A casting process measurement and control system based on cloud computing

Abstract

The present invention discloses a casting process measurement and control system based on cloud computing, comprising a data acquisition module, a process control module and a mold detection module, characterized in that: the data acquisition module is used to collect equipment operation data and visual images and temperatures of castings, and enter comprehensive parameters of castings to be produced into the system; the process control module is used to analyze the visual images and temperatures of castings, further analyze the operation parameters of the equipment, and adjust the operation parameters of the equipment according to the analysis results; the mold detection module is used to analyze the comprehensive parameters of castings, select raw materials and make corresponding casting molds according to the analysis results; the data acquisition module, the process control module and the mold detection module are electrically connected to each other; the data collection module comprises a sensor module, a visual module and a casting comprehensive parameter entry module; the sensor module is used to collect equipment operation data; the present invention has the characteristics of high accuracy and high production efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of casting technology, and in particular to a casting process measurement and control system based on cloud computing. Background Art

[0002] With the rapid development of information technology and automation technology in the industrial field, my country's manufacturing industry is gradually transforming towards digitalization and automation.

[0003] At present, casting is a commonly used manufacturing method in the parts processing industry because of its low manufacturing cost, great process flexibility, and the ability to obtain complex shapes and large castings. Some parts are still processed using casting technology. However, due to the large number of processes and complex influencing factors in the casting method, most existing technologies rely on the experience of technicians to adjust the operating parameters of the equipment, and are unable to accurately analyze the impact of various factors on the quality of castings, resulting in poor accuracy in the regulation of casting process parameters and more casting defects. Moreover, manual inspection cannot detect equipment failures in a timely manner, resulting in defects in a large number of castings, which require recasting, wasting a lot of time, and low production efficiency. Therefore, it is very necessary to design a casting process measurement and control system based on cloud computing with high design accuracy and high production efficiency. Summary of the invention

[0004] The purpose of the present invention is to provide a casting process measurement and control system based on cloud computing to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a casting process measurement and control system based on cloud computing, comprising a data acquisition module, a process control module and a mold detection module, characterized in that: the data acquisition module is used to collect real-time equipment operation data and visual images and temperatures of castings, and enter the comprehensive parameters of castings to be produced into the system; the process control module is used to analyze the visual images and temperatures of castings, further analyze the operation parameters of the equipment, and adjust the operation parameters of the equipment according to the analysis results; the mold detection module is used to analyze the comprehensive parameters of castings, select raw materials and make corresponding casting molds according to the analysis results, and the data acquisition module, process control module and mold detection module are electrically connected to each other;

[0006] The casting detection module includes a temperature analysis submodule and a casting detection submodule. The temperature analysis submodule is used to analyze the heating temperature change of the casting raw material and the cooling temperature change of the casting after casting, and adjust the temperature of the equipment according to the analysis results. The casting detection submodule is used to identify the defects of the casting and analyze the causes of the defects of the casting, and then adjust the operating parameters and casting process of the equipment according to the analysis results.

[0007] The equipment control module includes a pouring speed control submodule, a temperature control submodule and a processing control submodule. The pouring speed control submodule is used to calculate the pouring speed of the pouring equipment according to the analysis results of the mold structure. The temperature control submodule is used to analyze the metal thermal conductivity inertia of the metal material and control the heating temperature and heating time of the equipment according to the analysis results. The processing control submodule is used to analyze whether the casting defects meet the production standards of the casting after processing, and determine whether the casting needs to be recast according to the analysis results.

[0008] According to the above technical solution, the data collection module includes a sensor module, a visual module and a casting comprehensive parameter entry module. The sensor module is used to collect the operation data of the casting equipment and the comprehensive data of the casting in real time. The visual module is used to capture the visual image of the casting and the visual image of the pouring equipment pouring the molten metal. The casting comprehensive parameter entry module is used to enter the comprehensive parameters of the casting to be cast into the system.

