CN117556646A - Intelligent identification operation and maintenance management method and system based on environment parameters - Google Patents
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Abstract
The invention relates to the technical field of intelligent identification and discloses a method and a system for intelligent identification operation and maintenance management based on environment parameters.
Description
Technical Field
The invention relates to the technical field of intelligent identification, in particular to an intelligent identification operation and maintenance management method and system based on environmental parameters.
Background
Smart identification generally refers to an advanced form of identification system that upgrades and intelligently adapts a traditional identification system using modern information technologies, such as internet of things (IoT), big data, cloud computing, artificial intelligence, and the like.
In the conventional identification system, the combination work is performed through the internal visualization units arranged according to the fixed sequence so as to display the identification content, and the identification system working in the conventional manner cannot adaptively adjust the working parameters of the visualization units according to the change of the working environment and the actual performance of the internal visualization units, so that the conventional identification system cannot display the optimal identification effect.
Disclosure of Invention
The invention aims to provide an intelligent identification operation and maintenance management method and system based on environmental parameters, and aims to solve the problem that intelligent identification cannot be optimally adaptively displayed according to the actual performance of the intelligent identification and the external actual environment in the prior art.
The invention is realized in such a way that in a first aspect, the invention provides an intelligent identification operation and maintenance management method based on environmental parameters, comprising the following steps:
carrying out multidimensional parameter acquisition on an external environment through a pre-deployed sensor group, and substituting each acquired parameter into a preset visual operation and maintenance model to calculate the optimal visual operation and maintenance parameter of the intelligent identifier under each parameter; the intelligent identifier is provided with a plurality of visualization units for realizing the visualization function, and the optimal visualization operation and maintenance parameters are used for driving the visualization units to work;
Continuously collecting the working driving parameters and the working effect parameters of each visual unit in the intelligent identification through communication connection with the intelligent identification, and substituting the collected working driving parameters and the collected working effect parameters into a preset performance quality control model to obtain performance quality control maps of each visual unit;
and adjusting the optimal visual operation and maintenance parameters of the intelligent identification according to the performance quality control maps of the visual units to obtain the adjustment operation and maintenance parameters of the intelligent identification, and judging the feasibility of the adjustment operation and maintenance parameters according to the visual operation and maintenance model to determine the actual operation and maintenance scheme of the intelligent identification.
Preferably, the step of performing multidimensional parameter collection on the external environment through a pre-deployed sensor group, and substituting each collected parameter into a preset visual operation and maintenance model to calculate the optimal visual operation and maintenance parameter of the smart identifier under each parameter includes:
acquiring a multi-dimensional parameter of an external environment through a pre-deployed sensor group to acquire an ambient light intensity parameter, an ambient smoke concentration parameter and an ambient temperature parameter in the external environment, and substituting the ambient light intensity parameter, the ambient smoke concentration parameter and the ambient temperature parameter into an obstruction level in a preset visual operation and maintenance model;
Acquiring an expected work target of the intelligent identifier, and substituting the expected work target into a target level of the visual operation and maintenance model;
and carrying out parameter deduction on the driving level of the visual operation and maintenance model according to the blocking level and the target level of the visual operation and maintenance model so as to obtain the optimal visual operation and maintenance parameters of the intelligent identification.
Preferably, the step of parameter deduction includes:
the target level of the visual operation and maintenance model performs parameter mapping on the driving level of the visual operation and maintenance model according to the expected working target so as to determine preliminary driving parameters on the driving level;
and performing parameter mapping on a driving level of the visual operation and maintenance model according to the ambient light intensity parameter, the ambient smoke concentration parameter and the ambient temperature parameter by the blocking level of the visual operation and maintenance model so as to perform parameter correction on the preliminary driving parameter to obtain the optimal visual operation and maintenance parameter.
Preferably, the step of continuously collecting the working driving parameters and the working effect parameters of each visualization unit in the smart sign through communication connection with the smart sign, and substituting the collected working driving parameters and the collected working effect parameters into a preset performance quality control model to obtain performance quality control maps of each visualization unit includes:
Continuously collecting working driving parameters and working effect parameters of each visualization unit in the intelligent mark through communication connection with the intelligent mark; the working driving parameters are used for driving the visual unit to work, and the working effect parameters are used for describing the working effect of the visual unit;
binding the working driving parameters and the working effect parameters of the visualization unit at the same moment to obtain the performance characteristics of the visualization unit, and arranging the performance characteristics according to time sequence to obtain the performance characteristic sequence of the visualization unit; wherein the performance characteristic sequence of the visualization unit is a first level of a performance quality control map of the visualization unit;
judging each performance characteristic in a performance characteristic sequence of the visual unit according to a preset standard to obtain performance levels represented by each performance characteristic, and connecting each performance level to obtain a performance level change curve of the visual unit; wherein the performance level change curve of the visualization unit is a second level of the performance quality control map of the visualization unit;
Summarizing the performance characteristics with the same working driving parameters into a characteristic comparison sequence based on the performance characteristic sequence of the visualization unit, and obtaining a performance decay curve of the visualization unit through analysis of the characteristic comparison sequence; the characteristic comparison sequence of the visual unit is a third level of the performance quality control spectrum of the visual unit, and the performance decay curve of the visual unit is a fourth level of the performance quality control spectrum of the visual unit.
