CN113077128B - Heterogeneous industrial data intelligent analysis system based on user drive - Google Patents
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Abstract
The invention discloses an intelligent analysis system for heterogeneous industrial data based on user drive, which relates to the technical field of intelligent analysis of heterogeneous industrial data and solves the technical problem that the working efficiency of industrial production is reduced because industrial production data cannot be acquired and analyzed in the prior art, industrial production information is analyzed through a production acquisition unit, the ratio of high-quality products and low-quality products produced by industrial production equipment, the total times of monthly maintenance of the industrial production equipment and the dust content of the surrounding environment of the industrial production equipment are obtained, a production analysis coefficient Xi of the industrial production equipment is obtained through a formula, if the production analysis coefficient Xi of the industrial production equipment is more than or equal to a production analysis coefficient threshold value of the industrial production equipment, the production of the industrial production equipment is judged to be abnormal, the production equipment is detected, and the industrial production data is acquired and analyzed, the work efficiency of industrial production is improved, and the work efficiency of the acquisition system is improved.
Description
Technical Field
The invention relates to the technical field of intelligent analysis of heterogeneous industrial data, in particular to an intelligent analysis system of heterogeneous industrial data based on user drive.
Background
The industry is a product processing and manufacturing industry, and the industry is a product developed by the industry of society and passes through several development stages of handicraft industry and machine industry. The industry is a component of the second industry and is divided into light industry and heavy industry; with the development of industrial science and technology, the data informatization is rapidly advanced, and the related production data in the industrial production process is more and more important.
However, in the prior art, industrial production data cannot be collected and analyzed, which results in reduction of the work efficiency of industrial production.
Disclosure of Invention
The invention aims to provide a heterogeneous industrial data intelligent analysis system based on user driving, wherein industrial production information is analyzed through a production acquisition unit, so that data acquisition is carried out on industrial production, the ratio of high-quality products and low-quality products produced by industrial production equipment, the total monthly maintenance frequency of the industrial production equipment and the dust content of the peripheral environment of the industrial production equipment are obtained, a production analysis coefficient Xi of the industrial production equipment is obtained through a formula, if the production analysis coefficient Xi of the industrial production equipment is larger than or equal to a production analysis coefficient threshold value of the industrial production equipment, the production of the industrial production equipment is judged to be abnormal, a production abnormal signal is generated, and the production abnormal signal is sent to a heterogeneous analysis platform; if the production analysis coefficient Xi of the industrial production equipment is smaller than the production analysis coefficient threshold value of the industrial production equipment, judging that the industrial production equipment is normal in production, generating a normal production signal and sending the normal production signal to the heterogeneous analysis platform; the production equipment is detected, so that industrial production data are collected and analyzed, the working efficiency of industrial production is improved, and the working efficiency of an acquisition system is improved;
the purpose of the invention can be realized by the following technical scheme:
a heterogeneous industrial data intelligent analysis system based on user driving comprises a heterogeneous analysis platform, a production acquisition unit, a material acquisition unit, a worker supervision unit, a pollution detection unit, a registration unit and a database;
the production acquisition unit is used for analyzing industrial production information, thereby carry out data acquisition to industrial production, industrial production information includes product data, equipment data and environmental data, and product data is the ratio of high-quality product and the inferior product of industrial production equipment production, and equipment data is the total number of times of the whole month maintenance of industrial production equipment, and environmental data is the dust content of industrial production equipment week edge ring border, marks industrial production equipment as i, i is 1, 2, … …, n, n is positive integer, and concrete analysis acquisition process is as follows:
step S1: obtaining the ratio of high-quality products to low-quality products produced by industrial production equipment, and marking the ratio of the high-quality products to the low-quality products produced by the industrial production equipment as Bi;
step S2: acquiring the total times of the full-month maintenance of the industrial production equipment, and marking the total times of the full-month maintenance of the industrial production equipment as Ci;
step S3: acquiring the dust content of the surrounding environment of the industrial production equipment, and marking the dust content of the surrounding environment of the industrial production equipment as Hi;
step S4: by the formula
Obtaining a production analysis coefficient Xi of industrial production equipment, wherein a1, a2 and a3 are all proportional coefficients, a1 is more than a2 is more than a3 is more than 0, and beta is an error correction factor and is 2.03215121;
step S5: comparing the production analysis coefficient Xi of the industrial production equipment with a production analysis coefficient threshold value of the industrial production equipment:
if the production analysis coefficient Xi of the industrial production equipment is larger than or equal to the production analysis coefficient threshold value of the industrial production equipment, judging that the industrial production equipment is abnormal in production, generating a production abnormal signal and sending the production abnormal signal to the heterogeneous analysis platform;
and if the production analysis coefficient Xi of the industrial production equipment is smaller than the production analysis coefficient threshold value of the industrial production equipment, judging that the industrial production equipment is normal in production, generating a normal production signal and sending the normal production signal to the heterogeneous analysis platform.
