A quality monitoring and feedback system for aluminum-plastic equipment

Abstract

The invention relates to the field of quality monitoring and feedback of aluminum-plastic equipment, and specifically to a quality monitoring and feedback system for aluminum-plastic equipment, comprising an equipment information input module, a data acquisition module, a data analysis module, a displacement analysis module, an early warning processing module and an equipment maintenance module. The equipment maintenance module analyzes the maintenance time of the aluminum-plastic equipment according to the information sent by the equipment information input module, regularly maintains the equipment, and reduces the equipment failure rate. The displacement analysis module analyzes the displacement parameters of each flower disc sent by the receiving data acquisition module. The equipment information input module is used to input various information parameters of each aluminum-plastic equipment into a data center. The invention improves the stability and reliability of product quality, reduces the generation of defective products, and improves production efficiency, and provides a comprehensive, efficient and intelligent quality monitoring and feedback solution for aluminum-plastic equipment production.

Description

Technical Field

[0001] The invention relates to the field of quality monitoring and feedback of aluminum-plastic equipment, and in particular to a quality monitoring and feedback system of aluminum-plastic equipment. Background Art

[0002] Aluminum-plastic equipment plays an important role in modern industrial production and is widely used in pharmaceutical, food, chemical and other industries. However, ensuring product quality and equipment stability has always been a key issue during the operation of aluminum-plastic equipment. The traditional aluminum-plastic equipment quality inspection system mainly relies on image data processing. By obtaining images of the detected tablets, judging the images, and rejecting them according to the set rejection position. This method can detect the appearance defects of the product to a certain extent, but it is difficult to effectively detect problems such as mechanical dislocation during the operation of the equipment. When replacing PVC and stepper drive dislocation, it may be difficult for personnel to find it in time because the dislocation may not be obvious. This may cause the set rejection position to be misaligned, so that some unqualified products that should have been rejected were not discovered in time, while some qualified products were mistakenly rejected. Such a situation will not only delay a lot of working hours and affect production efficiency, but also increase the labor cost of the equipment because of the need to re-check the packaging quality.

[0003] In order to overcome these problems, improve the production efficiency and product quality of aluminum-plastic equipment and reduce costs, a more advanced and comprehensive aluminum-plastic equipment monitoring system is urgently needed. The system should be able to monitor the operating status of the equipment in real time and detect problems such as mechanical dislocation in a timely manner, so as to better meet the needs of modern industrial production and improve the competitiveness of enterprises. Summary of the invention

[0004] In order to solve the technical problems raised by the above background technology, the present invention provides an aluminum-plastic equipment quality monitoring feedback system.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A quality monitoring and feedback system for aluminum-plastic equipment comprises an equipment information input module, a data acquisition module, a data analysis module, a displacement analysis module, an early warning processing module, an equipment maintenance module and a data center.

[0007] The equipment information input module is used to input various information parameters of each aluminum-plastic equipment into the data center. The specific acquisition method is as follows:

[0008] The output end of the equipment information entry module is connected to the input end of the data center to establish the basic information of the equipment. The basic information includes the name of each aluminum-plastic equipment, the time it starts to be used, the equipment maintenance cycle, the number and location information. The basic information of each aluminum-plastic equipment is sent to the data center for storage. The data center divides the basic information of each aluminum-plastic equipment, marks the same type of equipment as an equipment group, marks each equipment group as j, marks the number of equipment corresponding to each equipment group as n, and combines each equipment group and the corresponding number of equipment into an aluminum-plastic equipment set.

[0009] The output end of the equipment information input module is connected to the input end of the equipment maintenance module, and the acquired information is sent to the equipment maintenance module.

[0010] The data acquisition module collects the data parameters of each aluminum-plastic equipment in real time according to each sensor. The specific acquisition process is as follows:

[0011] The photoelectric detector and the fixing plate are fixed by lowering 1 cm at the lowest point of the predetermined flower disc lifting process to prevent false information feedback. The photoelectric detector is used to monitor the actual position information of the flower disc in real time, and the displacement parameters of each flower disc are obtained in real time.