Preferably, the step of obtaining the performance decay curve of the visualization unit by analysis of the feature comparison sequence comprises:
summarizing the performance features continuously existing in the feature comparison sequence into feature paragraphs according to the time sequence;
carrying out change analysis on the mapping relation between the working driving parameters and the working effect parameters of the performance characteristics to obtain the performance continuous parameters of the characteristic paragraphs;
acquiring time intervals among the characteristic paragraphs, and analyzing according to the time intervals among the characteristic paragraphs and the differences of the performance continuous parameters of the characteristic paragraphs to obtain the performance decay parameters of the characteristic paragraphs in the time intervals;
And connecting each performance decay parameter in time sequence to obtain the performance decay curve of the visualization unit.
Preferably, the step of adjusting the best visual operation and maintenance parameters of the smart tag according to the performance quality control map of each visual unit to obtain adjusted operation and maintenance parameters of the smart tag, and judging the feasibility of the adjusted operation and maintenance parameters according to the visual operation and maintenance model to determine the actual operation and maintenance scheme of the smart tag includes:
judging the best visual operation and maintenance parameters of the intelligent identification according to a first level and a second level of a performance quality control map of each visual unit so as to judge whether each visual unit can implement the best visual operation and maintenance parameters, and marking the visual units which cannot implement the best visual operation and maintenance parameters as target units;
taking the optimal visual operation and maintenance parameters as reference, performing cross analysis according to a first level and a second level of the performance quality control spectrum of each target unit to obtain adjustment operation and maintenance parameters which can be implemented by each target unit;
substituting the adjustment operation and maintenance parameters into the visual operation and maintenance model to calculate the prediction operation and maintenance effect of the adjustment operation and maintenance parameters under the current external environment, and if the prediction operation and maintenance effect is within the range of the expected difference from the expected working target, determining the actual operation and maintenance scheme of the intelligent identifier by the adjustment operation and maintenance parameters;
If the predicted operation and maintenance effect and the expected operation and maintenance target are not in the expected difference range, the expected operation and maintenance target in the visual operation and maintenance model is lowered, and calculation and verification of the optimized visual operation and maintenance parameters are repeated.
In a second aspect, the present invention provides an intelligent identification operation and maintenance management system based on environmental parameters, including:
the data acquisition module is used for carrying out multidimensional parameter acquisition on the external environment through a pre-deployed sensor group, and substituting each acquired parameter into a preset visual operation and maintenance model so as to calculate the optimal visual operation and maintenance parameter of the intelligent identifier under each parameter; the intelligent identifier is provided with a plurality of visualization units for realizing the visualization function, and the optimal visualization operation and maintenance parameters are used for driving the visualization units to work;
the performance analysis module is used for continuously collecting the working driving parameters and the working effect parameters of each visual unit in the intelligent identification through communication connection with the intelligent identification, and substituting the collected working driving parameters and the collected working effect parameters into a preset performance quality control model so as to obtain performance quality control maps of each visual unit;
And the scheme analysis module is used for adjusting the optimal visual operation and maintenance parameters of the intelligent identification according to the performance quality control maps of the visual units to obtain the adjustment operation and maintenance parameters of the intelligent identification, and judging the feasibility of the adjustment operation and maintenance parameters according to the visual operation and maintenance model to determine the actual operation and maintenance scheme of the intelligent identification.
The invention provides an intelligent identification operation and maintenance management method based on environmental parameters, which has the following beneficial effects:
according to the intelligent identification system, the working environment of the intelligent identification is subjected to multidimensional parameter acquisition through the sensor group, the optimal visual operation and maintenance parameters are obtained through calculation through the visual operation and maintenance model, the working driving parameters and the working effect parameters of the visual unit are continuously obtained through communication connection with the intelligent identification, and the performance quality control map of the visual unit is obtained through analysis through the performance quality control model, so that whether the visual unit can implement the optimal visual operation and maintenance parameters is judged, if the visual unit cannot implement the optimal visual operation and maintenance parameters, the operation and maintenance parameters are generated and adjusted based on the optimal visual operation and maintenance parameters, and the problem that the intelligent identification in the prior art cannot be optimally displayed according to the actual performance of the intelligent identification system and the external actual environment is solved.
