CN115600130A - Plywood composite adhesive equipment operation management and control system based on data analysis - Google Patents
Plywood composite adhesive equipment operation management and control system based on data analysis Download PDFInfo
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Abstract
The invention discloses a management and control system for operation of plywood composite glue equipment based on data analysis, which relates to the technical field of operation and control of plywood glue equipment and solves the technical problem that whether the current operation efficiency of plywood glue equipment is qualified or not can not be accurately judged according to ladder mark setting analysis in the glue process in the prior art; the analysis object is tracked in the maintenance process, the fault part is analyzed according to the historical operation of the analysis object, the maintenance mode is reasonably selected for the fault of the current part, the maintenance accuracy of the analysis object is guaranteed, and the work efficiency of the analysis pair is guaranteed.
Description
Technical Field
The invention relates to the technical field of operation control of plywood composite cementing equipment, in particular to a data analysis-based operation control system of plywood composite cementing equipment.
Background
The plywood is one of common furniture materials and is an artificial board. The plywood is a three-layer or multi-layer plate material formed by rotary cutting wood sections into veneers or slicing battens into veneers and gluing the veneers by using an adhesive, the veneers with odd number of layers are usually glued by enabling the fiber directions of the veneers with adjacent layers to be vertical to each other, plywood groups with various thicknesses are obtained by gluing different numbers of veneers, and quality detection is needed in each link in the process.
However, in the prior art, whether the current operation efficiency of the composite glue of the plywood is qualified or not can not be accurately judged according to the ladder mark setting analysis in the gluing process, so that the operation state of gluing equipment cannot be accurately judged; in addition, the plywood cementing equipment cannot be accurately predicted according to the type of the position fault, so that the fault influence of the plywood cementing equipment cannot be controlled.
In view of the above technical drawbacks, a solution is proposed.
Disclosure of Invention
The invention aims to solve the problems, and provides a management and control system for the operation of a plywood composite gluing equipment based on data analysis, wherein real-time ladder marks are arranged in the operation process of the plywood composite gluing equipment for analysis, so that the quality detection is carried out in the gluing process of the real-time plywood, the gluing qualification of the plywood is improved, and meanwhile, when the gluing execution flow of the plywood is qualified, the detection of the gluing equipment is more accurate; carry out analysis and detection with the mucilage binding in-process of real-time mucilage binding task, judge the mucilage binding quality of real-time mucilage binding task and monitor the analysis, improved the monitoring dynamics of mucilage binding in-process, guarantee that the mucilage binding efficiency is in time put together the mucilage binding that appears unusually simultaneously, improved mucilage binding efficiency and also can carry out high-efficient the detection to mucilage binding equipment.
The purpose of the invention can be realized by the following technical scheme:
the utility model provides a plywood composite adhesive equipment operation management and control system based on data analysis, includes the server, and the server communication is connected with:
the ladder mark real-time analysis unit is used for analyzing the real-time ladder mark setting in the operation process of the plywood composite gluing equipment, marking the plywood composite gluing equipment as an analysis object, setting a mark i, wherein the mark i is a natural number greater than 1, generating a gluing process abnormal signal and a gluing process normal signal through real-time ladder mark analysis, and sending the gluing process abnormal signal and the gluing process normal signal to the server;
the cementing process analysis unit is used for analyzing and detecting the cementing process of the real-time cementing task, generating a normal cementing process signal and an abnormal cementing process signal through analysis, and sending the signals to the server;
the equipment operation tracking unit is used for tracking the operation of an analysis object in the maintenance process, analyzing fault parts according to the historical operation of the analysis object, dividing the analysis object into k parts, wherein k is a natural number greater than 1, acquiring a part fault analysis coefficient of the analysis object through analysis, dividing the parts into a primary fault part, a secondary fault part and a tertiary fault part according to the comparison of the part fault analysis coefficient, and sending the primary fault part, the secondary fault part and the tertiary fault part to the server;
and the operation fault prediction unit is used for performing fault prediction on an analysis object executing the real-time cementing task, generating a high fault risk prediction signal and a low fault risk prediction signal through analysis, and sending the high fault risk prediction signal and the low fault risk prediction signal to the server.
