Modeling method for quickly generating industrial identification analysis application

Abstract

The invention discloses a modeling method for quickly generating an industrial identification analysis application, particularly relates to the field of computer science, and is used for solving the problems that the code scanning duration is not easy to control due to different coding complexity degrees and adverse factors exist when the code scanning duration is too short or too long in the prior art. Comprising the following steps: collecting and analyzing identification coding information, and determining influence factors of coding complexity; comprehensively analyzing the coding complexity according to the collected identification coding information, and determining the coding complexity; combining the coding complexity and the environmental influence factors to comprehensively determine a coding time-constant adjustment proportion; regulating and early warning code scanning duration according to a coding time regulation proportion; according to the method, the code scanning time length coefficient is determined by comprehensively analyzing the coding complexity and combining the environmental influence factors, and the standard code scanning time length is accurately regulated and controlled according to the code scanning time length coefficient, so that the code scanning efficiency is improved on the premise that the identification code can be accurately identified.

Description

Technical Field

[0001] The present invention relates to the field of computer science and technology, and more specifically, to a modeling method for rapidly generating industrial identification resolution applications. Background Art

[0002] Rapid generation of industrial identification resolution application modeling mainly involves industrial production, logistics, quality control and other fields, in which items, production lines, equipment, etc. need to be identified and coded, and the identification needs to be scanned and identified to collect data and monitor and manage production processes, logistics, product quality, etc. With the promotion of industrial digitalization and intelligence, the demand for industrial identification resolution applications continues to increase. In order to quickly meet these needs, it is necessary to quickly generate industrial identification resolution application modeling.

[0003] At present, during the scanning process, due to the different complexity of the code, the scanning time is not easy to control. When the scanning time is too short, it may lead to failure to parse or recognize complex identification codes. If the scanning time is too long, the overall modeling time will also be prolonged, and it is impossible to effectively guarantee the rapid generation of industrial identification resolution application modeling.

[0004] In view of the above problems, the present invention proposes a solution. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a modeling method for quickly generating industrial identification resolution applications, which determines the scanning time coefficient by comprehensively analyzing the complexity of the code and combining the environmental influencing factors, and accurately adjusts the standard scanning time according to the scanning time coefficient, thereby ensuring that the scanning efficiency is improved while being able to accurately identify the identification code, so as to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A modeling method for quickly generating industrial identification resolution applications includes the following steps:

[0008] Step S1, collecting and analyzing identification coding information to determine factors affecting coding complexity;

[0009] Step S2, comprehensively analyzing the coding complexity according to the identification coding information collected in step S1 to determine the coding complexity;

[0010] Step S3, comprehensively determining the encoding timing adjustment ratio based on the encoding complexity and environmental influencing factors;

[0011] Step S4, adjusting the ratio according to the encoding time, and regulating the scanning time to warn.

[0012] In a preferred embodiment, in step S1, the collected identification coding information includes the amount of special symbols, the amount of repeated data and the total amount of data.

[0013] In a preferred embodiment, in step S2, the special symbol amount, repeated data amount and total data amount are marked as Unicode, Duplicate data and Data volume respectively, and the coding complexity evaluation coefficient C is calculated by a formula. The specific calculation expression is as follows:

[0014]

[0015] Wherein, g1, g2, and g3 are the preset proportional coefficients of the special symbol ratio, repeated data ratio, and total data volume, respectively, and g3>g1>g2>0;

[0016] The special symbol ratio refers to the ratio of the special symbol quantity to the total data quantity, and the repeated data ratio refers to the ratio of the repeated data quantity to the total data quantity.

[0017] In a preferred embodiment, in step S3, the scanning time is comprehensively evaluated by combining the coding complexity evaluation coefficient C and various environmental influencing factors, and the light intensity deviation value, the number of light sources and the dust content are calibrated as LX, LS and PM respectively. The environmental evaluation coefficient E is first calculated by the formula. The specific calculation expression is as follows:

[0018] E=ln(q1LX+q2LS+q3PM)

[0019] Where q1, q2, and q3 are preset proportional coefficients of light intensity deviation, number of light sources, and dust content, respectively, and q1>q2>q3>0;

[0020] It should be noted that the light intensity deviation value refers to the deviation value between the light intensity of the environment in which the scanner is located and the optimal light intensity for scanning.

[0021] In a preferred embodiment, the environmental assessment coefficient E is compared with a standard environmental threshold:

[0022] If the environmental assessment coefficient E is greater than or equal to the standard environmental threshold, an early warning will be issued for the scanned environment, prompting relevant staff to adjust the environmental influencing factors until the environmental assessment coefficient E is less than the standard environmental threshold.

