An intelligent temperature regulation system for plastic processing machinery

Abstract

The invention discloses an intelligent temperature regulating system for a plastic processing machine, which belongs to the technical field of temperature control of plastic processing machines, and comprises an equipment analysis module, a temperature acquisition module, a verification module and a temperature control module; the equipment analysis module is used for analyzing each temperature sensor in the plastic processing machine, and setting a comparison device, wherein the comparison device is used for collecting comparison temperatures at corresponding positions; the temperature acquisition module is used for real-time temperature detection according to each temperature sensor; the verification module is used for verifying the real-time detection temperature of the temperature sensor and obtaining a corresponding verification temperature; the verification temperature is compared with the real-time detection temperature, a detection difference is determined, and corresponding processing is performed according to the detection difference; the temperature control module is used for temperature control of the plastic processing machine, obtaining a corresponding real-time detection temperature, and controlling the temperature of the plastic processing machine according to a preset temperature control scheme according to the real-time detection temperature.

Description

[0001] This application is a divisional application of the application filed on September 19, 2023, with application number 202311205425.1 and invention name “An intelligent temperature control system for plastic processing machinery”. Technical Field

[0002] The invention belongs to the technical field of temperature control of plastic processing machinery, in particular to an intelligent temperature regulating system of plastic processing machinery. Background Art

[0003] Plastic processing is a common industrial manufacturing process involving heating, plasticizing, molding and cooling of thermoplastic materials. Temperature is an important parameter that affects the quality and efficiency of plastic processing. Too high or too low temperature may lead to poor product quality, such as inaccurate dimensions, thermal stress, incomplete plasticization and other problems. Traditional temperature control methods are usually manual control or simple mechanical adjustment, but traditional temperature control methods have many problems, such as complex operation: manual control requires the operator to pay close attention to temperature changes and make manual adjustments, which is prone to operating errors; instability: manual control is affected by human subjective consciousness and operating skills, and the stability of temperature regulation is poor, and temperature fluctuations are prone to occur; limited accuracy: traditional methods often cannot accurately control temperature parameters and cannot meet the requirements of complex processing technology; therefore, in order to improve the quality and efficiency of plastic processing and reduce the impact of human factors on temperature control, intelligent temperature control systems are gradually applied to the plastic processing industry; by using sensors, controllers, actuators and other equipment for real-time temperature monitoring and adjustment, intelligent control of plastic processing is realized.

[0004] However, with the widespread application of intelligent temperature control systems in plastic processing, stability issues have gradually emerged, as follows:

[0005] 1. Temperature data distortion: During the application process, the temperature sensor may fail due to various factors, causing the collected temperature data to be distorted, resulting in abnormal processing during the plastic processing, which is very likely to cause large economic losses.

[0006] 2. Work interruption problem: The intelligent temperature control system requires power supply to operate and control the heating and cooling devices; if the power supply is interrupted, it will cause the temperature control to fail, while certain types of production equipment are still working, resulting in abnormal processing during the plastic processing.

[0007] The above two problems will affect the stability of the intelligent temperature control system. Especially with the continuous development of unmanned factories, the stability problem has become a problem that needs to be solved urgently.

[0008] For example, the Chinese patent application with publication number CN106569519A discloses an intelligent temperature adjustment method, device and system for plastic processing machinery, the system comprising: a processor, a temperature acquisition device, a display device, a communication device, a storage device and a temperature adjustment device; the processor is respectively connected to the communication device, the display device, the temperature acquisition device, the storage device and the connected temperature adjustment device; the storage device is connected to the acquisition device; the communication device is connected to the display device; the plastic processing machinery communicates through the communication device; wherein the storage device is used to store the data collected by the acquisition device and the pre-stored temperature parameters of different types of plastic products. By applying the embodiments of the present invention, the intelligent adjustment of the temperature of the plastic processing machinery is realized.

[0009] The above patent can realize intelligent temperature regulation of plastic processing machinery, but it also has stability problems.

[0010] Therefore, in order to solve the stability problem of the existing intelligent temperature adjustment system during application, the present invention provides an intelligent temperature adjustment system for plastic processing machinery. Summary of the invention

[0011] In order to solve the problems existing in the above solutions, the present invention provides an intelligent temperature regulation system for plastic processing machinery.

[0012] The purpose of the present invention can be achieved through the following technical solutions:

[0013] An intelligent temperature regulation system for plastic processing machinery, comprising an equipment analysis module, a temperature acquisition module, a calibration module and a temperature control module;

[0014] The equipment analysis module is used to analyze each temperature sensor in the plastic processing machinery and set a corresponding comparison device; the comparison device is used to collect the comparison temperature at the corresponding position.

