Pipeline production data processing method, system and equipment based on Internet of Things

Abstract

The invention relates to the technical field of electric digital data processing, and particularly discloses a pipeline production data processing method, system and equipment based on the Internet of Things, and the method comprises the steps: obtaining a pipeline production environment data set, a pipeline production equipment data set and a pipeline production product sampling inspection data set, and carrying out the comprehensive analysis to obtain a pipeline production evaluation value; transmitting the pipeline production evaluation value to a control center, acquiring a pipeline production evaluation value transmission data set, judging whether the pipeline production evaluation value is successfully transmitted or not, analyzing the successfully transmitted pipeline production evaluation value, judging whether the pipeline production is qualified or not, and comparing to obtain an unqualified pipeline production improvement scheme. According to the invention, the problems of low management efficiency, insufficient data analysis capability and low automation degree of traditional pipeline production data are solved, each link in the pipeline production process is accurately evaluated, unqualified pipeline production is analyzed, an effective improvement scheme is provided, and the product quality is gradually improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic digital data processing, and in particular to a pipeline production data processing method, system and equipment based on the Internet of Things. Background Art

[0002] As an important part of modern infrastructure construction, concrete pipes are widely used in urban drainage, water supply, sewage treatment and other fields. With the acceleration of urbanization, the demand for concrete pipes continues to increase, requiring manufacturers to improve production efficiency and pipe quality to meet market demand. With the promotion of intelligent manufacturing concepts, concrete pipe production is gradually developing towards intelligence and automation. The Internet of Things can realize real-time monitoring and data analysis of production links, thereby optimizing production processes, reducing resource waste and reducing costs.

[0003] For example, the invention patent with announcement number CN115114860B discloses a data modeling and amplification method for concrete pipe damage identification. The method includes: concrete pipe damage model establishment, data processing, ShapContextNet model construction, model training, model parameter adjustment, model testing and real-time detection. The present invention proposes a data modeling and amplification method for concrete pipe damage identification, develops a ShapContextNet neural network algorithm suitable for concrete pipe damage detection, and uses data modeling methods to perform data amplification when the amount of real concrete pipe damage data is scarce, thereby improving the robustness and generalization ability of the method, thereby realizing automatic identification of concrete pipe damage.

[0004] Nowadays, there are still some shortcomings in the research on pipeline production data processing methods based on the Internet of Things. Specifically, traditional pipeline production data faces problems such as low management efficiency, insufficient data analysis capabilities, and low degree of automation. Manual or inefficient data management methods will extend the production cycle and cause delays in production plans. Low management efficiency will lead to waste of resources such as materials and energy. The lack of timely and accurate data analysis makes it impossible for management to respond quickly to market changes. Relying on experience and intuition to make decisions can easily lead to misjudgments. Data comes from multiple sources and lacks effective integration, resulting in information opacity and increasing the complexity of data processing. The lack of real-time data monitoring during the production process makes it difficult to identify and solve quality problems in a timely manner, which may lead to the production of unqualified products. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a pipeline production data processing method, system and device based on the Internet of Things, which can effectively solve the problems involved in the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: In a first aspect, the present invention provides a pipeline production data processing method based on the Internet of Things, comprising the following steps: obtaining a pipeline production environment data set, and based on the obtained pipeline production environment data set, comprehensively analyzing to obtain a pipeline production environment evaluation value; obtaining a pipeline production equipment data set, and based on the obtained pipeline production equipment data set, comprehensively analyzing to obtain a pipeline production equipment evaluation value; obtaining a pipeline production product sampling data set, and based on the obtained pipeline production product sampling data set, combining the pipeline production environment evaluation value and the pipeline production equipment evaluation value, comprehensively analyzing to obtain a pipeline production evaluation value; transmitting the pipeline production evaluation value to a control center, obtaining a pipeline production evaluation value transmission data set, and judging whether the pipeline production evaluation value is successfully transmitted based on the obtained pipeline production evaluation value transmission data set; analyzing the successfully transmitted pipeline production evaluation value, judging whether the pipeline production is qualified, and comparing the unqualified pipeline production improvement plan.

[0007] As a further method, based on the acquired pipeline production environment data set, a comprehensive analysis is performed to obtain a pipeline production environment assessment value. The specific analysis process is: obtaining a pipeline production environment data set, the pipeline production environment data set specifically includes the absolute value of the difference between the pipeline production environment temperature and the reference temperature, the absolute value of the difference between the pipeline production environment humidity and the reference humidity, and the pipeline production environment air particulate matter concentration; based on the acquired pipeline production environment data set, a comprehensive analysis is performed to obtain a pipeline production environment assessment value, and the pipeline production environment assessment value is used as an analysis basis for obtaining a pipeline production assessment value through comprehensive analysis.

[0008] As a further method, based on the acquired pipeline production equipment data set, a comprehensive analysis is performed to obtain a pipeline production equipment evaluation value. The specific analysis process is: obtain the pipeline production equipment data set, the pipeline production equipment data set specifically includes the absolute value of the difference between the pipeline production equipment molding pressure and the reference molding pressure, the pipeline production equipment noise decibel value, the pipeline production equipment vibration frequency, and the absolute value of the difference between the actual cement flow of the pipeline production equipment and the reference cement flow; based on the acquired pipeline production equipment data set, a comprehensive analysis is performed to obtain a pipeline production equipment evaluation value, and the pipeline production equipment evaluation value is used as an analysis basis for the comprehensive analysis to obtain the pipeline production evaluation value.

[0009] As a further method, based on the acquired pipeline production product sampling data set, combined with the pipeline production environment assessment value and the pipeline production equipment assessment value, a comprehensive analysis is performed to obtain the pipeline production assessment value. The specific analysis process is: obtaining the pipeline production product sampling data set, the pipeline production product sampling data set specifically includes the qualified proportion of pipeline production product sampling appearance, the qualified proportion of pipeline production product sampling internal structure, and the qualified proportion of pipeline production product sampling durability and insulation; based on the acquired pipeline production product sampling data set, a comprehensive analysis is performed to obtain the pipeline production product sampling assessment value, and the pipeline production product sampling assessment value is used as the analysis basis for the comprehensive analysis to obtain the pipeline production assessment value; the pipeline production product sampling assessment value, the pipeline production environment assessment value and the pipeline production equipment assessment value are added to obtain the pipeline production assessment value, and the pipeline production assessment value is used as the analysis basis for judging whether the pipeline production is qualified.

[0010] As a further method, the sampling evaluation value of pipeline production products, the specific analysis process is: ; In the formula, It is the sampling evaluation value of pipeline production products. The qualified proportion of pipeline production products in random inspections. To check the qualified ratio of internal structure of pipeline production products. To check the durability and insulation quality of pipeline products. It is the compensation factor for the qualified appearance ratio of pipeline production product sampling inspection. The compensation factor for the qualified ratio of internal structure of pipeline production products sampled. It is the compensation factor for the qualified proportion of durability and insulation of pipeline production products in random inspection.