[0012] Temperature sensors are distributed in the heating components and the forming area, and the temperature of each aluminum-plastic equipment during operation is collected in real time through the temperature sensors to obtain the temperature parameters of each aluminum-plastic equipment;

[0013] The pressure sensor is installed at the key parts of the aluminum-plastic equipment, including the mold and the pressing mechanism, and the pressure parameters of each aluminum-plastic equipment during operation in a specific period of time are monitored in real time by the pressure sensor to obtain the pressure parameters of each aluminum-plastic equipment;

[0014] The output end of the acquisition module is connected to the input end of the data analysis module and the image analysis module, and the acquired pressure parameters and temperature parameters are sent to the equipment analysis module, and the displacement parameters of each flower disc are sent to the displacement analysis module.

[0015] The data analysis module analyzes the parameter information of the data acquisition module, and the specific acquisition process is as follows:

[0016] The input end of the data analysis module is connected to the output end of the data center, and each temperature parameter is analyzed. The acquired temperature parameters and the corresponding acquisition time points are summarized to obtain the acquisition device temperature data set. The device temperature change graph is generated according to the acquisition device temperature data set. The first device temperature warning value and the second device temperature warning value are set in the device temperature change graph. The first device temperature warning value and the second device temperature warning value are subtracted to obtain the device temperature warning range and generate the device warning temperature set. The device warning temperature set is sent to the data center. The maximum temperature value and the minimum temperature value of the corresponding device are obtained according to the device temperature change graph, marked as KL and KG respectively, the acquisition temperature time point corresponding to the maximum temperature value and the acquisition temperature time point corresponding to the minimum temperature value are obtained, the maximum temperature acquisition time point and the minimum temperature acquisition time point are obtained, the maximum temperature acquisition time point and the minimum temperature acquisition time point are subtracted to obtain the maximum temperature difference period, marked as KT, the acquired temperature parameter values ​​are averaged to obtain the temperature average value, marked as KH, the temperature average value, the maximum temperature difference period, the maximum temperature value and the minimum temperature value are calculated using the formula The temperature intervention value is obtained, where B1, B2, B3 and B4 are preset proportional coefficients, j represents a certain equipment group number, and n represents the number of equipment corresponding to the equipment group. The obtained temperature intervention value is compared with the equipment temperature warning range. If the temperature intervention value is greater than or less than the equipment temperature warning range, a temperature abnormality signal is generated and sent to the warning processing module.

[0017] Analyze the pressure parameters, set a preset pressure monitoring time zone, divide the pressure monitoring time zone into several pressure monitoring time zones, obtain the pressure values ​​at all collection moments in the pressure time zone, calculate the mean of each pressure value to get the pressure average value corresponding to the pressure monitoring time zone, calculate the pressure standard deviation value based on the average value, extract the preset pressure standard deviation value of the data center, compare the actual pressure standard deviation value with the preset pressure standard deviation value, and if the actual pressure standard deviation is greater than the preset pressure standard deviation, generate a pressure signal and send it to the early warning processing module.

[0018] The displacement analysis module analyzes the displacement parameters of each faceplate sent by the receiving data acquisition module. The specific acquisition method is as follows:

