Self-contained data printing system and method and application of self-contained data printing system and method in ultrapure water machine

Abstract

The invention relates to the technical field of data processing, in particular to a built-in data printing system and method and application of the built-in data printing system and method in an ultrapure water machine. Collected ultrapure water quality demand data and established different ultrapure water quality grade production standard data are analyzed and processed to generate ultrapure water quality grade data; the method comprises the following steps: collecting corresponding normal running parameter interval data of the ultrapure water machine part, collecting real-time running parameter data of the ultrapure water machine part through a sensor, and processing the data to generate real-time running parameter data of the standard ultrapure water machine part; performing numerical value matching processing on the normal running parameter interval data of the ultrapure water machine component and the real-time running parameter data of the standard ultrapure water machine component, generating real-time running state analysis data of the ultrapure water machine according to a numerical value matching result, and finally constructing and storing ultrapure water production data. And data printing is performed through the data printing device, so that intelligent analysis of the data of the ultrapure water machine and accurate printing of the analysis data are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, in particular to a self-contained data printing system and method and application thereof in an ultrapure water machine. Background Art

[0002] Ultrapure water machine is a kind of water treatment equipment which adopts pretreatment, reverse osmosis technology, ultrapurification treatment and post-treatment to almost completely remove the conductive medium in the water, and remove the non-dissociated colloids, gases and organic matter in the water to a very low level.

[0003] The Chinese invention patent with publication number CN111367917B introduces a data storage method for water pump unit status evaluation. The water pump unit status monitoring system collects fast variable and process quantity status data, and performs working condition calibration on the collected status data. The calibrated status data is then divided into five types of data, namely real-time recording data, real-time data, current data, unit operation characteristic data and historical data, and stored in a database. The data can be stored in a hierarchical manner to improve the comprehensive database system of the monitoring system, ensure that sufficient useful data is stored for the unit status analysis, reduce the amount of data stored, and improve the database retrieval performance. However, no effective water pump unit operating status judgment standard is given, making it difficult to achieve intelligent analysis of the unit operating status. Summary of the invention

[0004] 1. Technical issues to be solved

[0005] In order to solve the deficiencies in the background technology, the present invention provides a self-contained data printing system, method and application thereof in an ultrapure water machine, so as to realize intelligent analysis of ultrapure water machine data and accurate printing of analysis data.

[0006] (II) Technical solution

[0007] The present invention discloses a data processing method, comprising the following steps:

[0008] S1. Collect ultrapure water quality demand data;

[0009] S2. Establish production standard data of different ultrapure water quality grades, perform ultrapure water quality grade analysis and processing according to the ultrapure water quality demand data and the production standard data of different ultrapure water quality grades, and generate ultrapure water quality grade data;

[0010] S3, collecting the normal operation parameter interval data of the ultrapure water machine components corresponding to the ultrapure water quality grade data;

[0011] S4, collect real-time operating parameter data of standard ultrapure water machine components;

[0012] S5, performing numerical matching processing based on the normal operation parameter interval data of the ultrapure water machine components and the real-time operation parameter data of the standard ultrapure water machine components to generate real-time operation status analysis data of the ultrapure water machine;

[0013] S6. Construct ultrapure water production data based on the ultrapure water quality demand data, the ultrapure water quality grade data, the real-time operating parameter data of the standard ultrapure water machine components and the real-time operating status analysis data of the ultrapure water machine, and store them in the ultrapure water production data management platform.

[0014] The present invention generates ultrapure water quality grade data by analyzing and processing the collected ultrapure water quality demand data and the established production standard data of different ultrapure water quality grades, collects the corresponding normal operation parameter interval data of ultrapure water machine components, collects the real-time operation parameter data of ultrapure water machine components through sensors, cleans the abnormal data and performs average numerical measurement processing to generate the real-time operation parameter data of standard ultrapure water machine components, performs numerical matching processing on the normal operation parameter interval data of the ultrapure water machine components and the real-time operation parameter data of the standard ultrapure water machine components, generates the real-time operation status analysis data of the ultrapure water machine according to the numerical matching result, finally constructs and stores the ultrapure water production data, and prints the data when printing is needed, thereby realizing the intelligent analysis of the ultrapure water machine data and the accurate printing of the analysis data.

[0015] Preferably, the specific steps for collecting ultrapure water quality demand data are as follows:

[0016] S11. Enter the quality requirement data of the ultrapure water currently required to be produced through the ultrapure water production control interface to generate ultrapure water quality requirement data A, wherein the ultrapure water quality requirement data includes ultrapure water resistivity, ultrapure water microbial content, ultrapure water organic carbon content, ultrapure water endotoxin content and ultrapure water specific ion concentration.