Further, heterogeneous analysis platform receives behind the production anomaly signal, generates material analysis signal and with material analysis signal transmission to material acquisition unit, material acquisition unit receives behind the material acquisition signal, gathers the material information of production facility to analyze production facility, the material information of production facility includes number of times data, speed data is in time long data, the number of times data lacks the number of times of material in the industrial production equipment production process, speed data is the material purchase speed that industrial production equipment corresponds, it is long for the material purchase interval that industrial production equipment corresponds to length of time data, concrete analysis acquisition process is as follows:
step SS 1: acquiring times of material shortage in the production process of industrial production equipment, and marking the times of material shortage in the production process of the industrial production equipment as CSi;
step SS 2: acquiring a material purchasing speed corresponding to industrial production equipment, and marking the material purchasing speed corresponding to the industrial production equipment as SDi;
step SS 3: acquiring material purchasing interval duration corresponding to industrial production equipment, and marking the material purchasing interval duration corresponding to the industrial production equipment as SCi;
step SS 4: by the formula
Obtaining a material collection analysis coefficient FXi corresponding to industrial production equipment, wherein c1, c2 and c3 are proportional coefficients, and c1 is larger than c2 and c3 is larger than 0;
step SS 5: comparing a material acquisition analysis coefficient FXi corresponding to industrial production equipment with a material acquisition analysis coefficient threshold value:
if the material collection and analysis coefficient FXi corresponding to the industrial production equipment is larger than or equal to the material collection and analysis coefficient threshold value, judging that the material collection corresponding to the industrial production equipment is abnormal, generating a material abnormal signal and sending the material abnormal signal to the heterogeneous analysis platform, and after receiving the material abnormal signal, the heterogeneous analysis platform generates a material settling signal and sends the material settling signal to a mobile phone terminal of a settling worker;
and if the material acquisition and analysis coefficient FXi corresponding to the industrial production equipment is smaller than the material acquisition and analysis coefficient threshold value, judging that the material acquisition of the corresponding industrial production equipment is normal, generating a material normal signal and sending the material normal signal to the heterogeneous analysis platform.
Further, after the heterogeneous analysis platform receives the material normal signal, a worker supervision signal is generated and sent to the worker supervision unit, and after the worker supervision unit receives the worker supervision signal, the worker supervision unit collects the working state information of the worker, so that the daily work of the worker is analyzed, the working state information of the worker includes the average time length of leaving the station every day in the daily working process of the worker, the number of errors occurring in the daily working process of the worker and the late arrival frequency in the daily working process of the worker, the worker is marked as o, o is 1, 2, … …, m, m is a positive integer, and the specific collection and analysis process is as follows:
step T1: acquiring the average time length of leaving the station every day in the daily work process of a worker, and marking the average time length of leaving the station every day in the daily work process of the worker as PSCo;
step T2: acquiring the error times of a worker in the daily working process, and marking the error times of the worker in the daily working process as CCso;
step T3: acquiring the late arrival frequency of a worker in the daily working process, and marking the late arrival frequency of the worker in the daily working process as CPLO;
step T4: by the formula
Acquiring worker working state analysis coefficients CJo, wherein v1, v2 and v3 are proportional coefficients, v1 is more than v2 is more than v3 is more than 0, and e is a natural constant;
step T5: worker work state analysis coefficient CJo is compared to a worker work state analysis coefficient threshold:
if the worker working state analysis coefficient CJo is not less than the worker working state analysis coefficient threshold, judging that the corresponding worker working state is abnormal, generating a worker abnormal signal and sending the worker abnormal signal to the heterogeneous analysis platform, and after receiving the worker abnormal signal, the heterogeneous analysis platform generates a worker mortgage signal and sends the worker mortgage signal to a mobile phone terminal of a mortgage worker;
and if the worker working state analysis coefficient CJo is smaller than the worker working state analysis coefficient threshold value, judging that the corresponding worker working state is normal, generating a worker normal signal and sending the worker normal signal to the heterogeneous analysis platform.