[0019] The output end of the displacement analysis module is connected to the input end of the early warning processing module, and the displacement parameters of each flower disc are analyzed. The motion state of the aluminum-plastic equipment is turned on, and the motion time point of the current flower disc motion state is obtained, marked as the initial time point. The flower disc position corresponding to the current initial time point is obtained through the photoelectric sensor, marked as the initial position, and the motion time point when the flower disc stops moving is obtained, marked as the end time point. The initial time point and the end time point are subtracted to obtain the flower disc motion period, marked as EF, and the corresponding flower disc position is obtained according to the end time point, marked as the end position, and the initial position and the end position corresponding to the flower disc are connected to obtain the corresponding movement distance of the flower disc, and the movement distance is marked as EK. Using the formula Get the average moving speed ER of the flower disk, divide the flower disk movement period into several flower disk movement time periods, marked as {t1, t2, ..., tn}, obtain the speed value corresponding to each flower disk movement time period, marked as {v1, v2, ..., vn}, and calculate using the formula Get the flower disc acceleration ET, calculate the flower disc movement period, flower disc movement distance, flower disc acceleration and flower disc average speed, and use the formula The faceplate displacement motion value is obtained, wherein C1, C2, C3 and C4 are preset proportional coefficients, tn represents the speed value of the faceplate in a certain period of time, the preset faceplate displacement motion threshold of the data center is extracted, and the actual faceplate displacement motion value is compared with the preset faceplate displacement motion value. If the actual faceplate displacement motion value is greater than the preset faceplate displacement motion value, it means that the current displacement is too large, and a processing signal is generated and sent to the early warning processing module.

[0020] The early warning processing module processes each signal received separately, and the specific acquisition method is as follows:

[0021] The input end of the early warning processing module is connected to the output end of the data center, and when it receives the abnormal temperature signal, it obtains the location information of the corresponding aluminum-plastic equipment in real time according to the positioning sensor, and feeds the location information back to the central processing system. The central processing system receives the location information and generates an open command, and sends the open command to the cold air device near the corresponding aluminum-plastic equipment. The cold air device starts the movement state to cool the aluminum-plastic equipment. The current temperature parameters are obtained in real time through the temperature sensor, and the equipment temperature early warning range is obtained. When the temperature drops to the equipment temperature early warning range, a stop command is generated and sent to the cold air device to stop the movement state.

[0022] The pressure signal is received and sent to the central processing system. The central processing system obtains the position information of the corresponding equipment according to the positioning sensor, generates an adjustment instruction and sends it to the corresponding aluminum-plastic equipment and the aluminum-plastic equipment control terminal. The aluminum-plastic equipment control terminal receives the adjustment instruction and adjusts the operating speed of the current aluminum-plastic equipment.

[0023] The processing signal is received and sent to the central processing system. The central processing system receives the processing signal to obtain the movement state of the corresponding aluminum-plastic equipment. If it is in the running state, a stop signal is generated and sent to the corresponding aluminum-plastic equipment. The corresponding aluminum-plastic equipment receives the stop signal and stops the current running state. The central processing system sends an early warning signal to the display terminal of the aluminum-plastic equipment. The display terminal receives the early warning signal and sends an audible and visual alarm through a speaker.

[0024] The equipment maintenance module analyzes the maintenance time of the aluminum-plastic equipment according to the information sent by the equipment information entry module, regularly maintains the equipment, and reduces the equipment failure rate. The specific acquisition process is as follows:

[0025] Get the start time of use of each aluminum-plastic equipment and the equipment maintenance cycle, add the start time of use and the equipment maintenance cycle to get each maintenance date, get the current maintenance date, and end with the current date of the system. Difference between the current date and the current maintenance date gets the maintenance value. If the maintenance value is a positive number, take the corresponding aluminum-plastic equipment as the origin, get the mobile terminal positioning of each maintenance personnel within the radius, and connect the positioning of the corresponding aluminum-plastic equipment with the mobile phone positioning of each maintenance personnel to get the straight-line distance of each maintenance, get the nearest straight-line distance and mark the corresponding maintenance personnel as the target personnel, generate a maintenance signal and send it to the target personnel for maintenance.