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FIG. 1 is a schematic diagram of steps of a smart identification operation and maintenance management method based on environmental parameters according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an intelligent identifier operation and maintenance management system based on environmental parameters according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The same or similar reference numerals in the drawings of the present embodiment correspond to the same or similar components; in the description of the present invention, it should be understood that, if there is an azimuth or positional relationship indicated by terms such as "upper", "lower", "left", "right", etc., based on the azimuth or positional relationship shown in the drawings, it is only for convenience of describing the present invention and simplifying the description, but it is not indicated or implied that the apparatus or element referred to must have a specific azimuth, be constructed and operated in a specific azimuth, and thus terms describing the positional relationship in the drawings are merely illustrative and should not be construed as limiting the present invention, and specific meanings of the terms described above may be understood by those of ordinary skill in the art according to specific circumstances.
The implementation of the present invention will be described in detail below with reference to specific embodiments.
Referring to fig. 1 and 2, a preferred embodiment of the present invention is provided.
In a first aspect, the present invention provides a smart identification operation and maintenance management method based on environmental parameters, including:
s1: carrying out multidimensional parameter acquisition on an external environment through a pre-deployed sensor group, and substituting each acquired parameter into a preset visual operation and maintenance model to calculate the optimal visual operation and maintenance parameter of the intelligent identifier under each parameter; the intelligent identifier is provided with a plurality of visualization units for realizing the visualization function, and the optimal visualization operation and maintenance parameters are used for driving the visualization units to work;
s2: continuously collecting the working driving parameters and the working effect parameters of each visual unit in the intelligent identification through communication connection with the intelligent identification, and substituting the collected working driving parameters and the collected working effect parameters into a preset performance quality control model to obtain performance quality control maps of each visual unit;
s3: and adjusting the optimal visual operation and maintenance parameters of the intelligent identification according to the performance quality control maps of the visual units to obtain the adjustment operation and maintenance parameters of the intelligent identification, and judging the feasibility of the adjustment operation and maintenance parameters according to the visual operation and maintenance model to determine the actual operation and maintenance scheme of the intelligent identification.
Specifically, the intelligent identifier is an identification system which is updated by utilizing an information technology, a plurality of visualization units are arranged in the intelligent identifier, and the visualization units are units for displaying functions in the intelligent identifier.
More specifically, in order to achieve the object, firstly, the sensor group deployed in advance is used for collecting the parameters of the external repayment in a multi-dimension way, and each collected parameter is used for describing the influence of the external environment on the display effect of the smart identifier, namely, the working parameter of the smart identifier, the influence of the external environment and the display effect of the smart identifier, wherein the three have a mutually-influenced mapping relation, and when two elements are determined in the three elements, the third element can be calculated through the mapping relation.
More specifically, in the invention, a visual operation and maintenance model is preset to describe the mapping relation of three elements and calculate, each collected parameter is put into the visual operation and maintenance model, namely, the optimal visual operation and maintenance parameter of the intelligent identifier under each parameter can be calculated, and when a visual unit in the intelligent identifier works according to the optimal visual operation and maintenance parameter, the optimal working effect in theory can be obtained.
More specifically, through the communication connection with the wisdom sign, continuously gather the work drive parameter and the work effect parameter of each visual unit in the wisdom sign to substituting the work drive parameter and the work effect parameter that gather into the performance quality control model of predetermineeing, in order to obtain the performance quality control map of each visual unit.
It should be noted that, the working driving parameter of the visualization unit is used to record the performance parameter executed when the visualization unit operates, the working effect parameter is used to describe the effect displayed by the visualization unit in actual work, the relation between the working driving parameter and the working effect parameter of the visualization unit is the actual performance of the visualization unit, when the actual performance of the visualization unit is normal, the relation between the working driving parameter and the working effect parameter of the visualization unit is in a certain range, and based on the above principle, a performance quality control model for calculating the working driving parameter and the working effect parameter of the visualization unit is constructed to obtain the performance quality control map of the visualization unit.
It can be understood that the performance quality control map of the visualization unit is used for feeding back the actual performance of the visualization unit, the optimal visual operation and maintenance parameters of the smart identification are adjusted according to the actual performance of each visualization unit through the performance quality control map of each visualization unit, so as to obtain the adjusted operation and maintenance parameters of the smart identification, and feasibility judgment is carried out on the adjusted operation and maintenance parameters according to the visual operation and maintenance model, so that the actual operation and maintenance scheme of the smart identification is determined.