Further, the pollution detection unit is used for analyzing industrial pollution data so as to detect industrial pollution, the industrial pollution data includes decibel values of noise generated during operation of industrial production equipment, sewage discharge amount during operation of the industrial production equipment and treatment times before sewage discharge, and the specific analysis and detection process is as follows:
step TT 1: acquiring a noise decibel value generated when the industrial production equipment operates, and marking the noise decibel value generated when the industrial production equipment operates as FBZ;
step TT 2: obtaining the sewage discharge amount when the industrial production equipment operates, and marking the sewage discharge amount when the industrial production equipment operates as PFL;
step TT 3: acquiring the treatment times of the industrial production equipment before sewage discharge in the production process, and marking the treatment times of the industrial production equipment before sewage discharge in the production process as CCS;
step TT 4: acquiring a pollution detection coefficient WS of industrial production equipment by using a formula WS (FBZ multiplied by s1+ PFL multiplied by s1+ CCS multiplied by s2), wherein s1, s2 and s3 are all proportional coefficients, s1 is greater than s2 is greater than s3 is greater than 0, and alpha is an error correction factor and is 2.301145;
step TT 5: comparing the pollution detection coefficient WS of the industrial production equipment with a pollution detection coefficient threshold value:
if the pollution detection coefficient WS of the industrial production equipment is larger than or equal to the pollution detection coefficient threshold, judging that the pollution generated by the corresponding industrial production equipment is low, generating a low-pollution signal and sending the low-pollution signal to a mobile phone terminal of a manager;
and if the pollution detection coefficient WS of the industrial production equipment is less than the pollution detection coefficient threshold value, judging that the pollution generated by the corresponding industrial production equipment is high, generating a high-pollution signal and sending the high-pollution signal to a mobile phone terminal of a mortgage worker.
Further, the registration and login unit is used for the managers and the rectification personnel to submit the information of the managers and the information of the rectification personnel through mobile phone terminals, and the information of the managers and the information of the rectification personnel which are successfully registered are sent to the database to be stored, the information of the managers comprises the names, the ages, the time of entry and the mobile phone numbers of the real name authentication of the managers, and the information of the rectification personnel comprises the names, the ages, the time of entry and the mobile phone numbers of the real name authentication of the managers.