[0015] Furthermore, the setting method of the comparison device includes:

[0016] Identify the installation position of each temperature sensor in the plastic processing machine, and determine the optional installation point of each comparison device corresponding to the temperature sensor according to the setting requirements of the plastic processing machine and the comparison device;

[0017] Based on the candidate combinations corresponding to the optional installation point settings, each candidate combination is evaluated to obtain a target combination; and each comparison device is set according to the target combination.

[0018] Furthermore, the method for evaluating each candidate combination includes:

[0019] Establishing simulation groups corresponding to the selected combinations, and collecting simulation data according to the simulation groups, wherein the simulation data includes the sensor detection temperature, the comparison temperature and the simulated detection temperature;

[0020] Mark the optional installation points in the candidate combination as i, where i=1, 2, ..., n, and n is a positive integer; mark the comparison temperature as Tbi; mark the simulation temperature as Tmi, and calculate the corresponding evaluation value PDS according to the evaluation formula PDS=[∑(|Tbi-Tmi| / Tmi)] / n; obtain several groups of simulation data, evaluate the evaluation value of each group of simulation data, and calculate the corresponding average evaluation value; and so on, calculate the average evaluation value of each candidate combination, and select the candidate combination with the lowest average evaluation value as the target combination.

[0021] The temperature acquisition module is used to perform real-time temperature detection and acquisition according to each temperature sensor.

[0022] The calibration module is used to calibrate the real-time detected temperature of the temperature sensor and establish a calibration model; obtain the comparison temperature collected by the comparison device, analyze the comparison temperature based on the calibration model, and obtain the corresponding calibration temperature;

[0023] The calibration temperature is compared with the real-time detection temperature to determine the detection difference, and corresponding processing is performed according to the detection difference.

[0024] Furthermore, a correction time is set in the verification module, and when the correction time is reached, the verification model is corrected.

[0025] Furthermore, the method for correcting the calibration model includes:

[0026] Correction data is collected, a corresponding correction set is set based on the correction data, and the verification model is corrected based on the correction set.

[0027] The temperature control module is used to perform temperature control on the plastic processing machinery, obtain the corresponding real-time detected temperature, and control the temperature of the plastic processing machinery according to a preset temperature control scheme based on the real-time detected temperature.

[0028] Furthermore, it also includes a power supply module, which is used for performing power supply analysis.

[0029] Furthermore, the working method of the power supply module includes:

[0030] Establishing a supply information database, the supply information database is used to store supply analysis equipment data, the supply analysis equipment data includes supply analysis equipment information, supply analysis objectives, supply methods, estimated effect values ​​and estimated costs;

[0031] Identify the user's plastic processing machinery information, input the plastic processing machinery information into the supply information database for matching, and determine the supply analysis equipment; identify the supply analysis target of the supply analysis equipment, and set corresponding application modes to be selected based on the supply analysis target;

[0032] The candidate application modes are screened to obtain a target application mode, and the supply analysis device is adjusted according to the target application mode.

[0033] Furthermore, the method for screening the application modes to be selected includes:

[0034] Identify the estimated effect value and the estimated cost of each of the selected application modes, and mark the estimated effect value and the estimated cost as XG and CB respectively;

[0035] The corresponding priority value YB is calculated according to the priority formula YB=c1×XG-c2×CB, where c1 and c2 are corresponding weight coefficients; the candidate application mode with the highest priority value is marked as the target application mode.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] Through the cooperation among the equipment analysis module, temperature acquisition module, verification module and temperature control module, the intelligent control of the temperature of the plastic processing machinery is realized, and the stability of the intelligent temperature regulation system is enhanced, so as to solve the stability problem of the current intelligent temperature regulation system caused by the distortion of temperature data; it is simple and easy to use, which is convenient for users to improve the existing plastic processing machinery used in it, realize the optimization of the existing plastic processing machinery and increase its working stability.

[0038] By setting up a power supply module, the power supply of the intelligent temperature control system can be guaranteed and potential stability problems caused by work interruptions can be solved; at the same time, it is convenient to optimize the system on the user side, avoiding problems that are difficult for users to analyze and implement. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0041] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] like Figure 1 As shown, an intelligent temperature regulation system for plastic processing machinery includes an equipment analysis module, a temperature acquisition module, a calibration module, a temperature control module and a power supply module;

[0043] The equipment analysis module is used to analyze the temperature sensors in the current plastic processing machinery, set corresponding comparison equipment, and calibrate the temperature sensors through the comparison equipment to determine whether the temperature sensors have abnormal problems; wherein the comparison equipment is a device that can change with temperature according to existing technologies and existing materials, such as using a thermosensitive coating for setting, which is a specially designed existing coating material whose color or color intensity changes at different temperatures; using a liquid crystal temperature indicator for setting, which is a device that uses liquid crystal materials to display different colors at different temperatures; the liquid crystal temperature indicator usually includes a liquid crystal layer and a temperature sensor, and when the temperature changes, the crystal structure of the liquid crystal material also changes, resulting in a change in color; it can also be set according to the temperature sensor.