[0017] Preferably, the specific steps of establishing production standard data of different ultrapure water quality grades, performing ultrapure water quality grade analysis and processing according to the ultrapure water quality demand data and the production standard data of different ultrapure water quality grades, and generating ultrapure water quality grade data are as follows:

[0018] S21, set the ultrapure water quality level set B = {b1, b2, ..., b i ,…,b k}, where b i represents the i-th ultrapure water quality grade, and k represents the total number of ultrapure water quality grades;

[0019] S22, establishing production standard data corresponding to each ultrapure water quality grade in the ultrapure water quality grade set, generating production standard data sets for different ultrapure water quality grades in, represents the production standard data of the i-th ultrapure water quality level;

[0020] S23, performing ultrapure water quality grade analysis and processing according to the ultrapure water quality demand data A and the different ultrapure water quality grade production standard data in the different ultrapure water quality grade production standard data sets to generate ultrapure water quality grade data D;

[0021] S231, construct the salp population, set the salp population size to N, the current number of iterations to t, and the maximum number of iterations to t max And the dimension of the search space for production standard data of different ultrapure water quality grades is P;

[0022] N groups of production standard data are randomly generated in the production standard data search space of different ultrapure water quality levels, each group of production standard data corresponds to a salp individual in the salp population, and the initial position set of the salp population is initialized as X = {X1, X2, ..., X i ,…,X N}, where X i represents the initial position of the i-th salp individual in the salp population;

[0023] S232, calculating the fitness function value of each salp individual in the salp population, arranging the salp individuals in the salp population from large to small according to the fitness function value, and selecting the salp individual with the highest fitness function value as the current optimal individual; the fitness function formula is as follows:

[0024]

[0025] Among them, Fit i represents the fitness function value of the i-th salp in the salp population, x i represents the ability of the production standard data corresponding to the i-th salp in the salp population to meet the ultrapure water quality demand data, and φ represents the correction value;

[0026] S233, the salps individuals in the salps population gather together to form a salps chain in the search space of the production standard data of different ultrapure water quality levels to hunt and forage, and the salps individual ranked first in the salps chain is used as the leader individual, and the remaining salps individuals are used as follower individuals;

[0027] S234. The leader individual will be affected by the position of the food in the search space of the production standard data of different ultrapure water quality levels and update its position; the position update formula is as follows:

[0028]

[0029] in, represents the position of the leader individual after the position update in the j-th dimension different ultrapure water quality level production standard data search space, X best Indicates the position of the current optimal individual, ub j and lb j They represent the search upper limit and search lower limit of the search space of the production standard data of different ultrapure water quality grades, rand1 and rand2 both represent random numbers that obey a uniform distribution between [0,1], α1 represents the convergence factor, and

[0030]

[0031] S235, the follower individual will follow the previous salp individual in the search space of the production standard data of different ultrapure water quality levels to update the position; the position update formula is as follows:

[0032]

[0033] in, represents the position of the i-th follower individual after the position update in the j-th dimension different ultrapure water quality level production standard data search space, and They represent the positions of the i-th and i-1-th follower individuals in the j-th dimension of the search space for production standards of different ultrapure water quality levels;

[0034] S236, calculating the fitness function value of each salp individual in the salp population after the position is updated, arranging the salp individuals in the salp population from large to small according to the fitness function value, and selecting the salp individual with the highest fitness function value as the current optimal individual;

[0035] S237, determine whether the current number of iterations t is less than the maximum number of iterations t max , if the current number of iterations t is less than the maximum number of iterations t max , then the current iteration number t is increased by 1, and the process returns to S233; otherwise, the current optimal individual is taken as the global optimal solution, and the ultrapure water quality grade corresponding to the production standard data corresponding to the global optimal solution is data-labeled to generate ultrapure water quality grade data D.

[0036] The ultrapure water quality grade analysis and processing is carried out through the salp optimization algorithm, which ensures the accuracy of the ultrapure water quality grade analysis results, accelerates the convergence speed of the analysis process, and effectively reduces the time cost of data processing. At the same time, the salp optimization algorithm has good robustness and can resist the interference caused by data noise to a certain extent, maintaining the stability and reliability of the analysis process.

[0037] Preferably, the specific steps of collecting the normal operation parameter interval data of the ultrapure water machine components corresponding to the ultrapure water quality grade data are as follows:

[0038] S31, calling the ultrapure water machine equipment normal operation parameter interval data corresponding to the ultrapure water quality grade data D from the ultrapure water machine historical operation data storage unit to generate an ultrapure water machine component normal operation parameter interval data set in, and They respectively represent the minimum and maximum values ​​of the operating parameter data of the ith component under normal operating conditions of the ultrapure water machine, and l represents the total number of ultrapure water machine components.

[0039] Preferably, the specific steps of collecting real-time operating parameter data of standard ultrapure water machine components are as follows:

[0040] S41, setting an ultrapure water machine operation data collection cycle, evenly dividing the ultrapure water machine operation data collection cycle into a number of ultrapure water machine operation data collection time points, generating an ultrapure water machine operation data collection time point set F = {f1, f2, ..., f i ,…,f p}, where f i represents the i-th ultrapure water machine operation data collection time point, and p represents the total number of ultrapure water machine operation data collection time points;

[0041] S42, using different high-precision sensors to collect the operating parameter data of each component of the ultrapure water machine in real time at each ultrapure water machine operating data collection time point in the ultrapure water machine operating data collection time point set, and generating a real-time operating parameter data matrix E' of the ultrapure water machine components as follows:

[0042]