Compared with the prior art, the invention has the beneficial effects that:
1. in the invention, industrial production information is analyzed through a production acquisition unit, so that data acquisition is carried out on industrial production, the ratio of high-quality products to low-quality products produced by industrial production equipment, the total times of monthly maintenance of the industrial production equipment and the dust content of the surrounding environment of the industrial production equipment are obtained, the production analysis coefficient Xi of the industrial production equipment is obtained through a formula, if the production analysis coefficient Xi of the industrial production equipment is more than or equal to the production analysis coefficient threshold value of the industrial production equipment, the production abnormality of the industrial production equipment is judged, a production abnormality signal is generated, and the production abnormality signal is sent to a heterogeneous analysis platform; if the production analysis coefficient Xi of the industrial production equipment is smaller than the production analysis coefficient threshold value of the industrial production equipment, judging that the industrial production equipment is normal in production, generating a normal production signal and sending the normal production signal to the heterogeneous analysis platform; the production equipment is detected, so that industrial production data are collected and analyzed, the working efficiency of industrial production is improved, and the working efficiency of an acquisition system is improved;
2. in the invention, the material information of the production equipment is collected after the material collecting unit receives the material collecting signal, thereby analyzing the production equipment, obtaining the times of material shortage in the production process of the industrial production equipment, the material purchasing speed corresponding to the industrial production equipment and the material purchasing interval duration corresponding to the industrial production equipment, obtaining a material acquisition and analysis coefficient FXi corresponding to industrial production equipment through a formula, if the material acquisition and analysis coefficient FXi corresponding to the industrial production equipment is more than or equal to a material acquisition and analysis coefficient threshold value, judging that the material collection of the corresponding industrial production equipment is abnormal, generating a material abnormal signal and sending the material abnormal signal to the heterogeneous analysis platform, after the heterogeneous analysis platform receives the material abnormal signal, generating a material rectification signal and sending the material rectification signal to a mobile phone terminal of a rectification worker; the material information in the industrial production process is collected and analyzed, so that the accuracy of industrial data analysis is improved, and the working efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an intelligent analysis system for heterogeneous industrial data based on user driving includes a heterogeneous analysis platform, a production acquisition unit, a material acquisition unit, a worker supervision unit, a pollution detection unit, a registration unit and a database;
the registration login unit is used for submitting manager information and mortgage person information through mobile phone terminals by managers and mortgage persons, and sending the manager information and mortgage person information which are successfully registered to a database for storage, wherein the manager information comprises names, ages and time of entry of the managers and mobile phone numbers of real name authentication of the persons, and the mortgage person information comprises names, ages and time of entry of the mortgage persons and mobile phone numbers of real name authentication of the persons;
the production acquisition unit is used for analyzing industrial production information, thereby carry out data acquisition to industrial production, industrial production information includes product data, equipment data and environmental data, product data is the ratio of high-quality product and the inferior product of industrial production equipment production, equipment data is the total number of times of full month maintenance of industrial production equipment, environmental data is the dust content of industrial production equipment week edge ring border, mark industrial production equipment as i, i is 1, 2, … …, n, n is positive integer, the specific analysis acquisition process is as follows:
step S1: obtaining the ratio of high-quality products to low-quality products produced by industrial production equipment, and marking the ratio of the high-quality products to the low-quality products produced by the industrial production equipment as Bi;
step S2: acquiring the total times of the full-month maintenance of the industrial production equipment, and marking the total times of the full-month maintenance of the industrial production equipment as Ci;
step S3: acquiring the dust content of the surrounding environment of the industrial production equipment, and marking the dust content of the surrounding environment of the industrial production equipment as Hi;
step S4: by the formula
Obtaining a production analysis coefficient Xi of industrial production equipment, wherein a1, a2 and a3 are all proportional coefficients, a1 is more than a2 is more than a3 is more than 0, and beta is an error correction factor and is 2.03215121;
step S5: comparing the production analysis coefficient Xi of the industrial production equipment with a production analysis coefficient threshold value of the industrial production equipment:
if the production analysis coefficient Xi of the industrial production equipment is larger than or equal to the production analysis coefficient threshold value of the industrial production equipment, judging that the industrial production equipment is abnormal in production, generating a production abnormal signal and sending the production abnormal signal to the heterogeneous analysis platform;
if the production analysis coefficient Xi of the industrial production equipment is smaller than the production analysis coefficient threshold value of the industrial production equipment, judging that the industrial production equipment is normal in production, generating a normal production signal and sending the normal production signal to the heterogeneous analysis platform;
after production abnormal signal is received to heterogeneous analysis platform, generate material analysis signal and with material analysis signal transmission to material acquisition unit, material acquisition unit receives material acquisition signal after, gather production facility's material information, thereby analyze production facility, production facility's material information includes the number of times data, speed data is in order in time long data, the number of times data lacks the number of times of material for industrial production equipment production process, speed data is the material purchase speed that industrial production equipment corresponds, it is long for the material purchase interval that industrial production equipment corresponds to long data, concrete analysis acquisition process is as follows:
