based on the feature library, the time sequence instruction list and expert knowledge by adopting a definable grammar; the relational expression is composed of a time expression and a characteristic expression;
and the combination submodule is used for combining the relational expressions through logic conditions to construct interpretation rules of all the parameters to be interpreted.
Optionally, the method further includes:
the expansion module is used for expanding a corresponding new feature extraction method in the feature library according to the received new feature expansion instruction;
and the modification module is used for modifying the corresponding feature extraction method in the feature library according to the received feature modification instruction.
Optionally, the semantic parsing module includes:
the analysis submodule is used for analyzing the interpretation rule to obtain a group of relational expressions;
the segmentation submodule is used for segmenting each relational expression to obtain a plurality of groups of characteristic expressions;
the interpretation module correspondingly comprises:
the calling submodule is used for loading parameter data related to the parameter to be judged and calling a corresponding feature extraction method in the feature library to evaluate the multiple groups of feature expressions;
and the interpretation submodule is used for calculating the values of the relational expressions according to the values of the characteristic expressions, calculating the logic value of the interpretation rule according to the values of the relational expressions and judging whether the parameters are normal or not according to the logic value.
The invention provides a method for automatically interpreting associated parameters based on rule configuration analysis, which comprises the following steps: constructing an interpretation rule of the parameter to be interpreted in the form of a character string; the interpretation rules comprise rules formed by multi-parameter characteristic association coupling; updating and perfecting a feature extraction method related to an interpretation rule in a feature library; loading interpretation rules of the parameters to be interpreted, and carrying out semantic analysis on the interpretation rules by combining the feature library; and loading the parameter data associated with the interpretation rule, and automatically interpreting the parameter data by using the interpretation rule after semantic analysis.
According to the technical scheme provided by the invention, the interpretation rule of the parameter to be interpreted is constructed in advance, the feature extraction method of the interpretation rule is updated and perfected in the feature library, the interpretation rule of the parameter to be interpreted is loaded, the semantic analysis is carried out on the interpretation rule by combining the feature library, finally, the parameter data associated with the interpretation rule is loaded, and the parameter data is interpreted by using the interpretation rule after the semantic analysis, so that the rapid and accurate interpretation of the associated parameter is realized, and the method is particularly suitable for the complex rule interpretation situations of time sequence associated parameters, multi-feature multi-parameter coupling association and the like. The scheme overcomes the defects of low manual interpretation efficiency, slow evidence collection and the like, is suitable for occasions where a large number of parameters are quickly and accurately interpreted, is particularly suitable for interpretation of complex associated parameters, and has good application prospects in the fields of industrial automation testing and intelligent fault diagnosis. The invention also provides a system for automatically judging the associated parameters based on rule configuration analysis, which has the beneficial effects and is not repeated herein.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a flowchart of a method for automatically interpreting associated parameters based on rule configuration analysis according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating a structure definition of a time expression according to an embodiment of the present invention;
fig. 3 is a diagram illustrating a feature expression structure definition according to an embodiment of the present invention;
fig. 4 is a diagram illustrating a structure definition of a relational expression according to an embodiment of the present invention;
FIG. 5 is a diagram illustrating a structure of an interpretation rule according to an embodiment of the present invention;
FIG. 6 is a flow chart of an actual representation of step S103 in the method for automatically interpreting related parameters based on rule configuration analysis provided in FIG. 1;
FIG. 7 is a flowchart of an actual representation of step S104 in the method for automatically interpreting associated parameters based on rule configuration analysis provided in FIG. 1;
FIG. 8 is a flow chart of an actual representation of step S702 in FIG. 7;
fig. 9 is a structural diagram of a system for automatically interpreting associated parameters based on rule configuration analysis according to an embodiment of the present invention;
fig. 10 is a block diagram of another system for automatically interpreting association parameters based on rule configuration analysis according to an embodiment of the present invention.
Detailed Description
The core of the invention is to provide a method, a system, equipment and a computer readable storage medium for automatically interpreting the associated parameters based on rule configuration and analysis, which are used for realizing the rapid and accurate interpretation of the complex associated parameters.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a flowchart of a method for automatically interpreting associated parameters based on rule configuration analysis according to an embodiment of the present invention.