[0011] As a further method, based on the acquired pipeline production assessment value transmission data set, it is judged whether the pipeline production assessment value is transmitted successfully. The specific analysis process is: the pipeline production assessment value is transmitted to the control center to obtain the pipeline production assessment value transmission data set, and the pipeline production assessment value transmission data set specifically includes the pipeline production assessment value transmission delay, the pipeline production assessment value transmission packet loss rate, and the pipeline production assessment value transmission network bandwidth; based on the acquired pipeline production assessment value transmission data set, a comprehensive analysis is performed to obtain the pipeline production assessment value transmission characteristic value, and the pipeline production assessment value transmission characteristic value is used as an analysis basis for judging whether the pipeline production assessment value is transmitted successfully; the pipeline production assessment value transmission characteristic value is compared with the pipeline production assessment value transmission boundary characteristic value stored in the database; if the pipeline production assessment value transmission characteristic value is higher than or equal to the pipeline production assessment value transmission boundary characteristic value, then the pipeline production assessment value corresponding to the pipeline production assessment value transmission characteristic value is transmitted successfully; if the pipeline production assessment value transmission characteristic value is lower than the pipeline production assessment value transmission boundary characteristic value, then the pipeline production assessment value corresponding to the pipeline production assessment value transmission characteristic value is not transmitted successfully, and the pipeline production assessment value needs to be re-transmitted.

[0012] As a further method, the pipeline production assessment value transmits the characteristic value, and the specific analysis process is as follows: ; In the formula, Transferring characteristic values ​​for pipeline production evaluation, Evaluate the transmission delay of the pipeline production value, The transmission packet loss rate of the pipeline production evaluation value, The network bandwidth for pipeline production assessment is is the compensation factor for the transmission delay of the set pipeline production assessment value, The compensation factor for the transmission packet loss rate of the set pipeline production evaluation value, A compensation factor for the transmission network bandwidth for a given pipeline production estimate.

[0013] As a further method, the successfully transmitted pipeline production evaluation value is analyzed to determine whether the pipeline production is qualified, and an improvement plan for unqualified pipeline production is compared. The specific analysis process is: the successfully transmitted pipeline production evaluation value is analyzed, and the pipeline production evaluation value is compared with the pipeline production reference evaluation value stored in the database; if the pipeline production evaluation value is higher than or equal to the pipeline production reference evaluation value, the pipeline production corresponding to the pipeline production evaluation value is qualified; if the pipeline production evaluation value is lower than the pipeline production reference evaluation value, the pipeline production corresponding to the pipeline production evaluation value is unqualified, and the difference between the pipeline production reference evaluation value and the pipeline production evaluation value corresponding to the unqualified pipeline production is recorded as the pipeline production evaluation deviation value, and the pipeline production evaluation deviation value is compared with the unqualified pipeline production improvement plan corresponding to each pipeline production evaluation deviation value stored in the database to obtain the unqualified pipeline production improvement plan corresponding to the pipeline production evaluation deviation value.

[0014] The second aspect of the present invention provides a pipeline production data processing system based on the Internet of Things, including a pipeline production environment evaluation value acquisition module, a pipeline production equipment evaluation value acquisition module, a pipeline production evaluation value acquisition module, a pipeline production evaluation value transmission judgment module and a pipeline production qualified judgment module, wherein: the pipeline production environment evaluation value acquisition module is used to acquire a pipeline production environment data set, and based on the acquired pipeline production environment data set, a comprehensive analysis is performed to obtain a pipeline production environment evaluation value; the pipeline production equipment evaluation value acquisition module is used to acquire a pipeline production equipment data set, and based on the acquired pipeline production equipment data set, a comprehensive analysis is performed to obtain a pipeline production equipment evaluation value; the pipeline The production evaluation value acquisition module is used to obtain a pipeline production product sampling data set, and based on the obtained pipeline production product sampling data set, combined with the pipeline production environment evaluation value and the pipeline production equipment evaluation value, a comprehensive analysis is performed to obtain the pipeline production evaluation value; the pipeline production evaluation value transmission judgment module is used to transmit the pipeline production evaluation value to the control center, obtain the pipeline production evaluation value transmission data set, and judge whether the pipeline production evaluation value is successfully transmitted based on the obtained pipeline production evaluation value transmission data set; the pipeline production qualified judgment module is used to analyze the successfully transmitted pipeline production evaluation value, judge whether the pipeline production is qualified, and compare the unqualified pipeline production improvement plan.

[0015] The third aspect of the present invention provides a pipeline production data processing device based on the Internet of Things, including a processor and a memory and a network interface connected to the processor, the network interface is connected to a non-volatile memory in a server, and the processor retrieves a computer program from the non-volatile memory through the network interface during operation, and runs the computer program through the memory.

[0016] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention provides a pipeline production data processing method, system and device based on the Internet of Things, which comprehensively analyzes the environment, equipment and product sampling data, and can accurately evaluate each link in the pipeline production process, help the management to make more scientific and effective decisions, obtain the pipeline production environment and equipment data, monitor the production status in real time, and find problems in time, thereby reducing downtime and resource waste and improving overall efficiency. Based on the environmental evaluation value and equipment evaluation value, combined with the product sampling data, it can quickly identify quality problems, take measures in time, and improve the product qualification rate. By analyzing the production of unqualified pipelines, it can propose effective improvement plans and gradually improve product quality.

[0017] (2) The present invention obtains a sampling data set of pipeline production products, combines the pipeline production environment evaluation value with the pipeline production equipment evaluation value, and comprehensively analyzes to obtain the pipeline production evaluation value, so as to better evaluate the overall production situation. The comprehensive evaluation value provides a scientific data basis for the management, helping them to make more wise and reasonable production decisions and reduce decision-making risks. With the help of the comprehensive evaluation value, potential problems or abnormalities in the production process, such as equipment failure, environmental discomfort, etc., can be discovered early, so that corrective measures can be taken in time. By analyzing the production evaluation value, the enterprise can more accurately identify the causes of unqualified products, formulate corresponding quality control standards, and improve the product qualification rate.

[0018] (3) The present invention analyzes the evaluation value of the successfully transmitted pipeline production to determine whether the pipeline production is qualified, and compares the improvement plan for the unqualified pipeline production. Through the evaluation value analysis, it is possible to specifically identify which links have quality problems and identify the characteristics of unqualified pipelines, thereby avoiding deviations caused by subjective judgment. The in-depth analysis of unqualified pipelines can be used to formulate specific improvement plans for them, which are highly targeted and more effective than general improvement measures. Analyzing the causes of unqualified pipelines helps to discover bottlenecks in the production process, thereby optimizing the production process and improving overall efficiency, thereby achieving the purpose of improving product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0020] Figure 1 The figure is a schematic flow chart of the method steps of the present invention.

[0021] Figure 2 It is a schematic diagram of system module connection of the present invention. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0023] Reference Figure 1 As shown, the first aspect of the present invention provides a pipeline production data processing method based on the Internet of Things, including obtaining a pipeline production environment data set, and obtaining a pipeline production environment evaluation value based on a comprehensive analysis of the obtained pipeline production environment data set.