The invention provides an intelligent identification operation and maintenance management method based on environmental parameters, which has the following beneficial effects:
according to the intelligent identification system, the working environment of the intelligent identification is subjected to multidimensional parameter acquisition through the sensor group, the optimal visual operation and maintenance parameters are obtained through calculation through the visual operation and maintenance model, the working driving parameters and the working effect parameters of the visual unit are continuously obtained through communication connection with the intelligent identification, and the performance quality control map of the visual unit is obtained through analysis through the performance quality control model, so that whether the visual unit can implement the optimal visual operation and maintenance parameters is judged, if the visual unit cannot implement the optimal visual operation and maintenance parameters, the operation and maintenance parameters are generated and adjusted based on the optimal visual operation and maintenance parameters, and the problem that the intelligent identification in the prior art cannot be optimally displayed according to the actual performance of the intelligent identification system and the external actual environment is solved.
Preferably, the step of performing multidimensional parameter collection on the external environment through a pre-deployed sensor group, and substituting each collected parameter into a preset visual operation and maintenance model to calculate the optimal visual operation and maintenance parameter of the smart identifier under each parameter includes:
s11: acquiring a multi-dimensional parameter of an external environment through a pre-deployed sensor group to acquire an ambient light intensity parameter, an ambient smoke concentration parameter and an ambient temperature parameter in the external environment, and substituting the ambient light intensity parameter, the ambient smoke concentration parameter and the ambient temperature parameter into an obstruction level in a preset visual operation and maintenance model;
S12: acquiring an expected work target of the intelligent identifier, and substituting the expected work target into a target level of the visual operation and maintenance model;
s13: and carrying out parameter deduction on the driving level of the visual operation and maintenance model according to the blocking level and the target level of the visual operation and maintenance model so as to obtain the optimal visual operation and maintenance parameters of the intelligent identification.
Specifically, parameters influencing the display effect of the visualization unit of the smart sign in the external environment include an ambient light intensity parameter, an ambient smoke concentration parameter and an ambient temperature parameter, and sensors corresponding to the parameters are deployed in the smart sign in advance to obtain corresponding parameters in the external environment.
More specifically, in the previous description, the working parameters of the smart label, the influence of the external environment, and the display effect of the smart label are described, and the three have the mapping relationship of mutual influence, and when the visual operation and maintenance model is constructed, the three elements are constructed according to the following steps:
the blocking level of the visual operation and maintenance model corresponds to the influence of the external environment and is used for substituting various parameters acquired by the sensor group, wherein the parameters include an ambient light intensity parameter, an ambient smoke concentration parameter and an ambient temperature parameter, and the parameters of other items can be added and the blocking level can be modified based on the added parameters;
The target level of the visual operation and maintenance model corresponds to the display effect of the intelligent mark and is used for substituting an expected working target, namely the working effect of the expected intelligent mark in an ideal state to be realized;
the driving level of the visual operation and maintenance model corresponds to the working parameters of the intelligent identification and is used for deducting according to the blocking level and the target level so as to obtain the optimal visual operation and maintenance parameters of the intelligent identification.
Preferably, the step of parameter deduction includes:
s131: the target level of the visual operation and maintenance model performs parameter mapping on the driving level of the visual operation and maintenance model according to the expected working target so as to determine preliminary driving parameters on the driving level;
s132: and performing parameter mapping on a driving level of the visual operation and maintenance model according to the ambient light intensity parameter, the ambient smoke concentration parameter and the ambient temperature parameter by the blocking level of the visual operation and maintenance model so as to perform parameter correction on the preliminary driving parameter to obtain the optimal visual operation and maintenance parameter.
Specifically, there is a mapping relationship between three levels of the visual operation and maintenance model, and the principle thereof is consistent with an equation of y=f (X), so that the third level can be acquired according to two levels of the three levels.
More specifically, the present invention provides a way of mapping computation: the external environment on the blocking level is preset as a standard environment parameter, the preliminary driving parameter on the driving level is calculated through the expected working target on the target level on the basis of the standard environment parameter, and then the actual parameters are put into the blocking level to carry out parameter correction on the preliminary driving parameter of the driving level so as to obtain the optimal visualized operation and maintenance parameter.
Preferably, the step of continuously collecting the working driving parameters and the working effect parameters of each visualization unit in the smart sign through communication connection with the smart sign, and substituting the collected working driving parameters and the collected working effect parameters into a preset performance quality control model to obtain performance quality control maps of each visualization unit includes:
s21: continuously collecting working driving parameters and working effect parameters of each visualization unit in the intelligent mark through communication connection with the intelligent mark; the working driving parameters are used for driving the visual unit to work, and the working effect parameters are used for describing the working effect of the visual unit;
S22: binding the working driving parameters and the working effect parameters of the visualization unit at the same moment to obtain the performance characteristics of the visualization unit, and arranging the performance characteristics according to time sequence to obtain the performance characteristic sequence of the visualization unit; wherein the performance characteristic sequence of the visualization unit is a first level of a performance quality control map of the visualization unit;
s23: judging each performance characteristic in a performance characteristic sequence of the visual unit according to a preset standard to obtain performance levels represented by each performance characteristic, and connecting each performance level to obtain a performance level change curve of the visual unit; wherein the performance level change curve of the visualization unit is a second level of the performance quality control map of the visualization unit;
s24: summarizing the performance characteristics with the same working driving parameters into a characteristic comparison sequence based on the performance characteristic sequence of the visualization unit, and obtaining a performance decay curve of the visualization unit through analysis of the characteristic comparison sequence; the characteristic comparison sequence of the visual unit is a third level of the performance quality control spectrum of the visual unit, and the performance decay curve of the visual unit is a fourth level of the performance quality control spectrum of the visual unit.