As a preferred embodiment of the present invention, the operation process of the ladder mark real-time analysis unit is as follows:
analyzing the real-time gluing task according to the analysis object, performing ladder mark setting on the plywood corresponding to the real-time gluing task, dividing the real-time gluing task according to the real-time gluing speed of the analysis object, distinguishing the real-time gluing task according to time points, dividing the real-time gluing task reduction amount of adjacent time points by the set ladder mark amount, and dividing the quotient into a group corresponding to the execution amount of the real-time gluing task, wherein the execution amount unit is a group; setting a real-time gluing task ladder scalar expected execution curve based on the real-time gluing speed, substituting the curve into a rectangular coordinate system, wherein the X axis of the rectangular coordinate system is a time point, and the Y axis of the rectangular coordinate system is a ladder scalar; the ladder scalar quantity shows for the plywood mucilage binding in-process, sets for quantity threshold value as unit plywood, if the ladder scalar quantity is ten, then the plywood is ten a set of, can judge whether real-time current mucilage binding is qualified through the setting of ladder scalar quantity.
As a preferred embodiment of the invention, the ladder scalar quantity of each time point is obtained according to the real-time cementing task execution process of an analysis object, and is substituted into a rectangular coordinate system to construct a ladder scalar real-time execution curve; collecting a curve slope difference value of the expected execution curve of the ladder mark and the corresponding time period in the real-time execution curve of the ladder mark and the time point deviation duration of the two curves corresponding to the same ladder mark, and respectively comparing the curve slope difference value with a threshold range and the time point deviation duration with a threshold range:
if the curve slope difference value of the corresponding time period in the expected execution curve of the ladder label and the real-time execution curve of the ladder label is not in the curve slope difference value threshold range, or the time point deviation duration of the two curves corresponding to the same ladder label is not in the time point deviation duration threshold range, generating an abnormal signal of the adhesive process and sending the abnormal signal of the adhesive process and the corresponding abnormal time to the server together;
if the curve slope difference value of the corresponding time period in the expected execution curve of the ladder label and the real-time execution curve of the ladder label is in the curve slope difference threshold range, and the time point deviation duration of the two curves corresponding to the same ladder label is in the time point deviation duration threshold range, marking the corresponding time point as a normal time, generating a normal signal of the glue binding process, and sending the normal signal of the glue binding process and the corresponding normal time to the server together.
As a preferred embodiment of the present invention, the operation of the cementing process analysis unit is as follows:
the method comprises the following steps of collecting a maximum rework amount difference value corresponding to a real-time adhesive bonding task between time points in the adhesive bonding process and a maximum rework amount increment of an adjacent time point, and comparing the maximum rework amount increment with a rework amount difference threshold and a rework amount increment threshold respectively:
if the corresponding maximum rework quantity difference value between the time points of the real-time adhesive bonding task exceeds the rework quantity difference value threshold value in the adhesive bonding process, or the maximum rework quantity increment of the adjacent time points exceeds the rework quantity increment threshold value, generating an abnormal signal of the adhesive bonding process and sending the abnormal signal of the adhesive bonding process to a server; and if the corresponding maximum rework quantity difference value between the time points of the real-time adhesive bonding task in the adhesive bonding process does not exceed the rework quantity difference value threshold value, and the maximum rework quantity increment of the adjacent time points does not exceed the rework quantity increment threshold value, generating a normal signal of the adhesive bonding process and sending the normal signal of the adhesive bonding process to the server.
As a preferred embodiment of the present invention, the operation process of the equipment operation tracking unit is as follows:
acquiring the historical operation time period of the analysis object by taking the current overhaul time of the analysis object as an end point, acquiring the duration of the fault of the part of the analysis object in the historical operation time period and the maintenance frequency of the corresponding part in the duration of the fault of the part; acquiring the average maintenance interval duration of each part corresponding to the analysis object in the historical operation time period;
acquiring a part fault analysis coefficient of an analysis object through analysis; comparing the part fault analysis coefficient of the analysis object with P1 and P2, wherein both P1 and P2 are part fault analysis coefficient threshold values, and P1 is larger than P2; if the part fault analysis coefficient of the analysis object exceeds P1, marking the corresponding part as a primary fault part; if the part fault analysis coefficient of the analysis object does not exceed P1 and exceeds P2, marking the corresponding part as a secondary fault part; and if the analysis coefficient of the part fault of the analysis object does not exceed P2, marking the corresponding part as a three-level fault part.