[0026] Compared with the prior art, the beneficial effects of the present invention are: improving product quality, through real-time monitoring and feedback, being able to timely discover and solve problems in equipment operation, reducing the generation of defective products, and improving the stability of product quality. Enhancing equipment reliability, timely detecting abnormal conditions such as mechanical dislocation, avoiding further deterioration of equipment failure, extending the service life of equipment, reducing maintenance costs, improving production efficiency, reducing downtime caused by equipment failure and quality problems, and improving production continuity and efficiency. Reducing labor costs, the automatic monitoring and alarm functions reduce the reliance on manual inspections and reduce labor costs. Timely early warning and processing, through sound and light alarms and other means, promptly notifying operators of abnormal conditions of equipment, enabling them to take measures quickly and reduce losses. Optimizing the production process, according to the analysis of monitoring data, the production process can be optimized, the scientificity and rationality of production can be improved, and the competitiveness of enterprises can be enhanced. High-quality products, efficient production and reliable equipment operation can help enhance the competitiveness of enterprises in the market. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. The following drawings are not intentionally scaled to the actual size, and the focus is on illustrating the main purpose of the present invention.

[0028] Figure 1It is a principle block diagram of the present invention.

[0029] Figure 2 It is the temperature variation diagram of the equipment of the present invention. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work also fall within the scope of protection of the present invention.

[0031] See also Figure 1-Figure 2 As shown, the aluminum-plastic equipment quality monitoring feedback system includes an equipment information input module, a data acquisition module, a data analysis module, a displacement analysis module, an early warning processing module, an equipment maintenance module and a data center.

[0032] The equipment information input module is used to input various information parameters of each aluminum-plastic equipment into the data center. The specific acquisition method is as follows:

[0033] The output end of the equipment information entry module is connected to the input end of the data center to establish the basic information of the equipment. The basic information includes the name of each aluminum-plastic equipment, the time it starts to be used, the equipment maintenance cycle, the number and location information. The basic information of each aluminum-plastic equipment is sent to the data center for storage. The data center divides the basic information of each aluminum-plastic equipment, marks the same type of equipment as an equipment group, marks each equipment group as j, marks the number of equipment corresponding to each equipment group as n, and combines each equipment group and the corresponding number of equipment into an aluminum-plastic equipment set.

[0034] The output end of the equipment information input module is connected to the input end of the equipment maintenance module, and the acquired information is sent to the equipment maintenance module.

[0035] The data acquisition module collects the data parameters of each aluminum-plastic equipment in real time according to each sensor. The specific acquisition process is as follows:

[0036] The photoelectric detector and the fixing plate are fixed by lowering 1 cm at the lowest point of the predetermined flower disc lifting process to prevent false information feedback. The photoelectric detector is used to monitor the actual position information of the flower disc in real time, and the displacement parameters of each flower disc are obtained in real time.

[0037] Temperature sensors are distributed in the heating components and the forming area, and the temperature of each aluminum-plastic equipment during operation is collected in real time through the temperature sensors to obtain the temperature parameters of each aluminum-plastic equipment;

[0038] The pressure sensor is installed at the key parts of the aluminum-plastic equipment, including the mold and the pressing mechanism, and the pressure parameters of each aluminum-plastic equipment during operation in a specific period of time are monitored in real time by the pressure sensor to obtain the pressure parameters of each aluminum-plastic equipment;

[0039] The output end of the acquisition module is connected to the input end of the data analysis module and the image analysis module, and the acquired pressure parameters and temperature parameters are sent to the equipment analysis module, and the displacement parameters of each disc are sent to the displacement analysis module.