Specifically, the working driving parameters of the visual unit are the functional parameters executed when the visual unit operates, so that the working instructions received by the visual unit are obtained through communication connection with the smart identifier to serve as the working driving parameters of the visual unit.
More specifically, the working effect parameters of the visualization unit are used for describing the working effect of the visualization unit displayed in actual working, and a series of parameters such as current, voltage, spectral frequency, light intensity and the like displayed by the visualization unit in the actual working process are obtained through communication connection with the intelligent identification and setting of the monitoring unit.
More specifically, the working driving parameter and the working effect parameter of the visualization unit at the same time are bound to obtain the performance characteristic of the visualization unit, that is, the performance state of the visualization unit is judged through the relation between the working driving parameter and the working effect parameter of the visualization unit at the same time.
More specifically, the performance quality control map is used for judging the performance state of the visualization unit through multidimensional analysis of the visualization unit, and in the performance quality control map, performance characteristics are analyzed through four levels:
First level: and arranging the performance characteristics according to the time sequence to obtain a performance characteristic sequence of the visualization unit.
Second level: judging each performance grade in the performance characteristic sequence of the visual unit according to a preset standard to obtain the performance grade represented by each performance characteristic, and linking each performance grade to obtain a performance grade change curve of the visual unit; it can be seen that the second hierarchy is a hierarchy obtained based on the first hierarchy, and the performance level change curve constructed by the second hierarchy has two roles: firstly, judging whether the performance grade at the current moment is qualified or not, and secondly, judging whether the performance grade is in a descending situation or not, and if so, initiating early warning according to the descending situation or not so as to maintain the visualization unit.
Third level: based on the performance characteristic sequence of the visual unit, summarizing the performance characteristics with the same working driving parameters into a characteristic comparison sequence; the second level is to analyze the performance characteristics of the visual units continuously according to the time sequence, the third level is to select the performance characteristics of the visual units with the same working driving parameters based on the first level, that is to say, analyze the performance characteristics of the visual units working under the same working driving parameters, and judge the performance situation of the visual units by comparing and analyzing the working effect parameters of the visual units under the same working driving parameters.
Fourth level: obtaining a performance decay curve of the visualization unit through analysis of the feature comparison sequence; the characteristic comparison sequence is a performance characteristic set with the same working driving parameters, in a certain time period, the visualization unit can keep the same working driving parameters, and after a certain time interval, the time period for implementing the performance characteristics of the same working driving parameters also appears, and the performance characteristics of the time periods are analyzed to intuitively compare and obtain the performance state of the visualization unit so as to obtain the performance decay curve of the visualization unit.
Preferably, the step of obtaining the performance decay curve of the visualization unit by analysis of the feature comparison sequence comprises:
s241: summarizing the performance features continuously existing in the feature comparison sequence into feature paragraphs according to the time sequence;
s242: carrying out change analysis on the mapping relation between the working driving parameters and the working effect parameters of the performance characteristics to obtain the performance continuous parameters of the characteristic paragraphs;
s243: acquiring time intervals among the characteristic paragraphs, and analyzing according to the time intervals among the characteristic paragraphs and the differences of the performance continuous parameters of the characteristic paragraphs to obtain the performance decay parameters of the characteristic paragraphs in the time intervals;
S244: and connecting each performance decay parameter in time sequence to obtain the performance decay curve of the visualization unit.
Specifically, the feature comparison sequence is a set of performance features with the same working driving parameters, and the performance features continuously existing in the feature comparison sequence are summarized into feature paragraphs according to time sequence, so that a plurality of feature paragraphs are obtained.
More specifically, the change analysis of the mapping relationship between the working driving parameters and the working effect parameters of each performance feature is performed on each feature paragraph, so as to obtain the performance continuous parameters of the feature paragraphs, where the performance continuous parameters are descriptions of the performance state change forms of the visualization units which continuously work according to the same working driving parameters.