As a preferred embodiment of the present invention, the operation procedure of the operation failure prediction unit is as follows:
acquiring the growth speed of a high-level fault part converted into a low-level fault part in the real-time running process of an analysis object and the real-time fault increase quantity of parts without faults in a historical time period, and comparing the real-time fault increase quantity with a growth speed threshold value and an increase quantity threshold value respectively:
if the increasing speed of the high-level fault part converted into the low-level fault part in the real-time running process of the analysis object exceeds an increasing speed threshold value, or the increasing number of the parts which do not have faults in the historical time period corresponding to the real-time faults exceeds an increasing number threshold value, generating a high fault risk prediction signal and sending the high fault risk prediction signal to a server; if the increasing speed of the high-level fault part converted into the low-level fault part in the real-time running process of the analysis object does not exceed the increasing speed threshold value, and the increasing number of the parts which do not have faults in the historical time period corresponding to the real-time faults does not exceed the increasing number threshold value, generating a low fault risk prediction signal and sending the low fault risk prediction signal to the server.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, the real-time ladder mark arrangement in the operation process of the plywood composite gluing equipment is analyzed, so that the quality detection is carried out in the gluing process of the real-time plywood, the gluing qualification rate of the plywood is improved, and meanwhile, when the gluing execution flow of the plywood is qualified, the detection on the gluing equipment is more accurate; the real-time cementing task is analyzed and detected in the cementing process, the cementing quality of the real-time cementing task is judged and monitored and analyzed, the monitoring strength in the cementing process is improved, the cementing efficiency is ensured, abnormal cementing is timely tidied, the cementing efficiency is improved, and the cementing equipment can be efficiently detected;
2. according to the invention, the operation of the analysis object is tracked in the maintenance process, the fault part is analyzed according to the historical operation of the analysis object, and the maintenance mode is reasonably selected for the fault of the current part, so that the maintenance efficiency of the analysis object is improved, the maintenance accuracy of the analysis object is ensured, the inefficient maintenance of the part of the analysis object is reduced, and the work efficiency of the analysis pair is ensured; whether the analysis object has fault risks in the operation process is judged, and fault prediction is carried out on the analysis object, so that the influence of the fault of the analysis object on the execution of the cementing task is reduced, the fault maintenance is favorably carried out in advance, and the operation efficiency of the analysis object is ensured to the greatest extent.
Drawings
To facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is a schematic block diagram of a control system for operation of plywood composite adhesive equipment based on data analysis.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are 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.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
Referring to fig. 1, a plywood composite glue equipment operation management and control system based on data analysis comprises a server, wherein the server is in communication connection with a ladder mark real-time analysis unit, a gluing process analysis unit, an equipment operation tracking unit and an operation fault prediction unit, and the server is in bidirectional communication connection with the ladder mark real-time analysis unit, the gluing process analysis unit, the equipment operation tracking unit and the operation fault prediction unit;
the server generates a ladder mark real-time analysis signal and sends the ladder mark real-time analysis signal to the ladder mark real-time analysis unit, and the ladder mark real-time analysis unit analyzes the real-time ladder mark arrangement in the operation process of the plywood composite gluing equipment after receiving the ladder mark real-time analysis signal, so that the quality detection is performed in the gluing process of the real-time plywood, the gluing qualification of the plywood is improved, and meanwhile, when the gluing execution flow of the plywood is qualified, the detection on the gluing equipment is more accurate;
marking the plywood composite gluing equipment as an analysis object, setting a mark i, wherein the mark i is a natural number greater than 1, analyzing a real-time gluing task corresponding to the analysis object, performing ladder mark setting on the plywood corresponding to the real-time gluing task, dividing the real-time gluing task according to the real-time gluing speed of the analysis object, and distinguishing the real-time gluing task according to time points, wherein the reduction amount of the real-time gluing task at adjacent time points is divided by the set ladder mark amount, and the quotient corresponds to the execution amount of the real-time gluing task, and the unit of the execution amount is a group; setting a real-time cementing task ladder scalar expected execution curve based on the real-time cementing speed, substituting the curve into a rectangular coordinate system, wherein the X axis of the rectangular coordinate system is a time point, and the Y axis is a ladder scalar; the ladder scalar is expressed as that in the gluing process of the plywood, a quantity threshold value is set as unit plywood, if the ladder scalar is ten, the plywood is a group of ten plywood, and whether the real-time current gluing is qualified or not can be judged through the ladder scalar setting;
