A method, system, medium and product for monitoring energy consumption anomalies in a tire vulcanization process

Abstract

A method, system, medium, and product for monitoring abnormal energy consumption during tire vulcanization, relating to the field of intelligent monitoring. The method includes: acquiring data on steam supply flow rate, pressure within the vulcanization chamber, and outlet temperature of the steam trap from the intake pipe of the vulcanizing machine during the pressure-holding vulcanization stage; marking the steam supply interval and the condensate discharge interval accordingly, and designating the area between adjacent supply intervals as a pressure natural decay interval; calculating the pressure decay rate of the pressure natural decay interval to assess system sealing, and calculating the synchronization coupling coefficient between the supply and condensate discharge intervals to quantify fluid behavior; determining an invalid penetration supply interval when the synchronization coupling coefficient and cumulative flow percentage meet the invalid penetration condition; and finally determining whether the abnormality is caused by physical leakage or direct discharge from the steam trap based on the pressure decay rate. This application solves the problem that traditional flow monitoring cannot accurately distinguish the root cause of abnormal energy consumption, achieving precise monitoring of steam latent heat utilization and automatic fault attribution.

Description

Technical Field

[0001] This application relates to the field of intelligent monitoring, and in particular to a method, system, medium, and product for monitoring abnormal energy consumption during the tire vulcanization process. Background Technology

[0002] Tire vulcanization is a crucial step in tire manufacturing. Currently, the mainstream vulcanizing medium is saturated steam, and its core mechanism utilizes the latent heat (heat of phase change) released when steam condenses into water within the mold or bladder to heat the tire. To maintain the constant high temperature required for vulcanization, the system typically has a steam trap at the outlet to promptly drain the condensate after the phase change, preventing water accumulation and temperature drops. In actual production, the operating status of the steam trap is often difficult to visually assess. Therefore, effectively monitoring the heat energy utilization during the vulcanization process is key to energy conservation and emission reduction in tire manufacturing.

[0003] To address these issues, relevant technologies typically employ the method of installing flow meters on the steam inlet pipe. Energy consumption is assessed by monitoring the instantaneous and cumulative steam flow entering the vulcanizing machine in real time. Based on a pre-defined baseline value for steam consumption per tire, when the monitored actual steam flow exceeds the baseline value, the system determines that the machine may have a leak or insulation failure and issues an alarm. This method achieves a certain degree of quantitative monitoring of large-scale leaks, helping companies identify obvious pipe damage or complete valve failure, thereby reducing inefficient energy waste.

[0004] However, since steam heating relies primarily on the release of latent heat rather than changes in sensible heat, if the steam trap malfunctions (i.e., steam enters and exits directly without condensation), the inlet flow meter may detect a large amount of steam flowing through, but the energy carried by this steam is not absorbed by the tire. This may cause the inlet flow meter to display a high flow rate, and the temperature sensor to display the normal vulcanization temperature due to being filled with saturated steam. However, the enormous latent heat carried by the steam is not absorbed by the tire but is directly lost through the system, thus reducing the accuracy of monitoring the actual utilization rate of the steam's latent heat. Summary of the Invention

[0005] This application provides a method, system, medium, and product for monitoring abnormal energy consumption during the tire vulcanization process, which can improve the accuracy of automated attribution of abnormal energy consumption during the tire vulcanization process.

[0006] Firstly, this application provides a method for monitoring abnormal energy consumption during the tire vulcanization process, applied to a steam monitoring server. The method includes: acquiring a steam supply flow rate data sequence from the intake pipe of the vulcanizing machine under test during the pressure-holding vulcanization stage, a pressure data sequence within the vulcanization chamber, and a temperature data sequence from the outlet of the steam trap; based on the steam supply flow rate data sequence and the temperature data sequence, marking the steam supply interval and the condensate removal action interval within a continuous monitoring period; using the monitoring time period between adjacent steam supply intervals as the pressure natural decay interval; and calculating the pressure data within the pressure natural decay interval. The absolute value of the slope of the sequence changing over time is used as the pressure holding attenuation rate; the proportion of time overlap between each steam supply interval and the condensate discharge interval in the time domain is used as the synchronization coupling coefficient; when the target steam supply interval meets the preset invalid penetration conditions, the target steam supply interval is determined as an invalid penetration supply interval. The invalid penetration conditions include: the synchronization coupling coefficient is greater than the preset coupling threshold, and the ratio of cumulative steam flow to total steam consumption exceeds the preset abnormal ratio threshold; based on the pressure holding attenuation rate of the pressure natural attenuation interval, the energy consumption anomaly type of the invalid penetration supply interval is determined, and the energy consumption anomaly signal is output.

[0007] By adopting the above technical solution, the steam monitoring server first deconstructs the continuous vulcanization process into a steam supply interval and a pressure natural decay interval. Next, using the non-supply state during the pressure natural decay interval, the steam monitoring server calculates the pressure holding decay rate to quantify the inherent sealing performance of the vulcanizing machine itself, eliminating the interference of inlet pressure supply on leakage detection. Simultaneously, the steam monitoring server quantifies the temporal overlap between inlet and outlet condensation behaviors by calculating the synchronization coupling coefficient. Finally, the steam monitoring server combines inherent sealing performance with dynamic fluid behavior—namely, the pressure holding decay rate and the synchronization coupling coefficient—to identify the causes of high steam consumption. In summary, this solution solves the technical problem of traditional monitoring methods that rely solely on total flow rate and cannot distinguish the root causes of abnormal energy consumption, thus improving the accuracy of monitoring steam latent heat utilization.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, based on the steam supply flow rate data sequence and temperature data sequence, the steam supply interval and the condensate removal action interval are marked within a continuous monitoring period. Specifically, this includes: performing a first-order difference calculation on the temperature data sequence at the outlet of the steam trap to obtain a temperature change rate sequence; identifying the condensate removal start time and condensate removal end time based on the temperature change rate sequence and a preset temperature change threshold; marking the time period between the condensate removal start time and the condensate removal end time as the condensate removal action interval; and marking the period when the steam supply flow rate data sequence is greater than a preset flow rate benchmark value as the steam supply interval.

[0009] By employing the above technical solution, the steam monitoring server processes the temperature data sequence at the outlet of the steam trap, capturing the characteristics of rapid temperature changes. This allows it to define the condensate discharge interval of the steam trap in the time domain, avoiding the problem of static temperature thresholds being affected by ambient temperature drift. Simultaneously, the steam monitoring server uses a preset flow baseline value to filter background noise from the intake pipe, identifying the actual steam supply interval. The steam monitoring server discretizes the continuous monitoring process into independent event segments with clear physical meaning, providing a precise data foundation for subsequent analysis of the spatiotemporal correlation between intake and condensate discharge, and improving the boundary accuracy of the synchronous coupling coefficient calculation.