[0023] In a preferred embodiment, when the code scanning environment meets the requirements, the code scanning duration coefficient H is determined according to the coding complexity evaluation coefficient C and the environment evaluation coefficient E. The specific calculation expression is as follows:

[0024] H=k1C+k2E

[0025] Wherein, k1 and k2 are preset proportional coefficients of the coding complexity assessment coefficient C and the environmental assessment coefficient E, respectively, and k1>k2>0;

[0026] The scanning time coefficient H is compared with the standard time threshold H0, and the time deviation coefficient Hp is calculated by the formula Hp=H / H0.

[0027] In a preferred embodiment, in step S4, the following steps are specifically included:

[0028] Step S4.1, obtaining the duration deviation coefficient Hp calculated in step S3;

[0029] Step S4.2, calculate the actual required scanning time T according to the formula T=Hp*T0;

[0030] Step S4.3, compare the actual required scanning time T with the maximum scanning time Tm to determine whether the code scanning time is reasonable;

[0031] If the actual scanning time T required is greater than the maximum scanning time Tm, an alarm prompt will be given as the coding is too complex.

[0032] Technical effects and advantages of a modeling method for quickly generating industrial identification resolution applications of the present invention:

[0033] The present invention comprehensively analyzes the complexity of the code, determines the code scanning time coefficient in combination with environmental influencing factors, and accurately adjusts the standard code scanning time according to the code scanning time coefficient, thereby ensuring that the code scanning efficiency is improved under the premise of being able to accurately identify the identification code;

[0034] The present invention also comprehensively analyzes the environmental factors that affect the code scanning in the code scanning environment, and alarms in real time to prompt relevant staff to adjust the environment, ensuring that the code scanner scans the code in a relatively good environment;

[0035] The present invention analyzes whether the scanning time after final adjustment exceeds the required range, optimizes and warns the identification data with too long scanning time, and prompts relevant staff to optimize the coding structure, thereby improving the efficiency of modeling for generating industrial identification resolution applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A flow chart of a modeling method for rapidly generating industrial identification resolution applications for the present invention;

[0037] Figure 2 This is a flow chart of the early warning method for regulating the scanning time of the present invention. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] The present invention provides a modeling method for quickly generating industrial identification resolution applications. The method comprehensively analyzes the complexity of the code, determines the scanning time coefficient in combination with environmental influencing factors, and accurately regulates the standard scanning time according to the scanning time coefficient, thereby ensuring that the scanning efficiency is improved under the premise of being able to accurately identify the identification code.

[0040] Example

[0041] Figure 1 A flow chart of a modeling method for rapidly generating industrial identification resolution applications is provided in the present invention.

[0042] The steps include:

[0043] Step S1, perform coding requirement analysis, collect and analyze identification coding information, and determine factors affecting coding complexity;

[0044] Step S2, performing coding data analysis, performing a comprehensive analysis on the coding complexity according to the identification coding information collected in step S1, and determining the coding complexity;

[0045] Step S3, analyze the scanning time, comprehensively determine the coding time adjustment ratio based on coding complexity and environmental factors, and issue an early warning prompt;

[0046] Step S4, adjusting the ratio according to the encoding time, and regulating the scanning time to warn.

[0047] In step S1, the requirement analysis of coding refers to a detailed analysis of the requirements of industrial identification applications, clarifying the problems that need to be solved by the application, as well as the specific requirements for identification coding, print output, parsing task management and data storage. In this embodiment, the identification coding information is mainly collected and analyzed. The coding complexity is related to the diversity, quantity, complexity, organizational form, etc. of the identification data. If the identification data contains a large number of special characters, mathematical symbols or multi-layer nested data structures, these data require higher coding complexity to encode so that the identification data can be encoded into a form that can be stored and transmitted. If the identification data contains a large amount of repeated data or data with simple encoding, the coding complexity is relatively low. Therefore, the complexity and characteristics of the identification data are the key factors that determine the coding complexity.

[0048] Specifically, the collected identification coding information includes the amount of special symbols, the amount of repeated data and the total amount of data. The amount of special symbols refers to the total number of special characters and mathematical symbols included in the identification data. When the total amount of data remains unchanged, the larger the amount of special symbols, the more special characters and mathematical symbols are contained in the identification data, and the more complex the encoding is; the amount of repeated data refers to the amount of repeated data in the identification data. When the total amount of data remains unchanged, the larger the amount of repeated data, the simpler the encoding is; the total amount of data refers to the total size of the identification data, the amount of special symbols, and the amount of repeated data. When the total amount of data remains unchanged, the larger the total amount of data, the more complex the encoding is.