The method specifically comprises the following steps:
s101: constructing an interpretation rule of the parameter to be interpreted in the form of a character string;
the parameters to be judged specifically may include correlation parameters to be judged or correlation characteristic coupling parameters to be judged, and the interpretation rules mentioned herein may specifically include rules formed by multi-parameter characteristic correlation coupling;
the interpretation rule for constructing the parameter to be judged in the character string form can specifically be that the interpretation requirement of all the parameters to be judged is obtained by analyzing a configuration file input by a user, and the interpretation rule of all the parameters to be judged is constructed according to the interpretation requirement;
preferably, the interpretation rules for constructing all parameters to be interpreted mentioned here may specifically be:
determining the relational expressions of all parameters to be judged based on a feature library, a time sequence instruction list and expert knowledge by adopting a definable grammar; the relational expression is composed of a time expression and a characteristic expression;
combining the relational expressions through logic conditions to construct interpretation rules of all parameters to be interpreted;
preferably, referring to fig. 2 to 5, fig. 2 is a structure definition diagram of a time expression provided by an embodiment of the present invention; fig. 3 is a diagram illustrating a feature expression structure definition according to an embodiment of the present invention; fig. 4 is a diagram illustrating a structure definition of a relational expression according to an embodiment of the present invention; FIG. 5 is a diagram illustrating a structure of an interpretation rule according to an embodiment of the present invention; the definitions of the grammars mentioned here, where the concepts involved are defined as follows:
a time expression T, which is an expression used for describing a time value, and is shown in FIG. 2, the structure of the expression is formed by connecting instruction codes or numerical constants in a plurality of time sequence instruction tables through an arithmetic operator, for example, T1 is tqt +5, and represents a time value delayed by 5 seconds from the occurrence time of the tqt instruction;
a characteristic expression F is used for describing certain characteristics of a certain parameter in a partial time period or a whole time period, as shown in FIG. 3, the structure of the characteristic expression F is composed of a characteristic name, a parameter code, a time expression, brackets and the like, for example, F1 ═ max (nw1[ tk1: tk2-5]), which indicates that for a parameter with the parameter code of nw1, the max characteristic of the maximum value in the time period of tk1 to tk2-5 is analyzed;
a relational expression P for judging whether a logic condition of a certain relational operation is satisfied between two characteristic expressions, as shown in FIG. 4, the structure of the relational expression P is formed by connecting two characteristic expressions through operators, for example, F1>5, and the value calculated by the characteristic expression F1 is more than 5;
interpretation rule R: a combination of logical conditions for determining whether the corresponding parameter is normal or abnormal, as shown in fig. 5, is structured by several relational expressions connected by logical operators, for example, R ═ P1& (P2| | P3), where Pk, k ═ 1,2,3 are the relational expressions, and & and | | are the logical operators, respectively representing logical "and" or "," (",") represents that part of the parentheses has a high priority for operation;
it should be noted that the preset format requirement is only an example given by the embodiment of the present invention, and the present invention is not limited to this specifically, and a user may set a corresponding format requirement according to a production environment and a personal habit.
S102: updating and perfecting the feature extraction method of the interpretation rule in the feature library;
the feature extraction method for updating and perfecting the interpretation rules in the feature library is convenient for the system to carry out semantic analysis on the interpretation rules by combining the feature library so as to understand the interpretation rules;
preferably, when the feature extraction method involved in the interpretation rule does not exist in the feature library, the method may further include:
expanding a corresponding new feature extraction method in the feature library according to the received new feature expansion instruction;
and modifying the corresponding feature extraction method in the feature library according to the received feature modification instruction.
S103: loading interpretation rules of the parameters to be interpreted, and carrying out semantic analysis on the interpretation rules by combining the feature library;
after the feature library finishes updating and perfecting the feature implementation mode of the interpretation rule, the interpretation rule of the parameter to be interpreted is loaded, and the semantic analysis is carried out on the interpretation rule by combining the feature library.
S104: and loading the parameter data associated with the interpretation rule, and interpreting the parameter data by using the interpretation rule after semantic analysis.
Preferably, after the interpretation of the parameters to be interpreted is completed, the interpretation result and the failure reason can be recorded in a rule base or output to a file.
