Method for dynamic testing of performance of high-temperature bonding machine for pipe joint

Abstract

The application discloses a kind of performance dynamic test methods of high-temperature bonding machine for connecting pipe, and it relates to the technical field of performance test.The performance dynamic test method of high-temperature bonding machine for connecting pipe includes the following steps: obtaining the ordinary temperature variation data set of the heating part of the high-temperature bonding machine for connecting pipe during ordinary mode test and the ordinary mode electrical safety data of the electrical control part when controlling the heating part of the bonding machine to perform ordinary mode test;Obtain the emergency cooling data of the high-temperature bonding machine for connecting pipe under emergency cooling mode and the emergency mode electrical safety data of the electrical control part when controlling the heating part of the bonding machine to perform emergency mode test;Based on ordinary temperature variation data set, ordinary mode electrical safety data, emergency cooling data and emergency mode electrical safety data, the safety performance of high-temperature bonding machine for connecting pipe is evaluated, which solves the problem that there is no safety performance test technology for high-temperature bonding machine in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of performance testing, in particular to a performance dynamic testing method of a high-temperature bonding machine for pipe connection. BACKGROUND

[0002] In the process of connecting the hose part and the metal joint part of the fire hose, the high-temperature bonding process is often used, and the corresponding equipment is needed for processing. The existing equipment heats the hose part to be bonded at high temperature when working, and then sets the hose on the metal joint to complete the subsequent operation such as high-temperature bonding.

[0003] Since the heating part of the high-temperature bonding machine has a high temperature during use, attention should be paid to its safety. However, there is no technology for testing the safety performance of the high-temperature bonding machine in the prior art. SUMMARY

[0004] In view of the deficiencies of the prior art, the present application provides a performance dynamic testing method of a high-temperature bonding machine for pipe connection, which solves the problem that there is no technology for testing the safety performance of the high-temperature bonding machine in the prior art.

[0005] To achieve the above purpose, the present application is implemented by the following technical scheme: a performance dynamic testing method of a high-temperature bonding machine for pipe connection, comprising the following steps: obtaining the ordinary temperature change data set of the heating part of the high-temperature bonding machine for pipe connection in the ordinary mode testing process and the ordinary mode electrical safety data of the electrical control part for controlling the heating part of the bonding machine to perform ordinary mode testing; obtaining the emergency cooling data of the high-temperature bonding machine for pipe connection in the emergency cooling mode and the emergency mode electrical safety data of the electrical control part for controlling the heating part of the bonding machine to perform emergency mode testing; and performing safety performance evaluation of the high-temperature bonding machine for pipe connection based on the ordinary temperature change data set, the ordinary mode electrical safety data, the emergency cooling data and the emergency mode electrical safety data.

[0006] Further, the safety performance evaluation of the takeover high-temperature bonding machine based on the general temperature change data set, the general mode electrical safety data, the emergency cooling data and the emergency mode electrical safety data comprises: performing fusion processing on the general temperature change data set and the general mode electrical safety data to obtain a high-temperature bonding machine general mode safety performance coefficient, which is used to represent the safety performance of the takeover high-temperature bonding machine in the general mode; performing fusion processing on the emergency cooling data and the emergency mode electrical safety data to obtain a high-temperature bonding machine emergency cooling mode safety performance coefficient, which is used to represent the safety performance of the takeover high-temperature bonding machine in the emergency cooling mode; and performing analysis processing on the high-temperature bonding machine general mode safety performance coefficient and the high-temperature bonding machine emergency cooling mode safety performance coefficient to obtain a safety performance index of the takeover high-temperature bonding machine, which is used to represent the safety performance of the takeover high-temperature bonding machine in the general mode and the emergency cooling mode.

[0007] Further, the safety performance index is obtained by multiplying the general mode safety performance coefficient by a first weight factor and adding the emergency cooling mode safety performance coefficient multiplied by a second weight factor.

[0008] Further, the high-temperature bonding machine general mode safety performance coefficient is obtained by:

[0009] The general temperature change data set is processed by a specific function, multiplied by a first weight factor, and added to the general mode electrical safety data processed by a specific function and multiplied by a second weight factor, and then the sum is subjected to exponential operation with a base of the natural logarithm to obtain the high-temperature bonding machine general mode safety performance coefficient.

[0010] Further, the general temperature change data set comprises temperature change data during temperature rise, temperature change data during temperature drop and temperature characteristic data during temperature stabilization, wherein: the temperature change data during temperature rise comprises temperature rise value deviation per unit time and deviation value of time required for temperature rise to stable temperature; the temperature change data during temperature drop comprises temperature drop value deviation per unit time and deviation value of time required for temperature drop to cooling temperature; and the temperature characteristic data during temperature stabilization comprises temperature standard deviation during temperature stabilization and heating portion temperature distribution uniformity.

[0011] Further, the process of acquiring temperature change data during temperature rise is as follows: real-time acquisition of temperature change value of the heating part of the high-temperature bonding machine during temperature rise, establishment of temperature rise curve, acquisition of actual temperature rise value per unit time based on the temperature rise curve, comparison of the actual temperature rise value with the reference temperature rise value stored in the database, acquisition of absolute value of the difference between the actual temperature rise value and the reference temperature rise value, denoted as temperature rise value per unit time deviation; determination of actual time required for temperature rise to stable temperature based on the temperature rise curve, comparison of the actual time required for temperature rise to stable temperature with the reference time required for temperature rise to stable temperature stored in the database, acquisition of absolute value of the difference between the actual time required for temperature rise to stable temperature and the reference time required for temperature rise to stable temperature, denoted as temperature rise to stable temperature time deviation value; the temperature rise value per unit time deviation and the temperature rise to stable temperature time deviation value are denoted as temperature change data during temperature rise; the process of acquiring temperature change data during temperature drop is as follows: real-time acquisition of temperature change value of the heating part of the high-temperature bonding machine during temperature drop, establishment of temperature drop curve, acquisition of actual temperature drop value per unit time based on the temperature drop curve, comparison of the actual temperature drop value with the reference temperature drop value stored in the database, acquisition of absolute value of the difference between the actual temperature drop value and the reference temperature drop value, denoted as temperature drop value per unit time deviation; determination of actual time required for temperature drop to cooling temperature based on the temperature drop curve, comparison of the actual time required for temperature drop to cooling temperature with the reference time required for temperature drop to cooling temperature stored in the database, acquisition of absolute value of the difference between the actual time required for temperature drop to cooling temperature and the reference time required for temperature drop to cooling temperature, denoted as temperature drop to cooling temperature time deviation value; the temperature drop value per unit time deviation and the temperature drop to cooling temperature time deviation value are denoted as temperature change data during temperature drop; the process of acquiring temperature characteristic data during temperature stabilization is as follows: acquisition of actual stable temperature of each sampling point of the heating part based on the set sampling period, acquisition of temperature standard deviation during temperature stabilization based on the actual stable temperature; acquisition of actual stable temperature of each sampling point of the heating part based on the set sampling period, acquisition of heating part temperature average value after temperature stabilization, acquisition of ratio of temperature standard deviation during temperature stabilization to heating part temperature average value after temperature stabilization, denoted as heating part temperature distribution uniformity; the temperature standard deviation during temperature stabilization and the heating part temperature distribution uniformity are denoted as temperature characteristic data during temperature stabilization.