[0009] According to the above technical solution, the process control module includes a casting detection module, which is used to analyze the temperature of the casting and the mold during the casting process, identify and analyze the defects of the casting, and then analyze the causes of the casting defects.

[0010] According to the above technical solution, the process control module also includes an equipment control module, which is used to analyze the pouring speed, heating temperature and grinding and cutting method, and control the operating parameters of the equipment according to the analysis results.

[0011] According to the above technical solution, the mold detection module includes a casting parameter analysis module and a mold structure analysis module. The casting parameter analysis module is used to analyze the parameter characteristics of the casting and then select the corresponding casting processing material and mold material. The mold structure analysis module is used to analyze the internal structure of the casting mold.

[0012] According to the above technical solution, the operation method of the casting process measurement and control system mainly includes the following steps:

[0013] Step S1: using the sensor module to collect the operation data of the casting equipment and the comprehensive data of the casting in real time, using the visual module to capture the visual image of the casting and the visual image of the pouring equipment pouring the molten metal, and using the casting comprehensive parameter input module to input the comprehensive parameters of the casting to be cast into the system;

[0014] Step S2: After the data collection is completed, the system starts the mold analysis module, starts to analyze the comprehensive parameters of the casting and the structure of the mold, and selects the casting raw material and mold according to the analysis results;

[0015] Step S3: During the casting process, the system starts the equipment control module, starts to analyze the metal characteristics of the casting raw materials, controls the heating temperature and heating time according to the metal properties, and adjusts the pouring speed according to the mold structure;

[0016] Step S4: After pouring is completed, the detection module is gradually started to analyze the temperature of the casting, adjust the cooling temperature of the casting according to the gradual temperature change and the metal characteristics of the casting raw materials, analyze the visual image of the casting, and process the casting to obtain the target casting.

[0017] According to the above technical solution, in step S2, comprehensive parameters of the casting are obtained, dimensional parameter characteristics of the casting are identified, a mold model is constructed according to the dimensional parameter characteristics of the casting, channel characteristic nodes for pouring molten metal in the mold model are identified, characteristic nodes are identified, a coordinate system is established, and the distance L between the characteristic nodes is calculated by a distance formula. If the distance L is less than the minimum threshold, the number of distances less than the minimum threshold is identified, and the corresponding pouring speed influence coefficient α in the database is retrieved according to the number of distances less than the minimum threshold. If the distance L is greater than the minimum threshold and less than the maximum threshold, the corresponding number of distances is identified, and the corresponding pouring speed influence coefficient β in the database is retrieved according to the number of distances. If the distance L is greater than the maximum threshold, the system continues to detect.

[0018] According to the above technical solution, step S3 further includes the following steps:

[0019] Step S31: Identify the material of the casting, retrieve the corresponding metal features in the database according to the material of the casting, identify the metal features, and retrieve the corresponding casting shrinkage coefficient in the database according to the metal features Calculate the dimensional parameters of the casting before cooling by formula In the formula, K represents the dimensional parameter of the casting before cooling, R represents the actual dimensional parameter of the target casting, and the control system adjusts the mold model according to the dimensional parameter K;

[0020] Step S32: Identify the metal characteristics of the casting raw material, identify the temperature of the current device, retrieve the heat conversion rate η between the corresponding device and the casting raw material in the database according to the temperature of the device and the metal characteristics of the casting material, if the energy conversion rate is less than the threshold, continue to heat the device, otherwise add raw materials to the device, retrieve the historical heating records of the device, calculate the average power of the device, and calculate the heating time of the casting raw material by the formula In the formula, T0 represents the heating time of the casting raw material, M represents the weight of the heated casting raw material, c represents the specific heat capacity of the casting raw material, t0 represents the temperature of the casting raw material before heating, t1 represents the heating temperature required for the casting raw material, and P1 represents the average power of the equipment;

[0021] Step S33: Calculate the melting rate of the casting raw material by formula In the formula, V represents the melting speed of the casting raw material. If the melting speed of the casting raw material is greater than the maximum threshold or less than the minimum threshold, the corresponding optimal melting speed in the database is retrieved, and the optimal heating power of the equipment is calculated according to the formula Wherein, κ represents the calculated error coefficient, and the device is controlled to heat according to the calculated optimal heating power of the device, otherwise the device is controlled to heat the casting raw material according to the average power of the device.