Based on the technical scheme, the method for automatically interpreting the associated parameters based on rule configuration analysis, provided by the invention, loads the interpretation rules of the parameters to be interpreted by pre-constructing the interpretation rules of the parameters to be interpreted, updates and perfects the feature extraction method of the interpretation rules in the feature library, performs semantic analysis on the interpretation rules by combining the feature library, finally loads the parameter data associated with the interpretation rules, and interprets the parameter data by using the interpretation rules after the semantic analysis, so that the associated parameters are quickly and accurately interpreted, and the method is particularly suitable for the interpretation situations of complex rules such as time sequence associated parameters, multi-feature multi-parameter coupling association and the like. The scheme overcomes the defects of low manual interpretation efficiency, slow evidence collection and the like, is suitable for occasions where a large number of parameters are quickly and accurately interpreted, is particularly suitable for interpretation of complex associated parameters, and has good application prospects in the fields of industrial automation testing and intelligent fault diagnosis.
Based on the above embodiment, semantic parsing is performed on each interpretation rule by referring to the combined feature library mentioned in step S103, which may specifically include the steps shown in fig. 6, please refer to fig. 6, and fig. 6 is a flowchart of an actual expression manner of step S103 in the method for automatically interpreting associated parameters based on rule configuration parsing provided in fig. 1.
The method specifically comprises the following steps:
s601: analyzing the interpretation rule to obtain a group of relational expressions;
s602: segmenting each relational expression to obtain a plurality of groups of characteristic expressions;
the interpretation rules mentioned here are structured by several relational expressions connected together by logical operators, such as R ═ P1& (P2| | | P3), where Pk, k ═ 1,2,3 are relational expressions, & & and | | | are logical operators, respectively representing logical and or, and "()" represents that the partial operation in parentheses is high in priority;
wherein the relational expression is used for judging whether a logic condition of a certain relational operation is satisfied between two characteristic expressions, and the structure of the relational expression is formed by connecting two characteristic expressions through an operator, such as F1>5, representing a characteristic expression F1The calculated value is greater than 5;
wherein, the characteristic expression is used to describe a certain characteristic of a parameter in a partial time period or a whole time period, and the structure of the characteristic expression is composed of a characteristic name, a parameter code, a time expression, brackets and the like, for example, F1＝max(nw1[tk1:tk2-5]) The maximum value max characteristic in the time period of tk1 to tk2-5 of the parameter with the parameter code number nw1 is analyzed;
aiming at the situation that each parameter data to be judged may have different interpretation rules, the embodiment of the invention analyzes the configuration file to obtain the interpretation rule expressions corresponding to the parameters to be judged, then divides the interpretation rule expressions to obtain the characteristic expressions of each group, then describes the characteristic expressions of each group respectively based on the stack algorithm to obtain the interpretation rules corresponding to the parameters to be judged, and can perform intelligent analysis and automatic interpretation aiming at the complex rules of time sequence correlation parameters, multi-feature multi-parameter coupling correlation and the like.
Further, referring to fig. 7, fig. 7 is a flowchart of an actual expression manner of step S104 in the method for automatically interpreting related parameters based on rule configuration analysis provided in fig. 1, where in the above embodiment, the step S104 uses the interpretation rule after semantic analysis to interpret parameter data, and the correspondence may include:
s701: loading parameter data related to the parameters to be judged, and calling corresponding feature extraction methods in the feature library to evaluate a plurality of groups of feature expressions;
s702: and calculating the value of each relational expression according to the values of the multiple groups of characteristic expressions, calculating the logic value of the interpretation rule according to the value of each relational expression, and judging whether the parameters are normal or not according to the logic value.
The embodiment of the invention firstly determines each feature and time expression in each group of feature expression, then judges whether each feature extraction method exists in the preset feature library, finally determines the time range according to the time expression, and calls the preset feature library to realize each group of feature expression to obtain the interpretation rule corresponding to each parameter to be interpreted, and can carry out intelligent analysis and automatic interpretation in the face of complex rules such as time sequence associated parameters, multi-feature multi-parameter coupling association and the like, thereby overcoming the defects of low manual interpretation efficiency, slow evidence collection and the like and having good application prospect in the fields of industrial automation test and intelligent fault diagnosis.
Based on the above embodiment, the steps mentioned in step S702 of calculating the values of the relational expressions according to the values of the sets of feature expressions and calculating the logical value of the interpretation rule according to the values of the relational expressions may specifically include the steps shown in fig. 8, please refer to fig. 8, and fig. 8 is a flowchart of an actual expression manner of step S702 in fig. 7.