[0012] Further, the normal mode electrical safety data includes a standard deviation of current at temperature rise, a power deviation at temperature rise, a current decrement rate deviation at temperature drop, and a standard deviation of voltage at temperature stability; the process of obtaining the normal mode electrical safety data is as follows: during the temperature rise process, the current value of each time sampling point is periodically obtained, and the standard deviation of current at temperature rise is obtained based on the current value of each time sampling point; after the temperature rise ends, the actual power of the heating part is obtained, the actual power of the heating part is compared with the power reference value stored in the database, the absolute value of the difference between the actual power of the heating part and the power reference value is obtained, and is recorded as the power deviation at temperature rise; during the temperature drop process, the current value of each time sampling point is periodically obtained, a current change curve of the current value changing with time is established based on the current value of each time sampling point, the current reduction value per unit time is recorded as the current decrement rate at temperature drop based on the current change curve, the current decrement rate at temperature drop is compared with the current decrement reference rate at temperature drop stored in the database, the absolute value of the difference between the current decrement rate at temperature drop and the current decrement reference rate at temperature drop is obtained, and is recorded as the current decrement rate deviation at temperature drop; after the temperature reaches a stable temperature, the stable voltage of each sampling time point is obtained based on the voltage sampling period, and the standard deviation of voltage at temperature stability is obtained based on the stable voltage of each sampling time point.

[0013] Further, the specific obtaining method of the high-temperature bonding machine emergency cooling mode safety performance coefficient is as follows: the emergency cooling data and the emergency mode electrical safety data are respectively processed by a function, multiplied by corresponding weight factors, then added, and subjected to exponential operation with the base number of the natural logarithm to obtain the high-temperature bonding machine emergency cooling mode safety performance coefficient.

[0014] Further, the emergency cooling data includes a unit time temperature drop value deviation at emergency cooling and a heating part temperature drop gradient deviation at emergency cooling; the process of obtaining the emergency cooling data is as follows: the temperature change value of the heating part of the high-temperature bonding machine at emergency cooling is obtained in real time, an emergency temperature drop curve is established, the emergency temperature drop actual value per unit time is obtained based on the emergency temperature drop curve, the emergency temperature drop actual value is compared with the emergency temperature drop reference value stored in the database, the absolute value of the difference between the emergency temperature drop actual value and the emergency temperature drop reference value is obtained, and is recorded as the unit time temperature drop value deviation at emergency cooling; the temperature drop rate of each monitoring point is obtained based on the established emergency temperature drop curve, the temperature drop rate of each monitoring point is subjected to mean value processing to obtain the heating part temperature drop gradient at emergency cooling, the heating part temperature drop gradient at emergency cooling is compared with the reference heating part temperature drop gradient at emergency cooling stored in the database, the absolute value of the difference between the heating part temperature drop gradient at emergency cooling and the reference heating part temperature drop gradient at emergency cooling is obtained, and is recorded as the heating part temperature drop gradient deviation at emergency cooling; the unit time temperature drop value deviation at emergency cooling and the heating part temperature drop gradient at emergency cooling are recorded as the emergency cooling data.

[0015] Further, the emergency mode electrical safety data includes an electrical control unit reaction time deviation during emergency cooling and an instantaneous current change value deviation; the process of obtaining the emergency mode electrical safety data is as follows: after a cooling command is issued to the control unit, the actual time of the control unit reaction and the actual instantaneous current change value within the actual time of the control unit reaction are obtained; the actual time of the control unit reaction is compared with the standard reaction time stored in the database to obtain the deviation of the actual time of the control unit reaction from the standard reaction time, which is recorded as the electrical control unit reaction time deviation during emergency cooling; the actual instantaneous current change value is compared with the reference instantaneous current change value stored in the database to obtain the deviation of the actual instantaneous current change value from the reference instantaneous current change value, which is recorded as the instantaneous current change value deviation.

[0016] The present application has the following advantages:

[0017] The performance dynamic test method of the high-temperature bonding machine for takeover comprehensively analyzes the safety status of the equipment from multiple angles by covering temperature changes, electrical safety, and the response time of the control unit, and can comprehensively evaluate the safety performance of the high-temperature bonding machine in daily operation and emergency situations by calculating the safety performance coefficients in normal mode and emergency mode.

[0018] Of course, implementing any product of the present application does not necessarily require all the advantages described above to be achieved at the same time. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 The performance dynamic test method of the high-temperature bonding machine for takeover is a flowchart.

[0020] Figure 2 The function image of the safety performance index of the performance dynamic test method of the high-temperature bonding machine for takeover. DETAILED DESCRIPTION

[0021] The performance dynamic test method of the high-temperature bonding machine for takeover in the embodiments of the present application realizes the testing of the safety performance of the high-temperature bonding machine by facilitating the electrical and temperature safety performance of the high-temperature bonding machine in normal operation and emergency situations.

[0022] The overall idea of the problems in the embodiments of the present application is as follows:

[0023] Under normal operating conditions, temperature data from the heating section and electrical safety data from the electrical control section of the adhesive machine are collected, reflecting the performance and safety of the equipment under standard operating conditions. Simulate emergency situations such as overheating or system failure, perform emergency cooling procedures, and in this mode, collect temperature reduction data from the heating section and electrical safety data from the electrical control section, which helps assess the response capability and safety of the equipment under abnormal or emergency conditions.

[0024] Compare the data collected in normal mode and emergency cooling mode to evaluate the temperature control capability, electrical stability and safety performance of the equipment in emergency situations. In this way, potential safety hazards can be identified, equipment design and operation processes can be optimized, and the overall safety and reliability of the equipment can be enhanced.

[0025] Overall, this testing method aims to ensure that high-temperature adhesive machines maintain stable and safe operation in all operating environments by simulating normal and emergency situations, thereby ensuring user safety and improving equipment operation efficiency.