[0043] Among them, e' ij Represents the real-time operating parameter data of the i-th component of the ultrapure water machine at the j-th ultrapure water machine operating data collection time point, wherein the high-precision sensors include but are not limited to pressure sensors, temperature sensors, flow sensors and liquid level sensors;

[0044] S43, using the Z-score method to clean abnormal data of the real-time operating parameter data of the ultrapure water machine components in the real-time operating parameter data matrix E' of the ultrapure water machine components, and generate a real data matrix of the real-time operating parameters of the ultrapure water machine components as follows:

[0045]

[0046] in, represents the real data of the real-time operating parameters of the jth ultrapure water machine component of the i-th component of the ultrapure water machine, o i It represents the total number of real data of real-time operating parameters of ultrapure water machine components obtained by real-time collection of operating parameter data of the i-th component of the ultrapure water machine; the abnormal data cleaning process is as follows:

[0047] S431, selecting the real-time operating parameter data of the i-th component of the ultrapure water machine at the j-th ultrapure water machine operating data collection time point in the real-time operating parameter data matrix of the ultrapure water machine components for abnormal data cleaning, When e' ij The abnormal point of the real-time operating parameter data of the ultrapure water machine components is e' ij Remove; otherwise, determine e' ij The real data of the real-time operating parameters of the ultrapure water machine components will be e' ij reserve;

[0048] Among them, μ i and σ i They respectively represent the mean and standard deviation of the real-time operating parameter data of all ultrapure water machine components obtained by real-time collection of the operating parameter data of the i-th component of the ultrapure water machine;

[0049] S432, repeating the operation in S431 until all the real-time operating parameter data of the ultrapure water machine components in the real-time operating parameter data matrix E' of the ultrapure water machine components are traversed, and then the abnormal data cleaning operation is terminated;

[0050] S44, using the mean formula to calculate the real data matrix of the real-time operating parameters of the ultrapure water machine components The real data of the real-time operating parameters of the ultrapure water machine components in the ultrapure water machine are averaged and measured to generate a standard ultrapure water machine component real-time operating parameter data set in, represents the real-time operating parameter data of the standard ultrapure water machine component of the i-th component of the ultrapure water machine, and

[0051] By using the Z-score method to clean abnormal data in the real-time operating parameter data of the ultrapure water machine components, the abnormal data in the real-time operating parameter data of the ultrapure water machine components can be accurately identified and scientifically eliminated, and then the mean formula is used to perform average numerical measurement processing on the cleaned data, so that the acquired data can better reflect the overall operating level of the ultrapure water machine over a period of time, ensuring the comprehensiveness of the acquired data.

[0052] Preferably, the specific steps of performing numerical matching processing on the normal operation parameter interval data of the ultrapure water machine components and the real-time operation parameter data of the standard ultrapure water machine components to generate the real-time operation status analysis data of the ultrapure water machine are as follows:

[0053] S51, using a width search algorithm to search for the ultrapure water machine component normal operation parameter interval data corresponding to each standard ultrapure water machine component real-time operation parameter data in the standard ultrapure water machine component real-time operation parameter data set in the ultrapure water machine component normal operation parameter interval data set, respectively numerically matching each standard ultrapure water machine component real-time operation parameter data in the standard ultrapure water machine component real-time operation parameter data set with the ultrapure water machine component normal operation parameter interval data corresponding to the ultrapure water machine component normal operation parameter interval data set, and generating ultrapure water machine real-time operation status analysis data F according to the numerical matching result. fenxi ;

[0054] If the real-time operating parameter data of each standard ultrapure water machine component in the standard ultrapure water machine component real-time operating parameter data set matches the corresponding ultrapure water machine component normal operating parameter interval data in the ultrapure water machine component normal operating parameter interval data set, the ultrapure water machine real-time operating status analysis data F is output. fenxi Normal; otherwise, output the real-time operation status analysis data F of the ultrapure water machine fenxi It is abnormal and issues a warning through the abnormal operation status alarm light of the ultrapure water machine.

[0055] The real-time operation status analysis data of the ultrapure water machine is generated according to the numerical matching results of the normal operation parameter interval data of the ultrapure water machine components and the real-time operation parameter data of the standard ultrapure water machine components, and the real-time operation status of the ultrapure water machine is scientifically analyzed to ensure the accuracy and reliability of the analysis results.

[0056] Preferably, the specific steps of constructing ultrapure water production data based on the ultrapure water quality demand data, the ultrapure water quality grade data, the real-time operating parameter data of the standard ultrapure water machine components and the real-time operating status analysis data of the ultrapure water machine, and storing the data in the ultrapure water production data management platform are as follows:

[0057] S61, the ultrapure water quality requirement data A, the ultrapure water quality grade data D, and the standard ultrapure water machine component real-time operating parameter data set and the real-time operation status analysis data F of the ultrapure water machine fenxi Combine data to construct ultrapure water production data

[0058] S62, transmitting the ultrapure water production data through the Internet of Things communication network Push to the ultrapure water production data management platform for data storage.

[0059] A data processing method further comprising S7;

[0060] S7. When data printing is required, the ultrapure water production data in the ultrapure water production data management platform is printed by a data printing device to generate paper data of ultrapure water production.