obtaining a ladder scalar quantity of each time point according to the real-time cementing task execution process of an analysis object, and substituting the ladder scalar quantity into a rectangular coordinate system to construct a ladder scalar real-time execution curve; acquiring a curve slope difference value of the expected execution curve of the ladder mark and the corresponding time period in the real-time execution curve of the ladder mark and the time point deviation duration of the two curves corresponding to the same ladder mark, and respectively comparing the curve slope difference value of the expected execution curve of the ladder mark and the corresponding time period in the real-time execution curve of the ladder mark and the time point deviation duration of the two curves corresponding to the same ladder mark with a curve slope difference threshold range and a time point deviation duration threshold range:
if the curve slope difference value of the expected execution curve of the ladder label and the corresponding time period in the real-time execution curve of the ladder label is not in the curve slope difference value threshold range, or the time point deviation duration of two curves corresponding to the same ladder scalar is not in the time point deviation duration threshold range, judging that an abnormality exists in the real-time glue-binding task execution process, marking the corresponding time point as an abnormal time, generating a glue-binding process abnormal signal, sending the glue-binding process abnormal signal and the corresponding abnormal time to a server together, after receiving the glue-binding process abnormal signal, monitoring the glue-binding process corresponding to the abnormal time, detecting the abnormal time to a historical time by taking the abnormal time as a starting point, judging the deviation value of the ladder scalar, judging that the time is a correction time point according to the deviation value, and re-executing the real-time glue-binding task execution quantity in the interval time period from the correction time point to the current system time point;
if the curve slope difference value of the corresponding time period in the expected execution curve of the ladder label and the real-time execution curve of the ladder label is in the curve slope difference threshold range, and the time point deviation duration of the two curves corresponding to the same ladder label is in the time point deviation duration threshold range, judging that the real-time cementing task execution process is normal, marking the corresponding time point as a normal time, generating a normal signal of the cementing process, and sending the normal signal of the cementing process and the corresponding normal time to the server together;
after the server receives the normal signals of the gluing process, the server generates gluing process analysis signals and sends the gluing process analysis signals to the gluing process analysis unit, the gluing process analysis unit receives the gluing process analysis signals and analyzes and detects the gluing process of the real-time gluing task, the gluing quality of the real-time gluing task is judged and monitored and analyzed, the monitoring force in the gluing process is improved, the gluing efficiency is guaranteed, meanwhile, abnormal gluing is timely tidied, and the gluing efficiency is improved, and the gluing equipment can also be efficiently detected;
the method comprises the following steps of collecting a maximum rework amount difference value corresponding to a real-time adhesive bonding task between time points in the adhesive bonding process and a maximum rework amount increment of an adjacent time point, and comparing the maximum rework amount difference value corresponding to the real-time adhesive bonding task between the time points in the adhesive bonding process and the maximum rework amount increment of the adjacent time point with a rework amount difference threshold value and a rework amount increment threshold value respectively:
if the maximum rework quantity difference value corresponding to the time points of the real-time adhesive bonding task exceeds the rework quantity difference value threshold value in the adhesive bonding process, or the maximum rework quantity increment of the adjacent time points exceeds the rework quantity increment threshold value, judging that the adhesive bonding process of the real-time adhesive bonding task is unqualified in analysis, generating an abnormal signal of the adhesive bonding process and sending the abnormal signal of the adhesive bonding process to a server, and after receiving the abnormal signal of the adhesive bonding process, the server overhauls an analysis object in a time period corresponding to the time points;
if the difference value of the corresponding maximum rework amount between the time points of the real-time cementing task does not exceed the rework amount difference value threshold value and the maximum rework amount increment of the adjacent time points does not exceed the rework amount increment threshold value in the cementing process, judging that the cementing process of the real-time cementing task is qualified through analysis, generating a normal signal of the cementing process and sending the normal signal of the cementing process to a server;