[0040] The data analysis module analyzes the parameter information of the data acquisition module, and the specific acquisition process is as follows:

[0041] The input end of the data analysis module is connected to the output end of the data center, and each temperature parameter is analyzed. The acquired temperature parameters and the corresponding acquisition time points are summarized to obtain the acquisition device temperature data set. The device temperature change graph is generated according to the acquisition device temperature data set. The first device temperature warning value and the second device temperature warning value are set in the device temperature change graph. The first device temperature warning value and the second device temperature warning value are subtracted to obtain the device temperature warning range and generate the device warning temperature set. The device warning temperature set is sent to the data center. The maximum temperature value and the minimum temperature value of the corresponding device are obtained according to the device temperature change graph, marked as KL and KG respectively, the acquisition temperature time point corresponding to the maximum temperature value and the acquisition temperature time point corresponding to the minimum temperature value are obtained, the maximum temperature acquisition time point and the minimum temperature acquisition time point are obtained, the maximum temperature acquisition time point and the minimum temperature acquisition time point are subtracted to obtain the maximum temperature difference period, marked as KT, the acquired temperature parameter values ​​are averaged to obtain the temperature average value, marked as KH, the temperature average value, the maximum temperature difference period, the maximum temperature value and the minimum temperature value are calculated using the formula The temperature intervention value is obtained, where B1, B2, B3 and B4 are preset proportional coefficients, j represents a certain equipment group number, and n represents the number of equipment corresponding to the equipment group. The obtained temperature intervention value is compared with the equipment temperature warning range. If the temperature intervention value is greater than or less than the equipment temperature warning range, a temperature abnormality signal is generated and sent to the warning processing module.

[0042] Analyze the pressure parameters, set a preset pressure monitoring time zone, divide the pressure monitoring time zone into several pressure monitoring time zones, obtain the pressure values ​​at all collection moments in the pressure time zone, calculate the mean of each pressure value to get the pressure average value corresponding to the pressure monitoring time zone, calculate the pressure standard deviation value based on the average value, extract the preset pressure standard deviation value of the data center, compare the actual pressure standard deviation value with the preset pressure standard deviation value, and if the actual pressure standard deviation is greater than the preset pressure standard deviation, generate a pressure signal and send it to the early warning processing module.

[0043] The displacement analysis module analyzes the displacement parameters of each faceplate sent by the receiving data acquisition module. The specific acquisition method is as follows:

[0044] The output end of the displacement analysis module is connected to the input end of the early warning processing module, and the displacement parameters of each flower disc are analyzed. The motion state of the aluminum-plastic equipment is turned on, and the motion time point of the current flower disc motion state is obtained, marked as the initial time point. The flower disc position corresponding to the current initial time point is obtained through the photoelectric sensor, marked as the initial position, and the motion time point when the flower disc stops moving is obtained, marked as the end time point. The initial time point and the end time point are subtracted to obtain the flower disc motion period, marked as EF, and the corresponding flower disc position is obtained according to the end time point, marked as the end position, and the initial position and the end position corresponding to the flower disc are connected to obtain the corresponding movement distance of the flower disc, and the movement distance is marked as EK. Using the formula Get the average moving speed ER of the flower disk, divide the flower disk movement period into several flower disk movement time periods, marked as {t1, t2, ..., tn}, obtain the speed value corresponding to each flower disk movement time period, marked as {v1, v2, ..., vn}, and calculate using the formula Get the flower disc acceleration ET, calculate the flower disc movement period, flower disc movement distance, flower disc acceleration and flower disc average speed, and use the formula The faceplate displacement motion value is obtained, wherein C1, C2, C3 and C4 are preset proportional coefficients, tn represents the speed value of the faceplate in a certain period of time, the preset faceplate displacement motion threshold of the data center is extracted, and the actual faceplate displacement motion value is compared with the preset faceplate displacement motion value. If the actual faceplate displacement motion value is greater than the preset faceplate displacement motion value, it means that the current displacement is too large, and a processing signal is generated and sent to the early warning processing module.

[0045] The early warning processing module processes each signal received separately, and the specific acquisition method is as follows:

[0046] The input end of the early warning processing module is connected to the output end of the data center, and when it receives the abnormal temperature signal, it obtains the location information of the corresponding aluminum-plastic equipment in real time according to the positioning sensor, and feeds the location information back to the central processing system. The central processing system receives the location information and generates an open command, and sends the open command to the cold air device near the corresponding aluminum-plastic equipment. The cold air device starts the movement state to cool the aluminum-plastic equipment. The current temperature parameters are obtained in real time through the temperature sensor, and the equipment temperature early warning range is obtained. When the temperature drops to the equipment temperature early warning range, a stop command is generated and sent to the cold air device to stop the movement state.