[0061] Preferably, the S7 comprises the following steps:

[0062] S71, when data printing is required, the ultrapure water production data in the ultrapure water production data management platform is printed by a data printing device. Data printing is performed to generate paper data of ultrapure water production, wherein the data printing device includes any one of an inkjet printer, a laser printer, a dot matrix printer and a 3D printer.

[0063] The present invention also discloses a self-contained data printing system, including an ultrapure water quality demand data acquisition module, an ultrapure water quality grade data analysis module, a normal operation parameter interval data collection module, an ultrapure water machine real-time operation parameter data acquisition module, an ultrapure water machine real-time operation status analysis module, an ultrapure water production data construction module and a paper data printing module;

[0064] The ultrapure water quality demand data acquisition module inputs the quality demand data of the ultrapure water currently required to be produced through the ultrapure water production control interface to generate the ultrapure water quality demand data;

[0065] The ultrapure water quality grade data analysis module performs ultrapure water quality grade analysis and processing according to the ultrapure water quality demand data and the established production standard data of different ultrapure water quality grades to generate ultrapure water quality grade data;

[0066] The normal operation parameter interval data collection module calls the ultrapure water machine equipment normal operation parameter interval data corresponding to the ultrapure water quality grade data from the ultrapure water machine historical operation data storage unit;

[0067] The ultrapure water machine real-time operation parameter data acquisition module collects the operation parameter data of each component of the ultrapure water machine in real time at each ultrapure water machine operation data acquisition time point set by different high-precision sensors, and performs abnormal data cleaning and average value measurement processing on the collected data to generate real-time operation parameter data of standard ultrapure water machine components;

[0068] The ultrapure water machine real-time operation status analysis module performs numerical matching processing based on the normal operation parameter interval data of the ultrapure water machine components and the real-time operation parameter data of the standard ultrapure water machine components to generate the ultrapure water machine real-time operation status analysis data;

[0069] The ultrapure water production data construction module combines the ultrapure water quality demand data, the ultrapure water quality grade data, the real-time operating parameter data of the standard ultrapure water machine components and the real-time operating status analysis data of the ultrapure water machine to construct ultrapure water production data, and pushes it to the ultrapure water production data management platform through the Internet of Things communication network for data storage;

[0070] When data printing is required, the paper data printing module prints the ultrapure water production data in the ultrapure water production data management platform through a data printing device to generate ultrapure water production paper data.

[0071] (III) Beneficial effects

[0072] 1. The present invention generates ultrapure water quality grade data by analyzing and processing the collected ultrapure water quality demand data and the established production standard data of different ultrapure water quality grades, collects the corresponding normal operation parameter interval data of ultrapure water machine components, collects the real-time operation parameter data of ultrapure water machine components through sensors, cleans abnormal data and performs average numerical measurement processing to generate standard ultrapure water machine component real-time operation parameter data, performs numerical matching processing on the normal operation parameter interval data of the ultrapure water machine components and the real-time operation parameter data of the standard ultrapure water machine components, generates ultrapure water machine real-time operation status analysis data according to the numerical matching results, and finally constructs and stores ultrapure water production data. When printing is required, data printing is performed through a data printing device to realize intelligent analysis of ultrapure water machine data and accurate printing of analysis data;

[0073] 2. The salp optimization algorithm is used to analyze and process the ultrapure water quality grade, which ensures the accuracy of the ultrapure water quality grade analysis results, accelerates the convergence speed of the analysis process, and effectively reduces the time cost of data processing. At the same time, the salp optimization algorithm has good robustness and can resist the interference caused by data noise to a certain extent, maintaining the stability and reliability of the analysis process;

[0074] 3. The Z-score method is used to clean abnormal data of the real-time operating parameter data of the ultrapure water machine components, which can accurately identify abnormal data in the real-time operating parameter data of the ultrapure water machine components and scientifically eliminate them. Then, the mean formula is used to perform average numerical measurement processing on the cleaned data, so that the acquired data can better reflect the overall operating level of the ultrapure water machine over a period of time, ensuring the comprehensiveness of the acquired data;

[0075] 4. Generate ultrapure water machine real-time operation status analysis data based on the numerical matching results of the normal operation parameter interval data of the ultrapure water machine components and the real-time operation parameter data of the standard ultrapure water machine components, scientifically analyze the real-time operation status of the ultrapure water machine, and ensure the accuracy and reliability of the analysis results. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] In order to more clearly illustrate the technical solutions of the embodiments of the invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the invention. For ordinary technicians in this field, they can also obtain drawings based on these drawings without paying creative work.

[0077] Figure 1 A flow chart of a data processing method provided by the present invention;

[0078] Figure 2 A schematic diagram of a module of a self-contained data printing system provided by the present invention. DETAILED DESCRIPTION

[0079] 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.

[0080] In the description of the present invention, it is necessary to understand that the terms "opening", "upper", "lower", "top", "middle", "inside" and the like indicating orientation or positional relationship are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the components or elements referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as limiting the invention.