[0024] Specifically, based on the acquired pipeline production environment data set, a comprehensive analysis is performed to obtain a pipeline production environment assessment value. The specific analysis process is: obtain a pipeline production environment data set, which specifically includes the absolute value of the difference between the pipeline production environment temperature and the reference temperature, the absolute value of the difference between the pipeline production environment humidity and the reference humidity, and the concentration of air particulate matter in the pipeline production environment. The absolute value of the difference between the pipeline production environment temperature and the reference temperature refers to the absolute difference between the actual temperature of the pipeline production environment and a certain standard or reference temperature (usually the design temperature or the optimal working temperature), which can help determine whether the current temperature conditions are suitable for pipeline production and processing. It can be measured by a temperature sensor (such as a thermocouple, thermal resistor, etc.) or a digital thermometer. The pipeline production environment humidity The absolute value of the difference with the reference humidity indicates the absolute difference between the actual ambient humidity and the reference humidity. For the processing and storage of many materials, too high or too low humidity may affect the properties of the materials and the quality of processing. It is measured by humidity sensors (such as relative humidity meters). The air particulate matter concentration in the pipeline production environment refers to the concentration of tiny particles in the air (such as dust, smoke, bacteria, etc.). It is very important for evaluating the cleanliness of the production environment and its potential impact on product quality. The particle concentration can be obtained through air quality monitoring instruments (such as dust detectors, laser particle size analyzers, etc.); based on the obtained pipeline production environment data set, a comprehensive analysis is performed to obtain the pipeline production environment assessment value, and the pipeline production environment assessment value is used as the analysis basis for the comprehensive analysis to obtain the pipeline production assessment value.

[0025] In a specific embodiment, temperature and humidity are closely related. When the temperature rises, the saturated water vapor content of the air will increase, so the relative humidity in the air may decrease. During the production of pipelines, the high temperature environment may cause the material to lose water or evaporate, affecting its physical properties. Humidity plays an important role in the suspension and sedimentation of particulate matter in the air. In a high humidity environment, some particulate matter may absorb moisture and increase weight, thereby settling to reduce concentration, while under low humidity conditions, the concentration of particulate matter may increase. The humidity environment may also affect the survival of organic matter and microorganisms in the air, thereby affecting the overall air quality. Temperature changes will also affect the formation and behavior of particulate matter. In a high temperature environment, some chemical reactions will be accelerated, which may lead to an increase in the generation of particulate matter. Changes in temperature may affect the sedimentation rate of particulate matter, thereby changing the concentration of particulate matter in the air.

[0026] It should be explained that the above comprehensive analysis of key factors such as temperature, humidity and air particle concentration can systematically evaluate the entire production environment, identify possible influencing factors and their interactions, and thus more comprehensively understand the impact of the production environment. Accurate evaluation values ​​can help identify situations where environmental conditions are not suitable, such as abnormally high or low temperature and humidity, and take timely adjustment measures to ensure that the quality of pipeline products meets standard requirements and reduce the failure rate. By analyzing the changing trend of evaluation values, production managers can adjust production parameters in real time and optimize production processes to make them more efficient and economical. They can formulate production strategies that adapt to different environmental conditions. Monitoring of environmental evaluation values ​​can detect early signs of potential problems, such as drastic fluctuations in temperature and humidity, and abnormal increases in air particle concentrations, so as to carry out preventive maintenance and reduce production downtime and maintenance costs. Evaluation values, as the basis for decision-making, can provide management with scientific reference data to help formulate reasonable production policies and improvement measures, thereby improving the overall management level and decision-making efficiency.

[0027] It should be explained that the specific analysis process of the above pipeline production environment assessment value is as follows: ; In the formula, is the pipeline production environment assessment value, is the absolute value of the difference between the pipeline production environment temperature and the reference temperature, is the absolute value of the difference between the pipeline production environment humidity and the reference humidity, is the concentration of particulate matter in the air of the pipeline production environment, is the compensation factor for the absolute value of the difference between the set pipeline production environment temperature and the reference temperature. The compensation factor for the absolute value of the difference between the set pipeline production environment humidity and the reference humidity. is the compensation factor for the set air particulate matter concentration in the pipeline production environment. is a natural constant.

[0028] It needs to be explained that the above pipeline production environment assessment value is calculated through the absolute value of the difference between the pipeline production environment temperature and the reference temperature, the absolute value of the difference between the pipeline production environment humidity and the reference humidity, and the concentration of air particles in the pipeline production environment. The absolute value of the difference between the pipeline production environment temperature and the reference temperature, the absolute value of the difference between the pipeline production environment humidity and the reference humidity, and the concentration of air particles in the pipeline production environment are normalized. Monitoring and evaluating the production environment can effectively prevent the impact of environmental factors on the quality of pipeline products and reduce the defect rate. Inappropriate temperature, humidity and air particle concentration may cause equipment failure or safety hazards. By monitoring these parameters, potential risks can be identified in advance to ensure production safety. According to changes in environmental assessment values, production parameters can be adjusted in time to optimize production processes and improve production efficiency. Environmental assessment provides a data basis for production decisions and helps management make more scientific decisions to set a pipeline production environment. The absolute value of the difference between the temperature and the reference temperature, the absolute value of the difference between the pipeline production environment humidity and the reference humidity, and the compensation factor of the pipeline production environment air particulate matter concentration are obtained from the database. According to the historical data, a mapping set of the absolute value of the difference between the historically measured pipeline production environment temperature and the reference temperature, the absolute value of the difference between the pipeline production environment humidity and the reference humidity, the pipeline production environment air particulate matter concentration and the absolute value of the difference between the pipeline production environment temperature and the reference temperature, the absolute value of the difference between the pipeline production environment humidity and the reference humidity, and the compensation factor of the pipeline production environment air particulate matter concentration is established to obtain the absolute value of the difference between the current pipeline production environment temperature and the reference temperature, the absolute value of the difference between the pipeline production environment humidity and the reference humidity, and the compensation factor of the pipeline production environment air particulate matter concentration.

[0029] A pipeline production equipment data set is obtained, and based on the obtained pipeline production equipment data set, a comprehensive analysis is performed to obtain an evaluation value of the pipeline production equipment.

[0030] Specifically, based on the acquired pipeline production equipment data set, a comprehensive analysis is performed to obtain the pipeline production equipment evaluation value. The specific analysis process is: obtain the pipeline production equipment data set, which specifically includes the absolute value of the difference between the molding pressure of the pipeline production equipment and the reference molding pressure, the noise decibel value of the pipeline production equipment, the vibration frequency of the pipeline production equipment, and the absolute value of the difference between the actual cement flow rate of the pipeline production equipment and the reference cement flow rate. The absolute value of the difference between the molding pressure and the reference molding pressure refers to the difference between the molding pressure actually used in the pipeline production process and the standard or set reference molding pressure, which can reflect whether the operating status of the equipment is normal and whether the molding pressure is within a reasonable range. Use pressure sensors (pressure transmitters) and related monitoring systems to monitor and record the molding pressure in real time. The noise decibel value refers to the production equipment The intensity of noise during operation is usually expressed in decibels (dB). Excessive noise levels may affect the operation of the equipment and the health and safety of employees. It is obtained using noise monitoring instruments. Vibration frequency refers to the frequency of vibration generated by the equipment during operation, which can reflect the health status of the equipment. Abnormal vibration frequency may indicate that the equipment is faulty or worn and requires maintenance or overhaul. It is obtained using vibration sensors. The actual cement flow rate refers to the volume or mass flow of cement actually transported during the pipeline production process. The accuracy of the cement flow rate is crucial to the molding process and directly affects the strength and quality of the product. It is obtained using a flow meter. Based on the acquired pipeline production equipment data set, a comprehensive analysis is performed to obtain the pipeline production equipment evaluation value, which is used as the analytical basis for the comprehensive analysis to obtain the pipeline production evaluation value.