in the maintenance process of an analysis object, a server generates an equipment operation tracking signal and sends the equipment operation tracking signal to an equipment operation tracking unit, the equipment operation tracking unit tracks the operation of the analysis object in the maintenance process after receiving the equipment operation tracking signal, the analysis is carried out according to the historical operation fault part of the analysis object, and the maintenance mode is reasonably selected for the current part fault, so that the maintenance efficiency of the analysis object is improved, the maintenance accuracy of the analysis object is ensured, the inefficient maintenance of the analysis object part is reduced, and the work efficiency of an analysis pair is favorably ensured;
dividing an analysis object into k parts, wherein k is a natural number greater than 1, acquiring a historical operation time period of the analysis object by taking the current maintenance time of the analysis object as an end point, acquiring the duration of the fault of the part of the analysis object in the historical operation time period and the maintenance frequency of the corresponding part in the part fault duration, and respectively marking the duration of the fault of the part of the analysis object in the historical operation time period and the maintenance frequency of the corresponding part in the part fault duration as CXSk and WXPk; acquiring the average maintenance interval duration of the analysis object corresponding to each part in the historical operation time period, and marking the average maintenance interval duration of the analysis object corresponding to each part in the historical operation time period as WXJk;
by the formula
Acquiring a part fault analysis coefficient Wk of an analysis object, wherein a1, a2 and a3 are preset proportionality coefficients, a1 is greater than a2 and greater than a3 and greater than 0, and beta is an error correction factor with a value of 0.698;
comparing the part failure analysis coefficient Wk of the analysis object with P1 and P2, wherein P1 and P2 are part failure analysis coefficient threshold values, and P1 is larger than P2:
if the part fault analysis coefficient Wk of the analysis object exceeds P1, marking the corresponding part as a primary fault part; if the part fault analysis coefficient Wk of the analysis object does not exceed P1 and exceeds P2, marking the corresponding part as a secondary fault part; if the part failure analysis coefficient Wk of the analysis object does not exceed P2, marking the corresponding part as a tertiary failure part; wherein not more than one is included in the present application;
sending the corresponding fault grades of the primary fault part, the secondary fault part and the tertiary fault part to a server; after receiving the corresponding fault grade, the server replaces equipment of the corresponding part aiming at the first-level fault part and replaces a maintenance mode of the corresponding part aiming at the second-level fault part; taking the corresponding part as a reference according to a historical maintenance mode aiming at the third-stage fault part, and continuously maintaining in the maintenance mode; meanwhile, the server generates an operation fault prediction signal and sends the operation fault prediction signal to an operation fault prediction unit;
after receiving the operation fault prediction signal, the operation fault prediction unit performs fault prediction on an analysis object executing the real-time cementing task, judges whether the analysis object has a fault risk in the operation process, performs fault prediction on the analysis object, reduces the influence of the fault of the analysis object on the cementing task execution, is beneficial to performing fault maintenance in advance, and ensures the operation efficiency of the analysis object to the maximum extent;
acquiring the increasing speed of the high-level fault part converted into the low-level fault part in the real-time running process of the analysis object and the corresponding real-time fault increasing quantity of the part without fault in the historical time period, and comparing the increasing speed of the high-level fault part converted into the low-level fault part in the real-time running process of the analysis object and the corresponding real-time fault increasing quantity of the part without fault in the historical time period with an increasing speed threshold value and an increasing quantity threshold value respectively: in the application, the conversion from the high-level fault part to the low-level fault part is represented as the conversion from the third-level fault part to the second-level fault part or the first-level fault part, and the second-level fault part is converted to the first-level fault part;
if the increasing speed of the high-level fault part converted from the low-level fault part in the real-time running process of the analysis object exceeds the increasing speed threshold value, or the increasing number of the parts which do not have faults in the historical time period corresponding to the real-time faults exceeds the increasing number threshold value, judging that the fault prediction of the analysis object is a high fault risk, generating a high fault risk prediction signal, sending the high fault risk prediction signal to a server, pausing a currently unexecuted adhesive binding task after the server receives the high fault risk prediction signal, reducing the executing speed of the adhesive binding task executed in real time, stopping adhesive binding when the parts have faults after the speed is reduced, and maintaining the analysis object;
if the increasing speed of the high-level fault part converted into the low-level fault part in the real-time running process of the analysis object does not exceed the increasing speed threshold value, and the increasing quantity of the parts which do not have faults in the historical time period corresponding to the real-time faults does not exceed the increasing quantity threshold value, the fault prediction of the analysis object is judged to be a low fault risk, a low fault risk prediction signal is generated, and the low fault risk prediction signal is sent to the server.