[0081] Embodiment 1 is as follows:

[0082] See also Figure 1 , a data processing method, comprising the following steps:

[0083] S1. Collect ultrapure water quality demand data;

[0084] S11. Enter the quality requirement data of the ultrapure water currently required to be produced through the ultrapure water production control interface to generate ultrapure water quality requirement data A, wherein the ultrapure water quality requirement data includes ultrapure water resistivity, ultrapure water microbial content, ultrapure water organic carbon content, ultrapure water endotoxin content and ultrapure water specific ion concentration.

[0085] S2. Establish production standard data of different ultrapure water quality grades, perform ultrapure water quality grade analysis and processing according to the ultrapure water quality demand data and the production standard data of different ultrapure water quality grades, and generate ultrapure water quality grade data;

[0086] S21, set the ultrapure water quality level set B = {b1, b2, ..., b i ,…,b k}, where b i represents the i-th ultrapure water quality grade, and k represents the total number of ultrapure water quality grades;

[0087] S22, establishing production standard data corresponding to each ultrapure water quality grade in the ultrapure water quality grade set, generating production standard data sets for different ultrapure water quality grades in, represents the production standard data of the i-th ultrapure water quality level;

[0088] S23, performing ultrapure water quality grade analysis and processing according to the ultrapure water quality demand data A and the different ultrapure water quality grade production standard data in the different ultrapure water quality grade production standard data sets to generate ultrapure water quality grade data D;

[0089] S231, construct the salp population, set the salp population size to N, the current number of iterations to t, and the maximum number of iterations to t max And the dimension of the search space for production standard data of different ultrapure water quality grades is P;

[0090] N groups of production standard data are randomly generated in the production standard data search space of different ultrapure water quality levels, each group of production standard data corresponds to a salp individual in the salp population, and the initial position set of the salp population is initialized as X = {X1, X2, ..., X i ,…,X N}, where X i represents the initial position of the i-th salp individual in the salp population;

[0091] S232, calculating the fitness function value of each salp individual in the salp population, arranging the salp individuals in the salp population from large to small according to the fitness function value, and selecting the salp individual with the highest fitness function value as the current optimal individual; the fitness function formula is as follows:

[0092]

[0093] Among them, Fit i represents the fitness function value of the i-th salp in the salp population, x i represents the ability of the production standard data corresponding to the i-th salp in the salp population to meet the ultrapure water quality demand data, and φ represents the correction value;

[0094] S233, the salps individuals in the salps population gather together to form a salps chain in the search space of the production standard data of different ultrapure water quality levels to hunt and forage, and the salps individual ranked first in the salps chain is used as the leader individual, and the remaining salps individuals are used as follower individuals;

[0095] S234. The leader individual will be affected by the position of the food in the search space of the production standard data of different ultrapure water quality levels and update its position; the position update formula is as follows:

[0096]

[0097] in, represents the position of the leader individual after the position update in the j-th dimension of the search space of the production standard data of different ultrapure water quality levels, X best Indicates the position of the current optimal individual, ub j and lb j They represent the search upper limit and search lower limit of the search space of the production standard data of different ultrapure water quality grades, rand1 and rand2 both represent random numbers that obey a uniform distribution between [0,1], α1 represents the convergence factor, and

[0098]

[0099] S235, the follower individual will follow the previous salp individual in the search space of the production standard data of different ultrapure water quality levels to update the position; the position update formula is as follows:

[0100]

[0101] in, represents the position of the i-th follower individual after the position update in the j-th dimension different ultrapure water quality level production standard data search space, and They represent the positions of the i-th and i-1-th follower individuals in the j-th dimension of the search space for production standards of different ultrapure water quality levels;

[0102] S236, calculating the fitness function value of each salp individual in the salp population after the position is updated, arranging the salp individuals in the salp population from large to small according to the fitness function value, and selecting the salp individual with the highest fitness function value as the current optimal individual;

[0103] S237, determine whether the current number of iterations t is less than the maximum number of iterations t max , if the current number of iterations t is less than the maximum number of iterations t max, then the current iteration number t is increased by 1, and the process returns to S233; otherwise, the current optimal individual is taken as the global optimal solution, and the ultrapure water quality grade corresponding to the production standard data corresponding to the global optimal solution is data-labeled to generate ultrapure water quality grade data D.

[0104] S3, collecting the normal operation parameter interval data of the ultrapure water machine components corresponding to the ultrapure water quality grade data;

[0105] S31, calling the ultrapure water machine equipment normal operation parameter interval data corresponding to the ultrapure water quality grade data D from the ultrapure water machine historical operation data storage unit to generate an ultrapure water machine component normal operation parameter interval data set in, and They respectively represent the minimum and maximum values ​​of the operating parameter data of the ith component under normal operating conditions of the ultrapure water machine, and l represents the total number of ultrapure water machine components.