[0047] The pressure signal is received and sent to the central processing system. The central processing system obtains the position information of the corresponding equipment according to the positioning sensor, generates an adjustment instruction and sends it to the corresponding aluminum-plastic equipment and the aluminum-plastic equipment control terminal. The aluminum-plastic equipment control terminal receives the adjustment instruction and adjusts the operating speed of the current aluminum-plastic equipment.

[0048] The processing signal is received and sent to the central processing system. The central processing system receives the processing signal to obtain the movement state of the corresponding aluminum-plastic equipment. If it is in the running state, a stop signal is generated and sent to the corresponding aluminum-plastic equipment. The corresponding aluminum-plastic equipment receives the stop signal and stops the current running state. The central processing system sends an early warning signal to the display terminal of the aluminum-plastic equipment. The display terminal receives the early warning signal and sends an audible and visual alarm through a speaker.

[0049] The equipment maintenance module analyzes the maintenance time of the aluminum-plastic equipment according to the information sent by the equipment information entry module, regularly maintains the equipment, and reduces the equipment failure rate. The specific acquisition process is as follows:

[0050] Get the start time of use of each aluminum-plastic equipment and the equipment maintenance cycle, add the start time of use and the equipment maintenance cycle to get each maintenance date, get the current maintenance date, and end with the current date of the system. Difference between the current date and the current maintenance date gets the maintenance value. If the maintenance value is a positive number, take the corresponding aluminum-plastic equipment as the origin, get the mobile terminal positioning of each maintenance personnel within the radius, and connect the positioning of the corresponding aluminum-plastic equipment with the mobile phone positioning of each maintenance personnel to get the straight-line distance of each maintenance, get the nearest straight-line distance and mark the corresponding maintenance personnel as the target personnel, generate a maintenance signal and send it to the target personnel for maintenance.

[0051] The above is an explanation of the present invention and should not be considered as a limitation thereof. Although several exemplary embodiments of the present invention have been described, it will be readily appreciated by those skilled in the art that many modifications may be made to the exemplary embodiments without departing from the novel teachings and advantages of the present invention. Therefore, all such modifications are intended to be included within the scope of the present invention as defined by the claims. It should be understood that the above is an explanation of the present invention and should not be considered as being limited to the specific embodiments disclosed, and modifications to the disclosed embodiments and other embodiments are intended to be included within the scope of the appended claims. The present invention is defined by the claims and their equivalents.

Claims

1. A quality monitoring and feedback system for aluminum-plastic equipment, comprising an equipment information input module, a data acquisition module, a data analysis module, an early warning processing module, an equipment maintenance module and a data center, characterized in that: Also includes displacement analysis module; The displacement analysis module analyzes the displacement parameters of each faceplate sent by the receiving data acquisition module. The output end of the displacement analysis module is connected to the input end of the early warning processing module to analyze the displacement parameters of each faceplate, start the motion state of the aluminum-plastic equipment, obtain the motion time point of the current faceplate motion state, mark it as the initial time point, obtain the faceplate position corresponding to the current initial time point through the photoelectric sensor, mark it as the initial position, obtain the motion time point of the faceplate stop motion state, mark it as the end time point, make a difference between the initial time point and the end time point to obtain the faceplate motion period, mark it as EF, obtain the corresponding faceplate position according to the end time point, mark it as the end position, connect the initial position and the end position corresponding to the faceplate to obtain the corresponding movement distance of the faceplate, mark the movement distance as EK, and use the formula Get the average moving speed ER of the flower disk, divide the flower disk movement period into several flower disk movement time periods {t1, t2, ...., tn}, obtain the speed value {v1, v2, ...., vn} corresponding to each flower disk movement time period, and calculate using the formula Get the flower disc acceleration ET, calculate the flower disc movement period, flower disc movement distance, flower disc acceleration and flower disc average speed, and use the formula The faceplate displacement motion value is obtained, wherein C1, C2, C3 and C4 are preset proportional coefficients, tn represents the speed value of the faceplate in a certain period of time, the preset faceplate displacement motion threshold of the data center is extracted, and the actual faceplate displacement motion value is compared with the preset faceplate displacement motion value. If the actual faceplate displacement motion value is greater than the preset faceplate displacement motion value, a processing signal is generated and sent to the early warning processing module.