[0031] It needs to be explained that the above-mentioned molding pressure is a key control parameter in the production process. The difference from the reference molding pressure reflects the stability of the equipment and the correctness of the production process. If the molding pressure deviates from the set value, it may lead to uneven filling or insufficient strength of cement during the production process. The noise level is usually related to the operating state and mechanical wear of the equipment. If the molding pressure is abnormal, it may cause the equipment to run unsteadily, thereby generating higher noise. Abnormal vibration frequency may also cause increased noise. The vibration state of the equipment during operation is directly related to the pipeline molding pressure. Excessive molding pressure may cause excessive vibration of the equipment, which further affects production efficiency and product quality. If the cement flow is abnormal, it may reflect that the molding pressure is unstable, which in turn affects noise and vibration.

[0032] It should be explained that the above evaluation values ​​comprehensively consider multiple key factors, such as molding pressure, noise, vibration frequency and cement flow, and can fully reflect the operating status of the equipment. During the production process, these parameters may affect each other, so the comprehensive evaluation helps to more accurately identify the overall performance of the equipment and provide data-based evaluation values, so that management and operators can make more scientific decisions. This quantitative result helps to optimize production operations, adjust equipment operating parameters and take appropriate maintenance measures, thereby improving overall production efficiency. Based on the evaluation values ​​obtained through analysis, potential problems with equipment can be more easily identified. High noise and vibration frequency may indicate equipment wear or failure. Monitoring changes in evaluation values ​​can provide early warning of equipment failures and reduce maintenance costs and downtime. Evaluation values ​​can be used as a basis for optimizing the production process. Through analysis of evaluation values, key factors affecting production efficiency and product quality can be identified, and corresponding improvement measures can be taken, such as adjusting molding pressure or flow control. It can also record and track equipment operation history, which is helpful for long-term trend analysis, understanding the performance of equipment under different operating conditions and time periods, and helping to formulate reasonable maintenance and upgrade plans.

[0033] It should be explained that the specific analysis process of the above pipeline production equipment evaluation value is as follows: ; In the formula, For the evaluation value of pipeline production equipment, It is the absolute value of the difference between the molding pressure of the pipeline production equipment and the reference molding pressure. is the noise decibel value of pipeline production equipment, is the vibration frequency of the pipeline production equipment, is the absolute value of the difference between the actual cement flow rate of the pipeline production equipment and the reference cement flow rate, The compensation factor for the absolute value of the difference between the set molding pressure of the pipeline production equipment and the reference molding pressure, is the compensation factor for the noise decibel value of the set pipeline production equipment, is the compensation factor of the vibration frequency of the set pipeline production equipment, It is the compensation factor for the absolute value of the difference between the actual cement flow rate of the set pipeline production equipment and the reference cement flow rate.

[0034] It needs to be explained that the above-mentioned evaluation value of pipeline production equipment is calculated through the absolute value of the difference between the molding pressure of pipeline production equipment and the reference molding pressure, the decibel value of pipeline production equipment noise, the vibration frequency of pipeline production equipment, and the absolute value of the difference between the actual cement flow rate of pipeline production equipment and the reference cement flow rate. The absolute value of the difference between the molding pressure of pipeline production equipment and the reference molding pressure, the decibel value of pipeline production equipment noise, the vibration frequency of pipeline production equipment, and the absolute value of the difference between the actual cement flow rate of pipeline production equipment and the reference cement flow rate are normalized, which can fully understand the operating status of the equipment, discover potential problems in time, and prevent equipment failures. It can help identify deviations in the production process and ensure that the produced pipes meet the design requirements and quality standards. The monitoring of noise and vibration can detect the abnormal operating status of the equipment in advance, thereby reducing the risk of accidents and ensuring the safety of employees and the production environment. Analyzing the difference in molding pressure and cement flow rate can optimize production parameters, improve production efficiency, and reduce resource waste. According to the evaluation value, predictive maintenance can be implemented, and the equipment can be maintained and adjusted in advance, thereby extending the service life of the equipment and reducing downtime. The set molding pressure of pipeline production equipment and the reference The absolute value of the molding pressure difference, the decibel value of the pipeline production equipment noise, the vibration frequency of the pipeline production equipment, and the compensation factor of the absolute value of the difference between the actual cement flow of the pipeline production equipment and the reference cement flow are obtained from the database. According to the historical data, a mapping set of the absolute value of the difference between the molding pressure of the pipeline production equipment and the reference molding pressure, the decibel value of the pipeline production equipment noise, the vibration frequency of the pipeline production equipment, the absolute value of the difference between the actual cement flow of the pipeline production equipment and the reference cement flow and the absolute value of the difference between the molding pressure of the pipeline production equipment and the reference molding pressure, the decibel value of the pipeline production equipment noise, the vibration frequency of the pipeline production equipment, and the compensation factor of the absolute value of the difference between the molding pressure of the pipeline production equipment and the reference molding pressure, the decibel value of the pipeline production equipment noise, the vibration frequency of the pipeline production equipment, and the absolute value of the difference between the actual cement flow of the pipeline production equipment and the reference cement flow corresponding to the absolute value of the difference between the molding pressure of the pipeline production equipment and the reference molding pressure, the decibel value of the pipeline production equipment noise, the vibration frequency of the pipeline production equipment, and the absolute value of the difference between the actual cement flow of the pipeline production equipment and the reference cement flow is established.

[0035] A pipeline production product sampling data set is obtained, and based on the obtained pipeline production product sampling data set, the pipeline production environment assessment value and the pipeline production equipment assessment value are combined to obtain a pipeline production assessment value through comprehensive analysis.