[0022] According to the above technical solution, step S33 further includes the following steps:

[0023] Step S331: obtaining cooling temperature data of the casting mold, identifying the temperature value and the corresponding timestamp, drawing a temperature change line graph according to the temperature value and the corresponding timestamp, identifying the temperature change characteristics under adjacent timestamps, and predicting the temperature of the casting mold according to the temperature change characteristics;

[0024] Step S332: Identify the timestamp of the predicted temperature and compare it with the database. If the temperature is less than the threshold, the heat conduction coefficient μ and the heat loss coefficient λ of the corresponding mold in the database are retrieved, and the heat loss of the mold is calculated by the formula Q=m·c|t3-t2|, where m represents the weight of the molten metal in the mold, t2 represents the temperature standard of the mold at the target timestamp, and t3 represents the predicted temperature of the mold at the target timestamp. The heating power of the equipment to the mold is calculated by the formula Where P2 represents the heating power of the equipment to the mold, m represents the weight of the molten metal in the mold, and T1 represents the time between the timestamp of the most recent predicted normal value of the mold temperature and the target timestamp. The timestamp of the most recent predicted normal value of the mold temperature is identified, and at this time, the equipment is controlled to heat the mold according to the calculated heating power. Otherwise, the system continues to detect.

[0025] According to the above technical solution, in step S4, the detection data of the casting is obtained, compared with the database, the abnormal data is anchored, the corresponding casting defect type in the database is retrieved according to the abnormal data, and the mark in the casting defect type is identified. If it is a repairable mark, the visual image of the casting is identified, the gradual defect position is anchored, and the system performs grinding and cutting to obtain a casting that meets the conditions. Otherwise, the casting is transferred to the equipment furnace for re-melting and recasting.

[0026] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention can accurately control the pouring speed of the molten metal by analyzing the diameter distance of the channel for pouring the molten metal in the mold model, avoid pouring too fast, resulting in the molten metal being unable to completely fill the mold, resulting in defects in the casting, greatly improving the accuracy of the system and the quality of the casting; by analyzing the metal characteristics of the material of the casting, and then controlling and adjusting the mold model parameters, it is possible to avoid the production of castings with unqualified dimensions, avoid wasting time adjusting the mold parameters, and further improve production efficiency; by analyzing the relationship between the temperature of the equipment and the heat conversion, the equipment can be operated at the optimal heat conversion efficiency, thereby improving energy utilization and reducing costs. By analyzing whether the melting speed of the casting raw materials meets the standards, it is possible to avoid the melting speed of the casting raw materials being too fast or too slow, accurately control the heating power of the equipment, greatly improve the accuracy of the system, and enable the equipment to shorten the heating time while meeting the casting standards, further improve production efficiency. By analyzing the temperature change characteristics during mold cooling and predicting the temperature of the mold, the mold can be heated when the temperature does not meet the standards during the mold cooling process, thereby reducing the defect rate of the casting and improving the quality of the casting. By analyzing the heat lost when the mold temperature is cooled to the standard value, the mold can be accurately compensated for heat to avoid the temperature not meeting the standards during the mold cooling process, further improving the accuracy of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0028] Figure 1 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] See also Figure 1, the present invention provides a technical solution: a casting process measurement and control system based on cloud computing, including a data acquisition module, a process control module and a mold detection module, characterized in that: the data acquisition module is used to collect real-time equipment operation data and visual images and temperatures of castings, and enter the comprehensive parameters of castings to be produced into the system, the process control module is used to analyze the visual images and temperatures of castings, further analyze the operation parameters of the equipment, and adjust the operation parameters of the equipment according to the analysis results, the mold detection module is used to analyze the comprehensive parameters of castings, select raw materials and make corresponding casting molds according to the analysis results, and the data acquisition module, the process control module and the mold detection module are electrically connected to each other;