The method specifically comprises the following steps:
s801: sequentially evaluating the characteristic expression, the relational expression and the interpretation rule from bottom to top by adopting a three-level stack algorithm;
preferably, the bottom-up evaluation of the feature expression, the relational expression and the interpretation rule by using a three-level stack algorithm may specifically include the following steps:
respectively calculating a plurality of groups of feature expression values by adopting a stack algorithm, and replacing feature expressions in relational expressions associated with the feature expressions by the plurality of groups of feature expression values to obtain a group of relational expressions;
respectively calculating the value of each relational expression by adopting a stack algorithm, and replacing the corresponding relational expression in the interpretation rule with the value of the relational expression to obtain an interpretation rule consisting of numerical values and logical operators;
calculating the value of the interpretation rule by adopting a stack algorithm, and if the value of the interpretation rule is FALSE, determining that the parameter to be interpreted is abnormal; if the value of the interpretation rule is TRUE, the parameter to be interpreted is normal;
and storing the interpretation result and the abnormal reason of the parameter to be interpreted into a database.
S802: when each level of expression is solved, an operator stack and an expression stack are established, a logical operator or a relational operator in the expression is pressed into the operator stack from left to right, and the next level of expression related to the level of expression is sequentially pressed into the expression stack;
the rule semantic parsing process mainly parses the rules in the form of character strings into a data structure required by the interpretation software, so as to facilitate program execution, and the data structure after the rule semantic parsing is represented by extensible markup language (XML for short). The following describes the parsing process by taking a specific rule as an example.
The interpretation rule corresponding to the parameter c1 is:
max (c1[ tqt +5:300]) <10& & min (c2) >5| | mean (c3) < mean (c4), then the xml file can be obtained by expression analysis as follows:
s803: evaluating each element in the current-level expression stack according to parameter data associated with the parameter to be judged;
s804: respectively adopting a stack algorithm to evaluate all expressions of the current level, repeatedly operating according to the priority in the operator stack until the operator stack is empty when each expression is evaluated, and determining the top element of the expression stack as the expression value of the current level;
s805: and replacing the corresponding expression item in the previous-level expression with all the expression values of the current level, circularly evaluating the expression of the previous level until the calculation of the rule level is finished, and determining the stack top element as the interpretation rule logical value.
Based on the technical scheme, the embodiment of the invention firstly analyzes each group of characteristic expressions of the interpretation rule corresponding to the parameter data to be judged to obtain each operational character and each expression, then establishing an operational character stack and an expression stack, storing each operational character into the operational character stack, storing each expression into the expression stack, assigning the stack top element of the expression stack according to the parameter data to be judged, when the top element of the expression stack meets the preset operation priority, acquiring a top operational character in the operational character stack, and the stack top operational character is utilized to carry out logic operation on the stack top element of the expression stack to obtain the interpretation result of the parameter data to be interpreted, thereby realizing quick and accurate interpretation of the parameter, overcoming the defects of low manual interpretation efficiency, slow evidence collection and the like, and having good application prospect in the fields of industrial automation test and intelligent fault diagnosis.
Referring to fig. 9, fig. 9 is a block diagram of a system for automatically interpreting correlation parameters based on rule configuration analysis according to an embodiment of the present invention.
The system may include:
the building module 100 is configured to build an interpretation rule of a parameter to be interpreted in a character string form; the interpretation rules comprise rules formed by multi-parameter characteristic association coupling;
an updating module 200, configured to update and perfect the feature extraction method related to the interpretation rule in the feature library;
the semantic analysis module 300 is used for loading the interpretation rules of the parameters to be interpreted and carrying out semantic analysis on the interpretation rules by combining the feature library;
the interpretation module 400 is configured to load parameter data associated with the interpretation rule, and automatically interpret the parameter data by using the interpretation rule after semantic analysis.
Referring to fig. 10, fig. 10 is a block diagram of another system for automatically interpreting correlation parameters based on rule configuration analysis according to an embodiment of the present invention.
The building block 100 may include:
the determining submodule is used for determining the relational expressions of all the parameters to be judged based on the feature library, the time sequence instruction list and expert knowledge by adopting a definable grammar; the relational expression is composed of a time expression and a characteristic expression;
and the combination submodule is used for combining the relational expressions through logic conditions to construct interpretation rules of all the parameters to be interpreted.
The system may further comprise:
the expansion module is used for expanding a corresponding new feature extraction method in the feature library according to the received new feature expansion instruction;
and the modification module is used for modifying the corresponding feature extraction method in the feature library according to the received feature modification instruction.