[0044] Specifically, the comparison equipment can be set according to the changes in actual related technologies, actual comparison and verification requirements and costs; that is, it is not limited, but for the comparison equipment set up by using thermal sensitive coatings, etc., because the corresponding temperature cannot be obtained directly, a corresponding recognition model can be set to compare and match the temperature corresponding to its standard color to determine the corresponding temperature, that is, for the comparison equipment that cannot read the temperature directly, it is necessary to set up a recognition model to realize temperature collection; exemplarily, the recognition model can be established based on a CNN network or a DNN network, and a corresponding training set is established manually, and the training set includes comparison equipment of various colors (according to different forms of temperature expression) and corresponding set temperatures; the temperature is identified by the recognition model after successful training.

[0045] Because the existing plastic processing machinery equipped with an intelligent temperature control system is already a finalized equipment when it arrives at the customer's site, it is necessary to ensure its stability without major changes.

[0046] The detailed working mode of the equipment analysis module is as follows:

[0047] Identify the installation position of each temperature sensor in the plastic processing machinery, and determine the optional installation point of the comparison device corresponding to each temperature sensor according to the setting requirements of the plastic processing machinery and the comparison device; that is, determine which positions in the plastic processing machinery can be installed with the comparison device corresponding to the temperature sensor according to the structure, working mode and installation requirements of the actual plastic processing machinery, and quickly determine the positions corresponding to the temperature sensor where the corresponding comparison device can be set up manually, such as first determining which areas can be set up with the comparison device according to the actual situation of the plastic processing machinery, and then determining the corresponding optional installation points according to the installation requirements of the comparison device, such as distance range requirements, multi-component isolation requirements, etc. The specific installation requirements need to be set according to the actual comparison device; it is faster and more cost-effective to manually determine the optional installation points of the comparison device corresponding to each temperature sensor; if the density is high, one comparison device can correspond to multiple temperature sensors.

[0048] Corresponding candidate combinations are formed according to the optional installation points corresponding to the temperature sensors, that is, the optional installation points that can be selected by each temperature sensor are arranged and combined to form various candidate combinations. For example, there are two sensors A and B, sensor A has 1 and 2 optional installation points, and sensor B has 1 and 2 optional installation points, then the candidate combinations are 11, 12, 21, and 22.

[0049] Each candidate combination is evaluated to obtain a target combination, and each comparison device is set according to the target combination.

[0050] The method for evaluating each candidate combination includes:

[0051] Establish a simulation group corresponding to each candidate combination. The simulation group is to install the comparison equipment on the corresponding optional installation point according to the corresponding candidate combination. When the plastic processing machinery is working, obtain the sensing detection temperature detected by the temperature sensor, the comparison temperature collected by the comparison equipment and the simulation detection temperature. The simulation detection temperature is the temperature detected by the existing precise temperature detection equipment at the corresponding optional installation point, and is collected at the same time as the comparison temperature. Perform simulation data collection according to the simulation group. The simulation data includes the sensing detection temperature, the comparison temperature and the simulation detection temperature.

[0052] Mark the optional installation points in the candidate combination as i, where i=1, 2, ..., n, where n is a positive integer; mark the comparison temperature as Tbi; mark the simulation temperature as Tmi, and calculate the corresponding evaluation value PDS according to the evaluation formula PDS=[∑(|Tbi-Tmi| / Tmi)] / n; obtain several groups of simulation data within a period of time, evaluate several groups of evaluation values, calculate the average of the obtained evaluation values, and mark it as the average evaluation value; and so on, calculate the average evaluation value of each candidate combination, and select the candidate combination with the lowest average evaluation value as the target combination.

[0053] The temperature acquisition module is used to perform real-time temperature detection and acquisition according to each temperature sensor.