More specifically, the difference between the analysis and the second level is that the second level is to judge the area where the performance feature is located to obtain the performance level to which the performance feature belongs, and the analysis of the change of the mapping relationship between the operation driving parameter and the operation effect parameter of the performance feature is to judge the difference between the actual performance and the ideal performance, and in another way, the analysis can be regarded as performing more level subdivisions on the same performance level of the visualization unit, the subdivided levels all belong to the same performance level, and as the visualization unit continuously works, the subdivision level fed back by the performance feature of the visualization unit reciprocally changes, and the performance continuous parameter is obtained by judging the change of the subdivision level fed back by the performance feature.
More specifically, the time intervals between the characteristic paragraphs are obtained, and analysis is performed according to the time intervals between the characteristic paragraphs and the differences of the performance duration parameters of the characteristic paragraphs to obtain the performance decay parameters of the characteristic paragraphs in the time intervals.
It will be appreciated that at both ends of the time interval, the visualization units operate according to the same operation driving parameters, if the performance of the visualization units is unchanged, the performance duration parameters of the visualization units should also not change, if the performance of the visualization units is negatively changed, the performance of the visualization units is faded, and the performance decay parameters of the feature segments at the time interval can be obtained by dividing the performance degree of the fading by the time interval.
More specifically, the performance decay parameters are connected in time sequence to obtain a performance decay curve of the visualization unit, where the performance decay curve is used to predict a performance risk of the visualization unit, so that an early warning is sent before the normal service life of the visualization unit is over.
Preferably, the step of adjusting the best visual operation and maintenance parameters of the smart tag according to the performance quality control map of each visual unit to obtain adjusted operation and maintenance parameters of the smart tag, and judging the feasibility of the adjusted operation and maintenance parameters according to the visual operation and maintenance model to determine the actual operation and maintenance scheme of the smart tag includes:
S31: judging the best visual operation and maintenance parameters of the intelligent identification according to a first level and a second level of a performance quality control map of each visual unit so as to judge whether each visual unit can implement the best visual operation and maintenance parameters, and marking the visual units which cannot implement the best visual operation and maintenance parameters as target units;
s32: taking the optimal visual operation and maintenance parameters as reference, performing cross analysis according to a first level and a second level of the performance quality control spectrum of each target unit to obtain adjustment operation and maintenance parameters which can be implemented by each target unit;
s33: substituting the adjustment operation and maintenance parameters into the visual operation and maintenance model to calculate the prediction operation and maintenance effect of the adjustment operation and maintenance parameters under the current external environment, and if the prediction operation and maintenance effect is within the range of the expected difference from the expected working target, determining the actual operation and maintenance scheme of the intelligent identifier by the adjustment operation and maintenance parameters;
s34: if the predicted operation and maintenance effect and the expected operation and maintenance target are not in the expected difference range, the expected operation and maintenance target in the visual operation and maintenance model is lowered, and calculation and verification of the optimized visual operation and maintenance parameters are repeated.
Specifically, whether the visualization unit is in a normal performance level as a whole, particularly whether the performance level is normal when the working driving parameter close to the optimal visual operation and maintenance parameter is implemented is judged by the first level and the second level of the performance quality control map of the visualization unit.
It can be understood that the smart sign is operated by a plurality of visualization units together, if some of the visualization units cannot implement the optimal visual operation and maintenance parameters, a vulnerability is caused to the overall effect of the smart sign, so that the whole visualization units need to be judged, and the visualization units which cannot implement the optimal visual operation and maintenance parameters are marked as target units.
More specifically, based on the optimal visual operation and maintenance parameters, cross analysis is performed according to the performance quality control maps of each target unit, so as to obtain the adjustable operation and maintenance parameters which can be implemented by each target unit, and the purpose of the step is that: because the target units cannot realize the optimal visual operation and maintenance parameters, the operation driving parameters which are closest to the optimal visual operation and maintenance parameters and can be normally implemented by all the target units are found out according to the performance of all the target units under all the operation driving parameters and are used as the operation and maintenance adjustment parameters.
More specifically, substituting the adjustment operation and maintenance parameters into the visual operation and maintenance model to calculate the prediction operation and maintenance effect of the adjustment operation and maintenance parameters under the current external environment, and if the prediction operation and maintenance effect and the expected working target are in the expected difference range, determining the adjustment operation and maintenance parameters as an actual operation and maintenance scheme of the intelligent identification.
The method comprises the following specific steps:
s331: judging the quantity ratio of the target unit to the rest of the visualized units in the visualized units;
s332: if the ratio of the number of the target units in the visualization units to the number of the remaining visualization units is smaller than the expected standard, driving the target units to implement the operation and maintenance parameter adjustment, and implementing the optimal visualization operation and maintenance parameters by the remaining visualization units;
s333: if the ratio of the number of target units in the visualization units to the number of remaining visualization units is less than the expected standard, all visualization units implement the operation and maintenance parameter adjustment.