[0026] Please refer to Figure 1 The embodiment of the present application provides a technical solution: a performance dynamic testing method for a high-temperature adhesive machine for pipe connection, comprising the following steps: obtaining normal temperature change data set of the heating section of the high-temperature adhesive machine for pipe connection during normal mode testing and normal mode electrical safety data of the electrical control section when controlling the heating section of the adhesive machine to perform normal mode testing; obtaining emergency cooling data of the high-temperature adhesive machine for pipe connection in emergency cooling mode and emergency mode electrical safety data of the electrical control section when controlling the heating section of the adhesive machine to perform emergency mode testing; based on the normal temperature change data set, the normal mode electrical safety data, the emergency cooling data and the emergency mode electrical safety data, the safety performance of the high-temperature adhesive machine for pipe connection is evaluated.

[0027] First, test the device in its normal operating mode to obtain temperature change data from the heating section and safety data from the electrical control section. This step is to ensure the performance and safety of the device in daily use environment, and is a basic data collection process. Then, test under simulated emergency conditions (such as emergency cooling when overheating or system failure), collect emergency cooling data and related electrical control safety data. This step aims to evaluate the response efficiency and safety of the device when facing potential risks or abnormal situations.

[0028] By analyzing the data in normal mode and emergency mode, the temperature control capability and electrical stability of the device under different conditions are evaluated, and the overall safety performance of the device is evaluated. This step is the core of the entire testing method, and by comparing and analyzing, potential problems can be found and improvement measures can be proposed.

[0029] Specifically, the safety performance evaluation of the high-temperature bonding machine for takeover is performed based on the normal temperature change data set, the normal mode electrical safety data, the emergency cooling data and the emergency mode electrical safety data, including: performing fusion processing on the normal temperature change data set and the normal mode electrical safety data to obtain a high-temperature bonding machine normal mode safety performance coefficient, the high-temperature bonding machine normal mode safety performance coefficient being used to represent the safety performance of the high-temperature bonding machine for takeover in the normal mode; performing fusion processing on the emergency cooling data and the emergency mode electrical safety data to obtain a high-temperature bonding machine emergency cooling mode safety performance coefficient, the high-temperature bonding machine emergency cooling mode safety performance coefficient being used to represent the safety performance of the high-temperature bonding machine for takeover in the emergency cooling mode; and performing analysis processing on the high-temperature bonding machine normal mode safety performance coefficient and the high-temperature bonding machine emergency cooling mode safety performance coefficient to obtain a safety performance index of the high-temperature bonding machine for takeover, the safety performance index being used to represent the safety performance of the high-temperature bonding machine for takeover in the normal mode and the emergency cooling mode.

[0030] By fusion processing the temperature change data and the electrical safety data in the normal mode, a comprehensive performance index reflecting the safety of the equipment under normal operating conditions, i.e., the high-temperature bonding machine normal mode safety performance coefficient, can be obtained. Similarly, by fusion processing the emergency cooling data and the emergency mode electrical safety data, the high-temperature bonding machine emergency cooling mode safety performance coefficient reflecting the safety performance of the equipment under emergency conditions can be obtained.

[0031] These performance coefficients provide quantitative safety performance indicators, so that the safety performance of the equipment can be compared and analyzed numerically. This quantitative method helps to identify which aspects of safety performance need to be improved. By analyzing the safety performance coefficients in the two modes and further integrating them into a general safety performance index, this index provides an overall safety evaluation of the equipment under all test scenarios, allowing the equipment performance under normal and emergency conditions to be evaluated and compared through a systematic method, ensuring that the equipment design and function are safe under various possible operating environments.

[0032] The calculation formula of the safety performance index is as follows:

[0033] ;

[0034] In the formula, is the safety performance index, is the high-temperature bonding machine normal mode safety performance coefficient, is the weight factor of , is the high-temperature bonding machine emergency cooling mode safety performance coefficient, is the weight coefficient of , .

[0035] Table 1 Data table for safety performance index

[0036]

[0037] This table shows how changes in the high temperature bonding machine normal mode safety performance coefficient affect the safety performance index, with the high temperature bonding machine emergency cooling mode safety performance coefficient remaining fixed. It can be more clearly observed that an increase in the high temperature bonding machine normal mode safety performance coefficient increases the safety performance index, indicating that the overall safety performance of the equipment under these conditions is getting worse.

[0038] Figure 2 For the safety performance index versus high temperature bonding machine normal mode safety performance coefficient graph, it can be seen that as the high temperature bonding machine normal mode safety performance coefficient increases, the safety performance index also increases, indicating that the overall safety performance of the high temperature bonding machine under these conditions is getting worse.

[0039] In this embodiment, using the natural logarithm, the product of the performance coefficients is converted to a linear scale that is easier to interpret and compare. This transformation can normalize the data, reduce the influence of extreme values, and make the results more stable and interpretable. By combining the weighted average of the high temperature bonding machine normal mode safety performance coefficient and the high temperature bonding machine emergency cooling mode safety performance coefficient, a comprehensive safety assessment is provided that integrates both normal and emergency situations. The weight factor allows different modes to be adjusted according to their importance and impact.

[0040] For the weight factor and can be directly obtained from the database, and the weight factors stored in the database can be determined using historical data analysis. First, historical operation data of the high temperature bonding machine under different modes (normal mode and emergency cooling mode) need to be collected, and detailed statistical analysis is conducted to evaluate the performance and safety performance of the equipment under each mode, and the correlation between different performance indicators, such as the relationship between temperature change and failure rate, is evaluated. Based on the results of statistical analysis, risk assessment is carried out. Assess the impact of various failure modes on safety, which will help determine which mode's data should have a higher weight in the safety performance evaluation. For example, if historical data shows that failures in the emergency cooling mode have a greater impact on the integrity of the equipment and the safety of operation, then this mode should be given a higher weight.

[0041] In order to manage and call the weight factors of the high temperature bonding machine in normal mode and emergency cooling mode and , design a database to store the weight of each pattern, combined with historical data analysis to determine the weight value. Through the dictionary structure in Python, create a mapping set to store these weight factors, provide an interface for real-time updating and calling these data, so that when performing security performance evaluation, the corresponding pattern weight factor can be extracted from the database as needed, thereby improving the accuracy and operability of the evaluation.

[0042] Specifically, the general temperature change dataset includes temperature change data during heating, temperature change data during cooling, and temperature characteristics data during temperature stabilization, wherein: the temperature change data during heating includes the deviation of the temperature rise value per unit time during heating and the deviation of the time required to heat to a stable temperature; the temperature change data during cooling includes the deviation of the temperature drop value per unit time during cooling and the deviation of the time required to cool to a cooling temperature; the temperature characteristics data during temperature stabilization includes the standard deviation of temperature during temperature stabilization and the temperature distribution uniformity of the heating part.