[0054] The verification module is used to verify the real-time detection temperature of the temperature sensor, obtain the simulation data of the target combination, and establish a corresponding training set according to the obtained simulation data, the training set includes the comparison temperature, the simulation detection temperature and the sensor detection temperature, that is, in the subsequent analysis process, the corresponding simulation detection temperature is calculated according to the comparison temperature, and then the sensor detection temperature is calculated according to the simulation detection temperature; a corresponding verification model is established according to a CNN network or a DNN network, and training is performed through the established training set. The comparison temperature is analyzed by the verification model after successful training to obtain the corresponding verification temperature, and the verification temperature is the corresponding sensor detection temperature of the analysis; because the neural network is a prior art in this field, the specific establishment and training process is not described in detail in the present invention;

[0055] The calibration model can also be an intelligent model established using other existing technologies; the obtained calibration temperature is compared with the real-time detection temperature of the temperature sensor, and the detection difference is determined, and the corresponding temperature sensor processing is performed according to whether the detection difference is within the allowable range; including marking abnormal problem sensors, no operation when there is no problem, corresponding detection temperature correction and other processing; the detection temperature correction operation is only an emergency measure, and the staff needs to deal with the abnormal temperature sensor in time.

[0056] In one embodiment, as time goes by, the calibration temperature error may become larger. Therefore, the calibration model can be corrected regularly, that is, correction data can be collected within the corresponding time. The correction data can be the comparison temperature and the collected simulation temperature for correction. The collected simulation temperature corrects the simulation temperature calculated based on the comparison temperature, thereby correcting the calibration temperature. This correction can be performed during the operation of the plastic processing machinery. Another correction method is to simulate during the stoppage of the plastic processing machinery, collect the simulation temperature and the calibration temperature, and correct the simulation temperature and the calibration temperature calculated based on the comparison temperature through the collected simulation temperature and the calibration temperature, thereby correcting the calibration model. The specific correction time can be set by the corresponding management personnel and is not fixed. A corresponding correction set is established based on the correction data, and the calibration model is corrected through the correction set.

[0057] The temperature control module is used to control the temperature of the plastic processing machinery. A corresponding temperature control scheme is preset. The temperature control scheme is to control the corresponding temperature within an allowable range at the corresponding stage and is set according to the temperature control method of the current plastic processing machinery; the corresponding real-time detection temperature is obtained, and the temperature of the plastic processing machinery is controlled according to the obtained real-time detection temperature and the temperature control scheme.

[0058] Through the cooperation among the equipment analysis module, temperature acquisition module, verification module and temperature control module, the intelligent control of the temperature of the plastic processing machinery is realized, and the stability of the intelligent temperature regulation system is enhanced, so as to solve the stability problem of the current intelligent temperature regulation system caused by the distortion of temperature data; it is simple and easy to use, which is convenient for users to improve the existing plastic processing machinery used in it, realize the optimization of the existing plastic processing machinery and increase its working stability.

[0059] The power supply module is used to perform power supply analysis. It analyzes the actual situation of each plastic processing machine. First, it analyzes whether the plastic processing machine needs power supply guarantee. If not, there is no need to modify or optimize it, so as to reduce costs and avoid unnecessary efforts. If the analysis shows that power supply guarantee is needed, the appropriate supply method is determined according to the information of the plastic processing machine. Different plastic processing machines may have different applicable supply methods, such as using backup power supply, energy storage technology, etc. Energy storage technology, such as supercapacitors or energy storage systems, is used to store electricity for use. In this way, when the power supply is interrupted, the system can use energy storage equipment to provide power to maintain the necessary temperature control. In order to distinguish and explain, the intelligent temperature control system to be analyzed is marked as the target to be analyzed, and the intelligent temperature control system that determines the power supply setting is marked as the supply analysis target.

[0060] Here’s how it works:

[0061] According to various plastic processing machinery currently on the market, plastic processing machinery that needs to be analyzed for power supply is determined and marked as supply analysis equipment. Various intelligent temperature control systems that may be equipped with the supply analysis equipment are analyzed, and various supply methods that can be applied to the intelligent temperature control system and the corresponding estimated effect values ​​and estimated costs are set. The estimated effect value is set according to the percentage system and is set according to the power supply effect that can be achieved. If the full power supply can be guaranteed and there is no adverse effect on the plastic processing machinery, the estimated effect value is 100, otherwise it will gradually decrease; all are evaluated and set manually, that is, various types of supply analysis equipment are obtained manually, and in the process of determining the supply analysis equipment, the various supply methods, estimated effect values ​​and estimated costs that can be applied are set; after sorting, the data of each supply analysis equipment is formed, including supply analysis equipment information, supply analysis target (intelligent temperature control system), various supply methods, estimated effect values ​​and estimated costs;

[0062] Establish a supply information base based on the data of each supply analysis device; and update the supply database.