The formulas are obtained by acquiring a large amount of data and performing software simulation, and the coefficients in the formulas are set by the technicians in the field according to actual conditions;
when the real-time ladder mark analysis system is used, the real-time ladder mark in the operation process of the plywood composite gluing equipment is set for analysis through the ladder mark real-time analysis unit, the plywood composite gluing equipment is marked as an analysis object, a mark i is set, the mark i is a natural number larger than 1, an abnormal gluing process signal and a normal gluing process signal are generated through real-time ladder mark analysis, and the signals are sent to a server; analyzing and detecting the gluing process of the real-time gluing task through a gluing process analyzing unit, generating a normal gluing process signal and an abnormal gluing process signal through analysis, and sending the signals to a server; the method comprises the steps that an analysis object is subjected to operation tracking in the overhaul process through an equipment operation tracking unit, analysis is carried out according to historical operation fault positions of the analysis object, the analysis object is divided into k positions, k is a natural number larger than 1, a position fault analysis coefficient of the analysis object is obtained through analysis, the positions are divided into a primary fault position, a secondary fault position and a tertiary fault position according to comparison of the position fault analysis coefficient, and the primary fault position, the secondary fault position and the tertiary fault position are sent to a server; and performing fault prediction on an analysis object executing the real-time cementing task by operating a fault prediction unit, generating a high fault risk prediction signal and a low fault risk prediction signal by analysis, and sending the high fault risk prediction signal and the low fault risk prediction signal to a server.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (6)
1. The utility model provides a plywood composite adhesive equipment operation management and control system based on data analysis which characterized in that, includes the server, and the server communication is connected with: the ladder mark real-time analysis unit is used for analyzing the real-time ladder mark setting in the operation process of the plywood composite gluing equipment, marking the plywood composite gluing equipment as an analysis object, setting a mark number i, wherein the mark number i is a natural number greater than 1, generating a gluing process abnormal signal and a gluing process normal signal through real-time ladder mark analysis, and sending the gluing process abnormal signal and the gluing process normal signal to the server; the system comprises a gluing process analysis unit, a server and a real-time gluing task analysis unit, wherein the gluing process analysis unit is used for analyzing and detecting the gluing process of a real-time gluing task, generating a normal gluing process signal and an abnormal gluing process signal through analysis, and sending the signals to the server; the equipment operation tracking unit is used for tracking the operation of an analysis object in the overhaul process, analyzing the analysis object according to the historical operation fault part of the analysis object, dividing the analysis object into k parts, wherein k is a natural number greater than 1, acquiring a part fault analysis coefficient of the analysis object through analysis, dividing the parts into a primary fault part, a secondary fault part and a tertiary fault part according to the comparison of the part fault analysis coefficient, and sending the primary fault part, the secondary fault part and the tertiary fault part to the server; and the operation fault prediction unit is used for performing fault prediction on an analysis object executing the real-time cementing task, generating a high fault risk prediction signal and a low fault risk prediction signal through analysis, and sending the high fault risk prediction signal and the low fault risk prediction signal to the server.
2. The operation control system for plywood composite adhesive equipment based on data analysis as claimed in claim 1, wherein the operation process of the ladder mark real-time analysis unit is as follows: analyzing according to a real-time gluing task corresponding to an analysis object, performing ladder mark setting on plywood corresponding to the real-time gluing task, dividing the real-time gluing task according to the real-time gluing speed of the analysis object, and distinguishing the real-time gluing task according to time points, wherein the reduction amount of the real-time gluing task at the adjacent time points is divided by the ladder mark setting amount, and the quotient corresponds to the execution amount of the real-time gluing task, and the execution amount unit is a group; the real-time gluing speed is used as a basis to set a real-time gluing task ladder scalar expected execution curve, the curve is substituted into a rectangular coordinate system, the X axis of the rectangular coordinate system is a time point, and the Y axis is a ladder scalar.