[0010] In some embodiments of the first aspect, before using the time overlap ratio between each steam supply interval and the condensate removal operation interval in the time domain as the synchronization coupling coefficient, the method further includes: treating each steam supply interval and the condensate removal operation interval that is closest to it on the time axis as associated units; calculating the time difference between the start time of the steam supply interval and the start time of the condensate removal operation interval in each associated unit as the response lag time; when the absolute value of the response lag time is less than a preset associated time window, performing the step of calculating the synchronization coupling coefficient; if the absolute value of the response lag time is greater than or equal to the preset associated time window, then determining that the steam supply interval is an independent supply interval not caused by condensate removal, and not calculating the synchronization coupling coefficient.

[0011] By adopting the above technical solution, before calculating the coupling coefficient, the steam monitoring server first establishes the correlation units between the steam supply interval and the condensate removal interval, and then filters these correlation units, eliminating condensate removal actions that are too far apart on the time axis or do not have a causal relationship thermodynamically, such as condensate removal caused by a delay in the previous round of gas supply. Only when the condensate removal action occurs immediately after the gas supply action and within a reasonable time window does the steam monitoring server perform the synchronous coupling coefficient calculation. In summary, this solution, based on the thermodynamic response delay characteristics, eliminates interference from irrelevant data and improves the robustness of anomaly detection.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, the energy consumption anomaly type of the ineffective penetration supply interval is determined based on the pressure holding attenuation rate of the pressure natural attenuation interval, and an energy consumption anomaly signal is output. Specifically, this includes: obtaining the pressure holding attenuation rate of the pressure natural attenuation interval immediately preceding the ineffective penetration supply interval time sequence; if the pressure holding attenuation rate is greater than or equal to a preset attenuation threshold, the current anomaly type is determined to be a system physical leak, and a first-level alarm signal is output; if the pressure holding attenuation rate is less than the preset attenuation threshold, the current anomaly type is determined to be a functional direct discharge of the steam trap, and a second-level alarm signal is output.

[0013] By adopting the above technical solution, the steam monitoring server, after confirming an invalid penetration supply zone, retrospectively analyzes the pressure decay rate of the adjacent natural pressure decay zone. If the steam monitoring server detects a high pressure decay rate, it indicates that the pressure drops rapidly when the machine is not replenished with gas, which is determined to be a physical leak in the system, and outputs a level one alarm to prompt emergency repair. If the pressure decay rate is low, it indicates that the machine is well sealed, and the steam monitoring server logically deduces that the anomaly is caused by the steam trap failing to close, resulting in functional direct discharge of the steam trap, i.e., only heat energy is lost but the pressure is still maintained. In summary, this solution realizes automated attribution diagnosis of the causes of abnormal energy consumption, thereby improving the accuracy of monitoring the latent heat utilization rate of steam.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, within the natural pressure decay interval, the absolute value of the slope of the pressure data sequence changing with time is calculated as the pressure holding decay rate. Specifically, this includes: obtaining the start time and end time of the natural pressure decay interval; obtaining the fitting start point by delaying a preset denoising time after the start time, obtaining the fitting end point by advancing a preset denoising time before the end time, and extracting the pressure data sequence between the fitting start point and the fitting end point; performing linear regression fitting on the extracted pressure data sequence to obtain a pressure fitting line; and determining the absolute value of the slope of the pressure fitting line as the pressure holding decay rate.

[0015] By adopting the above technical solution, the steam monitoring server, when calculating the pressure holding decay rate, eliminates transient pressure fluctuations caused by valve opening and closing actions at the beginning and end of the interval by delaying and advancing the preset noise reduction time, retaining the data segment in steady-state decay. This method enables the steam monitoring server to extract feature values ​​reflecting the true sealing performance of the system from the raw data containing high-frequency noise from sensors, avoiding errors caused by single-point calculations and improving the anti-interference capability and accuracy of the pressure holding decay rate calculation.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, after calculating the absolute value of the slope of the pressure data sequence changing with time as the pressure attenuation rate, the method further includes: extending the pressure fitting line backward along the time axis to the end time of the target steam supply interval to form a theoretical attenuation baseline; calculating the integral of the absolute value of the difference between the pressure data sequence in the target steam supply interval and the theoretical attenuation baseline as the pressure recovery response area; obtaining the time integral of the steam supply flow rate data sequence in the target steam supply interval as the total steam consumption of the interval; and determining the ratio of the pressure recovery response area to the total steam consumption of the interval as the supply pressurization efficiency index.

[0017] By adopting the above technical solution, the steam monitoring server constructs a theoretical attenuation baseline under no-replenishment conditions and calculates the pressure recovery response area between the actual pressure and this baseline. This area physically characterizes the effective pressure-maintaining work done by the replenished steam. Subsequently, the steam monitoring server compares this effective work with the total steam consumption in the interval to obtain the replenishment pressurization efficiency index. The steam monitoring server uses this index to intuitively quantify the efficiency of converting a unit mass of steam into pressure maintenance efficiency within the sulfurization chamber. In summary, this solution provides an in-depth evaluation of the steam replenishment process from an energy conversion perspective, and can identify inefficient replenishment behaviors that fail to effectively increase or maintain pressure even with a large flow rate.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, when the target steam supply interval meets the preset invalid penetration condition, the target steam supply interval is determined to be an invalid penetration supply interval. Specifically, this includes: when the synchronization coupling coefficient of the target steam supply interval is greater than the preset coupling threshold, and the ratio of the cumulative steam flow to the total steam consumption exceeds the preset abnormal ratio threshold, determining whether the supply boosting efficiency index of the target steam supply interval is less than the preset efficiency threshold; if so, then confirming the target steam supply interval as an invalid penetration supply interval.

[0019] By adopting the above technical solution, after initially screening out suspected abnormal intervals, the steam monitoring server introduces the replenishment pressurization efficiency index as a secondary verification indicator. The steam monitoring server determines that even if the intake and exhaust condensate levels are synchronized, indicating suspected penetration, if the replenishment pressurization efficiency index remains high, it means that although the steam is discharged quickly, it has made sufficient contribution to maintaining pressure, which may be a normal high-load condition. Only when the efficiency index is also lower than the preset efficiency threshold does the steam monitoring server finally confirm the interval as an invalid penetration replenishment interval. In summary, this solution reduces the false alarm rate under complex operating conditions by combining fluid behavior characteristics and energy conversion efficiency for dual verification.

[0020] In a second aspect, this application provides a steam monitoring server, which includes: one or more processors and a memory; the memory is coupled to one or more processors, and the memory is used to store computer program code, which includes computer instructions, and the one or more processors call the computer instructions to cause the steam monitoring server to perform the method described in the first aspect and any possible implementation thereof.

[0021] Thirdly, this application provides a computer-readable storage medium storing computer instructions that, when executed on a steam monitoring server, cause the steam monitoring server to perform the method described in the first aspect and any possible implementation thereof.