More specifically, if the predicted operation and maintenance effect and the expected operation and maintenance target are not within the expected difference range, the expected operation and maintenance target in the visual operation and maintenance model is lowered, and calculation and verification of the optimized visual operation and maintenance parameters are repeated.
Referring to fig. 2, in a second aspect, the present invention provides a smart id operation and maintenance management system based on environmental parameters, including:
The data acquisition module is used for carrying out multidimensional parameter acquisition on the external environment through a pre-deployed sensor group, and substituting each acquired parameter into a preset visual operation and maintenance model so as to calculate the optimal visual operation and maintenance parameter of the intelligent identifier under each parameter; the intelligent identifier is provided with a plurality of visualization units for realizing the visualization function, and the optimal visualization operation and maintenance parameters are used for driving the visualization units to work;
the performance analysis module is used for continuously collecting the working driving parameters and the working effect parameters of each visual unit in the intelligent identification through communication connection with the intelligent identification, and substituting the collected working driving parameters and the collected working effect parameters into a preset performance quality control model so as to obtain performance quality control maps of each visual unit;
and the scheme analysis module is used for adjusting the optimal visual operation and maintenance parameters of the intelligent identification according to the performance quality control maps of the visual units to obtain the adjustment operation and maintenance parameters of the intelligent identification, and judging the feasibility of the adjustment operation and maintenance parameters according to the visual operation and maintenance model to determine the actual operation and maintenance scheme of the intelligent identification.
The above modules all operate according to an artificial intelligence dialogue method provided in the first aspect, and are not described herein.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (7)
1. The intelligent identification operation and maintenance management method based on the environment parameters is characterized by comprising the following steps of:
carrying out multidimensional parameter acquisition on an external environment through a pre-deployed sensor group, and substituting each acquired parameter into a preset visual operation and maintenance model to calculate the optimal visual operation and maintenance parameter of the intelligent identifier under each parameter; the intelligent identifier is provided with a plurality of visualization units for realizing the visualization function, and the optimal visualization operation and maintenance parameters are used for driving the visualization units to work;
continuously collecting the working driving parameters and the working effect parameters of each visual unit in the intelligent identification through communication connection with the intelligent identification, and substituting the collected working driving parameters and the collected working effect parameters into a preset performance quality control model to obtain performance quality control maps of each visual unit;
And adjusting the optimal visual operation and maintenance parameters of the intelligent identification according to the performance quality control maps of the visual units to obtain the adjustment operation and maintenance parameters of the intelligent identification, and judging the feasibility of the adjustment operation and maintenance parameters according to the visual operation and maintenance model to determine the actual operation and maintenance scheme of the intelligent identification.
2. The method for intelligent identification operation and maintenance management based on environment parameters according to claim 1, wherein the steps of performing multidimensional parameter acquisition on the external environment through a pre-deployed sensor group, and substituting each acquired parameter into a preset visual operation and maintenance model to calculate the optimal visual operation and maintenance parameter of the intelligent identification under each parameter comprise the following steps:
acquiring a multi-dimensional parameter of an external environment through a pre-deployed sensor group to acquire an ambient light intensity parameter, an ambient smoke concentration parameter and an ambient temperature parameter in the external environment, and substituting the ambient light intensity parameter, the ambient smoke concentration parameter and the ambient temperature parameter into an obstruction level in a preset visual operation and maintenance model;
acquiring an expected work target of the intelligent identifier, and substituting the expected work target into a target level of the visual operation and maintenance model;
And carrying out parameter deduction on the driving level of the visual operation and maintenance model according to the blocking level and the target level of the visual operation and maintenance model so as to obtain the optimal visual operation and maintenance parameters of the intelligent identification.
3. The method for intelligent identification operation and maintenance management based on environmental parameters as set forth in claim 2, wherein the step of parameter deduction includes:
the target level of the visual operation and maintenance model performs parameter mapping on the driving level of the visual operation and maintenance model according to the expected working target so as to determine preliminary driving parameters on the driving level;
and performing parameter mapping on a driving level of the visual operation and maintenance model according to the ambient light intensity parameter, the ambient smoke concentration parameter and the ambient temperature parameter by the blocking level of the visual operation and maintenance model so as to perform parameter correction on the preliminary driving parameter to obtain the optimal visual operation and maintenance parameter.