[0036] Specifically, based on the obtained pipeline production product sampling data set, combined with the pipeline production environment assessment value and the pipeline production equipment assessment value, a comprehensive analysis is performed to obtain the pipeline production assessment value. The specific analysis process is: obtain the pipeline production product sampling data set, which specifically includes the pipeline production product sampling inspection appearance qualified ratio, pipeline production product sampling internal structure qualified ratio, pipeline production product sampling durability and insulation qualified ratio. The sampling appearance qualified ratio refers to the proportion of pipeline products that meet the appearance standards in the spot check. The appearance qualified standards usually include the surface finish, color uniformity, and the number and distribution of defects (such as cracks, bubbles, dents, etc.) of the product, which reflects the appearance quality of the product. Based on the visual inspection system, the sampling internal structure qualified ratio refers to the proportion of pipeline products that meet the internal structure standards in the spot check. The internal structure may include the wall thickness uniformity, internal The smoothness of the wall and the presence of internal defects (such as pores, inclusions, etc.) can ensure the reliability and safety of the product, which is obtained based on non-destructive testing equipment. The qualified proportion of durability and insulation in random inspections refers to the proportion of pipeline products that meet the durability requirements (such as compressive strength, high temperature resistance, corrosion resistance, etc.) and insulation requirements when conducting durability and insulation tests. The durability and insulation inspection ensures the durability and reliability of the product in actual use, which is obtained based on mechanical testing equipment and insulation testing equipment; based on the obtained pipeline production product random inspection data set, a comprehensive analysis is performed to obtain the pipeline production product random inspection evaluation value, and the pipeline production product random inspection evaluation value is used as the analytical basis for comprehensive analysis to obtain the pipeline production evaluation value; the pipeline production product random inspection evaluation value, the pipeline production environment evaluation value and the pipeline production equipment evaluation value are added together to obtain the pipeline production evaluation value, and the pipeline production evaluation value is used as the analytical basis for judging whether the pipeline production is qualified.

[0037] It needs to be explained that the above-mentioned appearance qualified ratio reflects the visible external quality of the product, such as surface finish and defects (cracks, bubbles, etc.), while the internal structure qualified ratio focuses on the internal non-destructive characteristics of the pipeline (such as pores, inclusions, etc.). If there are obvious defects in the appearance, there may also be problems with the internal structure. The qualified rates of appearance and internal structure affect each other. Appearance inspection is often used as a preliminary screening. Products with unqualified appearance can be quickly eliminated through visual review. For the internal structure, it is usually necessary to confirm it through non-destructive testing and other means. The quality of the internal structure, including wall thickness, material uniformity, etc., directly affects the physical properties of the product, and then affects its durability and insulation. In tensile or compression tests, if there are defects inside the pipeline (such as bubbles or inclusions), its compression resistance, durability and insulation may decrease.

[0038] It needs to be explained that the above integration of product sampling evaluation values, production environment evaluation values ​​and production equipment evaluation values ​​can evaluate pipeline production from multiple dimensions. Multi-dimensional evaluation can help discover potential problems and avoid the decline in overall quality due to the imbalance of a single indicator. Comprehensive evaluation values ​​can provide more reliable data support for decision makers, including production managers, quality control personnel, etc., to make more informed decisions when formulating production plans, improvement measures and resource allocation to ensure production process optimization. Through comprehensive evaluation, it can be found that a certain stage or certain equipment has an impact on the quality of pipeline production. Enterprises can adjust the production process, equipment or environment in time to improve the overall production quality and avoid major defects caused by small problems. Quantifying various evaluation values ​​can make the quality of production clearer, which is helpful for formulating quality standards, It is very important to evaluate the effects of production improvements and implement quality control measures. Clear quantitative data can achieve more accurate quality management. When enterprises can use scientific evaluation systems to monitor and ensure the quality of pipeline products, customers' trust in their products will increase, which will have a positive effect on improving brand image and market competitiveness. Enterprises can establish a mechanism for continuous improvement, track and analyze changes in evaluation values, identify problems in a timely manner and take corresponding measures to form a closed-loop management and improve overall production efficiency. Many industries have specific standards and quality control requirements in the production process, which can also better ensure that the company's production process meets relevant standards, thereby reducing compliance risks. Many industries have specific standards and quality control requirements in the production process, which can better ensure that the company's production process meets relevant standards, thereby reducing risks.

[0039] It should be explained that the above-mentioned pipeline production product sampling data set is obtained, combined with the pipeline production environment assessment value and the pipeline production equipment assessment value, and a comprehensive analysis is performed to obtain the pipeline production assessment value, so as to better evaluate the overall production situation. The comprehensive assessment value provides a scientific data basis for the management, helping them to make more wise and reasonable production decisions and reduce decision-making risks. With the help of the comprehensive assessment value, potential problems or abnormalities in the production process, such as equipment failure, environmental unsuitability, etc., can be discovered early, so that corrective measures can be taken in time. Through the analysis of the production assessment value, the company can more accurately identify the causes of unqualified products, formulate corresponding quality control standards, and improve the product qualification rate.

[0040] Furthermore, the sampling evaluation value of pipeline production products is analyzed in the following specific process: ; In the formula, It is the sampling evaluation value of pipeline production products. The qualified proportion of pipeline production products in random inspections. To check the qualified ratio of internal structure of pipeline production products. To check the durability and insulation quality of pipeline products. It is the compensation factor for the qualified appearance ratio of pipeline production product sampling inspection. The compensation factor for the qualified ratio of internal structure of pipeline production products sampled. It is the compensation factor for the qualified proportion of durability and insulation of pipeline production products in random inspection.

[0041] It needs to be explained that the above-mentioned sampling inspection evaluation values ​​of pipeline production products are calculated through the qualified proportion of sampling inspection appearance of pipeline production products, the qualified proportion of sampling inspection internal structure of pipeline production products, and the qualified proportion of sampling inspection durability and insulation of pipeline production products. The qualified proportion of sampling inspection appearance of pipeline production products, the qualified proportion of sampling inspection internal structure of pipeline production products, and the qualified proportion of sampling inspection durability and insulation of pipeline production products are normalized. By sampling inspection based on multiple indicators such as appearance, internal structure, durability and insulation, the quality of pipeline products can be comprehensively evaluated to ensure that the final product meets the design and use standards. Regular sampling inspection and evaluation can discover possible defects and problems in the production process at an early stage, and take improvement measures in time to avoid unqualified products from entering the market. By analyzing the sampling inspection and evaluation results, enterprises can identify deficiencies in the production process, optimize the production process, and improve overall production efficiency and product quality. A high qualified proportion and good sampling inspection and evaluation results will enhance customer trust in the product, improve customer satisfaction and loyalty, and help establish a brand image. The sampling inspection and evaluation results The results provide data support for the management, which is helpful to formulate production and quality control strategies more scientifically and improve the scientific nature of management. The compensation factors for the qualified proportion of sampling appearance of pipeline production products, the qualified proportion of sampling internal structure of pipeline production products, and the qualified proportion of sampling durability and insulation of pipeline production products are obtained from the database. According to historical data, a mapping set of the historically measured qualified proportion of sampling appearance of pipeline production products, the qualified proportion of sampling internal structure of pipeline production products, the qualified proportion of sampling durability and insulation of pipeline production products and the compensation factors for the qualified proportion of sampling appearance of pipeline production products, the qualified proportion of sampling internal structure of pipeline production products, and the qualified proportion of sampling durability and insulation of pipeline production products are established to obtain the compensation factors for the qualified proportion of sampling appearance of pipeline production products, the qualified proportion of sampling internal structure of pipeline production products, and the qualified proportion of sampling durability and insulation of pipeline production products corresponding to the current qualified proportion of sampling appearance of pipeline production products, the qualified proportion of sampling internal structure of pipeline production products, and the qualified proportion of sampling durability and insulation of pipeline production products.