[0022] Fourthly, this application provides a computer program product, including a computer program or instructions that, when run on a steam monitoring server, cause the steam monitoring server to perform the method described in the first aspect and any possible implementation thereof.

[0023] It is understood that the steam monitoring server provided in the second aspect, the computer-readable storage medium provided in the third aspect, and the computer program product provided in the fourth aspect are all used to execute the methods provided in the embodiments of this application. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0025] 1. By using a method that marks the steam supply interval and condensate discharge interval based on steam supply flow data sequence and temperature data sequence, and calculates the pressure holding decay rate and synchronous coupling coefficient of the pressure natural decay interval, the static system sealing performance and dynamic fluid penetration behavior can be decoupled and analyzed. This effectively solves the problem in related technologies that relying solely on inlet flow monitoring cannot accurately distinguish whether energy consumption anomalies are caused by pipeline physical leakage or direct discharge failure of steam traps. As a result, it achieves accurate monitoring of the latent heat utilization rate of steam in the tire vulcanization process and accurate identification of the root cause of anomalies.

[0026] 2. By employing the technique of calculating the response lag time between the steam supply interval and the condensation discharge interval, and only calculating the synchronization coupling coefficient when the absolute value of the response lag time is less than the preset correlation time window, the interference of non-causally related condensation discharge actions in the time domain can be eliminated based on the thermodynamic response delay characteristics. This effectively solves the problem of misjudgment caused by the distortion of the calculation of the synchronization between air intake and condensation discharge due to random or delayed condensation discharge behavior in related technologies, thereby improving the robustness and accuracy of the determination of invalid penetration supply intervals.

[0027] 3. By employing a technical approach that compares the pressure decay rate of the pressure natural decay zone immediately preceding the ineffective penetration replenishment zone with a preset decay threshold to determine the type of energy consumption anomaly and output alarm signals of different levels, it is possible to further diagnose whether the anomaly is caused by a pressure loss leakage due to the failure of the system's physical seal or by a non-pressure loss direct discharge due to the failure of the steam trap function. This effectively solves the problem of vague energy consumption anomaly alarms and lack of fault attribution guidance in related technologies, thereby realizing automated hierarchical diagnosis and maintenance guidance for vulcanizing machine fault types. Attached Figure Description

[0028] Figure 1This is a flowchart illustrating a method for monitoring abnormal energy consumption during the tire vulcanization process, as described in an embodiment of this application.

[0029] Figure 2 This is another flowchart illustrating a method for monitoring abnormal energy consumption during the tire vulcanization process, as described in this application.

[0030] Figure 3 This is a schematic diagram of the physical device structure of a steam monitoring server in an embodiment of this application. Detailed Implementation

[0031] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification of this application, the singular expressions “a,” “an,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0032] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0033] This application provides a method for monitoring abnormal energy consumption during the tire vulcanization process. For ease of understanding, the application scenarios of the embodiments of this application are described below.

[0034] In related technologies, excessive energy consumption can be monitored in a crude manner by deploying flow meters at the steam inlet of the vulcanizing machine and setting an alarm threshold for gas consumption. For example, in a tire manufacturing workshop, the monitoring system detected that the instantaneous steam flow rate of a vulcanizing machine was consistently higher than the standard curve, issuing an abnormal energy consumption alarm. After maintenance personnel arrived on site, they first checked the external pipelines for obvious leaks. If no visible leaks were found, they often could only suspect, based on experience, that it was a mold sealing problem or a malfunctioning steam trap. Due to the lack of multi-dimensional judgment criteria, maintenance personnel may need to shut down the machine and check multiple components one by one. Furthermore, when a "steam penetration" fault occurs (i.e., steam is discharged directly without condensation to release latent heat), although the inlet flow rate is high, the machine temperature and pressure readings are normal. This hidden energy waste is often mistakenly identified by the system as normal production fluctuations and ignored, leading to long-term ineffective energy loss.

[0035] The method, system, medium, and product for monitoring abnormal energy consumption during the tire vulcanization process described in this application embodiment utilize a steam monitoring server to jointly analyze time-series data on air intake flow, cavity pressure, and drain valve temperature. This enables refined diagnosis of abnormal energy consumption, not only detecting anomalies but also pinpointing their root causes. In this application, the steam monitoring server collects real-time data from machines undergoing pressure-holding vulcanization, automatically deconstructing the process into two states: steam replenishment and natural pressure decay. When a machine is detected to be experiencing simultaneous and violent drain valve movement during air replenishment, and the cavity pressure is well maintained after air replenishment stops, the steam monitoring server no longer simply reports high flow rate but directly outputs a secondary alarm signal of "drain valve direct discharge / penetration anomaly." Conversely, if the pressure drops extremely rapidly after air replenishment stops, the steam monitoring server will indicate "system physical seal failure," guiding personnel to check pipeline connections.

[0036] As can be seen, by adopting the dual judgment mechanism based on pressure attenuation rate and synchronous coupling coefficient in the embodiments of this application, while realizing real-time monitoring of steam energy consumption in the sulfidation process, it can also effectively solve the technical problem that traditional flow monitoring is difficult to distinguish between "physical leakage" and "functional direct discharge", thereby realizing automated and accurate fault attribution and improving operation and maintenance efficiency.

[0037] The following describes the process of the method provided in this implementation. Please refer to [link / reference]. Figure 1 This is a flowchart illustrating a method for monitoring abnormal energy consumption during the tire vulcanization process in an embodiment of this application.

[0038] S101. Obtain the steam supply flow rate data sequence of the air inlet pipe, the pressure data sequence inside the vulcanizing chamber, and the temperature data sequence of the outlet of the steam trap of the vulcanizing machine under pressure vulcanization during the pressure holding vulcanization stage.

[0039] Among them, the vulcanizing machine to be monitored refers to the tire vulcanizing equipment that has been connected to the IoT monitoring system of the steam monitoring server and is in actual production operation. The equipment transmits sensor data to the steam monitoring server in real time through the communication interface.

[0040] The steam supply flow rate data sequence refers to the set of data formed by arranging the instantaneous steam flow rate values ​​collected by the flow meter installed on the inlet pipe of the vulcanizing machine in chronological order. The data sampling frequency is 1 to 10 times per second, and the data unit is kilograms per second or cubic meters per hour. The pressure data sequence refers to the set of data formed by arranging the instantaneous pressure values ​​collected by the pressure sensor inside the vulcanizing chamber in chronological order, with the sampling frequency synchronized with the flow rate data. The temperature data sequence refers to the set of data formed by arranging the instantaneous temperature values ​​collected by the temperature sensor installed on the return water pipe at the outlet of the steam trap in chronological order, with the sampling frequency also synchronized.