2. The aluminum-plastic equipment quality monitoring feedback system according to claim 1 is characterized in that: The data analysis module analyzes the parameter information of the data acquisition module. The specific process is as follows: The input end of the data analysis module is connected to the output end of the data center, and each temperature parameter is analyzed. The acquired temperature parameters and the corresponding acquisition time points are summarized to obtain the acquisition device temperature data set. The device temperature change graph is generated according to the acquisition device temperature data set. The first device temperature warning value and the second device temperature warning value are set in the device temperature change graph. The first device temperature warning value and the second device temperature warning value are subtracted to obtain the device temperature warning range and generate the device warning temperature set. The device warning temperature set is sent to the data center. The maximum temperature value and the minimum temperature value of the corresponding device are obtained according to the device temperature change graph, marked as KL and KG respectively, the acquisition temperature time point corresponding to the maximum temperature value and the acquisition temperature time point corresponding to the minimum temperature value are obtained, the maximum temperature acquisition time point and the minimum temperature acquisition time point are obtained, the maximum temperature acquisition time point and the minimum temperature acquisition time point are subtracted to obtain the maximum temperature difference period, marked as KT, the acquired temperature parameter values ​​are averaged to obtain the temperature average value, marked as KH, the temperature average value, the maximum temperature difference period, the maximum temperature value and the minimum temperature value are calculated using the formula The temperature intervention value is obtained, where B1, B2, B3 and B4 are preset proportional coefficients, j represents the number of a certain device group, and n represents the number of devices corresponding to the device group. The obtained temperature intervention value is compared with the device temperature warning range. If the temperature intervention value is greater than or less than the device temperature warning range, a temperature abnormality signal is generated and sent to the warning processing module; Analyze the pressure parameters, set a preset pressure monitoring time zone, divide the pressure monitoring time zone into several pressure monitoring time zones, obtain the pressure values ​​at all collection moments in the pressure time zone, calculate the mean of each pressure value to get the pressure average value corresponding to the pressure monitoring time zone, calculate the pressure standard deviation value based on the average value, extract the preset pressure standard deviation value of the data center, compare the actual pressure standard deviation value with the preset pressure standard deviation value, and if the actual pressure standard deviation is greater than the preset pressure standard deviation, generate a pressure signal and send it to the early warning processing module.

3. The aluminum-plastic equipment quality monitoring feedback system according to claim 1 is characterized in that: The early warning processing module processes each signal received separately, and the specific method is as follows: The input end of the early warning processing module is connected to the output end of the data center, and after receiving the abnormal temperature signal, the location information of the corresponding aluminum-plastic equipment is obtained in real time according to the positioning sensor, and the location information is fed back to the central processing system. The central processing system receives the location information and generates an opening instruction, and sends the opening instruction to the cold air device near the corresponding aluminum-plastic equipment. The cold air device starts the movement state, cools down the aluminum-plastic equipment, obtains the current temperature parameters in real time through the temperature sensor, obtains the equipment temperature early warning range, and generates a stop instruction to send to the cold air device to stop the movement state when the temperature drops to the equipment temperature early warning range; After receiving the pressure signal, the pressure signal is sent to the central processing system. The central processing system obtains the location information of the corresponding equipment according to the positioning sensor, generates an adjustment instruction and sends it to the corresponding aluminum-plastic equipment and the aluminum-plastic equipment control terminal. The aluminum-plastic equipment control terminal receives the adjustment instruction and adjusts the operating speed of the current aluminum-plastic equipment. The processing signal is received and sent to the central processing system. The central processing system receives the processing signal to obtain the movement state of the corresponding aluminum-plastic equipment. If it is in the running state, a stop signal is generated and sent to the corresponding aluminum-plastic equipment. The corresponding aluminum-plastic equipment receives the stop signal and stops the current running state. The central processing system sends an early warning signal to the display terminal of the aluminum-plastic equipment. The display terminal receives the early warning signal and sends an audible and visual alarm through a speaker.