[0106] S4, collect real-time operating parameter data of standard ultrapure water machine components;

[0107] S41, setting an ultrapure water machine operation data collection cycle, evenly dividing the ultrapure water machine operation data collection cycle into a number of ultrapure water machine operation data collection time points, generating an ultrapure water machine operation data collection time point set F = {f1, f2, ..., f i ,…,f p}, where f i represents the i-th ultrapure water machine operation data collection time point, and p represents the total number of ultrapure water machine operation data collection time points;

[0108] S42, using different high-precision sensors to collect the operating parameter data of each component of the ultrapure water machine in real time at each ultrapure water machine operating data collection time point in the ultrapure water machine operating data collection time point set, and generating a real-time operating parameter data matrix E' of the ultrapure water machine components as follows:

[0109]

[0110] Among them, e' ij Represents the real-time operating parameter data of the i-th component of the ultrapure water machine at the j-th ultrapure water machine operating data collection time point, wherein the high-precision sensors include but are not limited to pressure sensors, temperature sensors, flow sensors and liquid level sensors;

[0111] S43, using the Z-score method to clean abnormal data of the real-time operating parameter data of the ultrapure water machine components in the real-time operating parameter data matrix E' of the ultrapure water machine components, and generate a real data matrix of the real-time operating parameters of the ultrapure water machine components as follows:

[0112]

[0113] in, represents the real data of the real-time operating parameters of the jth ultrapure water machine component of the i-th component of the ultrapure water machine, o i It represents the total number of real data of real-time operating parameters of ultrapure water machine components obtained by real-time collection of operating parameter data of the i-th component of the ultrapure water machine; the abnormal data cleaning process is as follows:

[0114] S431, selecting the real-time operating parameter data of the i-th component of the ultrapure water machine at the j-th ultrapure water machine operating data collection time point in the real-time operating parameter data matrix of the ultrapure water machine components for abnormal data cleaning, When e' ij The abnormal point of the real-time operating parameter data of the ultrapure water machine components is e' ij Remove; otherwise, determine e' ij The real data of the real-time operating parameters of the ultrapure water machine components will be e' ij reserve;

[0115] Among them, μ i and σ i They respectively represent the mean and standard deviation of the real-time operating parameter data of all ultrapure water machine components obtained by real-time collection of the operating parameter data of the i-th component of the ultrapure water machine;

[0116] S432, repeating the operation in S431 until all the real-time operating parameter data of the ultrapure water machine components in the real-time operating parameter data matrix E' of the ultrapure water machine components are traversed, and then the abnormal data cleaning operation is terminated;

[0117] S44, using the mean formula to calculate the real data matrix of the real-time operating parameters of the ultrapure water machine components The real data of the real-time operating parameters of the ultrapure water machine components in the ultrapure water machine are averaged and measured to generate a standard ultrapure water machine component real-time operating parameter data set in, represents the real-time operating parameter data of the standard ultrapure water machine component of the i-th component of the ultrapure water machine, and

[0118] S5, performing numerical matching processing based on the normal operation parameter interval data of the ultrapure water machine components and the real-time operation parameter data of the standard ultrapure water machine components to generate real-time operation status analysis data of the ultrapure water machine;

[0119] S51, using a width search algorithm to search for the ultrapure water machine component normal operation parameter interval data corresponding to each standard ultrapure water machine component real-time operation parameter data in the standard ultrapure water machine component real-time operation parameter data set in the ultrapure water machine component normal operation parameter interval data set, respectively numerically matching each standard ultrapure water machine component real-time operation parameter data in the standard ultrapure water machine component real-time operation parameter data set with the ultrapure water machine component normal operation parameter interval data corresponding to the ultrapure water machine component normal operation parameter interval data set, and generating ultrapure water machine real-time operation status analysis data F according to the numerical matching result. fenxi ;

[0120] If the real-time operating parameter data of each standard ultrapure water machine component in the standard ultrapure water machine component real-time operating parameter data set matches the corresponding ultrapure water machine component normal operating parameter interval data in the ultrapure water machine component normal operating parameter interval data set, the ultrapure water machine real-time operating status analysis data F is output. fenxi Normal; otherwise, output the real-time operation status analysis data F of the ultrapure water machine fenxi It is abnormal and issues a warning through the abnormal operation status alarm light of the ultrapure water machine.

[0121] S6. Constructing ultrapure water production data based on the ultrapure water quality demand data, the ultrapure water quality grade data, the real-time operating parameter data of the standard ultrapure water machine components and the real-time operating status analysis data of the ultrapure water machine, and storing the data in the ultrapure water production data management platform;

[0122] S61, the ultrapure water quality requirement data A, the ultrapure water quality grade data D, and the standard ultrapure water machine component real-time operating parameter data set and the real-time operation status analysis data F of the ultrapure water machine fenxi Combine data to construct ultrapure water production data

[0123] S62, transmitting the ultrapure water production data through the Internet of Things communication network Push to the ultrapure water production data management platform for data storage.

[0124] In some embodiments, after S6, there is also S7; S7, when data printing is required, the ultrapure water production data in the ultrapure water production data management platform is printed by a data printing device to generate ultrapure water production paper data;

[0125] S71, when data printing is required, the ultrapure water production data in the ultrapure water production data management platform is printed by a data printing device. Data printing is performed to generate paper data of ultrapure water production, wherein the data printing device includes any one of an inkjet printer, a laser printer, a dot matrix printer and a 3D printer.