[0041] The steam monitoring server establishes a communication connection with the data acquisition layer of the vulcanization workshop via industrial Ethernet or fieldbus protocols (such as Modbus TCP, OPC UA). When the vulcanizing machine under monitoring enters the pressure-holding vulcanization stage, the steam monitoring server receives a process status signal from the vulcanizing machine control system. This signal indicates that the current vulcanization cycle has completed the temperature and pressure increase and entered the pressure-holding stage. The steam monitoring server initiates the data acquisition task based on this trigger signal. The pressure-holding vulcanization stage refers to the period during the tire vulcanization process when the mold is completely closed, steam or hot medium fills the vulcanization chamber, and constant pressure and temperature are maintained for the rubber crosslinking reaction. This stage is the core time window for energy consumption monitoring, with a typical duration of 8 to 25 minutes.

[0042] The steam monitoring server reads the instantaneous steam flow rate values ​​for the current and subsequent moments from the flow meter in the intake pipe. Each flow rate data point contains two fields: a timestamp and the flow rate value. The data is stored in a buffer queue in chronological order to form a steam supply flow rate data sequence. Simultaneously, the steam monitoring server reads the pressure value at the synchronized timestamp from the pressure sensor in the vulcanizing chamber, forming a pressure data sequence. The steam monitoring server also reads the temperature value at the synchronized timestamp from the temperature sensor at the outlet of the steam trap, forming a temperature data sequence. The three sets of data sequences are aligned using a unified timestamp to ensure a one-to-one correspondence in the time domain.

[0043] The steam monitoring server continuously collects the above three sets of data sequences throughout the pressure holding and vulcanization stage until the pressure holding and vulcanization stage of the machine ends. All data sequences are completely stored in the time series database for subsequent analysis.

[0044] S102. Based on the steam supply flow rate data sequence and temperature data sequence, mark the steam supply interval and condensate removal action interval within the continuous monitoring period.

[0045] The steam supply interval refers to the time period during which a significant and continuous steam flow is detected in the intake pipe. The start and end times of this interval are determined by the abrupt change characteristics of the flow rate values ​​in the flow data sequence. The condensate discharge interval refers to the time period during which the steam trap performs the condensate discharge action. This interval is identified by the significant change characteristics of the steam trap outlet temperature.

[0046] The steam monitoring server employs a dual-channel parallel threshold detection algorithm to mark characteristic intervals in the steam supply flow rate data sequence and temperature data sequence. For marking the steam supply intervals, the steam monitoring server first calculates the background noise level of the steam supply flow rate data sequence. It then extracts the flow rate data from a preset time period before the start of the pressure-holding and vulcanizing stage (e.g., 30 to 60 seconds before start) and calculates its mean and standard deviation. The mean plus three times the standard deviation is used as the preset supply flow rate threshold. The steam monitoring server scans the flow rate data sequence point by point. When the flow rate values ​​at three or more consecutive sampling points exceed the preset supply flow rate threshold, the first time exceeding the threshold is marked as the start time of the steam supply interval. When the flow rate values ​​at three or more consecutive sampling points are below the threshold, the last time exceeding the threshold is marked as the end time of the steam supply interval.

[0047] To mark the condensate removal action interval, the steam monitoring server performs first-order difference calculation on the temperature data sequence to obtain the temperature change rate sequence. When the absolute value of the temperature change rate exceeds the preset temperature change rate threshold (typically 2 to 5 degrees Celsius per second) and the duration exceeds the preset condensate removal duration (typically 2 to 5 seconds), the time period is marked as the condensate removal action interval.

[0048] S103. The monitoring time period between adjacent steam supply intervals shall be taken as the pressure natural decay interval.

[0049] The pressure natural decay interval refers to the time period between two steam replenishments. During this period, the inlet valve is closed, the vulcanization chamber is in a closed state, and the pressure inside the chamber gradually decreases due to natural heat dissipation and condensation, as well as possible minor leaks. The pressure change characteristics in this interval reflect the sealing integrity and heat loss level of the system.

[0050] The steam monitoring server iterates through all the steam supply intervals marked in step S102, arranges them in chronological order, and extracts adjacent interval pairs. For the nth and (n+1)th steam supply intervals in the time series, the steam monitoring server defines the time period between the end time of the nth interval and the start time of the (n+1)th interval as a pressure natural decay interval.

[0051] In practice, to ensure that the interval is indeed in a state of no steam supply, the steam monitoring server needs to verify that all sampled values ​​of the flow data sequence within this time period are lower than the preset flow threshold. If the time span between two steam supply intervals is too short, shorter than the preset minimum decay observation duration, then the interval is marked as an invalid pressure natural decay interval and excluded from subsequent analysis, because the pressure change trend within such a short time window is not statistically significant.

[0052] The steam monitoring server records all valid natural pressure decay intervals as a set of time intervals, each containing two timestamp attributes: start time and end time. This approach is based on the essential logic of the physical process: only pressure drops observed without steam replenishment can truly reflect the system's own pressure-holding capacity; if pressure changes are observed during steam replenishment, the opposing effects of steam replenishment and pressure decay are mixed up, making it impossible to separate the system's inherent leakage characteristics.

[0053] S104. Within the natural pressure decay range, calculate the absolute value of the slope of the pressure data sequence as a function of time, and use it as the pressure decay rate.

[0054] This step specifically includes:

[0055] Obtain the start and end times of the natural pressure decay interval;

[0056] The fitting start point is obtained by delaying the preset denoising time after the start time, and the fitting end point is obtained by advancing the preset denoising time before the end time. The pressure data sequence between the fitting start point and the fitting end point is then extracted.

[0057] Linear regression fitting was performed on the extracted pressure data sequence to obtain the pressure fitting line;

[0058] The absolute value of the slope of the pressure fitting line is determined as the pressure holding attenuation rate.

[0059] Among them, the pressure decay rate refers to the quantitative index of the rate at which the pressure in the vulcanizing cavity decreases over time within the natural pressure decay range. The magnitude of this index directly reflects the sealing performance and heat loss of the system. The pressure fitting line refers to the linear function expression obtained by fitting the extracted pressure data sequence through a linear regression algorithm. The slope of this line represents the linear change trend of pressure over time.

[0060] The steam monitoring server performs a pressure decay rate calculation process for each pressure natural decay interval. Specifically, the steam monitoring server first reads the start and end times from the time attribute of the pressure natural decay interval.

[0061] Due to the propagation of pipeline pressure waves and local turbulence at the moment the intake valve closes, the pressure data at the beginning of the interval exhibits brief unsteady fluctuations. Similarly, the pre-action of the control system before the next gas replenishment start also causes disturbances at the end of the interval. To eliminate the interference of these boundary effects on trend fitting, the steam monitoring server delays the denoising time backward from the starting time to obtain the timestamp of the fitting start point; and advances the denoising time forward from the ending time to obtain the timestamp of the fitting end point.