[0043] By recording and analyzing the temperature changes during heating and cooling in detail, the possible failures and performance degradation of the equipment can be more accurately predicted, for example, if the deviation of the time required to heat to a stable temperature increases, it may indicate that the heating system is inefficient or has a fault, and maintenance or replacement of parts should be performed in advance to avoid sudden failures and production interruptions.

[0044] By analyzing the temperature change data, especially the standard deviation and temperature distribution uniformity during temperature stabilization, the control strategy of the heating process can be optimized, for example, if it is found that the temperature distribution is uneven, the layout or control strategy of the heating elements may need to be adjusted to ensure more uniform heating and improve product quality.

[0045] Monitoring the temperature changes during heating and cooling can timely detect overheating or insufficient cooling conditions, prevent the equipment from running in a non-design state, and thus avoid potential safety risks. For example, by monitoring the deviation of the temperature drop value per unit time during cooling, it can be ensured that the emergency cooling system can respond quickly when necessary to prevent the equipment from being damaged due to high temperature.

[0046] The process of obtaining temperature change data during heating is as follows: install temperature sensors at key heating parts of the high-temperature bonding machine, real-time acquire temperature change values of the heating part of the high-temperature bonding machine during heating, set up a data recorder or corresponding software for automatically recording and storing temperature data acquired from the sensors, use a data acquisition system to draw a temperature rise curve showing the change of temperature with time, establish a temperature rise curve, obtain the actual temperature rise value per unit time based on the temperature rise curve, compare the actual temperature rise value with the reference temperature rise value stored in the database, obtain the absolute value of the difference between the actual temperature rise value and the reference temperature rise value, denoted as the deviation of the temperature rise value per unit time during heating.

[0047] For the temperature rise reference value per unit time during heating, a series of standardized tests are conducted at the initial installation of the equipment, and the temperature data during the heating process is systematically recorded. Statistical analysis is performed on the collected data to calculate the average heating rate and related variability (such as standard deviation). Based on the analysis results and production requirements, the final temperature rise reference value per unit time during heating is determined and stored in the database.

[0048] Based on the temperature rise curve, the actual time required to heat to the stable temperature is determined. The actual time required to heat to the stable temperature is compared with the reference time stored in the database to obtain the absolute value of the difference between the actual time required to heat to the stable temperature and the reference time required to heat to the stable temperature, which is recorded as the deviation value of the time required to heat to the stable temperature. The temperature change data during heating is recorded as the temperature change data during heating.

[0049] Detailed performance tests are conducted on the reference time required to heat to the stable temperature to simulate the heating process in actual operation. The time required to reach the stable temperature from the starting temperature is recorded, and the past operation data of the equipment is analyzed to determine the average time required to heat to the stable temperature in actual operation. The average value of the test and historical data is taken as the reference time, which may be adjusted slightly considering the consistency and production efficiency of the equipment and stored in the database.

[0050] Real-time monitoring of temperature changes and establishment of temperature rise curves, calculation of actual temperature rise per unit time, and comparison with reference values to determine deviations, actual heating times, and time deviations. By monitoring the deviations in heating time and speed, potential efficiency declines or faults in the heating system can be identified in a timely manner, allowing for preventive maintenance. Precise heating data helps to adjust and optimize heating procedures, ensuring consistency in the production process and product quality.

[0051] The process of obtaining temperature change data during cooling is as follows: temperature sensors are used to monitor the cooling process, and real-time temperature change values of the heating part of the high-temperature bonding machine during cooling are obtained. A temperature drop curve is established to show the temperature decrease over time. Based on the temperature drop curve, the actual temperature drop per unit time is obtained, and the actual temperature drop is compared with the reference temperature drop stored in the database to obtain the absolute value of the difference between the actual temperature drop and the reference temperature drop, which is recorded as the temperature drop per unit time deviation during cooling.

[0052] For the temperature drop reference value per unit time during cooling, cooling tests are conducted in a controlled environment, and the temperature drop per unit time at different stages and under different environmental conditions is accurately measured. The average temperature drop rate and variability obtained from multiple tests are calculated, and the statistically analyzed average temperature drop rate is recorded as the reference value in the database.

[0053] Based on the temperature drop curve, the actual time required to cool to the cooling temperature is determined, the actual time required to cool to the cooling temperature is compared with the reference time stored in the database required to cool to the cooling temperature, the absolute value of the difference between the actual time required to cool to the cooling temperature and the reference time required to cool to the cooling temperature is obtained, and is recorded as the deviation value of the time required to cool to the cooling temperature; The deviation of the temperature drop value per unit time and the deviation value of the time required to cool to the cooling temperature are recorded as the temperature change data during cooling.

[0054] For the reference time required to cool to the cooling temperature, a cooling test is implemented in the operation of the equipment, the actual time to reach the set cooling temperature is recorded, the test data is analyzed, the average time to reach the cooling temperature is calculated, and the calculated average time is stored in the database as the reference time after possible adjustment.

[0055] Real-time monitoring of temperature changes during cooling and establishing a temperature drop curve, calculating the actual temperature drop value per unit time, and comparing with the reference value, obtaining the deviation, determining the actual cooling time, and comparing with the reference time, obtaining the time deviation. Effective monitoring of temperature changes during cooling can prevent overheating problems, especially in high temperature working environment, reduce safety risk, accurate cooling data helps to protect equipment from damage caused by too fast or uneven temperature change.

[0056] The process of obtaining temperature characteristic data when the temperature is stable is as follows: based on the set sampling period, the actual stable temperature of each sampling point of the heating part is collected, and the temperature standard deviation when the temperature is stable is obtained based on the actual stable temperature; Based on the set sampling period, the actual stable temperature of each sampling point of the heating part is collected to obtain the average temperature of the heating part after temperature stabilization, and the ratio of the temperature standard deviation when the temperature is stable to the average temperature of the heating part after temperature stabilization is obtained, which is recorded as the temperature distribution uniformity of the heating part; The temperature standard deviation when the temperature is stable and the temperature distribution uniformity of the heating part are recorded as the temperature characteristic data when the temperature is stable.

[0057] Collecting the actual temperature of each sampling point of the heating part after stabilization, calculating the temperature standard deviation when the temperature is stable and the temperature distribution uniformity of the heating part, and monitoring the stability and uniformity of the temperature, which can ensure the quality standard of the product in the production process, and avoid quality problems caused by temperature fluctuation.

[0058] First, all parameters (deviation of temperature rise per unit time, deviation of time required to reach stable temperature, deviation of temperature drop per unit time, deviation of time required to reach cooling temperature, temperature standard deviation when temperature is stable, and heating portion temperature distribution uniformity) are normalized to ensure that they are on the same order of magnitude for comparison and calculation, and an exponential or logarithmic function is considered to enhance or weaken the influence of certain parameters. For example, for the deviation value (time deviation value for heating and cooling), an exponential decay function can be considered to represent its influence on performance. After considering all parameters, a product form is used to emphasize that all parameters need to be at a good level to get a good performance score. For example, the normalized parameters can be inversely transformed into a product form of a score index, that is, each index must be good, and the overall performance will be good.