[0126] Embodiment 2 is as follows:

[0127] See also Figure 2 , a self-contained data printing system, including an ultrapure water quality demand data acquisition module, an ultrapure water quality grade data analysis module, a normal operation parameter interval data collection module, an ultrapure water machine real-time operation parameter data acquisition module, an ultrapure water machine real-time operation status analysis module, an ultrapure water production data construction module and a paper data printing module;

[0128] The ultrapure water quality demand data acquisition module inputs the quality demand data of the ultrapure water currently required to be produced through the ultrapure water production control interface to generate the ultrapure water quality demand data;

[0129] The ultrapure water quality grade data analysis module performs ultrapure water quality grade analysis and processing according to the ultrapure water quality demand data and the established production standard data of different ultrapure water quality grades to generate ultrapure water quality grade data;

[0130] The normal operation parameter interval data collection module calls the ultrapure water machine equipment normal operation parameter interval data corresponding to the ultrapure water quality grade data from the ultrapure water machine historical operation data storage unit;

[0131] The ultrapure water machine real-time operation parameter data acquisition module collects the operation parameter data of each component of the ultrapure water machine in real time at each ultrapure water machine operation data acquisition time point set by different high-precision sensors, and performs abnormal data cleaning and average value measurement processing on the collected data to generate real-time operation parameter data of standard ultrapure water machine components;

[0132] The ultrapure water machine real-time operation status analysis module performs numerical matching processing based on the normal operation parameter interval data of the ultrapure water machine components and the real-time operation parameter data of the standard ultrapure water machine components to generate the ultrapure water machine real-time operation status analysis data;

[0133] The ultrapure water production data construction module combines the ultrapure water quality demand data, the ultrapure water quality grade data, the real-time operating parameter data of the standard ultrapure water machine components and the real-time operating status analysis data of the ultrapure water machine to construct ultrapure water production data, and pushes it to the ultrapure water production data management platform through the Internet of Things communication network for data storage;

[0134] When data printing is required, the paper data printing module prints the ultrapure water production data in the ultrapure water production data management platform through a data printing device to generate ultrapure water production paper data.

[0135] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0136] The preferred embodiments of the invention disclosed above are only used to help explain the invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the invention, so that those skilled in the art can understand and use the invention well.

Claims

1. A data processing method, characterized in that: The steps include: S1. Collect ultrapure water quality demand data; S2. Establish production standard data of different ultrapure water quality grades, perform ultrapure water quality grade analysis and processing according to the ultrapure water quality demand data and the production standard data of different ultrapure water quality grades, and generate ultrapure water quality grade data; S3, collecting the normal operation parameter interval data of the ultrapure water machine components corresponding to the ultrapure water quality grade data; S4, collect real-time operating parameter data of standard ultrapure water machine components; S5, performing numerical matching processing based on the normal operation parameter interval data of the ultrapure water machine components and the real-time operation parameter data of the standard ultrapure water machine components to generate real-time operation status analysis data of the ultrapure water machine; S6. Construct ultrapure water production data based on the ultrapure water quality demand data, the ultrapure water quality grade data, the real-time operating parameter data of the standard ultrapure water machine components and the real-time operating status analysis data of the ultrapure water machine, and store them in the ultrapure water production data management platform.

2. A data processing method according to claim 1, characterized in that: The S1 comprises the following steps: S11. Enter the quality requirement data of the ultrapure water currently required to be produced through the ultrapure water production control interface to generate ultrapure water quality requirement data A, wherein the ultrapure water quality requirement data includes ultrapure water resistivity, ultrapure water microbial content, ultrapure water organic carbon content, ultrapure water endotoxin content and ultrapure water specific ion concentration.

3. A data processing method according to claim 2, characterized in that: The S2 comprises the following steps: S21, set the ultrapure water quality level set B = {b1, b2, ..., b i ,…,b k }, where b i represents the i-th ultrapure water quality grade, and k represents the total number of ultrapure water quality grades; S22, establishing production standard data corresponding to each ultrapure water quality grade in the ultrapure water quality grade set, generating production standard data sets for different ultrapure water quality grades in, represents the production standard data of the i-th ultrapure water quality level; S23, performing ultrapure water quality grade analysis and processing according to the ultrapure water quality demand data A and the different ultrapure water quality grade production standard data in the different ultrapure water quality grade production standard data sets to generate ultrapure water quality grade data D; S231, construct the salp population, set the salp population size to N, the current number of iterations to t, and the maximum number of iterations to t max And the dimension of the search space for production standard data of different ultrapure water quality grades is P; N groups of production standard data are randomly generated in the production standard data search space of different ultrapure water quality levels, each group of production standard data corresponds to a salp individual in the salp population, and the initial position set of the salp population is initialized as X = {X1, X2, ..., X i ,…,X N }, where X i represents the initial position of the i-th salp individual in the salp population; S232, calculating the fitness function value of each salp individual in the salp population, arranging the salp individuals in the salp population from large to small according to the fitness function value, and selecting the salp individual with the highest fitness function value as the current optimal individual; S233, the salps individuals in the salps population gather together to form a salps chain in the search space of the production standard data of different ultrapure water quality levels to hunt and forage, and the salps individual ranked first in the salps chain is used as the leader individual, and the remaining salps individuals are used as follower individuals; S234, the leader individual will be affected by the location of food and update its position in the search space of the production standard data of different ultrapure water quality levels; S235, the follower individual will follow the previous salp individual to update its position in the search space of production standard data of different ultrapure water quality levels; S236, calculating the fitness function value of each salp individual in the salp population after the position is updated, arranging the salp individuals in the salp population from large to small according to the fitness function value, and selecting the salp individual with the highest fitness function value as the current optimal individual; S237, determine whether the current number of iterations t is less than the maximum number of iterations t max , if the current number of iterations t is less than the maximum number of iterations t max , then the current iteration number t is increased by 1, and the process returns to S233; otherwise, the current optimal individual is taken as the global optimal solution, and the ultrapure water quality grade corresponding to the production standard data corresponding to the global optimal solution is data-labeled to generate ultrapure water quality grade data D.