[0042] The pipeline production assessment value is transmitted to the control center, a pipeline production assessment value transmission data set is obtained, and based on the obtained pipeline production assessment value transmission data set, it is determined whether the pipeline production assessment value is successfully transmitted.

[0043] Specifically, based on the obtained pipeline production assessment value transmission data set, determine whether the pipeline production assessment value is successfully transmitted. The specific analysis process is: transmit the pipeline production assessment value to the control center to obtain the pipeline production assessment value transmission data set. The pipeline production assessment value transmission data set specifically includes the pipeline production assessment value transmission delay, the pipeline production assessment value transmission packet loss rate, and the pipeline production assessment value transmission network bandwidth. The transmission delay refers to the time required for data to be sent from the source device to the destination device, including the processing time, queuing time, transmission time and propagation time of the data packet. The packet loss rate refers to the proportion of lost data packets to the total data packets sent during the data transmission process. The packet loss phenomenon will affect the integrity and reliability of the data. The network bandwidth refers to the maximum data transmission rate supported by the network channel, usually expressed in bits per second bps. The larger the bandwidth, the more data the network can transmit. Use network monitoring The tool obtains the pipeline production assessment value transmission delay, the pipeline production assessment value transmission packet loss rate, and the pipeline production assessment value transmission network bandwidth; based on the obtained pipeline production assessment value transmission data set, a comprehensive analysis is performed to obtain the pipeline production assessment value transmission characteristic value, and the pipeline production assessment value transmission characteristic value is used as the analysis basis for judging whether the pipeline production assessment value is successfully transmitted; the pipeline production assessment value transmission characteristic value is compared with the pipeline production assessment value transmission boundary characteristic value stored in the database; if the pipeline production assessment value transmission characteristic value is higher than or equal to the pipeline production assessment value transmission boundary characteristic value, the pipeline production assessment value corresponding to the pipeline production assessment value transmission characteristic value is successfully transmitted; if the pipeline production assessment value transmission characteristic value is lower than the pipeline production assessment value transmission boundary characteristic value, the pipeline production assessment value corresponding to the pipeline production assessment value transmission characteristic value is not successfully transmitted, and the pipeline production assessment value needs to be retransmitted.

[0044] It needs to be explained that the above bandwidth is a key factor affecting the data transmission rate. If the bandwidth is sufficient, the data packets can be transmitted faster, thereby reducing the transmission delay. If the bandwidth is insufficient, the data packets need to queue up for transmission, which will result in increased delay. In a high-bandwidth environment, even if there are delays caused by other factors, the overall delay may still remain at a low level, but in the case of limited bandwidth, network congestion will significantly increase the delay. When there is high latency in the network, data packets may be lost during transmission due to long queue waiting. Data packets wait for transmission in the buffer of the router or switch. If the packet loss rate increases, it will cause the retransmission mechanism of protocols such as TCP (Transmission Control Protocol) to be activated, further increasing the overall transmission delay. When the bandwidth is insufficient, the network traffic may exceed the network capacity, resulting in data packets being discarded. When the bandwidth utilization is too high (close to or exceeding 100%), the packet loss rate will usually increase.

[0045] It needs to be explained that the above retransmission can ensure that the control center receives accurate and up-to-date pipeline production assessment values ​​and avoid information distortion caused by packet loss or delay. Retransmission can reduce or eliminate data loss caused by network problems and ensure data integrity and reliability. Accurate pipeline production assessment values ​​can help managers monitor pipeline conditions in real time, thereby improving the ability to respond to emergencies. Pipeline production assessment values ​​are crucial to production management and decision-making. Ensuring the timely transmission of these values ​​in the control center enables management to respond in a timely manner. Accurate pipeline production assessment values ​​help to timely predict and discover potential safety hazards and reduce possible safety accidents and environmental risks. Ensuring data is timely and accurate can activate emergency response plans more quickly to protect the safety of pipelines and surrounding environments. Optimizing the transmission process and timely retransmission can reduce the number of future retransmissions and improve the efficiency of the entire data transmission system. By analyzing the causes of transmission failures (such as delays, packet loss, etc.), it can provide a basis for optimizing network architecture or transmission protocols and improve future transmission efficiency.

[0046] Furthermore, the pipeline production assessment value transmits the characteristic value, and the specific analysis process is as follows: ; In the formula, Transferring characteristic values ​​for pipeline production evaluation, Evaluate the transmission delay of the pipeline production value, The transmission packet loss rate of the pipeline production evaluation value, The network bandwidth for pipeline production assessment is is the compensation factor for the transmission delay of the set pipeline production assessment value, The compensation factor for the transmission packet loss rate of the set pipeline production evaluation value, A compensation factor for the transmission network bandwidth for a given pipeline production estimate.

[0047] It needs to be explained that the above-mentioned pipeline production assessment value transmission characteristic value is calculated through pipeline production assessment value transmission delay, pipeline production assessment value transmission packet loss rate, and pipeline production assessment value transmission network bandwidth. The pipeline production assessment value transmission delay, pipeline production assessment value transmission packet loss rate, and pipeline production assessment value transmission network bandwidth are normalized, and the transmission delay and network bandwidth are analyzed, so as to optimize the data transmission path and strategy, ensure that the pipeline production assessment value transmission characteristic value can be quickly and effectively transmitted to the relevant system, thereby improving the overall production efficiency. Considering the transmission packet loss rate in the evaluation, problems in data transmission can be discovered and solved in time, ensuring the integrity and accuracy of information, and reducing subsequent problems caused by data loss. Continuous monitoring of transmission delay and other network parameters can realize real-time monitoring of the pipeline production assessment value transmission process, which is helpful to make timely adjustments. Network parameter evaluation can provide data support for management and ensure the smooth operation of production. By implementing more accurate decisions in product quality control and production scheduling and analyzing the bandwidth usage of the transmission network, enterprises can allocate resources more reasonably, avoid network congestion, and improve the overall performance of the system. The set compensation factors for pipeline production assessment value transmission delay, pipeline production assessment value transmission packet loss rate, and pipeline production assessment value transmission network bandwidth are obtained from the database. According to historical data, a mapping set of historically measured pipeline production assessment value transmission delay, pipeline production assessment value transmission packet loss rate, pipeline production assessment value transmission network bandwidth and pipeline production assessment value transmission delay, pipeline production assessment value transmission packet loss rate, and pipeline production assessment value transmission network bandwidth compensation factors is established to obtain the compensation factors for pipeline production assessment value transmission delay, pipeline production assessment value transmission packet loss rate, and pipeline production assessment value transmission network bandwidth corresponding to the current pipeline production assessment value transmission delay, pipeline production assessment value transmission packet loss rate, and pipeline production assessment value transmission network bandwidth.

[0048] Analyze the successfully transmitted pipeline production evaluation value to determine whether the pipeline production is qualified, and compare the improvement plan for unqualified pipeline production.