step SS 1: acquiring times of material shortage in the production process of industrial production equipment, and marking the times of material shortage in the production process of the industrial production equipment as CSi;
step SS 2: acquiring a material purchasing speed corresponding to industrial production equipment, and marking the material purchasing speed corresponding to the industrial production equipment as SDi;
step SS 3: acquiring material purchasing interval duration corresponding to industrial production equipment, and marking the material purchasing interval duration corresponding to the industrial production equipment as SCi;
step SS 4: by the formula
Obtaining a material collection analysis coefficient FXi corresponding to industrial production equipment, wherein c1, c2 and c3 are proportional coefficients, and c1 is larger than c2 and c3 is larger than 0;
step SS 5: comparing a material acquisition analysis coefficient FXi corresponding to industrial production equipment with a material acquisition analysis coefficient threshold value:
if the material collection and analysis coefficient FXi corresponding to the industrial production equipment is larger than or equal to the material collection and analysis coefficient threshold value, judging that the material collection corresponding to the industrial production equipment is abnormal, generating a material abnormal signal and sending the material abnormal signal to the heterogeneous analysis platform, and after receiving the material abnormal signal, the heterogeneous analysis platform generates a material settling signal and sends the material settling signal to a mobile phone terminal of a settling worker;
if the material acquisition and analysis coefficient FXi corresponding to the industrial production equipment is smaller than the material acquisition and analysis coefficient threshold value, judging that the material acquisition of the corresponding industrial production equipment is normal, generating a material normal signal and sending the material normal signal to the heterogeneous analysis platform;
after the heterogeneous analysis platform receives the normal material signal, generate workman's supervision signal and send workman's supervision signal to workman's supervision unit, workman's supervision unit receives workman's supervision signal after, gather workman's operating condition information, thereby carry out the analysis to workman's daily work, workman's operating condition information includes that the average duration that leaves the station every day in the workman's daily work process, the error number of times that appears in the workman's daily work process and the frequency of tardiness in the workman's daily work process, mark the workman as o, o is 1, 2, … …, m, m is positive integer, the concrete collection analytic process as follows:
step T1: acquiring the average time length of leaving the station every day in the daily work process of a worker, and marking the average time length of leaving the station every day in the daily work process of the worker as PSCo;
step T2: acquiring the error times of a worker in the daily working process, and marking the error times of the worker in the daily working process as CCso;
step T3: acquiring the late arrival frequency of a worker in the daily working process, and marking the late arrival frequency of the worker in the daily working process as CPLO;
step T4: by the formula
Acquiring worker working state analysis coefficients CJo, wherein v1, v2 and v3 are proportional coefficients, v1 is more than v2 is more than v3 is more than 0, and e is a natural constant;
step T5: worker work state analysis coefficient CJo is compared to a worker work state analysis coefficient threshold:
if the worker working state analysis coefficient CJo is not less than the worker working state analysis coefficient threshold, judging that the corresponding worker working state is abnormal, generating a worker abnormal signal and sending the worker abnormal signal to the heterogeneous analysis platform, and after receiving the worker abnormal signal, the heterogeneous analysis platform generates a worker mortgage signal and sends the worker mortgage signal to a mobile phone terminal of a mortgage worker;
if the worker working state analysis coefficient CJo is smaller than the worker working state analysis coefficient threshold value, judging that the corresponding worker working state is normal, generating a worker normal signal and sending the worker normal signal to the heterogeneous analysis platform;
the pollution detection unit is used for analyzing industrial pollution data so as to detect industrial pollution, the industrial pollution data comprise noise decibel values generated when industrial production equipment operates, sewage discharge amount when the industrial production equipment operates and treatment times before sewage discharge, and the specific analysis and detection process is as follows:
step TT 1: acquiring a noise decibel value generated when the industrial production equipment operates, and marking the noise decibel value generated when the industrial production equipment operates as FBZ;
step TT 2: obtaining the sewage discharge amount when the industrial production equipment operates, and marking the sewage discharge amount when the industrial production equipment operates as PFL;
step TT 3: acquiring the treatment times of the industrial production equipment before sewage discharge in the production process, and marking the treatment times of the industrial production equipment before sewage discharge in the production process as CCS;
step TT 4: acquiring a pollution detection coefficient WS of industrial production equipment by using a formula WS (FBZ multiplied by s1+ PFL multiplied by s1+ CCS multiplied by s2), wherein s1, s2 and s3 are all proportional coefficients, s1 is greater than s2 is greater than s3 is greater than 0, and alpha is an error correction factor and is 2.301145;
step TT 5: comparing the pollution detection coefficient WS of the industrial production equipment with a pollution detection coefficient threshold value:
if the pollution detection coefficient WS of the industrial production equipment is larger than or equal to the pollution detection coefficient threshold, judging that the pollution generated by the corresponding industrial production equipment is low, generating a low-pollution signal and sending the low-pollution signal to a mobile phone terminal of a manager;
and if the pollution detection coefficient WS of the industrial production equipment is less than the pollution detection coefficient threshold value, judging that the pollution generated by the corresponding industrial production equipment is high, generating a high-pollution signal and sending the high-pollution signal to a mobile phone terminal of a mortgage worker.