[0031] The casting detection module includes a temperature analysis submodule and a casting detection submodule. The temperature analysis submodule is used to analyze the heating temperature change of the casting raw material and the cooling temperature change of the casting after casting, and adjust the temperature of the equipment according to the analysis results. The casting detection submodule is used to identify the defects of the casting and analyze the causes of the defects of the casting, and then adjust the operating parameters of the equipment and the casting process according to the analysis results.

[0032] The equipment control module includes a pouring speed control submodule, a temperature control submodule and a processing control submodule. The pouring speed control submodule is used to calculate the pouring speed of the pouring equipment according to the analysis results of the mold structure. The temperature control submodule is used to analyze the metal thermal conductivity inertia of the metal material and control the heating temperature and heating time of the equipment according to the analysis results. The processing control submodule is used to analyze whether the casting defects meet the production standards of the casting after processing, and determine whether the casting needs to be recast according to the analysis results.

[0033] The data collection module includes a sensor module, a vision module and a casting comprehensive parameter entry module. The sensor module is used to collect the operation data of the casting equipment and the comprehensive data of the casting in real time. The vision module is used to take the visual image of the casting and the visual image of the pouring equipment pouring the molten metal. The casting comprehensive parameter entry module is used to enter the comprehensive parameters of the casting to be cast into the system.

[0034] The process control module includes a casting detection module, which is used to analyze the temperature of the casting and the mold during the casting process, identify and analyze the defects of the casting, and then analyze the causes of the casting defects.

[0035] The process control module also includes an equipment control module, which is used to analyze the pouring speed, heating temperature and grinding and cutting methods, and control the operating parameters of the equipment according to the analysis results.

[0036] The mold detection module includes a casting parameter analysis module and a mold structure analysis module. The casting parameter analysis module is used to analyze the parameter characteristics of the casting and then select the corresponding casting processing materials and mold materials. The mold structure analysis module is used to analyze the internal structure of the casting mold.

[0037] The operation method of the casting process measurement and control system mainly includes the following steps:

[0038] Step S1: using the sensor module to collect the operation data of the casting equipment and the comprehensive data of the casting in real time, using the visual module to capture the visual image of the casting and the visual image of the pouring equipment pouring the molten metal, and using the casting comprehensive parameter input module to input the comprehensive parameters of the casting to be cast into the system;

[0039] Step S2: After the data collection is completed, the system starts the mold analysis module, starts to analyze the comprehensive parameters of the casting and the structure of the mold, and selects the casting raw material and mold according to the analysis results;

[0040] Step S3: During the casting process, the system starts the equipment control module, starts to analyze the metal characteristics of the casting raw materials, controls the heating temperature and heating time according to the metal properties, and adjusts the pouring speed according to the mold structure;

[0041] Step S4: After pouring is completed, the detection module is gradually started to analyze the temperature of the casting, adjust the cooling temperature of the casting according to the gradual temperature change and the metal characteristics of the casting raw materials, analyze the visual image of the casting, and process the casting to obtain the target casting.