[0049] Specifically, the successfully transmitted pipeline production evaluation value is analyzed to determine whether the pipeline production is qualified, and an improvement plan for unqualified pipeline production is compared. The specific analysis process is: the successfully transmitted pipeline production evaluation value is analyzed, and the pipeline production evaluation value is compared with the pipeline production reference evaluation value stored in the database; if the pipeline production evaluation value is higher than or equal to the pipeline production reference evaluation value, the pipeline production corresponding to the pipeline production evaluation value is qualified; if the pipeline production evaluation value is lower than the pipeline production reference evaluation value, the pipeline production corresponding to the pipeline production evaluation value is unqualified, and the difference between the pipeline production reference evaluation value and the pipeline production evaluation value corresponding to the unqualified pipeline production is recorded as the pipeline production evaluation deviation value, and the pipeline production evaluation deviation value is compared with the unqualified pipeline production improvement plan corresponding to each pipeline production evaluation deviation value stored in the database to obtain the unqualified pipeline production improvement plan corresponding to the pipeline production evaluation deviation value.

[0050] In a specific embodiment, by evaluating the deviation value, the problems and deficiencies in pipeline production can be more clearly identified, thereby providing targeted information for subsequent improvements. Different deviation values ​​may correspond to different types of problems. By using existing data, targeted in-depth analysis can be carried out. According to the specific deviation value, a personalized improvement plan can be formulated for each unqualified pipeline to improve the effectiveness and pertinence of the improvement measures. By comparing the data, a verified improvement plan can be provided for the existing problems to enhance the scientific nature of the decision. By implementing the improvement plan, various indicators of pipeline production can be gradually improved, the incidence of unqualified products can be reduced, and the overall production quality can be ultimately improved. By implementing improvement measures in a timely manner, the economic losses caused by unqualified products can be reduced, and the subsequent processing costs caused by unqualified products can be reduced. The process of analyzing and improving through deviation values ​​can form a feedback mechanism for continuous improvement and promote the transformation of corporate culture to quality management and continuous improvement.

[0051] It needs to be explained that the above-mentioned analysis of the evaluation value of the successfully transmitted pipeline production is used to determine whether the pipeline production is qualified, and to compare the improvement plan for the unqualified pipeline production. Through the evaluation value analysis, it is possible to specifically identify which links have quality problems, identify the characteristics of unqualified pipelines, and avoid deviations caused by subjective judgment. In-depth analysis of unqualified pipelines can be used to formulate specific improvement plans for them, which are highly targeted and more effective than general improvement measures. Analyzing the causes of unqualified pipelines will help discover bottlenecks in the production process, thereby optimizing the production process, improving overall efficiency, and achieving the goal of improving product quality.

[0052] Reference Figure 2As shown, the second aspect of the present invention provides a pipeline production data processing system based on the Internet of Things, including a pipeline production environment evaluation value acquisition module, a pipeline production equipment evaluation value acquisition module, a pipeline production evaluation value acquisition module, a pipeline production evaluation value transmission judgment module and a pipeline production qualified judgment module.

[0053] The pipeline production environment assessment value acquisition module is used to acquire the pipeline production environment data set, and based on the acquired pipeline production environment data set, comprehensively analyze and obtain the pipeline production environment assessment value.

[0054] The pipeline production equipment evaluation value acquisition module is used to acquire the pipeline production equipment data set, and based on the acquired pipeline production equipment data set, comprehensively analyze and obtain the pipeline production equipment evaluation value.

[0055] The pipeline production evaluation value acquisition module is used to obtain the pipeline production product sampling data set, and based on the obtained pipeline production product sampling data set, combined with the pipeline production environment evaluation value and the pipeline production equipment evaluation value, a comprehensive analysis is performed to obtain the pipeline production evaluation value.

[0056] The pipeline production assessment value transmission judgment module is used to transmit the pipeline production assessment value to the control center, obtain the pipeline production assessment value transmission data set, and judge whether the pipeline production assessment value is successfully transmitted based on the obtained pipeline production assessment value transmission data set.

[0057] The pipeline production qualification judgment module is used to analyze the successfully transmitted pipeline production evaluation value, judge whether the pipeline production is qualified, and compare the improvement plan for unqualified pipeline production.

[0058] The third aspect of the present invention provides a pipeline production data processing device based on the Internet of Things, including a processor and a memory and a network interface connected to the processor, the network interface is connected to a non-volatile memory in a server, and the processor retrieves a computer program from the non-volatile memory through the network interface during operation, and runs the computer program through the memory.

[0059] It needs to be explained that the above-mentioned method, system and equipment for processing pipeline production data based on the Internet of Things can comprehensively analyze the environment, equipment and product sampling data, accurately evaluate each link in the pipeline production process, help management make more scientific and effective decisions, obtain pipeline production environment and equipment data, monitor production status in real time, and find problems in time, thereby reducing downtime and waste of resources and improving overall efficiency. Based on environmental assessment values ​​and equipment assessment values, combined with product sampling data, quality problems can be quickly identified, measures can be taken in time, and product qualification rates can be improved. By analyzing the production of unqualified pipelines, effective improvement plans can be proposed to gradually improve product quality.

[0060] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A pipeline production data processing method based on the Internet of Things, characterized in that: The following steps are involved: Acquire a pipeline production environment data set, and obtain a pipeline production environment assessment value through comprehensive analysis based on the acquired pipeline production environment data set; Acquire a pipeline production equipment data set, and obtain a pipeline production equipment evaluation value through comprehensive analysis based on the acquired pipeline production equipment data set; Obtain a pipeline production product sampling data set, and based on the obtained pipeline production product sampling data set, combine the pipeline production environment assessment value and the pipeline production equipment assessment value, and perform comprehensive analysis to obtain the pipeline production assessment value; Transmitting the pipeline production assessment value to the control center, obtaining a pipeline production assessment value transmission data set, and judging whether the pipeline production assessment value is successfully transmitted based on the obtained pipeline production assessment value transmission data set; Analyze the successfully transmitted pipeline production evaluation value to determine whether the pipeline production is qualified, and compare the improvement plan for unqualified pipeline production.

2. The method for processing pipeline production data based on the Internet of Things according to claim 1 is characterized in that: Based on the obtained pipeline production environment data set, the pipeline production environment assessment value is obtained through comprehensive analysis. The specific analysis process is as follows: Obtain a pipeline production environment data set, which specifically includes an absolute value of a difference between the pipeline production environment temperature and a reference temperature, an absolute value of a difference between the pipeline production environment humidity and a reference humidity, and a concentration of air particulate matter in the pipeline production environment; Based on the acquired pipeline production environment data set, a pipeline production environment assessment value is obtained through comprehensive analysis, and the pipeline production environment assessment value serves as an analysis basis for obtaining a pipeline production assessment value through comprehensive analysis.

3. The method for processing pipeline production data based on the Internet of Things according to claim 1 is characterized in that: Based on the obtained pipeline production equipment data set, the pipeline production equipment evaluation value is obtained through comprehensive analysis. The specific analysis process is as follows: Acquire a pipeline production equipment data set, the pipeline production equipment data set specifically including an absolute value of a difference between a molding pressure of the pipeline production equipment and a reference molding pressure, a decibel value of noise of the pipeline production equipment, a vibration frequency of the pipeline production equipment, and an absolute value of a difference between an actual cement flow rate of the pipeline production equipment and a reference cement flow rate; Based on the acquired pipeline production equipment data set, a comprehensive analysis is performed to obtain a pipeline production equipment evaluation value, and the pipeline production equipment evaluation value is used as an analysis basis for obtaining a pipeline production evaluation value through comprehensive analysis.