[0062] The preset denoising duration setting scheme is as follows: by performing time-frequency analysis on the pressure waveforms of multiple normal vulcanization cycles, the decay time constant of the boundary disturbance signal is identified, and twice the time constant is taken as the preset denoising duration to ensure that the intercepted data segment enters the steady-state decay stage.

[0063] The steam monitoring server extracts all pressure samples within a specific time window from the complete pressure data sequence based on the timestamps of the fitting start and end points, forming a pressure subsequence to be fitted. The server applies a least-squares linear regression algorithm to this subsequence, using time as the independent variable and pressure as the dependent variable, to calculate the slope and intercept parameters of the optimal fitted line. Since pressure decreases during natural decay, the slope of the fitted line is negative. The steam monitoring server extracts this slope value and calculates its absolute value, using this absolute value as the pressure decay rate corresponding to the natural decay interval.

[0064] S105. The time overlap ratio between each steam supply interval and the condensate removal action interval in the time domain is used as the synchronization coupling coefficient.

[0065] The synchronization coupling coefficient quantifies the degree of time synchronization between the intake and exhaust actions. A coefficient close to 0 indicates that the two actions are basically non-overlapping, while a coefficient close to 1 indicates that exhaust is continuous during intake. Time overlap in the time domain refers to the portion where two time intervals intersect on the time axis.

[0066] The steam monitoring server iterates through each steam supply interval marked in step S102 and calculates the corresponding synchronization coupling coefficient for each steam supply interval. The specific calculation process is as follows: the steam monitoring server extracts the start time and end time of the current steam supply interval and calculates the total duration of the interval as the denominator.

[0067] The steam monitoring server iterates through all condensate removal action intervals and determines whether each condensate removal action interval overlaps with the current steam supply interval on the time axis. The method for determining time overlap is as follows: if the end time of the condensate removal action interval is later than the start time of the steam supply interval, and the start time of the condensate removal action interval is earlier than the end time of the steam supply interval, then there is a time overlap between the two.

[0068] For overlapping condensate removal / expelling action intervals, the steam monitoring server calculates the overlap duration with the steam supply interval. The overlap duration is equal to the difference between the end time and the start time of the overlapping portion of the two intervals. The steam monitoring server sums the overlap durations of the steam supply interval with all condensate removal / expelling action intervals to obtain the total overlap duration. The steam monitoring server then calculates the ratio of the total overlap duration to the total overlap duration of the steam supply interval to obtain the synchronization coupling coefficient corresponding to that steam supply interval.

[0069] S106. When the target steam supply interval meets the preset invalid penetration conditions, the target steam supply interval is determined to be an invalid penetration supply interval. The invalid penetration conditions include: the synchronous coupling coefficient is greater than the preset coupling threshold, and the ratio of the cumulative steam flow to the total steam consumption exceeds the preset abnormal ratio threshold.

[0070] Among them, the invalid penetration replenishment zone refers to the steam replenishment zone where direct steam discharge has been confirmed, and most of the steam replenished in this zone is discharged from the system without releasing its latent heat. The preset coupling threshold refers to the critical judgment value of the synchronization coupling coefficient; exceeding this value indicates a high degree of synchronization between the air intake and condensation discharge actions. The cumulative steam flow rate refers to the integral value of the flow rate data sequence over time within the target steam replenishment zone, representing the total steam consumption of this replenishment event. Total steam consumption refers to the total steam consumption during the entire pressure holding and vulcanization stage. The preset abnormal proportion threshold refers to the abnormal upper limit of the proportion of a single replenishment amount to the total steam consumption; exceeding this value indicates abnormally concentrated single replenishment.

[0071] Specifically, the steam monitoring server first reads the synchronization coupling coefficient corresponding to the target steam supply interval and compares this coefficient with a preset coupling threshold. The preset coupling threshold is set as follows: the steam monitoring server collects the historical synchronization coupling coefficient distribution of this model under normal production conditions, calculates its mean and standard deviation, and takes the mean plus three times the standard deviation as the preset coupling threshold.

[0072] If the synchronization coupling coefficient is greater than the preset coupling threshold, it indicates that the condensation and decondensation actions are abnormally active during the gas replenishment period, satisfying the first criterion. The steam monitoring server further calculates the cumulative steam flow rate of the target steam replenishment interval, and obtains the total steam mass or volume of the gas replenishment by numerically integrating the flow rate data sequence within the interval.

[0073] The steam monitoring server calculates the total cumulative steam flow rate across all steam supply intervals during the entire pressure-holding vulcanization stage, obtaining the total steam consumption. Next, it calculates the ratio of the cumulative steam flow rate of the target steam supply interval to the total steam consumption. If this ratio exceeds a preset abnormal ratio threshold, it indicates that the single-time air supply volume is abnormally large, satisfying the second criterion. The preset abnormal ratio threshold is set based on the statistical patterns of the number of air supply cycles and the amount of air supplied per cycle during normal vulcanization. If, under normal circumstances, the pressure-holding stage requires several air supply cycles with relatively even distribution, then the proportion of a single air supply volume should not exceed a reasonable upper limit of the total. This upper limit is determined through percentile analysis of historical data, and the highest percentile value is taken as the preset abnormal ratio threshold.

[0074] The steam monitoring server performs a logical AND operation on the two criteria. If and only if both conditions are met simultaneously, the steam monitoring server determines the target steam supply interval as an invalid penetration supply interval and adds an invalid penetration mark to its attribute label.

[0075] S107. Based on the pressure attenuation rate of the pressure natural attenuation range, determine the energy consumption anomaly type of the ineffective penetration supply range and output the energy consumption anomaly signal.

[0076] After identifying an invalid penetration supply interval, the steam monitoring server extracts the pressure holding attenuation rate values ​​corresponding to the pressure natural attenuation intervals before and after that interval. The pressure holding attenuation rate is then compared with a preset attenuation rate benchmark threshold. The preset attenuation rate benchmark threshold is set as follows: a benchmark test is conducted under the condition that the sealing performance of the vulcanizing machine is qualified, the pressure holding attenuation rate of multiple vulcanizing cycles is recorded, the mean and the upper limit of the confidence interval are calculated, and the upper limit value is used as the preset attenuation rate benchmark threshold.

[0077] If the pressure attenuation rate is significantly higher than the preset attenuation rate benchmark threshold, and the multiple of this threshold exceeds the preset attenuation abnormal multiple, it indicates that the pressure loss rate is abnormally fast during the non-gas replenishment stage. The steam monitoring server determines that the energy consumption abnormality type is a physical leakage fault in the system. This fault is usually caused by hardware damage such as aging of sealing rings, pipe cracks, loose flanges, or improper mold closure.