[0059] ;

[0060] wherein, is the deviation of temperature rise per unit time, is the deviation of time required to reach stable temperature, is the deviation of temperature drop per unit time, is the deviation of time required to reach cooling temperature, is the temperature standard deviation when temperature is stable, is the heating portion temperature distribution uniformity, is the natural constant.

[0061] The time deviation value is processed using an exponential function to represent that the greater the time deviation, the more significant the influence on performance; the temperature characteristics are processed using a logarithmic function to slow down the speed of its influence on overall performance, but still maintain the existence of the influence.

[0062] The normal mode electrical safety data includes current standard deviation during temperature rise, power deviation during temperature rise, current decrease rate deviation during temperature drop, and voltage standard deviation when temperature is stable; the process of obtaining normal mode electrical safety data is as follows: install a current sensor and connect it with a data recorder, periodically obtain the current value of each time sampling point during temperature rise, and obtain the current standard deviation during temperature rise based on the current value of each time sampling point (the standard deviation of data calculated using software tools or programming methods).

[0063] For the reference value of current standard deviation during temperature rise, a series of test runs are performed after the initial installation or overhaul of the device, during which current data is collected, and the standard deviation of the current is calculated using these test data. The average current standard deviation obtained from multiple tests is stored in the database as a reference value.

[0064] Periodically measure the current value during the temperature rise process, use these data to calculate the standard deviation of the current value, the current standard deviation can reveal the fluctuation of the current, large fluctuation may indicate potential problems of the electrical system.

[0065] After the temperature rise, measure the actual power of the heating part using the power meter, obtain the actual power of the heating part, compare the actual power of the heating part with the power reference value stored in the database, obtain the absolute value of the difference between the actual power of the heating part and the power reference value, recorded as the power deviation during temperature rise. Monitoring the deviation of power consumption and expected power helps to evaluate the energy efficiency of the equipment, by adjusting to ensure the equipment runs at the best power level, reducing energy waste.

[0066] The reference value for the power deviation during temperature rise is calculated based on the design specifications of the equipment and the expected electrical load, the theoretical power is measured in multiple cycles of normal operation of the equipment, the theoretical and actual power are compared, and the average actual power of multiple measurements is taken as the reference value.

[0067] Connect the current sensor and the recording device, during the temperature drop process, based on the periodic acquisition of the current value at each time sampling point, establish the current change curve of the current value with time, based on the current change curve, record the current reduction value per unit time as the current decrement rate during temperature drop, compare the current decrement rate during temperature drop with the current decrement reference rate during temperature drop stored in the database, obtain the absolute value of the difference between the current decrement rate during temperature drop and the current decrement reference rate during temperature drop, recorded as the current decrement rate deviation during temperature drop; the current decrement rate can reflect the efficiency of the cooling system of the equipment, and the large decrement rate deviation may indicate problems of the cooling system.

[0068] For the reference value of the current decrement rate during temperature drop, in a standardized test environment, the equipment is cooled from a specified high temperature to a cooling temperature, and the current value is recorded, the rate of current decrement, i.e. the amount of current reduction per unit time, is analyzed, multiple tests are performed to ensure consistency, and the average decrement rate is taken as the reference value.

[0069] Install a voltage sensor and connect it to the data recording system, after the temperature reaches a stable temperature, obtain the stable voltage at each sampling time point based on the voltage sampling period, and obtain the voltage standard deviation during temperature stabilization based on the stable voltage at each sampling time point. Low voltage standard deviation indicates stable voltage, increasing the safety of the equipment, stable voltage is crucial for the continuous and safe operation of the equipment.

[0070] For the reference value of the voltage standard deviation during temperature stabilization, when the equipment reaches a temperature stabilization state, measure the voltage value periodically, use these voltage data to calculate the standard deviation, and store the calculated average standard deviation as the reference standard deviation during voltage stabilization in the database.

[0071] All parameters are normalized to eliminate the influence of dimensions, ensuring that each parameter is evaluated on the same scale. Considering the sensitivity of electrical equipment safety to deviations, using nonlinear functions such as exponentials or logarithms can better highlight the impact of different parameters on overall performance. Using the product and exponential form emphasizes the necessity of all parameters being good, so that the poor performance of any one parameter will significantly affect the overall score.

[0072] ;

[0073] where, is the current standard deviation at temperature rise, is the power deviation at temperature rise, is the current decrement rate deviation at temperature drop, is the voltage standard deviation at temperature stability, is the natural constant.

[0074] The current standard deviation and power deviation at temperature rise are processed using exponential functions to highlight their important influence on safety performance. For the current decrement rate deviation at temperature drop, a sigmoid function (logistic function) is used, which allows the impact on performance to be gradual when the deviation changes within a certain range. The voltage standard deviation at temperature stability is processed using a logarithmic function to reduce the speed of its impact on the overall score, but maintain the existence of the impact.

[0075] The calculation formula of the safety performance coefficient of the high temperature bonding machine in normal mode is as follows:

[0076] ;

[0077] where, is the processing function of the normal temperature change data set, is the normal temperature change data set, is the weight factor of , is the processing function of the normal mode electrical safety data, is the normal mode electrical safety data, is the weight factor of , , is the natural constant.

[0078] The weight factors and can be directly obtained from the database, and the weight factors and can be obtained by establishing a risk assessment model, including possible risk events and their impact on equipment operation. Score the probability and severity of each risk event, and assign weights based on these scores.

[0079] In order to manage and call the weight factor when calculating the safety performance coefficient of the high temperature bonding machine in normal mode And A database is designed to store the weight, and the weight value is determined by combining historical data analysis. Through the dictionary structure in Python, a mapping set is created to store these weight factors, and an interface is provided for real-time updating and calling these data, so that the corresponding mode weight factor can be extracted from the database as needed when performing safety performance evaluation, thereby improving the accuracy and operability of the evaluation. In this embodiment, And These processing functions are used to transform the normal temperature change data set and the normal mode electrical safety data into a form that can be used for further analysis. By combining temperature change and electrical safety data, a more comprehensive device safety performance description can be obtained. The allocation of weights reflects the contribution of different safety characteristics to the overall machine safety. The use of natural constant exponential form can amplify the influence of the processed function value on the result, while keeping the function value within a reasonable range to avoid the unreasonable influence of extreme values on the safety performance coefficient.