3. The plywood composite gluing equipment operation management and control system based on data analysis as claimed in claim 2, wherein a ladder scalar quantity of each time point is obtained according to a real-time gluing task execution process of an analysis object, and is substituted into a rectangular coordinate system to construct a ladder scalar real-time execution curve; acquiring a curve slope difference value of a corresponding time period in the expected execution curve of the ladder standard and the real-time execution curve of the ladder standard and the time point deviation duration of the two curves corresponding to the same ladder standard quantity, and respectively comparing the curve slope difference value threshold range with the time point deviation duration threshold range: if the curve slope difference value of the corresponding time period in the expected execution curve of the ladder mark and the real-time execution curve of the ladder mark is not in the curve slope difference value threshold range, or the time point deviation duration of the two curves corresponding to the same ladder mark is not in the time point deviation duration threshold range, generating an abnormal signal of the adhesive binding process and sending the abnormal signal of the adhesive binding process and the corresponding abnormal time to the server together; if the curve slope difference value of the corresponding time period in the expected execution curve of the ladder label and the real-time execution curve of the ladder label is in the curve slope difference threshold range, and the time point deviation duration of the two curves corresponding to the same ladder label is in the time point deviation duration threshold range, marking the corresponding time point as a normal time, generating a normal signal of the glue binding process, and sending the normal signal of the glue binding process and the corresponding normal time to the server together.
4. The operation control system for plywood composite veneer gluing equipment based on data analysis according to claim 1, wherein the operation process of the gluing process analysis unit is as follows: the method comprises the following steps of collecting a maximum rework amount difference value corresponding to a real-time adhesive bonding task between time points in the adhesive bonding process and a maximum rework amount increment of an adjacent time point, and comparing the maximum rework amount increment with a rework amount difference threshold and a rework amount increment threshold respectively: if the corresponding maximum rework quantity difference value between the time points of the real-time adhesive bonding task exceeds the rework quantity difference value threshold value in the adhesive bonding process, or the maximum rework quantity increment of the adjacent time points exceeds the rework quantity increment threshold value, generating an abnormal signal of the adhesive bonding process and sending the abnormal signal of the adhesive bonding process to a server; and if the corresponding maximum rework quantity difference value between the time points of the real-time adhesive bonding task in the adhesive bonding process does not exceed the rework quantity difference value threshold value, and the maximum rework quantity increment of the adjacent time points does not exceed the rework quantity increment threshold value, generating a normal signal of the adhesive bonding process and sending the normal signal of the adhesive bonding process to the server.
5. The plywood composite adhesive equipment operation control system based on data analysis according to claim 1, wherein the operation process of the equipment operation tracking unit is as follows: acquiring a historical operation time period of an analysis object by taking the current maintenance time of the analysis object as an end point, and acquiring the fault duration of a part of the analysis object in the historical operation time period and the maintenance frequency of a corresponding part in the fault duration of the part; acquiring the average maintenance interval duration of each part corresponding to the analysis object in the historical operation time period; acquiring a part fault analysis coefficient of an analysis object through analysis; comparing the part fault analysis coefficient of the analysis object with P1 and P2, wherein both P1 and P2 are part fault analysis coefficient threshold values, and P1 is larger than P2; if the part fault analysis coefficient of the analysis object exceeds P1, marking the corresponding part as a primary fault part; if the part fault analysis coefficient of the analysis object does not exceed P1 and exceeds P2, marking the corresponding part as a secondary fault part; and if the analysis coefficient of the part fault of the analysis object does not exceed P2, marking the corresponding part as a three-level fault part.
6. The plywood compound adhesive equipment operation control system based on data analysis according to claim 1, wherein the operation process of the operation failure prediction unit is as follows: acquiring the growth speed of a high-level fault part converted into a low-level fault part in the real-time running process of an analysis object and the real-time fault increase quantity of parts without faults in a historical time period, and comparing the real-time fault increase quantity with a growth speed threshold value and an increase quantity threshold value respectively: if the increasing speed of the high-level fault part converted from the low-level fault part in the real-time running process of the analysis object exceeds an increasing speed threshold value, or the increasing number of the real-time faults corresponding to the part which does not have faults in the historical time period exceeds an increasing number threshold value, generating a high fault risk prediction signal and sending the high fault risk prediction signal to a server; if the increasing speed of the high-level fault part converted into the low-level fault part in the real-time running process of the analysis object does not exceed the increasing speed threshold value, and the increasing number of the parts which do not have faults in the historical time period corresponding to the real-time faults does not exceed the increasing number threshold value, generating a low fault risk prediction signal and sending the low fault risk prediction signal to the server.
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