The working principle of the invention is as follows:
when the intelligent analysis system works, industrial production information is analyzed through a production acquisition unit, so that data acquisition is carried out on industrial production, the ratio of high-quality products to low-quality products produced by industrial production equipment, the total times of monthly maintenance of the industrial production equipment and the dust content of the surrounding environment of the industrial production equipment are obtained, the production analysis coefficient Xi of the industrial production equipment is obtained through a formula, if the production analysis coefficient Xi of the industrial production equipment is not less than the production analysis coefficient threshold of the industrial production equipment, the production of the industrial production equipment is judged to be abnormal, a production abnormal signal is generated, and the production abnormal signal is sent to a heterogeneous analysis platform; if the production analysis coefficient Xi of the industrial production equipment is smaller than the production analysis coefficient threshold value of the industrial production equipment, judging that the industrial production equipment is normal in production, generating a normal production signal and sending the normal production signal to the heterogeneous analysis platform; the production equipment is detected, so that the industrial production data is collected and analyzed, the working efficiency of industrial production is improved, and the working efficiency of an acquisition system is improved.
The above formulas are all calculated by taking the numerical value of the dimension, the formula is a formula which obtains the latest real situation by acquiring a large amount of data and performing software simulation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (5)
1. A heterogeneous industrial data intelligent analysis system based on user driving is characterized by comprising a heterogeneous analysis platform, a production acquisition unit, a material acquisition unit, a worker supervision unit, a pollution detection unit, a registration unit and a database;
the production acquisition unit is used for analyzing industrial production information, thereby carry out data acquisition to industrial production, industrial production information includes product data, equipment data and environmental data, and product data is the ratio of high-quality product and the inferior product of industrial production equipment production, and equipment data is the total number of times of the whole month maintenance of industrial production equipment, and environmental data is the dust content of industrial production equipment week edge ring border, marks industrial production equipment as i, i is 1, 2, … …, n, n is positive integer, and concrete analysis acquisition process is as follows:
step S1: obtaining the ratio of high-quality products to low-quality products produced by industrial production equipment, and marking the ratio of the high-quality products to the low-quality products produced by the industrial production equipment as Bi;
step S2: acquiring the total times of the full-month maintenance of the industrial production equipment, and marking the total times of the full-month maintenance of the industrial production equipment as Ci;
step S3: acquiring the dust content of the surrounding environment of the industrial production equipment, and marking the dust content of the surrounding environment of the industrial production equipment as Hi;
step S4: by the formula
Obtaining a production analysis coefficient Xi of industrial production equipment, wherein a1, a2 and a3 are all proportional coefficients, a1 is more than a2 is more than a3 is more than 0, and beta is an error correction factor and is 2.03215121;
step S5: comparing the production analysis coefficient Xi of the industrial production equipment with a production analysis coefficient threshold value of the industrial production equipment:
if the production analysis coefficient Xi of the industrial production equipment is larger than or equal to the production analysis coefficient threshold value of the industrial production equipment, judging that the industrial production equipment is abnormal in production, generating a production abnormal signal and sending the production abnormal signal to the heterogeneous analysis platform;
and if the production analysis coefficient Xi of the industrial production equipment is smaller than the production analysis coefficient threshold value of the industrial production equipment, judging that the industrial production equipment is normal in production, generating a normal production signal and sending the normal production signal to the heterogeneous analysis platform.