4. The method for processing pipeline production data based on the Internet of Things according to claim 1 is characterized in that: Based on the obtained pipeline production product sampling data set, the pipeline production environment evaluation value and the pipeline production equipment evaluation value are combined to obtain the pipeline production evaluation value through comprehensive analysis. The specific analysis process is as follows: Obtain a pipeline production product sampling data set, which specifically includes the percentage of pipeline production products that pass the sampling inspection of appearance, the percentage of pipeline production products that pass the sampling inspection of internal structure, and the percentage of pipeline production products that pass the sampling inspection of durability and insulation; Based on the acquired pipeline production product sampling data set, a comprehensive analysis is performed to obtain a pipeline production product sampling evaluation value, and the pipeline production product sampling evaluation value is used as an analysis basis for the comprehensive analysis to obtain the pipeline production evaluation value; The pipeline production assessment value is obtained by adding the pipeline production product sampling assessment value, the pipeline production environment assessment value and the pipeline production equipment assessment value. The pipeline production assessment value is used as the analysis basis for judging whether the pipeline production is qualified.

5. The method for processing pipeline production data based on the Internet of Things according to claim 4 is characterized in that: The specific analysis process of the sampling assessment value of the pipeline production product is as follows: ； In the formula, It is the sampling evaluation value of pipeline production products. The qualified proportion of pipeline production products in random inspections. To check the qualified ratio of internal structure of pipeline production products. To check the durability and insulation quality of pipeline products. It is the compensation factor for the qualified appearance ratio of pipeline production product sampling inspection. The compensation factor for the qualified ratio of internal structure of pipeline production products sampled. It is the compensation factor for the qualified proportion of durability and insulation of pipeline production products in random inspection.

6. The method for processing pipeline production data based on the Internet of Things according to claim 1 is characterized in that: The pipeline production evaluation value transmission data set obtained is used to determine whether the pipeline production evaluation value is successfully transmitted. The specific analysis process is as follows: Transmitting the pipeline production assessment value to the control center to obtain a pipeline production assessment value transmission data set, wherein the pipeline production assessment value transmission data set specifically includes the pipeline production assessment value transmission delay, the pipeline production assessment value transmission packet loss rate, and the pipeline production assessment value transmission network bandwidth; Based on the acquired pipeline production assessment value transmission data set, a pipeline production assessment value transmission characteristic value is obtained through comprehensive analysis, and the pipeline production assessment value transmission characteristic value is used as an analysis basis for judging whether the pipeline production assessment value is successfully transmitted; comparing the pipeline production assessment value transmission characteristic value with the pipeline production assessment value transmission definition characteristic value stored in the database; If the pipeline production assessment value transmission characteristic value is higher than or equal to the pipeline production assessment value transmission boundary characteristic value, the pipeline production assessment value corresponding to the pipeline production assessment value transmission characteristic value is successfully transmitted; If the pipeline production assessment value transmission characteristic value is lower than the pipeline production assessment value transmission boundary characteristic value, the pipeline production assessment value corresponding to the pipeline production assessment value transmission characteristic value is not successfully transmitted, and the pipeline production assessment value needs to be retransmitted.

7. The method for processing pipeline production data based on the Internet of Things according to claim 6 is characterized in that: The pipeline production assessment value transmission characteristic value, the specific analysis process is: ； In the formula, Transferring characteristic values ​​for pipeline production evaluation, Evaluate the transmission delay of the pipeline production value, The transmission packet loss rate of the pipeline production evaluation value, The network bandwidth for pipeline production assessment is is the compensation factor for the transmission delay of the set pipeline production assessment value, The compensation factor for the transmission packet loss rate of the set pipeline production evaluation value, A compensation factor for the transmission network bandwidth for a given pipeline production estimate.

8. The method for processing pipeline production data based on the Internet of Things according to claim 1 is characterized by: The successful transmission pipeline production evaluation value is analyzed to determine whether the pipeline production is qualified, and an improvement plan for unqualified pipeline production is compared. The specific analysis process is as follows: Analyze the pipeline production evaluation value that has been successfully transmitted, and compare the pipeline production evaluation value with the pipeline production reference evaluation value stored in the database; If the pipeline production assessment value is higher than or equal to the pipeline production reference assessment value, the pipeline production corresponding to the pipeline production assessment value is qualified; If the pipeline production assessment value is lower than the pipeline production reference assessment value, the pipeline production corresponding to the pipeline production assessment value is unqualified, and the difference between the pipeline production reference assessment value and the pipeline production assessment value corresponding to the unqualified pipeline production is recorded as the pipeline production assessment deviation value. The pipeline production assessment deviation value is compared with the unqualified pipeline production improvement plan corresponding to each pipeline production assessment deviation value stored in the database to obtain the unqualified pipeline production improvement plan corresponding to the pipeline production assessment deviation value.

9. The pipeline production data processing system based on the Internet of Things is characterized by: The method for processing pipeline production data based on the Internet of Things as claimed in any one of claims 1 to 8 comprises a pipeline production environment evaluation value acquisition module, a pipeline production equipment evaluation value acquisition module, a pipeline production evaluation value acquisition module, a pipeline production evaluation value transmission judgment module and a pipeline production qualified judgment module, wherein: The pipeline production environment evaluation value acquisition module is used to acquire a pipeline production environment data set, and obtain a pipeline production environment evaluation value through comprehensive analysis based on the acquired pipeline production environment data set; The pipeline production equipment evaluation value acquisition module is used to acquire a pipeline production equipment data set, and obtain a pipeline production equipment evaluation value through comprehensive analysis based on the acquired pipeline production equipment data set; The pipeline production evaluation value acquisition module is used to acquire a pipeline production product sampling data set, and based on the acquired pipeline production product sampling data set, combined with the pipeline production environment evaluation value and the pipeline production equipment evaluation value, comprehensively analyze to obtain the pipeline production evaluation value; The pipeline production assessment value transmission judgment module is used to transmit the pipeline production assessment value to the control center, obtain the pipeline production assessment value transmission data set, and judge whether the pipeline production assessment value is successfully transmitted based on the obtained pipeline production assessment value transmission data set; The pipeline production qualification judgment module is used to analyze the successfully transmitted pipeline production evaluation value, judge whether the pipeline production is qualified, and compare and find out the improvement plan for unqualified pipeline production.

10. Pipeline production data processing equipment based on the Internet of Things, characterized in that: The method for processing pipeline production data based on the Internet of Things as described in any one of claims 1 to 8 comprises a processor and a memory and a network interface connected to the processor, wherein the network interface is connected to a non-volatile memory in a server, and the processor retrieves a computer program from the non-volatile memory through the network interface during operation, and runs the computer program through the memory.

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