[0078] If the pressure attenuation rate is within the normal range and does not exceed the preset attenuation rate benchmark threshold, it indicates that the sealing of the vulcanization cavity itself is intact. At this time, the cause of the invalid penetration is located as the failure of the steam trap function. The steam monitoring server determines that the abnormal energy consumption type is a direct discharge type of steam trap failure. This failure is caused by the steam trap valve core being stuck in the open position, spring fatigue failure, or valve seat wear leading to incomplete closure.

[0079] If both abnormal pressure attenuation rate and ineffective penetration are detected simultaneously, the steam monitoring server determines it to be a compound fault, indicating that there is both physical leakage and steam trap failure.

[0080] The steam monitoring server generates a structured energy consumption anomaly signal based on the determined type of energy consumption anomaly. This signal includes fields such as fault machine identifier, anomaly type code, anomaly occurrence time, key parameter values, and severity level score. The steam monitoring server sends the energy consumption anomaly signal to the human-machine interface of the central monitoring system via industrial Ethernet, where operators are alerted through pop-ups, audible and visual alarms, or color coding.

[0081] In this embodiment, by using a method that marks the steam supply interval and condensate discharge interval based on steam supply flow data sequence and temperature data sequence, and calculates the pressure holding decay rate and synchronous coupling coefficient of the pressure natural decay interval, the static system sealing performance and dynamic fluid penetration behavior can be decoupled and analyzed. This effectively solves the problem in related technologies that relying solely on inlet flow monitoring cannot accurately distinguish whether abnormal energy consumption is due to physical leakage in the pipeline or failure of the steam trap. As a result, it achieves accurate monitoring of the latent heat utilization rate of steam in the tire vulcanization process and accurate identification of the root cause of abnormalities.

[0082] The above embodiments focus on describing how energy consumption anomalies are classified and monitored by deconstructing vulcanization process data and utilizing two core indicators: pressure attenuation rate and synchronization coupling coefficient. In practical applications, to cope with the complex noise environment and nonlinear thermodynamic response characteristics of industrial sites, it is often necessary to perform more refined verification of the temporal correlation between intake and exhaust condensation, thereby further improving the robustness and diagnostic accuracy of energy consumption monitoring during tire vulcanization.

[0083] Based on the above embodiments, the method provided in this embodiment will be described in further detail below. Please refer to... Figure 2 This is another flowchart illustrating a method for monitoring abnormal energy consumption during the tire vulcanization process in an embodiment of this application.

[0084] S201. Obtain the steam supply flow rate sequence of the air inlet pipe, the pressure data sequence inside the vulcanizing chamber, and the temperature data sequence at the outlet of the drain valve of the vulcanizing machine under pressure holding stage.

[0085] This step is similar to the description of step S101 in the above embodiment, and will not be repeated here.

[0086] S202. Based on the temperature data sequence, mark the condensate drainage action interval within the continuous monitoring period, specifically including:

[0087] The temperature change rate sequence of the steam trap outlet is obtained by performing first-order difference calculation on the temperature data sequence.

[0088] The start and end times of condensation drainage are identified based on the temperature change rate sequence and a preset temperature change threshold.

[0089] The time interval between the start and end of the coagulation drainage process is marked as the coagulation drainage action interval.

[0090] The first-order difference calculation refers to the difference operation between the temperature values ​​of two adjacent sampling points in the temperature data sequence to obtain the temperature change at that moment. The temperature change rate sequence refers to the data set formed by arranging the temperature changes obtained through the first-order difference calculation in chronological order. The preset temperature change threshold is the critical value of the temperature change rate used to determine whether the steam trap should be opened for condensate drainage. The setting scheme is as follows: analyze the historical temperature change rate data during normal operation of the steam trap, calculate the average and standard deviation of the temperature change rate during operation, subtract one standard deviation from the average as the condensate drainage start threshold, and add one standard deviation to the negative value of the average as the condensate drainage end threshold. The condensate drainage start moment is the moment when the temperature change rate suddenly rises and exceeds the positive preset temperature change threshold. The condensate drainage end moment is the moment when the temperature change rate changes from a positive value to a negative value and the absolute value exceeds the negative preset temperature change threshold.

[0091] The steam monitoring server executes this step after acquiring the temperature data sequence. Specifically, the steam monitoring server performs a first-order difference calculation on the temperature data sequence point by point. It subtracts the temperature value of the i-th sampling point from the temperature value of the (i-1)-th sampling point and divides by the sampling time interval to obtain the temperature change rate sequence. The steam monitoring server scans the temperature change rate sequence point by point. When the temperature change rate abruptly changes from a negative value or a small positive value to exceed a preset positive temperature change threshold, this moment is recorded as the start time of condensation removal. When the temperature change rate moves from a positive value into a negative value region and the absolute value of the negative value exceeds a preset negative temperature change threshold, this moment is recorded as the end time of condensation removal. The steam monitoring server marks the time period between the start and end times of condensation removal as the condensation removal action interval and assigns a unique identifier.

[0092] S203. Mark the time period when the steam supply flow rate data sequence is greater than the preset flow rate benchmark value as the steam supply interval.

[0093] The preset flow benchmark value is used to distinguish the flow threshold between the actual steam supply state and the pipeline quiescent state. The setting scheme is as follows: collect the air intake pipeline flow data as a baseline sample when the vulcanizing machine is not working or during the quiescent period, calculate the mean and standard deviation of the baseline sample, and add three to five times the standard deviation to the mean as the preset flow benchmark value.

[0094] After acquiring the steam supply flow rate data sequence, the steam monitoring server executes this step in parallel with step S202. Specifically, the steam monitoring server reads or calculates in real time the preset flow rate benchmark value corresponding to the vulcanizing machine from the configuration parameter library, and then scans the steam supply flow rate data sequence point by point.

[0095] When the steam monitoring server detects that the flow rate values ​​at several consecutive sampling points (typically three to five sampling points) exceed the preset flow rate benchmark, the system determines that it will begin the steam replenishment operation, recording the timestamp corresponding to the first sampling point exceeding the threshold as the start time of this steam replenishment interval. The steam monitoring server continues to scan the flow rate data sequence, and when it detects that the flow rate values ​​at several consecutive sampling points have all dropped below the preset flow rate benchmark, it determines that this steam replenishment operation will end, recording the timestamp corresponding to the last sampling point exceeding the threshold as the end time of this steam replenishment interval. The steam monitoring server traverses the steam replenishment flow rate data sequence throughout the entire pressure holding and vulcanization stage, identifying all steam replenishment intervals that meet the conditions.

[0096] S204. The monitoring time period between adjacent steam supply intervals shall be taken as the pressure natural decay interval.

[0097] S205. Within the natural pressure decay range, calculate the absolute value of the slope of the pressure data sequence as a function of time, and use it as the pressure decay rate.

[0098] Steps S204 and S205 are similar to those described in steps S103 and S104 in the above embodiments, and will not be repeated here.