2. The intelligent analysis system for the heterogeneous industrial data based on the user driving as claimed in claim 1, wherein the heterogeneous analysis platform generates a material analysis signal and sends the material analysis signal to the material collection unit after receiving the production abnormal signal, the material collection unit collects material information of the production equipment after receiving the material collection signal, so as to analyze the production equipment, the material information of the production equipment comprises time data and speed data so as to obtain timely long data, the time data is the times of material shortage in the production process of the industrial production equipment, the speed data is the material purchasing speed corresponding to the industrial production equipment, the time data is the material purchasing interval time corresponding to the industrial production equipment, and the specific analysis and collection process is as follows:
step SS 1: acquiring times of material shortage in the production process of industrial production equipment, and marking the times of material shortage in the production process of the industrial production equipment as CSi;
step SS 2: acquiring a material purchasing speed corresponding to industrial production equipment, and marking the material purchasing speed corresponding to the industrial production equipment as SDi;
step SS 3: acquiring material purchasing interval duration corresponding to industrial production equipment, and marking the material purchasing interval duration corresponding to the industrial production equipment as SCi;
step SS 4: by the formula
Obtaining a material collection analysis coefficient FXi corresponding to industrial production equipment, wherein c1, c2 and c3 are proportional coefficients, and c1 is larger than c2 and c3 is larger than 0;
step SS 5: comparing a material acquisition analysis coefficient FXi corresponding to industrial production equipment with a material acquisition analysis coefficient threshold value:
if the material collection and analysis coefficient FXi corresponding to the industrial production equipment is larger than or equal to the material collection and analysis coefficient threshold value, judging that the material collection corresponding to the industrial production equipment is abnormal, generating a material abnormal signal and sending the material abnormal signal to the heterogeneous analysis platform, and after receiving the material abnormal signal, the heterogeneous analysis platform generates a material settling signal and sends the material settling signal to a mobile phone terminal of a settling worker;
and if the material acquisition and analysis coefficient FXi corresponding to the industrial production equipment is smaller than the material acquisition and analysis coefficient threshold value, judging that the material acquisition of the corresponding industrial production equipment is normal, generating a material normal signal and sending the material normal signal to the heterogeneous analysis platform.
3. The intelligent analysis system for heterogeneous industrial data based on user driving as claimed in claim 1, wherein after receiving the material normal signal, the heterogeneous analysis platform generates a worker supervision signal and sends the worker supervision signal to the worker supervision unit, and after receiving the worker supervision signal, the worker supervision unit collects the working state information of the worker, so as to analyze the daily work of the worker, wherein the working state information of the worker includes an average time length of leaving a station every day during the daily work of the worker, the number of errors occurring during the daily work of the worker, and a late arrival frequency during the daily work of the worker, and the worker is marked as o, o is 1, 2, … …, m, m is a positive integer, and the specific collection and analysis process is as follows:
step T1: acquiring the average time length of leaving the station every day in the daily work process of a worker, and marking the average time length of leaving the station every day in the daily work process of the worker as PSCo;
step T2: acquiring the error times of a worker in the daily working process, and marking the error times of the worker in the daily working process as CCso;
step T3: acquiring the late arrival frequency of a worker in the daily working process, and marking the late arrival frequency of the worker in the daily working process as CPLO;
step T4: by the formula
Acquiring worker working state analysis coefficients CJo, wherein v1, v2 and v3 are proportional coefficients, v1 is more than v2 is more than v3 is more than 0, and e is a natural constant;
step T5: worker work state analysis coefficient CJo is compared to a worker work state analysis coefficient threshold:
if the worker working state analysis coefficient CJo is not less than the worker working state analysis coefficient threshold, judging that the corresponding worker working state is abnormal, generating a worker abnormal signal and sending the worker abnormal signal to the heterogeneous analysis platform, and after receiving the worker abnormal signal, the heterogeneous analysis platform generates a worker mortgage signal and sends the worker mortgage signal to a mobile phone terminal of a mortgage worker;
and if the worker working state analysis coefficient CJo is smaller than the worker working state analysis coefficient threshold value, judging that the corresponding worker working state is normal, generating a worker normal signal and sending the worker normal signal to the heterogeneous analysis platform.