[0042] In step S2, comprehensive parameters of the casting are obtained, the dimensional parameter characteristics of the casting are identified, a mold model is constructed according to the dimensional parameter characteristics of the casting, characteristic nodes of the channel for pouring molten metal in the mold model are identified, characteristic nodes are identified, a coordinate system is established, and the distance L between the characteristic nodes is calculated by a distance formula. If the distance L is less than a minimum threshold, the number of distances less than the minimum threshold is identified, and the corresponding pouring speed influence coefficient α in the database is retrieved according to the number of distances less than the minimum threshold. If the distance L is greater than the minimum threshold and less than the maximum threshold, the corresponding number of distances is identified, and the corresponding pouring speed influence coefficient β in the database is retrieved according to the number of distances. If the distance L is greater than the maximum threshold, the system continues to detect, and by analyzing the diameter distance of the channel for pouring molten metal in the mold model, the pouring speed of the molten metal can be accurately controlled to avoid excessive pouring speed, which causes the molten metal to be unable to completely fill the mold, resulting in defects in the casting, thereby greatly improving the accuracy of the system and the quality of the casting.

[0043] Step S3 further comprises the following steps:

[0044] Step S31: Identify the material of the casting, retrieve the corresponding metal features in the database according to the material of the casting, identify the metal features, and retrieve the corresponding casting shrinkage coefficient in the database according to the metal features Calculate the dimensional parameters of the casting before cooling by formula In the formula, K represents the dimensional parameter of the casting before cooling, and R represents the actual dimensional parameter of the target casting. The control system adjusts the mold model according to the dimensional parameter K. By analyzing the metal characteristics of the casting material, the mold model parameters are controlled and adjusted, which can avoid the production of unqualified castings and waste time adjusting mold parameters, thereby further improving production efficiency.

[0045] Step S32: Identify the metal characteristics of the casting raw material, identify the temperature of the current device, retrieve the heat conversion rate η between the corresponding device and the casting raw material in the database according to the temperature of the device and the metal characteristics of the casting material, if the energy conversion rate is less than the threshold, continue to heat the device, otherwise add raw materials to the device, retrieve the historical heating records of the device, calculate the average power of the device, and calculate the heating time of the casting raw material by the formula In the formula, T0 represents the heating time of the casting raw material, M represents the weight of the heated casting raw material, c represents the specific heat capacity of the casting raw material, t0 represents the temperature of the casting raw material before heating, t1 represents the heating temperature required for the casting raw material, and P1 represents the average power of the equipment. By analyzing the relationship between the temperature and heat conversion of the equipment, the equipment can be operated at the optimal heat conversion efficiency, thereby improving energy utilization and reducing costs;

[0046] Step S33: Calculate the melting rate of the casting raw material by formula In the formula, V represents the melting speed of the casting raw material. If the melting speed of the casting raw material is greater than the maximum threshold or less than the minimum threshold, the corresponding optimal melting speed in the database is retrieved, and the optimal heating power of the equipment is calculated according to the formula In the formula, κ represents the calculated error coefficient. The equipment is controlled to heat according to the calculated optimal heating power of the equipment. Otherwise, the equipment is controlled to heat the casting raw materials according to the average power of the equipment. By analyzing whether the melting speed of the casting raw materials meets the standards, it is possible to avoid the melting speed of the casting raw materials being too fast or too slow, accurately control the heating power of the equipment, greatly improve the accuracy of the system, and enable the equipment to shorten the heating time while meeting the casting standards, thereby further improving production efficiency.

[0047] Step S33 further includes the following steps:

[0048] Step S331: obtaining cooling temperature data of the casting mold, identifying the temperature value and the corresponding timestamp, drawing a temperature change line graph according to the temperature value and the corresponding timestamp, identifying the temperature change characteristics under adjacent timestamps, and predicting the temperature of the casting mold according to the temperature change characteristics;