[0099] S206. Each steam supply interval and the nearest exhaust / condensate action interval on the time axis are respectively used as related units.

[0100] Among them, the correlation unit refers to a paired data structure consisting of a steam supply interval and its nearest condensate discharge action interval on the time axis. This data structure is used to quantitatively analyze the spatiotemporal correlation between specific steam supply behavior and condensate discharge behavior of steam traps.

[0101] After marking the condensate removal and steam supply intervals in steps S202 and S203 respectively, the steam monitoring server further establishes interval pairing relationships. Specifically, the steam monitoring server traverses all marked steam supply intervals and, for each steam supply interval, calculates the time difference between its start time and the start times of all condensate removal intervals. The steam monitoring server uses the absolute value of the time difference as a distance metric and finds the condensate removal interval that minimizes this distance metric. The steam monitoring server groups this steam supply interval with the nearest selected condensate removal interval into an association unit, assigns a pairing identifier to this association unit, and stores the pairing information in the association table.

[0102] In practice, the steam monitoring server uses a time-axis scanning algorithm to optimize the pairing process: Since the steam supply interval and the condensate removal action interval are arranged in chronological order, the steam monitoring server maintains two pointers pointing to the current steam supply interval to be paired and the candidate condensate removal action interval, respectively. By comparing the timestamp relationship, the pointer positions are gradually advanced to avoid repeatedly calculating the distance of all interval pairs.

[0103] After the steam monitoring server completes the pairing of all steam supply intervals, it generates a complete set of associated units. Each associated unit in this set contains a steam supply interval identifier, a condensate discharge action interval identifier, time boundary information between the two, and a distance metric.

[0104] S207. Calculate the time difference between the start time of steam supply in the steam supply interval and the start time of condensate discharge in the condensate discharge action interval in each associated unit, and use it as the response lag time.

[0105] The response lag time refers to the time interval between the steam supply action and the steam trap condensate discharge action. This parameter is used to determine whether there is a reasonable causal response relationship between the two. Under normal circumstances, after the steam enters, it needs to go through a condensation process to accumulate enough condensate to trigger the steam trap. The response lag time is a positive value.

[0106] After completing step S206 to establish the associated unit, the steam monitoring server performs this step to calculate the response lag time for each associated unit. Specifically, the steam monitoring server extracts the start time of the steam replenishment interval and the start time of the condensate removal interval from the data structure of the associated unit, calculates the time difference between the start time of condensate removal and the start time of replenishment, and retains the positive or negative sign of this time difference as the response lag time.

[0107] The steam monitoring server stores the calculated response lag time as an attribute field of the associated unit. A positive response lag time indicates that gas is supplied before condensate discharge, which conforms to the normal thermodynamic process logic; a negative response lag time indicates that the condensate discharge action of the steam trap occurs before the current gas supply, and this condensate discharge behavior is actually caused by an earlier gas supply or other heat source, and there is no direct causal relationship between the two; a response lag time close to zero indicates that gas supply and condensate discharge are highly synchronized, which is a typical characteristic of steam direct discharge caused by steam trap failure.

[0108] After the steam monitoring server completes the response lag time calculation for all associated units, it uses these time parameters to determine the validity of the association, filtering out pairing relationships with unreasonable time logic, and ensuring that the calculation of the synchronization coupling coefficient is based on real causal relationships rather than accidental time coincidences.

[0109] S208. When the absolute value of the response lag time is less than the preset associated time window, perform the step of calculating the synchronization coupling coefficient.

[0110] The preset correlation time window refers to the time threshold used to determine whether there is an effective time domain correlation between the steam supply interval and the condensate discharge interval. The preset correlation time window setting scheme is as follows: based on the thermodynamic response characteristics of the sulfidation process, analyze the typical delay time distribution from the time the steam enters the sulfidation chamber to the action of the steam trap under normal operating conditions, calculate the mean and standard deviation of the distribution, and add two to three times the standard deviation to the mean as the upper limit of the preset correlation time window.

[0111] After completing step S207 to calculate the response lag time of each associated unit, the steam monitoring server performs this step to determine the validity of the association for each associated unit. Specifically, the steam monitoring server extracts the response lag time and calculates its absolute value, comparing it with a preset association time window. When the absolute value is less than the preset association time window, it is determined that the associated unit has a reasonable time association relationship, a valid association mark is added to it, and it is added to the queue for calculating the synchronization coupling coefficient.

[0112] S209. If the absolute value of the response lag time is greater than or equal to the preset associated time window, the steam supply interval is determined to be an independent supply interval not caused by condensate discharge, and the synchronization coupling coefficient is not calculated.

[0113] When the absolute value of the response lag time is greater than or equal to the preset associated time window, the steam monitoring server determines that there is no reasonable temporal causal relationship between the steam supply interval and the condensate discharge action interval, adds an independent supply tag to the steam supply interval, and sets its synchronization coupling coefficient field to null.

[0114] In the subsequent invalid penetration determination, the steam monitoring server adopts different determination logic for independent replenishment intervals, and instead analyzes the trend of replenishment pressurization efficiency index or pressure holding attenuation rate to ensure that no potential energy consumption anomalies in independent replenishment intervals are missed.

[0115] S210. The time overlap ratio between each steam supply interval and the condensate discharge interval in the time domain is used as the synchronization coupling coefficient.

[0116] S211. When the target steam supply interval meets the preset invalid penetration conditions, the target steam supply interval is determined to be an invalid penetration supply interval. The invalid penetration conditions include: the synchronous coupling coefficient is greater than the preset coupling threshold, and the ratio of cumulative steam flow to total steam consumption exceeds the preset abnormal ratio threshold.

[0117] Steps S210 and S211 are similar to those described in steps S105 and S106 in the above embodiments, and will not be repeated here.

[0118] Optionally, in some embodiments, the steam monitoring server can also extend the pressure fitting line backward along the time axis to the end time of the target steam supply interval to form a theoretical attenuation baseline; calculate the integral of the absolute value of the difference between the pressure data sequence in the target steam supply interval and the theoretical attenuation baseline as the pressure recovery response area; obtain the time integral of the steam supply flow rate data sequence in the target steam supply interval as the total steam consumption of the interval; and determine the ratio of the pressure recovery response area to the total steam consumption of the interval as the supply pressurization efficiency index.

[0119] When the synchronization coupling coefficient of the target steam supply interval is greater than the preset coupling threshold, and the ratio of cumulative steam flow to total steam consumption exceeds the preset abnormal ratio threshold, it is further determined whether the supply boosting efficiency index of the target steam supply interval is less than the preset efficiency threshold; if so, the target steam supply interval is confirmed as an invalid penetration supply interval.

[0120] S212. Obtain the pressure holding decay rate of the pressure natural decay interval immediately preceding the invalid penetration supply interval timing.