The semantic parsing module 300 may include:
the analysis submodule is used for analyzing the interpretation rule to obtain a group of relational expressions;
the segmentation submodule is used for segmenting each relational expression to obtain a plurality of groups of characteristic expressions;
the interpretation module 400 may correspondingly include:
the calling submodule is used for loading parameter data related to the parameter to be judged and calling a corresponding feature extraction method in the feature library to evaluate the multiple groups of feature expressions;
and the interpretation submodule is used for calculating the values of the relational expressions according to the values of the characteristic expressions, calculating the logic value of the interpretation rule according to the values of the relational expressions and judging whether the parameters are normal or not according to the logic value.
Further, the interpretation sub-module may include:
the first calculating subunit is used for calculating a plurality of groups of characteristic expression values by adopting a stack algorithm, and replacing the characteristic expressions in the relational expressions associated with the characteristic expressions by the plurality of groups of characteristic expression values to obtain a group of relational expressions;
the second calculating subunit is used for calculating the value of each relational expression by adopting a stack algorithm, and replacing the corresponding relational expression in the interpretation rule with the value of the relational expression to obtain an interpretation rule consisting of numerical values and logical operators;
the interpretation subunit is used for calculating the value of the interpretation rule by adopting a stack algorithm, and if the value of the interpretation rule is FALSE, the parameter to be interpreted is abnormal; if the value of the interpretation rule is TRUE, the parameter to be interpreted is normal;
and the storage subunit is used for storing the interpretation result and the abnormal reason of the parameter to be interpreted into a database.
Since the embodiment of the system part corresponds to the embodiment of the method part, the embodiment of the system part is described with reference to the embodiment of the method part, and is not repeated here.
The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The method and the system for automatically interpreting the associated parameters based on rule configuration analysis provided by the application are introduced in detail above. The principles and embodiments of the present application are explained herein using specific examples, which are provided only to help understand the method and the core idea of the present application. It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present application without departing from the principle of the present application, and such improvements and modifications also fall within the scope of the claims of the present application.
It is further noted that, in the present specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Claims (7)
1. A method for automatically judging and reading associated parameters based on rule configuration and analysis is characterized by comprising the following steps:
constructing an interpretation rule of the parameter to be interpreted in the form of a character string; wherein the interpretation rule comprises a rule formed by multi-parameter feature association coupling;
updating and perfecting the feature extraction method related to the interpretation rule in a feature library;
loading the interpretation rule of the parameter to be interpreted, and carrying out semantic analysis on the interpretation rule by combining the feature library;
loading parameter data associated with the interpretation rule, and automatically interpreting the parameter data by using the interpretation rule after semantic analysis; wherein:
performing semantic analysis on the interpretation rule of the parameter, including:
analyzing the interpretation rule to obtain a group of relational expressions;
dividing each relational expression to obtain a plurality of groups of characteristic expressions;
the interpreting the parameter data by using the interpreting rule after the semantic analysis correspondingly comprises the following steps:
loading parameter data related to the parameters to be judged, and calling corresponding feature extraction methods in the feature library to evaluate the multiple groups of feature expressions;
calculating the value of each relational expression according to the values of the multiple groups of characteristic expressions, calculating the logic value of the interpretation rule according to the value of each relational expression, and judging whether the parameters are normal or not according to the logic value;
calculating the values of the relational expressions according to the values of the characteristic expressions, and calculating the logic values of the interpretation rule according to the values of the relational expressions, wherein the method comprises the following steps:
sequentially evaluating the feature expression, the relational expression and the interpretation rule from bottom to top by adopting a three-level stack algorithm;
when each level of expression is solved, establishing an operator stack and an expression stack, pressing a logic operator or a relational operator in the expression into the operator stack from left to right, and sequentially pressing a next level of expression related to the level of expression into the expression stack;
evaluating each element in the expression stack at the current level according to the parameter data associated with the parameter to be judged;
evaluating all expressions of the current level by respectively adopting a stack algorithm, repeatedly operating each expression according to the priority in the operator stack until the operator stack is empty during evaluation, and determining that the top element of the expression stack is the expression value of the current level;
and replacing the corresponding expression item of the current level in the expression of the previous level with all the expression values of the current level, circularly evaluating the expression of the previous level until the rule level is calculated, and determining that the stack top element is the interpretation rule logical value.