[0049] It should be noted that the total amount of special symbols in the identification data is automatically collected and obtained by the program. Usually, the program can be run on the storage medium of the identification data (such as a database, file, etc.) to scan the identification data to calculate the total amount of special symbols. The total amount of special symbols can also be calculated by statistical analysis of the identification data.

[0050] The amount of duplicate data can be obtained and calculated through data comparison or deduplication algorithms. First, analyze the data to find out the parts that are repeated with other data, remove them, and get non-duplicate data. The specific implementation method can use hash tables, dictionary trees, or sorting algorithms. It is important to ensure that the method used can compare the similarity of the data to ensure accurate results.

[0051] In step S2, the coding data analysis refers to a comprehensive analysis of the coding complexity according to the identification coding information collected in step S1. Specifically, the special symbol amount, the repeated data amount and the total data amount are marked as Unicode, Duplicated data and Data volume respectively, and the coding complexity evaluation coefficient C is calculated by the formula. The specific calculation expression is as follows:

[0052]

[0053] In the formula, g1, g2, and g3 are preset proportional coefficients of the proportion of special symbols, the proportion of repeated data, and the total amount of data, respectively, and g3>g1>g2>0.

[0054] The special symbol ratio refers to the ratio of the special symbol quantity to the total data quantity, and the repeated data ratio refers to the ratio of the repeated data quantity to the total data quantity.

[0055] In step S3, analyzing the scanning time refers to obtaining the scanning time coefficient by combining the coding complexity and environmental influencing factors. Environmental influencing factors include light conditions, light source status and dust content. Light conditions refer to the light intensity of the environment where the scanner is located. Strong light or shadow may affect the reading effect of the scanner. Light source status refers to the number of light sources in the environment where the scanner is located. The more light sources there are, the scanner may be disturbed by different light sources during the scanning process, affecting the reading effect. Dust content refers to the dust content in the air in the environment where the scanner is located. The more dust content there is, the worse the scanning effect of the scanner is. Therefore, it is necessary to determine the environmental state to indirectly reflect the difficulty of scanning. The greater the difficulty of scanning, the longer the corresponding scanning time needs to be.

[0056] Specifically, in step S3, the scanning time is comprehensively evaluated by combining the coding complexity evaluation coefficient C and various environmental influencing factors, and the light intensity deviation value, the number of light sources, and the dust content are calibrated as LX, LS, and PM, respectively. The environmental evaluation coefficient E is first calculated by the formula. The specific calculation expression is as follows:

[0057] E=ln(q1LX+q2LS+q3PM)

[0058] Wherein, q1, q2, and q3 are preset proportional coefficients of light intensity deviation, number of light sources, and dust content, respectively, and q1>q2>q3>0.

[0059] It should be noted that the light intensity deviation value refers to the deviation between the light intensity of the environment in which the scanner is located and the optimal light intensity for scanning. The larger the deviation value, the worse the scanning environment.

[0060] Compare the environmental assessment coefficient E with the standard environmental threshold to determine whether the scanning environment meets the requirements.

[0061] If the environmental assessment coefficient E is greater than or equal to the standard environmental threshold, it means that the scanning environment is poor, which is likely to affect the scanning accuracy and reduce the scanning efficiency. At this time, an early warning will be issued for the scanning environment to prompt relevant staff to make targeted adjustments based on the specific influencing parameter values ​​of the environmental assessment coefficient E (light intensity deviation value, number of light sources, and dust content) until the environmental assessment coefficient E is less than the standard environmental threshold before proceeding to the next step.

[0062] When the code scanning environment meets the requirements, the code scanning time coefficient H is determined according to the coding complexity evaluation coefficient C and the environment evaluation coefficient E. The specific calculation expression is as follows:

[0063] H=k1C+k2E

[0064] Wherein, k1 and k2 are preset proportional coefficients of the coding complexity assessment coefficient C and the environmental assessment coefficient E, respectively, and k1>k2>0.

[0065] Since the scanning time is related to both the encoding complexity and the scanning environment, a comprehensive analysis of the two is required to determine the scanning time coefficient H.

[0066] The code scanning duration coefficient H is compared with the standard duration threshold H0 to calculate the duration deviation coefficient Hp, that is, Hp = H / H0.

[0067] If the duration deviation coefficient Hp is greater than 1, it means that the actual scanning time required is longer than the preset scanning time T0. Otherwise, it means that the actual accurate scanning time required is less than the preset scanning time T0. The scanning efficiency can be improved by shortening the scanning time.