[0080] Specifically, the emergency cooling data includes the unit time temperature drop value deviation during emergency cooling and the heating part temperature drop gradient deviation during emergency cooling; the process of obtaining the emergency cooling data is as follows: high-precision temperature sensors are installed on the heating part of the high-temperature bonding machine to obtain the temperature change value of the heating part of the high-temperature bonding machine during emergency cooling in real time, the collected temperature data is time-sequenced, an emergency temperature drop curve is constructed, an emergency temperature drop curve is established, the actual value of the emergency temperature drop in unit time is obtained based on the emergency temperature drop curve, the actual value of the emergency temperature drop is compared with the reference value of the emergency temperature drop stored in the database, the absolute value of the difference between the actual value of the emergency temperature drop and the reference value of the emergency temperature drop is obtained, and is recorded as the unit time temperature drop value deviation during emergency cooling. For the reference value of the temperature drop value in unit time during emergency cooling, a series of controlled experimental tests are performed after the initial installation or maintenance of the equipment, the actual temperature drop during emergency cooling is monitored, the test data is analyzed, the average temperature drop value is determined, and the consistency and reliability of the equipment performance are considered to determine a practically achievable reference temperature drop value. The average temperature drop value calculated or tested is used as the reference value in the database.

[0081] The temperature drop rate of each monitoring point is obtained based on the established emergency temperature drop curve, the temperature drop rate of each monitoring point is processed by mean value to obtain the temperature drop gradient of the heating part during emergency cooling, the temperature drop gradient of the heating part during emergency cooling is compared with the reference temperature drop gradient of the heating part during emergency cooling stored in the database, the absolute value of the difference between the temperature drop gradient of the heating part during emergency cooling and the reference temperature drop gradient of the heating part during emergency cooling is obtained, and is recorded as the current decrement rate during emergency cooling. For the temperature drop gradient reference value of the heating part during emergency cooling, a computational fluid dynamics (CFD) or thermodynamic simulation tool is used to simulate the emergency cooling process, the temperature drop gradient of different regions is predicted, or temperature sensors are installed at different parts of the device to perform actual emergency cooling tests, and the temperature drop data of each point is collected. The collected data is statistically analyzed, including calculating the average value and standard deviation of the temperature drop rate of each point, to evaluate the temperature drop uniformity of the entire heating part.

[0082] The unit time temperature drop value deviation during emergency cooling and the temperature drop gradient of the heating part during emergency cooling are recorded as emergency cooling data.

[0083] The unit time temperature drop value deviation during emergency cooling and the temperature drop gradient deviation are normalized to have values in the same order of magnitude, facilitating calculation and comparison. Since the efficiency and uniformity of emergency cooling are extremely important for overall performance, a nonlinear function can be used to emphasize these effects. Suitable nonlinear functions include exponential, logarithmic, and reciprocal functions. A function is designed such that poor performance of any one parameter significantly affects the overall score, ensuring that all key aspects of emergency cooling meet good performance standards.

[0084] ;

[0085] In the formula, is the unit time temperature drop value deviation during emergency cooling, is the temperature drop gradient deviation of the heating part during emergency cooling, is a natural constant.

[0086] The unit time temperature drop value deviation during emergency cooling is processed using an exponential function , so that when is large, it indicates poor cooling efficiency, and has a greater negative impact on performance. For the temperature drop gradient deviation of the heating part during emergency cooling , a sigmoid function (logistic function) is used, so that when changes within a certain range, the impact on the overall score is nonlinear, reflecting the importance of temperature drop gradient uniformity.

[0087] Table 2 Data table of calculation function of emergency cooling data

[0088]

[0089] As can be seen from the data in Table 2, the function value of the calculation function of the emergency cooling data significantly increases with the increase of the unit time temperature drop value deviation and the heating part temperature drop gradient deviation during emergency cooling, reflecting that in the case of larger deviation, the emergency cooling performance is poorer.

[0090] The emergency mode electrical safety data includes the electrical control unit reaction time deviation and the instantaneous current change value deviation during emergency cooling. The process of obtaining the emergency mode electrical safety data is as follows: after the cooling command is sent to the control unit, the actual time of the control unit reaction and the actual instantaneous current change value within the actual time of the control unit reaction are recorded by using a high-precision timing device, and the actual instantaneous current change value is obtained by real-time monitoring and recording through the installation of a current sensor in the electrical system; the actual time of the control unit reaction is compared with the standard reaction time stored in the database to obtain the deviation of the actual time of the control unit reaction from the standard reaction time, which is denoted as the electrical control unit reaction time deviation during emergency cooling. The reference value of the electrical control unit reaction time during emergency cooling is based on the design specifications of the control unit and the performance data provided by the manufacturer to determine the optimal reaction time in theory, or a series of performance tests are conducted during the installation and debugging of the device to measure the actual reaction time of the control unit from receiving the cooling command to executing the command, and the average reaction time is calculated by collecting multiple test data and considering the standard deviation of the data to ensure that the set reference value is not only based on a single test, but also the average value obtained is taken as the standard reference value of the control unit reaction time and is recorded in the database.

[0091] The actual instantaneous current change value is compared with the reference instantaneous current change value stored in the database to obtain the deviation of the actual instantaneous current change value from the reference instantaneous current change value, which is denoted as the instantaneous current change value deviation. The reference instantaneous current change value is predicted according to the design parameters and theoretical model of the electrical system to determine the expected range of instantaneous current change during emergency cooling, or the emergency cooling process is simulated under non-emergency conditions to accurately measure the instantaneous change of current, and the average value and variability of the instantaneous current change are determined by statistical analysis of multiple test data. Based on these data, a reference value of the instantaneous current change that can be achieved in actual operation is set and stored in the database.

[0092] By continuously monitoring and evaluating the reaction time, potential maintenance needs or system failures can be identified, and timely adjustments or repairs can be made to ensure that the control unit can quickly respond in emergency situations, reduce delays, and reduce risks caused by delayed response. Analyzing the change of instantaneous current can help evaluate the performance of the electrical system under emergency conditions and ensure that it does not exceed the safety range. Continuous monitoring of current changes helps to identify abnormal behavior of the electrical system and prevent failures.

[0093] The reaction time deviation of the electrical control unit during emergency cooling and the instantaneous current change value deviation are normalized to the same order of magnitude for easy calculation. In order to highlight the impact of the poor performance of any one parameter on the overall performance, a nonlinear function such as an exponential or logarithmic function can be used, which can amplify the impact of changes in parameter values on the result. By multiplying the functions of the parameters, it is emphasized that the overall performance will be optimal only when all parameters perform well.

[0094] ;

[0095] In the formula, is the reaction time deviation of the electrical control unit during emergency cooling, is the instantaneous current change value deviation, is a natural constant.