4. The aluminum-plastic equipment quality monitoring feedback system according to claim 1 is characterized in that: The equipment maintenance module analyzes the maintenance time of the aluminum-plastic equipment according to the information sent by the equipment information entry module, and regularly maintains the equipment. The specific process is as follows: Get the start time of use of each aluminum-plastic equipment and the equipment maintenance cycle, add the start time of use and the equipment maintenance cycle to get each maintenance date, get the current maintenance date, and end with the current date of the system. Difference between the current date and the current maintenance date gets the maintenance value. If the maintenance value is a positive number, take the corresponding aluminum-plastic equipment as the origin, get the mobile terminal positioning of each maintenance personnel within the radius, and connect the positioning of the corresponding aluminum-plastic equipment with the mobile phone positioning of each maintenance personnel to get the straight-line distance of each maintenance, get the nearest straight-line distance and mark the corresponding maintenance personnel as the target personnel, generate a maintenance signal and send it to the target personnel for maintenance.

5. The aluminum-plastic equipment quality monitoring feedback system according to claim 1 is characterized in that: The equipment information input module is used to input the information parameters of each aluminum-plastic equipment into the data center. The specific method is as follows: The output end of the equipment information input module is connected to the input end of the data center to establish the basic information of the equipment. The basic information includes the name of each aluminum-plastic equipment, the start time of use, the equipment maintenance cycle, the number and the location information. The basic information of each aluminum-plastic equipment is sent to the data center for storage. The data center divides the basic information of each aluminum-plastic equipment, marks the same type of equipment as an equipment group, marks each equipment group as j, marks the number of equipment corresponding to each equipment group as n, and merges each equipment group and the corresponding number of equipment into an aluminum-plastic equipment set; The output end of the equipment information input module is connected to the input end of the equipment maintenance module, and the acquired information is sent to the equipment maintenance module.

6. The aluminum-plastic equipment quality monitoring feedback system according to claim 1, characterized in that: The data acquisition module collects the data parameters of each aluminum-plastic equipment in real time according to each sensor. The specific process is as follows: The photoelectric detector and the fixing plate are fixed by lowering 1 cm at the lowest point of the predetermined flower disc lifting process to prevent false information feedback, and the actual position information of the flower disc is monitored in real time by the photoelectric detector, and the displacement parameters of each flower disc are obtained in real time; the temperature sensors are distributed in the heating components and the forming area, and the temperature of each aluminum-plastic equipment during operation is collected in real time by the temperature sensors, and the temperature parameters of each aluminum-plastic equipment are obtained; the pressure sensors are installed at the key parts of the aluminum-plastic equipment, including the mold and the pressing mechanism, and the pressure parameters of each aluminum-plastic equipment during operation in a specific period of time are monitored in real time by the pressure sensors, and the pressure parameters of each aluminum-plastic equipment are obtained; The output end of the acquisition module is connected to the input end of the data analysis module and the image analysis module, and the acquired pressure parameters and temperature parameters are sent to the equipment analysis module, and the displacement parameters of each flower disc are sent to the displacement analysis module.

Images