[0049] Step S332: Identify the timestamp of the predicted temperature and compare it with the database. If the temperature is less than the threshold, the heat conduction coefficient μ and the heat loss coefficient λ of the corresponding mold in the database are retrieved, and the heat loss of the mold is calculated by the formula Q=m·c|t3-t2|, where m represents the weight of the molten metal in the mold, t2 represents the temperature standard of the mold at the target timestamp, and t3 represents the predicted temperature of the mold at the target timestamp. The heating power of the equipment to the mold is calculated by the formula Wherein, P2 represents the heating power of the equipment to the mold, m represents the weight of the molten metal in the mold, T1 represents the time between the timestamp of the most recent predicted normal value of the mold temperature and the target timestamp, and the timestamp of the most recent predicted normal value of the mold temperature is identified. At this time, the equipment is controlled to heat the mold according to the calculated heating power, otherwise the system continues to detect, and the temperature of the mold is predicted by analyzing the temperature change characteristics during mold cooling. When the temperature does not meet the standard during the mold cooling process, the mold can be heated, thereby reducing the defect rate of the casting and improving the quality of the casting. By analyzing the heat lost when the mold temperature is cooled to the standard value, the heat compensation of the mold can be accurately performed to avoid the temperature not meeting the standard during the mold cooling process, further improving the accuracy of the system.

[0050] In step S4, the inspection data of the casting is obtained, compared with the database, and the abnormal data is anchored. The corresponding casting defect type in the database is retrieved according to the abnormal data, and the mark in the casting defect type is identified. If it is a repairable mark, the visual image of the casting is identified, and the gradual defect position is anchored. The system performs grinding and cutting to obtain a casting that meets the conditions. Otherwise, the casting is transferred to the equipment furnace for re-melting and recasting.