[0068] In step S4, if Figure 2 As shown, the specific steps include:

[0069] Step S4.1, obtaining the duration deviation coefficient Hp calculated in step S3;

[0070] Step S4.2, calculate the actual required scanning time T according to the formula T=Hp*T0;

[0071] Step S4.3, compare the actual required scanning time T with the maximum scanning time Tm to determine whether the code scanning time is reasonable;

[0072] If the actually required scanning time T is greater than the maximum scanning time Tm, it means that the actually required scanning time is too long, which makes the overall process too slow and affects the efficiency. Otherwise, it means that the actually required scanning time T is within a reasonable range.

[0073] If the actual scanning time T is greater than the maximum scanning time Tm, an alarm will be issued for the coding being too complex, prompting the relevant staff to optimize and simplify the structure or content of the coding to avoid difficulties in the scanning process. If the actual scanning time T is less than or equal to the maximum scanning time Tm, it means that the scanning time is within a reasonable range and there is no need to issue an alarm to prompt the relevant staff to optimize.

[0074] It should be noted that although the duration of scanning is affected by both the coding complexity and the scanning environment, in step S3, specifically before determining the scanning duration coefficient H, the scanning environment has been adjusted to ensure that the environmental assessment coefficient E is within a reasonable range. Therefore, in step S4, only the impact of coding complexity on scanning is considered.

[0075] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0076] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0077] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0078] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0079] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A modeling method for rapidly generating industrial identification resolution applications, characterized in that: The steps include: Step S1, collecting and analyzing identification coding information to determine factors affecting coding complexity; Step S2, comprehensively analyzing the coding complexity according to the identification coding information collected in step S1 to determine the coding complexity; Step S3, comprehensively determining the encoding timing adjustment ratio based on the encoding complexity and environmental influencing factors; Step S4, adjusting the ratio according to the encoding time, and regulating the scanning time to warn.

2. A modeling method for rapidly generating industrial identification resolution applications according to claim 1, characterized in that: In step S1, the collected identification coding information includes the amount of special symbols, the amount of repeated data and the total amount of data.

3. A modeling method for rapidly generating industrial identification resolution applications according to claim 2, characterized in that: In step S2, the amount of special symbols, the amount of repeated data and the total amount of data are marked as Unicode, Duplicated data and Data volume respectively, and the coding complexity evaluation coefficient C is calculated by the formula. The specific calculation expression is as follows: Wherein, g1, g2, and g3 are the preset proportional coefficients of the special symbol ratio, repeated data ratio, and total data volume, respectively, and g3>g1>g2>0; The special symbol ratio refers to the ratio of the special symbol quantity to the total data quantity, and the repeated data ratio refers to the ratio of the repeated data quantity to the total data quantity.

4. A modeling method for rapidly generating industrial identification resolution applications according to claim 3, characterized in that: In step S3, the scanning time is comprehensively evaluated by combining the coding complexity evaluation coefficient C and various environmental influencing factors, and the light intensity deviation value, the number of light sources and the dust content are calibrated as LX, LS and PM respectively. The environmental evaluation coefficient E is first calculated by the formula. The specific calculation expression is as follows; E=ln(q1LX+q2LS+q3PM) Where q1, q2, and q3 are preset proportional coefficients of light intensity deviation, number of light sources, and dust content, respectively, and q1>q2>q3>0; It should be noted that the light intensity deviation value refers to the deviation value between the light intensity of the environment in which the scanner is located and the optimal light intensity for scanning.

5. A modeling method for rapidly generating industrial identification resolution applications according to claim 4, characterized in that: Compare the environmental assessment factor E with the standard environmental threshold: If the environmental assessment coefficient E is greater than or equal to the standard environmental threshold, an early warning will be issued for the scanned environment, prompting relevant staff to adjust the environmental influencing factors until the environmental assessment coefficient E is less than the standard environmental threshold.

6. A modeling method for rapidly generating industrial identification resolution applications according to claim 4, characterized in that: When the code scanning environment meets the requirements, the code scanning duration coefficient H is determined according to the coding complexity evaluation coefficient C and the environment evaluation coefficient E. The specific calculation expression is as follows: H=k1C+k2E Wherein, k1 and k2 are preset proportional coefficients of the coding complexity assessment coefficient C and the environmental assessment coefficient E, respectively, and k1>k2>0; The scanning time coefficient H is compared with the standard time threshold H0, and the time deviation coefficient Hp is calculated by the formula Hp=H / H0.

7. A modeling method for rapidly generating industrial identification resolution applications according to claim 6, characterized in that: In step S4, the following steps are specifically included: Step S4.1, obtaining the duration deviation coefficient Hp calculated in step S3; Step S4.2, calculate the actual required scanning time T according to the formula T=Hp*T0; Step S4.3, compare the actual required scanning time T with the maximum scanning time Tm to determine whether the code scanning time is reasonable; If the actual scanning time T required is greater than the maximum scanning time Tm, an alarm prompt will be given as the coding is too complex.

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