4. A data processing method according to claim 3, characterized in that: The S3 comprises the following steps: S31, calling the ultrapure water machine equipment normal operation parameter interval data corresponding to the ultrapure water quality grade data D from the ultrapure water machine historical operation data storage unit to generate an ultrapure water machine component normal operation parameter interval data set in, and They respectively represent the minimum and maximum values ​​of the operating parameter data of the ith component under normal operating conditions of the ultrapure water machine, and l represents the total number of ultrapure water machine components.

5. A data processing method according to claim 4, characterized in that: The S4 comprises the following steps: S41, setting an ultrapure water machine operation data collection cycle, evenly dividing the ultrapure water machine operation data collection cycle into a number of ultrapure water machine operation data collection time points, generating an ultrapure water machine operation data collection time point set F = {f1, f2, ..., f i ,…,f p }, where f i represents the i-th ultrapure water machine operation data collection time point, and p represents the total number of ultrapure water machine operation data collection time points; S42, using different high-precision sensors to collect the operating parameter data of each component of the ultrapure water machine in real time at each ultrapure water machine operating data collection time point in the ultrapure water machine operating data collection time point set, to generate a real-time operating parameter data matrix E' of the ultrapure water machine components; S43, using the Z-score method to clean abnormal data of the real-time operating parameter data of the ultrapure water machine components in the real-time operating parameter data matrix E' of the ultrapure water machine components, and generate a real data matrix of the real-time operating parameters of the ultrapure water machine components S44, using the mean formula to calculate the real data matrix of the real-time operating parameters of the ultrapure water machine components The real data of the real-time operating parameters of the ultrapure water machine components in the ultrapure water machine are averaged and measured to generate a standard ultrapure water machine component real-time operating parameter data set in, Represents the real-time operating parameter data of the standard ultrapure water machine component of the i-th component of the ultrapure water machine.

6. A data processing method according to claim 5, characterized in that: The S5 comprises the following steps: S51, using a width search algorithm to search for the ultrapure water machine component normal operation parameter interval data corresponding to each standard ultrapure water machine component real-time operation parameter data in the standard ultrapure water machine component real-time operation parameter data set in the ultrapure water machine component normal operation parameter interval data set, respectively numerically matching each standard ultrapure water machine component real-time operation parameter data in the standard ultrapure water machine component real-time operation parameter data set with the ultrapure water machine component normal operation parameter interval data corresponding to the ultrapure water machine component normal operation parameter interval data set, and generating ultrapure water machine real-time operation status analysis data F according to the numerical matching result. fenxi ; If the real-time operating parameter data of each standard ultrapure water machine component in the standard ultrapure water machine component real-time operating parameter data set matches the corresponding ultrapure water machine component normal operating parameter interval data in the ultrapure water machine component normal operating parameter interval data set, the ultrapure water machine real-time operating status analysis data F is output. fenxi Normal; otherwise, output the real-time operation status analysis data F of the ultrapure water machine fenxi It is abnormal and issues a warning through the abnormal operation status alarm light of the ultrapure water machine.

7. A data processing method according to claim 6, characterized in that: The S6 comprises the following steps: S61, the ultrapure water quality requirement data A, the ultrapure water quality grade data D, and the standard ultrapure water machine component real-time operating parameter data set and the real-time operation status analysis data F of the ultrapure water machine fenxi Combine data to construct ultrapure water production data S62, transmitting the ultrapure water production data through the Internet of Things communication network Push to the ultrapure water production data management platform for data storage.

8. A data processing method according to claim 7, characterized in that: Also includes S7; S7. When data printing is required, the ultrapure water production data in the ultrapure water production data management platform is printed by a data printing device to generate paper data of ultrapure water production; The S7 comprises the following steps: S71, when data printing is required, the ultrapure water production data in the ultrapure water production data management platform is printed by a data printing device. Data printing is performed to generate paper data of ultrapure water production, wherein the data printing device includes any one of an inkjet printer, a laser printer, a dot matrix printer and a 3D printer.

9. A self-contained data printing system for implementing the data processing method according to any one of claims 1 to 8, characterized in that: It includes ultrapure water quality demand data collection module, ultrapure water quality grade data analysis module, normal operation parameter interval data collection module, ultrapure water machine real-time operation parameter data collection module, ultrapure water machine real-time operation status analysis module, ultrapure water production data construction module and paper data printing module.

10. Application of the data processing method according to any one of claims 1 to 8 in an ultrapure water machine.

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