[0051] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0052] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A casting process measurement and control system based on cloud computing, including a data acquisition module, a process control module and a mold detection module, characterized in that: The data acquisition module is used to collect real-time equipment operation data and visual images and temperatures of castings, and enter the comprehensive parameters of castings to be produced into the system; the process control module is used to analyze the visual images and temperatures of castings, further analyze the operation parameters of the equipment, and adjust the operation parameters of the equipment according to the analysis results; the mold detection module is used to analyze the comprehensive parameters of castings, select raw materials and make corresponding casting molds according to the analysis results, and the data acquisition module, the process control module and the mold detection module are electrically connected to each other; The process control module includes a casting detection module, which is used to analyze the temperature of the casting and the mold during the casting process, identify and analyze the defects of the casting, and then analyze the causes of the casting defects; The process control module also includes an equipment control module, which is used to analyze the pouring speed, heating temperature and grinding and cutting method, and control the operating parameters of the equipment according to the analysis results; The casting detection module includes a temperature analysis submodule and a casting detection submodule. The temperature analysis submodule is used to analyze the heating temperature change of the casting raw material and the cooling temperature change of the casting after casting, and adjust the temperature of the equipment according to the analysis results. The casting detection submodule is used to identify the defects of the casting and analyze the causes of the defects of the casting, and then adjust the operating parameters and casting process of the equipment according to the analysis results. The equipment control module includes a pouring speed control submodule, a temperature control submodule and a processing control submodule. The pouring speed control submodule is used to calculate the pouring speed of the pouring equipment according to the analysis results of the mold structure. The temperature control submodule is used to analyze the metal thermal conductivity inertia of the metal material and control the heating temperature and heating time of the equipment according to the analysis results. The processing control submodule is used to analyze whether the casting defects meet the production standards of the casting after processing, and determine whether the casting needs to be recast according to the analysis results. The operation method of the casting process measurement and control system mainly includes the following steps: Step S1: using the sensor module to collect the operation data of the casting equipment and the comprehensive data of the casting in real time, using the visual module to capture the visual image of the casting and the visual image of the pouring equipment pouring the molten metal, and using the casting comprehensive parameter input module to input the comprehensive parameters of the casting to be cast into the system; Step S2: After the data collection is completed, the system starts the mold analysis module, starts to analyze the comprehensive parameters of the casting and the structure of the mold, and selects the casting raw material and mold according to the analysis results; Step S3: During the casting process, the system starts the equipment control module, starts to analyze the metal characteristics of the casting raw materials, controls the heating temperature and heating time according to the metal properties, and adjusts the pouring speed according to the mold structure; Step S4: After the pouring is completed, the detection module is gradually started to analyze the temperature of the casting, adjust the cooling temperature of the casting according to the gradual temperature change and the metal characteristics of the casting raw material, analyze the visual image of the casting, and process the casting to obtain the target casting; In the step S2, comprehensive parameters of the casting are obtained, the size parameter characteristics of the casting are identified, a mold model is constructed according to the size parameter characteristics of the casting, channel feature nodes for pouring molten metal in the mold model are identified, feature nodes are identified, a coordinate system is established, and the distance L between the feature nodes is calculated by a distance formula. If the distance L is less than a minimum threshold, the number of distances less than the minimum threshold is identified, and the corresponding pouring speed influence coefficient α in the database is retrieved according to the number of distances less than the minimum threshold. If the distance L is greater than the minimum threshold and less than the maximum threshold, the corresponding number of distances is identified, and the corresponding pouring speed influence coefficient β in the database is retrieved according to the number of distances. If the distance L is greater than the maximum threshold, the system continues to detect; The step S3 further comprises the following steps: Step S31: Identify the material of the casting, retrieve the corresponding metal features in the database according to the material of the casting, identify the metal features, and retrieve the corresponding casting shrinkage coefficient in the database according to the metal features Calculate the dimensional parameters of the casting before cooling by formula In the formula, K represents the dimensional parameter of the casting before cooling, R represents the actual dimensional parameter of the target casting, and the control system adjusts the mold model according to the dimensional parameter K; Step S32: Identify the metal characteristics of the casting raw material, identify the temperature of the current device, retrieve the heat conversion rate η between the corresponding device and the casting raw material in the database according to the temperature of the device and the metal characteristics of the casting material, if the energy conversion rate is less than the threshold, continue to heat the device, otherwise add raw materials to the device, retrieve the historical heating records of the device, calculate the average power of the device, and calculate the heating time of the casting raw material by the formula In the formula, T0 represents the heating time of the casting raw material, M represents the weight of the heated casting raw material, c represents the specific heat capacity of the casting raw material, t0 represents the temperature of the casting raw material before heating, t1 represents the heating temperature required for the casting raw material, and P1 represents the average power of the equipment; In step S33, the melting rate of the casting raw material is calculated by the formula: In the formula, V represents the melting speed of the casting raw material. If the melting speed of the casting raw material is greater than the maximum threshold or less than the minimum threshold, the corresponding optimal melting speed in the database is retrieved, and the optimal heating power of the equipment is calculated according to the formula In the formula, κ represents the calculated error coefficient. The equipment is controlled to heat according to the calculated optimal heating power of the equipment. Otherwise, the equipment is controlled to heat the casting raw material according to the average power of the equipment. In step S4, the detection data of the casting is obtained, compared with the database, and the abnormal data is anchored. The corresponding casting defect type in the database is retrieved according to the abnormal data, and the mark in the casting defect type is identified. If it is a repairable mark, the visual image of the casting is identified, and the gradual defect position is anchored. The system performs grinding and cutting to obtain a casting that meets the conditions. Otherwise, the casting is transferred to the equipment furnace for re-casting.

2. The casting process measurement and control system based on cloud computing according to claim 1, characterized in that: The data collection module includes a sensor module, a vision module and a casting comprehensive parameter entry module. The sensor module is used to collect the operation data of the casting equipment and the comprehensive data of the casting in real time. The vision module is used to capture the visual image of the casting and the visual image of the pouring equipment pouring the molten metal. The casting comprehensive parameter entry module is used to enter the comprehensive parameters of the casting to be cast into the system.

3. The casting process measurement and control system based on cloud computing according to claim 2 is characterized in that: The mold detection module includes a casting parameter analysis module and a mold structure analysis module. The casting parameter analysis module is used to analyze the parameter characteristics of the casting and then select the corresponding casting processing material and mold material. The mold structure analysis module is used to analyze the internal structure of the casting mold.

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