4. The method for managing operation and maintenance of smart markers based on environmental parameters as set forth in claim 2, wherein the steps of continuously collecting the operation driving parameters and the operation effect parameters of each of the visualization units in the smart markers through communication connection with the smart markers, and substituting the collected operation driving parameters and the collected operation effect parameters into a preset performance quality control model to obtain the performance quality control map of each of the visualization units comprise:
Continuously collecting working driving parameters and working effect parameters of each visualization unit in the intelligent mark through communication connection with the intelligent mark; the working driving parameters are used for driving the visual unit to work, and the working effect parameters are used for describing the working effect of the visual unit;
binding the working driving parameters and the working effect parameters of the visualization unit at the same moment to obtain the performance characteristics of the visualization unit, and arranging the performance characteristics according to time sequence to obtain the performance characteristic sequence of the visualization unit; wherein the performance characteristic sequence of the visualization unit is a first level of a performance quality control map of the visualization unit;
judging each performance characteristic in a performance characteristic sequence of the visual unit according to a preset standard to obtain performance levels represented by each performance characteristic, and connecting each performance level to obtain a performance level change curve of the visual unit; wherein the performance level change curve of the visualization unit is a second level of the performance quality control map of the visualization unit;
Summarizing the performance characteristics with the same working driving parameters into a characteristic comparison sequence based on the performance characteristic sequence of the visualization unit, and obtaining a performance decay curve of the visualization unit through analysis of the characteristic comparison sequence; the characteristic comparison sequence of the visual unit is a third level of the performance quality control spectrum of the visual unit, and the performance decay curve of the visual unit is a fourth level of the performance quality control spectrum of the visual unit.
5. The method of intelligent sign operation and maintenance management based on environmental parameters according to claim 4, wherein the step of obtaining the performance decay curve of the visualization unit through analysis of the feature comparison sequence comprises:
summarizing the performance features continuously existing in the feature comparison sequence into feature paragraphs according to the time sequence;
carrying out change analysis on the mapping relation between the working driving parameters and the working effect parameters of the performance characteristics to obtain the performance continuous parameters of the characteristic paragraphs;
acquiring time intervals among the characteristic paragraphs, and analyzing according to the time intervals among the characteristic paragraphs and the differences of the performance continuous parameters of the characteristic paragraphs to obtain the performance decay parameters of the characteristic paragraphs in the time intervals;
And connecting each performance decay parameter in time sequence to obtain the performance decay curve of the visualization unit.
6. The method for intelligent sign operation and maintenance management based on environment parameters according to claim 5, wherein the steps of adjusting the best visual operation and maintenance parameters of the intelligent sign according to the performance quality control map of each visual unit to obtain adjusted operation and maintenance parameters of the intelligent sign, and judging the feasibility of the adjusted operation and maintenance parameters according to the visual operation and maintenance model to determine the actual operation and maintenance scheme of the intelligent sign comprise:
judging the best visual operation and maintenance parameters of the intelligent identification according to a first level and a second level of a performance quality control map of each visual unit so as to judge whether each visual unit can implement the best visual operation and maintenance parameters, and marking the visual units which cannot implement the best visual operation and maintenance parameters as target units;
taking the optimal visual operation and maintenance parameters as reference, performing cross analysis according to a first level and a second level of the performance quality control spectrum of each target unit to obtain adjustment operation and maintenance parameters which can be implemented by each target unit;
Substituting the adjustment operation and maintenance parameters into the visual operation and maintenance model to calculate the prediction operation and maintenance effect of the adjustment operation and maintenance parameters under the current external environment, and if the prediction operation and maintenance effect is within the range of the expected difference from the expected working target, determining the actual operation and maintenance scheme of the intelligent identifier by the adjustment operation and maintenance parameters;
if the predicted operation and maintenance effect and the expected operation and maintenance target are not in the expected difference range, the expected operation and maintenance target in the visual operation and maintenance model is lowered, and calculation and verification of the optimized visual operation and maintenance parameters are repeated.
7. An intelligent identification operation and maintenance management system based on environmental parameters is characterized by comprising:
the data acquisition module is used for carrying out multidimensional parameter acquisition on the external environment through a pre-deployed sensor group, and substituting each acquired parameter into a preset visual operation and maintenance model so as to calculate the optimal visual operation and maintenance parameter of the intelligent identifier under each parameter; the intelligent identifier is provided with a plurality of visualization units for realizing the visualization function, and the optimal visualization operation and maintenance parameters are used for driving the visualization units to work;
The performance analysis module is used for continuously collecting the working driving parameters and the working effect parameters of each visual unit in the intelligent identification through communication connection with the intelligent identification, and substituting the collected working driving parameters and the collected working effect parameters into a preset performance quality control model so as to obtain performance quality control maps of each visual unit;
and the scheme analysis module is used for adjusting the optimal visual operation and maintenance parameters of the intelligent identification according to the performance quality control maps of the visual units to obtain the adjustment operation and maintenance parameters of the intelligent identification, and judging the feasibility of the adjustment operation and maintenance parameters according to the visual operation and maintenance model to determine the actual operation and maintenance scheme of the intelligent identification.
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