[0096] An exponential function is used to process each deviation, where the exponential function will significantly increase the function value when the deviation value is larger, indicating a decrease in performance. A logistic function is used to provide a smoother performance decrease for smaller deviation values.

[0097] The calculation formula of the safety performance coefficient of the high-temperature bonding machine emergency cooling mode is as follows:

[0098] ;

[0099] In the formula, is the calculation function of emergency cooling data, is the emergency cooling data, is the weight factor of is the calculation function of emergency mode electrical safety data, is the emergency mode electrical safety data, is the weight factor of , , , is a natural constant.

[0100] In this embodiment, by combining physical and electrical safety parameters, a comprehensive safety performance index is provided, which helps to accurately evaluate the performance of the device in emergency situations, and emergency cooling data and emergency mode electrical safety data are processed to convert the data into a form suitable for safety performance evaluation. Through the weight factor, the formula can be adjusted according to the different needs of specific device configurations and operating environments.

[0101] The weight factor can be directly obtained from the database, and the database stores​​ and The influence of each type of safety data on the safety of the device, including the severity and frequency of accidents, can be evaluated by analyzing the device's past operation, emergency cooling data, and accident records related to emergency mode electrical safety data. Statistical methods such as regression analysis can be used to quantify the impact of different safety data on the probability of accidents, and the weight factor can be adjusted based on the analysis results.

[0102] In order to manage and call the weight factor when calculating the safety performance coefficient of the high-temperature bonding machine emergency cooling mode and A database is designed to store the weights and determine the weight values based on historical data analysis. By using a dictionary structure in Python, a mapping set is created to store these weight factors, and an interface is provided for real-time updating and calling these data, so that the corresponding mode weight factor can be extracted from the database as needed during safety performance evaluation, thereby improving the accuracy and operability of the evaluation.

[0103] An electronic device, comprising: a processor and a memory, wherein the memory stores computer program instructions, and the computer program instructions, when executed by the processor, cause the processor to perform the performance dynamic test method of the takeover high-temperature bonding machine as described above.

[0104] A computer-readable storage medium for storing a program, wherein the program, when executed by a processor, implements the performance dynamic test method of the takeover high-temperature bonding machine as described above.

[0105] In summary, the present application has at least the following effects:

[0106] It covers temperature changes, electrical safety, and the response time of the control unit, ensuring comprehensive analysis of the safety of the device from multiple angles. By calculating the safety performance coefficients in normal mode and emergency mode, the safety performance of the high-temperature bonding machine in daily operation and emergency situations can be fully evaluated.

[0107] Those skilled in the art will appreciate that embodiments of the application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0108] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 means for functionally implementing the steps listed in the flowchart block or blocks.

[0109] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the function specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 means for functionally implementing the steps listed in the flowchart block or blocks.

[0110] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 means for functionally implementing the steps listed in the flowchart block or blocks.

[0111] While the preferred embodiments of the application have been described, additional variations and modifications can be made to the embodiments described and shown, and it is therefore intended that the application cover any and all variations of the preferred embodiments which fall within the scope of the present application. Accordingly, the appended claims are intended to cover all such modifications and variations as falling within the scope of the application.

[0112] It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application cover the modifications and variations of this application provided they come within the scope of the appended claims and their equivalents.

Claims

1. A dynamic performance testing method for a high-temperature bonding machine for pipe fittings, characterized in that, Includes the following steps: Acquire the dataset of normal temperature changes of the heating part of the bonding machine during normal mode testing of the high temperature bonding machine for pipe fitting, and the normal mode electrical safety data of the electrical control part when controlling the heating part of the bonding machine to perform normal mode testing; The electrical safety data in the normal mode includes the standard deviation of current during temperature rise, the power deviation during temperature rise, the current deceleration rate deviation during temperature drop, and the standard deviation of voltage when the temperature stabilizes. The process of obtaining electrical safety data in normal mode is as follows: During the temperature rise process, the current value at each time sampling point is periodically acquired, and the standard deviation of the current during the temperature rise is obtained based on the current value at each time sampling point. After the temperature rise is completed, the actual power of the heating part is obtained. The actual power of the heating part is compared with the power reference value stored in the database, and the absolute value of the difference between the actual power of the heating part and the power reference value is obtained, which is recorded as the power deviation during the temperature rise. During the temperature drop process, the current value at each time sampling point is periodically acquired, and a current change curve is established to show the change of current value over time. Based on the current change curve, the current decrease per unit time is recorded as the current deceleration rate during temperature drop. The current deceleration rate during temperature drop is compared with the current deceleration reference rate during temperature drop stored in the database, and the absolute value of the difference between the current deceleration rate during temperature drop and the current deceleration reference rate during temperature drop is recorded as the current deceleration rate deviation during temperature drop. After the temperature reaches a stable temperature, the stable voltage at each sampling time point is obtained based on the voltage sampling period, and the standard deviation of the voltage when the temperature is stable is obtained based on the stable voltage at each sampling time point. Acquire emergency cooling data of the high-temperature adhesive machine for pipe fitting in emergency cooling mode and emergency mode electrical safety data of the electrical control part when the heating part of the adhesive machine is tested in emergency mode; Safety performance assessment of high-temperature bonding machine for pipe fitting based on normal temperature change dataset, normal mode electrical safety data, emergency cooling data, and emergency mode electrical safety data.

2. The method for dynamic performance testing of a high-temperature bonding machine for pipe fittings according to claim 1, characterized in that, The safety performance evaluation of the high-temperature bonding machine for pipe fitting, based on ordinary temperature change datasets, ordinary mode electrical safety data, emergency cooling data, and emergency mode electrical safety data, includes: The ordinary temperature change dataset and the ordinary mode electrical safety data are fused to obtain the ordinary mode safety performance coefficient of the high temperature bonding machine. The ordinary mode safety performance coefficient of the high temperature bonding machine is used to represent the safety performance of the high temperature bonding machine for pipe fitting in the ordinary mode. The emergency cooling data and emergency mode electrical safety data are fused together to obtain the safety performance coefficient of the high temperature bonding machine in the emergency cooling mode. The safety performance coefficient of the high temperature bonding machine in the emergency cooling mode is used to represent the safety performance of the high temperature bonding machine for pipe fitting in the emergency cooling mode. The safety performance coefficients of the high-temperature bonding machine in normal mode and emergency cooling mode are analyzed and processed to obtain the safety performance index of the high-temperature bonding machine for pipe assembly. The safety performance index is used to represent the safety performance of the high-temperature bonding machine for pipe assembly in normal mode and emergency cooling mode.

3. The method for dynamic performance testing of a high-temperature bonding machine for pipe fittings according to claim 2, characterized in that, The specific method for obtaining the security performance index is as follows: The safety performance index is obtained by multiplying the safety performance coefficient of the normal mode by the first weighting factor and adding the safety performance coefficient of the emergency cooling mode by the second weighting factor.