4. The intelligent analysis system for heterogeneous industrial data based on user driving according to claim 1, wherein the pollution detection unit is configured to analyze industrial pollution data so as to detect industrial pollution, the industrial pollution data includes decibel values of noise generated during operation of industrial production equipment, discharge amount of sewage generated during operation of industrial production equipment, and treatment times before discharge of sewage, and the specific analysis and detection processes are as follows:
step TT 1: acquiring a noise decibel value generated when the industrial production equipment operates, and marking the noise decibel value generated when the industrial production equipment operates as FBZ;
step TT 2: obtaining the sewage discharge amount when the industrial production equipment operates, and marking the sewage discharge amount when the industrial production equipment operates as PFL;
step TT 3: acquiring the treatment times of the industrial production equipment before sewage discharge in the production process, and marking the treatment times of the industrial production equipment before sewage discharge in the production process as CCS;
step TT 4: acquiring a pollution detection coefficient WS of industrial production equipment by using a formula WS (FBZ multiplied by s1+ PFL multiplied by s1+ CCS multiplied by s2), wherein s1, s2 and s3 are all proportional coefficients, s1 is greater than s2 is greater than s3 is greater than 0, and alpha is an error correction factor and is 2.301145;
step TT 5: comparing the pollution detection coefficient WS of the industrial production equipment with a pollution detection coefficient threshold value:
if the pollution detection coefficient WS of the industrial production equipment is larger than or equal to the pollution detection coefficient threshold, judging that the pollution generated by the corresponding industrial production equipment is low, generating a low-pollution signal and sending the low-pollution signal to a mobile phone terminal of a manager;
and if the pollution detection coefficient WS of the industrial production equipment is less than the pollution detection coefficient threshold value, judging that the pollution generated by the corresponding industrial production equipment is high, generating a high-pollution signal and sending the high-pollution signal to a mobile phone terminal of a mortgage worker.
5. The system of claim 1, wherein the registration and login unit is configured to submit manager information and mortgage person information through a mobile phone terminal, and send the manager information and mortgage person information that are successfully registered to the database for storage, the manager information includes a name, an age, an attendance time of the manager and a mobile phone number of real name authentication of the person, and the mortgage person information includes a name, an age, an attendance time of the mortgage person and a mobile phone number of real name authentication of the person.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101655936A (en) * | 2009-06-09 | 2010-02-24 | 北京千禧维讯技术服务有限公司 | Network monitoring method for maintaining telecommunication equipment |
| CN105446992A (en) * | 2014-07-08 | 2016-03-30 | 阿里巴巴集团控股有限公司 | Method and device for building goods object recovery information database and determining value information |
| US10691773B2 (en) * | 2015-12-30 | 2020-06-23 | General Electric Company | Cell processing techniques |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7079912B2 (en) * | 2002-11-25 | 2006-07-18 | Philip Morris Usa Inc. | System and method for high speed control and rejection |
-
2021
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101655936A (en) * | 2009-06-09 | 2010-02-24 | 北京千禧维讯技术服务有限公司 | Network monitoring method for maintaining telecommunication equipment |
| CN105446992A (en) * | 2014-07-08 | 2016-03-30 | 阿里巴巴集团控股有限公司 | Method and device for building goods object recovery information database and determining value information |
| US10691773B2 (en) * | 2015-12-30 | 2020-06-23 | General Electric Company | Cell processing techniques |
Non-Patent Citations (1)
| Title |
|---|
| "精益生产方式在FS公司的应用研究";赵玉峰;《中国优秀硕士学位论文全文数据库 经济与管理科学辑》;20120615(第6期);J152-679页 * |
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