2. The method of claim 1, wherein the constructing the interpretation rules for all parameters to be interpreted comprises:
determining the relational expressions of all parameters to be judged based on the feature library, the time sequence instruction list and expert knowledge by adopting a definable grammar; the relational expression is composed of a time expression and a characteristic expression;
and combining the relational expressions through logic conditions to construct an interpretation rule of the parameter to be judged.
3. The method according to claim 1, when the feature extraction method involved in the interpretation rule does not exist in the feature library, further comprising:
expanding a corresponding new feature extraction method in the feature library according to the received new feature expansion instruction;
and modifying the corresponding feature extraction method in the feature library according to the received feature modification instruction.
4. The method of claim 1, wherein evaluating the feature expression, the relational expression, and the interpretation rule sequentially from bottom to top using a three-level stack algorithm comprises:
respectively calculating a plurality of groups of feature expression values by adopting a stack algorithm, and replacing feature expressions in relational expressions associated with the feature expressions by the plurality of groups of feature expression values to obtain a group of relational expressions;
respectively calculating the value of each relational expression by adopting a stack algorithm, and replacing the corresponding relational expression in the interpretation rule with the value of the relational expression to obtain an interpretation rule consisting of numerical values and logical operators;
calculating the value of the interpretation rule by adopting a stack algorithm, wherein if the value of the interpretation rule is FALSE, the parameter to be interpreted is abnormal; if the value of the interpretation rule is TRUE, the parameter to be interpreted is normal;
and storing the interpretation result and the abnormal reason of the parameter to be judged in a database.
5. A system for automatically interpreting associated parameters based on rule configuration analysis is characterized by comprising the following steps:
the construction module is used for constructing an interpretation rule of the parameter to be interpreted in the form of a character string; wherein the interpretation rule comprises a rule formed by multi-parameter feature association coupling;
the updating module is used for updating and perfecting the feature extraction method related to the interpretation rule in a feature library;
the semantic analysis module is used for loading the interpretation rule of the parameter to be interpreted and carrying out semantic analysis on the interpretation rule by combining the feature library;
the interpretation module is used for loading the parameter data associated with the interpretation rule and automatically interpreting the parameter data by utilizing the interpretation rule after semantic analysis; wherein:
the semantic parsing module comprises:
the analysis submodule is used for analyzing the interpretation rule to obtain a group of relational expressions;
the segmentation submodule is used for segmenting each relational expression to obtain a plurality of groups of characteristic expressions;
the interpretation module correspondingly comprises:
the calling submodule is used for loading parameter data related to the parameter to be judged and calling a corresponding feature extraction method in the feature library to evaluate the multiple groups of feature expressions;
the interpretation submodule is used for calculating the value of each relational expression according to the values of the multiple groups of characteristic expressions, calculating the logic value of the interpretation rule according to the value of each relational expression and judging whether the parameters are normal or not according to the logic value;
calculating the values of the relational expressions according to the values of the characteristic expressions, and calculating the logic values of the interpretation rule according to the values of the relational expressions, wherein the method comprises the following steps:
sequentially evaluating the feature expression, the relational expression and the interpretation rule from bottom to top by adopting a three-level stack algorithm;
when each level of expression is solved, establishing an operator stack and an expression stack, pressing a logic operator or a relational operator in the expression into the operator stack from left to right, and sequentially pressing a next level of expression related to the level of expression into the expression stack;
evaluating each element in the expression stack at the current level according to the parameter data associated with the parameter to be judged;
evaluating all expressions of the current level by respectively adopting a stack algorithm, repeatedly operating each expression according to the priority in the operator stack until the operator stack is empty during evaluation, and determining that the top element of the expression stack is the expression value of the current level;
and replacing the corresponding expression item of the current level in the expression of the previous level with all the expression values of the current level, circularly evaluating the expression of the previous level until the rule level is calculated, and determining that the stack top element is the interpretation rule logical value.
6. The system of claim 5, wherein the building module comprises:
the determining submodule is used for determining the relational expressions of all the parameters to be judged based on the feature library, the time sequence instruction list and expert knowledge by adopting a definable grammar; the relational expression is composed of a time expression and a characteristic expression;
and the combination submodule is used for combining the relational expressions through logic conditions to construct interpretation rules of all the parameters to be interpreted.
7. The system of claim 5, further comprising:
the expansion module is used for expanding a corresponding new feature extraction method in the feature library according to the received new feature expansion instruction;
and the modification module is used for modifying the corresponding feature extraction method in the feature library according to the received feature modification instruction.
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