4. The method for dynamic performance testing of a high-temperature bonding machine for pipe fittings according to claim 3, characterized in that, The specific method for obtaining the safety performance factor of the high-temperature bonding machine in normal mode is as follows: The ordinary temperature change dataset is processed by a specific function and multiplied by the first weighting factor. This is then combined with the ordinary mode electrical safety data, which is processed by a specific function and multiplied by the second weighting factor. The two datasets are added together, and then an exponential operation is performed using the base of the natural logarithm to obtain the safety performance coefficient of the ordinary mode of the high-temperature bonding machine.

5. The method for dynamic performance testing of a high-temperature bonding machine for pipe fittings according to claim 4, characterized in that, The general temperature change dataset includes temperature change data during heating, temperature change data during cooling, and temperature feature data when the temperature is stable, wherein: The temperature change data during heating includes the temperature rise deviation per unit time and the deviation of the time required to reach a stable temperature. The temperature change data during cooling includes the deviation of temperature drop per unit time and the deviation of the time required to cool down to the cooling temperature. The temperature characteristic data when the temperature is stable includes the temperature standard deviation when the temperature is stable and the temperature distribution uniformity of the heated part.

6. The method for dynamic performance testing of a high-temperature bonding machine for pipe fittings according to claim 5, characterized in that: The process of obtaining temperature change data during heating is as follows: The temperature change value of the heating part of the high temperature bonding machine for pipe assembly is acquired in real time during the heating process. A temperature rise curve is established. The actual temperature rise value per unit time is obtained based on the temperature rise curve. The actual temperature rise value is compared with the temperature rise reference value stored in the database. The absolute value of the difference between the actual temperature rise value and the temperature rise reference value is obtained and recorded as the temperature rise value deviation per unit time during heating. Based on the temperature rise curve, the actual time required to rise to the stable temperature is determined. The actual time required to rise to the stable temperature is compared with the reference time required to rise to the stable temperature stored in the database. The absolute value of the difference between the actual time required to rise to the stable temperature and the reference time required to rise to the stable temperature is recorded as the deviation value of the time required to rise to the stable temperature. The deviation of temperature rise per unit time and the deviation of time required to reach stable temperature during heating are recorded as temperature change data during heating. The process of obtaining temperature change data during cooling is as follows: The temperature change value of the heating part of the high temperature bonding machine for pipe fitting is obtained in real time during the cooling process. A temperature drop curve is established. Based on the temperature drop curve, the actual temperature drop value per unit time is obtained. The actual temperature drop value is compared with the temperature drop reference value stored in the database. The absolute value of the difference between the actual temperature drop value and the temperature drop reference value is recorded as the temperature drop value deviation per unit time during cooling. Based on the temperature drop curve, the actual time required to cool down to the cooling temperature is determined. The actual time required to cool down to the cooling temperature is compared with the reference time required to cool down to the cooling temperature stored in the database. The absolute value of the difference between the actual time required to cool down to the cooling temperature and the reference time required to cool down to the cooling temperature is recorded as the deviation value of the time required to cool down to the cooling temperature. The deviation of the temperature drop per unit time and the deviation of the time required to cool down to the cooling temperature are recorded as the temperature change data during cooling. The process of obtaining temperature characteristic data when the temperature is stable is as follows: The actual stabilized temperature of each sampling point in the heating section is collected based on the set sampling period, and the temperature standard deviation when the temperature is stable is obtained based on the actual stabilized temperature. Based on the set sampling period, the actual stable temperature of each sampling point of the heating part is collected to obtain the average temperature of the heating part after the temperature stabilizes. The ratio of the temperature standard deviation when the temperature stabilizes to the average temperature of the heating part after the temperature stabilizes is recorded as the temperature distribution uniformity of the heating part. The temperature standard deviation and the temperature distribution uniformity of the heated part when the temperature is stable are recorded as the temperature characteristic data when the temperature is stable.

7. The method for dynamic performance testing of a high-temperature bonding machine for pipe fittings according to claim 3, characterized in that, The specific method for obtaining the safety performance factor of the emergency cooling mode of the high-temperature bonding machine is as follows: The emergency cooling data and emergency mode electrical safety data are processed separately using functions, multiplied by the corresponding weighting factors, and then added together. The exponential operation is performed using the base of the natural logarithm to obtain the safety performance coefficient of the emergency cooling mode of the high-temperature bonding machine.

8. The method for dynamic performance testing of a high-temperature bonding machine for pipe fittings according to claim 7, characterized in that, The emergency cooling data includes the temperature drop deviation per unit time during emergency cooling and the temperature drop gradient deviation of the heating part during emergency cooling; The process of obtaining emergency cooling data is as follows: The temperature change value of the heating part of the high temperature bonding machine for pipe fitting is acquired in real time during emergency cooling. An emergency temperature drop curve is established. Based on the emergency temperature drop curve, the actual value of emergency temperature drop per unit time is obtained. The actual value of emergency temperature drop is compared with the emergency temperature drop reference value stored in the database. The absolute value of the difference between the actual value of emergency temperature drop and the emergency temperature drop reference value is recorded as the temperature drop deviation per unit time during emergency cooling. Based on the established emergency temperature drop curve, the temperature drop rate of each set monitoring point is obtained. The average temperature drop rate of each monitoring point is processed to obtain the temperature drop gradient of the heating part during emergency cooling. The temperature drop gradient of the heating part during emergency cooling is compared with the reference temperature drop gradient of the heating part during emergency cooling stored in the database. The absolute value of the difference between the temperature drop gradient of the heating part during emergency cooling and the reference temperature drop gradient of the heating part during emergency cooling is recorded as the current deceleration rate deviation during temperature drop. The temperature drop deviation per unit time and the temperature drop gradient of the heating part during emergency cooling are recorded as emergency cooling data.

9. The method for dynamic performance testing of a high-temperature bonding machine for pipe fittings according to claim 7, characterized in that, The emergency mode electrical safety data includes the deviation of the electrical control unit's response time and the deviation of the instantaneous current change value during emergency cooling; The process of obtaining emergency mode electrical safety data is as follows: The actual time it takes for the control unit to respond after the cooling command is sent, and the actual instantaneous current change during the actual response time, are obtained. The actual response time of the control unit is compared with the standard response time stored in the database to obtain the deviation between the actual response time of the control unit and the standard response time, which is recorded as the response time deviation of the electrical control unit during emergency cooling. The actual instantaneous current change value is compared with the reference instantaneous current change value stored in the database to obtain the deviation between the actual instantaneous current change value and the reference instantaneous current change value, which is recorded as the instantaneous current change value deviation.

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