[0063] Identify the user's plastic processing machinery information, input the plastic processing machinery information into the supply information database for matching, and when no supply analysis equipment data is matched, determine that the corresponding plastic processing machinery does not need to be subjected to supply analysis; when the supply analysis equipment data is matched, mark the corresponding plastic processing machinery as supply analysis equipment; identify the supply analysis target of the supply analysis equipment, determine the various supply methods that can be applied to the supply analysis equipment, and mark them as candidate application methods; identify the estimated effect value and estimated cost of each candidate application method, and mark them as XG and CB respectively; obtain the weight coefficients set by the user for the estimated effect value and estimated cost, and mark them as c1 and c2 respectively;

[0064] Remove the dimension and take its numerical calculation, calculate the corresponding priority value YB according to the priority formula YB=c1×XG-c2×CB, select the candidate application method with the highest priority value as the target application method, and adjust the supply analysis equipment according to the target application method.

[0065] By setting up a power supply module, the power supply of the intelligent temperature control system can be guaranteed and potential stability problems caused by work interruptions can be solved; at the same time, it is convenient to optimize the system on the user side, avoiding problems that are difficult for users to analyze and implement.

[0066] The above formulas are all calculated by removing dimensions and taking numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data.

[0067] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An intelligent temperature control system for plastic processing machinery, characterized in that: It includes equipment analysis module, temperature acquisition module, calibration module and temperature control module; The equipment analysis module is used to analyze each temperature sensor in the plastic processing machinery and set a comparison device, which is used to collect the comparison temperature at the corresponding position; The temperature acquisition module is used to perform real-time temperature detection and acquisition according to each temperature sensor; The calibration module is used to calibrate the real-time detected temperature of the temperature sensor and establish a calibration model; obtain the comparison temperature collected by the comparison device, analyze the comparison temperature based on the calibration model, and obtain the corresponding calibration temperature; Compare the calibration temperature with the real-time detection temperature to determine a detection difference, and perform corresponding processing according to the detection difference; The temperature control module is used to control the temperature of the plastic processing machinery, obtain the corresponding real-time detection temperature, and control the temperature of the plastic processing machinery according to the real-time detection temperature according to a preset temperature control scheme; The setup methods for the comparison device include: Identify the installation position of each temperature sensor in the plastic processing machine, and determine the optional installation point of each comparison device corresponding to the temperature sensor according to the setting requirements of the plastic processing machine and the comparison device; Based on the candidate combinations corresponding to the optional installation point settings, each candidate combination is evaluated to obtain a target combination; and each comparison device is set according to the target combination; Methods for evaluating each candidate combination include: Establishing simulation groups corresponding to the selected combinations, and collecting simulation data according to the simulation groups, wherein the simulation data includes the sensor detection temperature, the comparison temperature and the simulated detection temperature; Mark the optional installation points in the candidate combination as i, i=1, 2, ..., n, n is a positive integer; mark the comparison temperature as Tbi; mark the simulated detection temperature as Tmi, and calculate the corresponding evaluation value PDS according to the evaluation formula PDS=[∑(|Tbi-Tmi| / Tmi)] / n; obtain several groups of simulation data, evaluate the evaluation value of each group of simulation data, and calculate the corresponding average evaluation value; and so on, calculate the average evaluation value of each candidate combination, and select the candidate combination with the lowest average evaluation value as the target combination; A correction time is set in the verification module. When the correction time is reached, the verification model is corrected. The method for correcting the verification model includes: Collecting correction data, setting a corresponding correction set based on the correction data, and correcting the verification model based on the correction set; It also includes a power supply module, which is used for performing power supply analysis.

2. The intelligent temperature control system for plastic processing machinery according to claim 1, characterized in that: The working method of the power supply module includes: Establishing a supply information database, the supply information database is used to store supply analysis equipment data, the supply analysis equipment data includes supply analysis equipment information, supply analysis objectives, supply methods, estimated effect values ​​and estimated costs; Identify the user's plastic processing machinery information, input the plastic processing machinery information into the supply information database for matching, and determine the supply analysis equipment; identify the supply analysis target of the supply analysis equipment, and set corresponding application modes to be selected based on the supply analysis target; The candidate application modes are screened to obtain a target application mode, and the supply analysis device is adjusted according to the target application mode.

3. The intelligent temperature control system for plastic processing machinery according to claim 2, characterized in that: Methods for selecting applications include: Identify the estimated effect value and the estimated cost of each of the selected application modes, and mark the estimated effect value and the estimated cost as XG and CB respectively; The corresponding priority value YB is calculated according to the priority formula YB=c1×XG-c2×CB, where c1 and c2 are corresponding weight coefficients; the candidate application mode with the highest priority value is marked as the target application mode.

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