[0121] After determining the invalid penetration replenishment interval, the steam monitoring server proceeds to the energy consumption anomaly type diagnosis stage to execute this step. Specifically, the steam monitoring server reads the start time of the invalid penetration replenishment interval, searches in reverse chronological order in the set of marked pressure natural decay intervals, and locates the pressure natural decay interval whose end time is equal to or closest to the start time of the invalid penetration replenishment interval. This interval reflects the system's pressure maintenance capability before the occurrence of steam direct discharge anomaly.

[0122] The steam monitoring server verifies the continuity of the pressure natural decay interval and the invalid penetration replenishment interval on the time axis, confirming that there are no other steam replenishment intervals or missing data segments between them. The steam monitoring server reads the calculated and stored pressure decay rate value from the attribute data of the pressure natural decay interval.

[0123] The pressure holding attenuation rate reflects the natural pressure decay rate of the vulcanization chamber before the occurrence of an ineffective penetration event. The physical meaning of this value is as follows: if the pressure holding attenuation rate is within the normal range, it indicates that the system is well sealed and the ineffective penetration phenomenon is mainly caused by the failure of the steam trap; if the pressure holding attenuation rate is abnormally high, it indicates that there is a physical leak in the system itself and the direct steam discharge phenomenon is caused by both seal failure and valve failure.

[0124] S213. If the pressure attenuation rate is greater than or equal to the preset attenuation threshold, the current abnormality type is determined to be a system physical leak, and a first-level alarm signal is output.

[0125] The preset attenuation threshold is a critical value for the pressure attenuation rate used to distinguish between normal sealing and physical leakage. The preset attenuation threshold is set as follows: when the sealing performance acceptance test or periodic calibration is completed on the vulcanizing machine, a standard pressure test is performed under the condition that the components are intact. The pressure attenuation rate of multiple test cycles is recorded, and the preset attenuation threshold is set according to its mean and standard deviation.

[0126] System physical leakage refers to a failure mode in which static sealing fails due to reasons such as aging of seals or damage to pipelines, causing steam to be discharged directly from the system through the steam trap without being fully condensed.

[0127] The Level 1 alarm signal refers to the highest level of energy consumption anomaly alarm. This signal indicates that there is a functional fault in the system that causes a large amount of latent heat of vapor to be wasted but does not affect the sealing safety, and it needs to be prioritized for maintenance.

[0128] After obtaining the pressure holding attenuation rate in step S212, the steam monitoring server performs this step to determine the anomaly type. Specifically, the steam monitoring server compares the obtained pressure holding attenuation rate value with a preset attenuation threshold. When the pressure holding attenuation rate is greater than or equal to the preset attenuation threshold, it indicates that the cavity pressure drops rapidly even during the non-gas replenishment phase, suggesting a physical leakage path in the system. Therefore, even if ineffective penetration is also present, the root cause is attributed to a more serious physical leakage problem.

[0129] The steam monitoring server encodes the anomaly type as a physical system leak, generates a level one alarm signal containing fields such as the faulty machine number, type code, timestamp, and key parameters, and sends it to the central monitoring system via industrial Ethernet. This triggers the highest priority alarm and displays the fault details on the interface, while simultaneously writing the record to the fault log database.

[0130] S214. If the pressure attenuation rate is less than the preset attenuation threshold, the current abnormality type is determined to be a direct discharge of the steam trap, and a secondary alarm signal is output.

[0131] Among them, functional direct discharge of steam traps refers to the phenomenon of steam directly penetrating and discharging due to the inability of the steam trap to close properly, even when the sealing integrity of the vulcanization chamber is good. The second-level alarm signal is the next most severe energy consumption anomaly alarm, indicating a problem with reduced thermal efficiency in the system, but without significant pressure leakage risk, and can be addressed during planned maintenance.

[0132] After obtaining the pressure attenuation rate in step S212, the steam monitoring server determines that the sealing performance of the vulcanization system is within the normal range when the pressure attenuation rate is less than the preset attenuation threshold. The server also determines that the natural pressure attenuation rate does not exceed a reasonable range, thus confirming normal sealing performance of the vulcanization system. Furthermore, it is inferred that the root cause of the abnormal energy consumption in this invalid penetration supply section is the failure of the steam trap. That is, steam enters the cavity but is directly discharged by the steam trap without sufficient condensation to release latent heat. This is a non-pressure-loss-related penetration anomaly that only occurs during gas replenishment.

[0133] Therefore, the steam monitoring server infers that there is direct steam discharge from the vulcanization system within this invalid penetration supply interval, and encodes the current anomaly type as functional direct discharge from the steam trap. The steam monitoring server generates a secondary alarm signal and sends it to the monitoring system; the data structure of this signal is similar to that of the primary alarm signal.

[0134] In this embodiment, by using the correlation filtering method based on the response lag time of the steam supply interval and the condensate discharge interval, and introducing the supply pressurization efficiency index to perform secondary verification of the invalid penetration supply interval, the interference of condensate discharge actions that are not thermodynamically causally related can be eliminated, and inefficient supply behavior can be identified from the perspective of energy conversion efficiency. This effectively solves the problem of false alarms caused by random condensate discharge or high-load gas supply under complex operating conditions, thereby achieving a robust improvement in the judgment of energy consumption anomalies and a refined classification and diagnosis of fault types.

[0135] The steam monitoring server in the embodiments of this invention is described below from the perspective of hardware processing. Please refer to [link / reference]. Figure 3 This is a schematic diagram of the physical device structure of a steam monitoring server in an embodiment of this application.

[0136] It should be noted that, Figure 3 The structure of the steam monitoring server shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0137] like Figure 3 As shown, the steam monitoring server includes a CPU 301, which can perform various appropriate actions and processes according to a program stored in the read-only memory ROM 302 or a program loaded from the storage section 308 into the random access memory RAM 303, such as performing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An I / O interface 305 is also connected to the bus 304.

[0138] The following components are connected to I / O interface 305: input section 306 including audio input devices, push-button switches, etc.; output section 307 including a liquid crystal display (LCD) and audio output devices, indicator lights, etc.; storage section 308 including a hard disk, etc.; and communication section 309 including a network interface card such as a LAN (Local Area Network) card, modem, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0139] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program / instructions carried on a computer-readable medium, the computer program / instructions containing computer program / instructions for performing the methods shown in the flowcharts. In such embodiments, the computer program / instructions can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by CPU 301, it performs the various functions defined in the present invention.

[0140] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0141] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, program segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those shown in the drawings.

[0142] Specifically, the steam monitoring server in this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, it implements the method for monitoring abnormal energy consumption in the tire vulcanization process provided in the above embodiment.

[0143] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the steam monitoring server described in the above embodiments; or it may exist independently and not assembled into the steam monitoring server. The storage medium carries one or more computer programs that, when executed by a processor of the steam monitoring server, cause the steam monitoring server to implement the method for monitoring abnormal energy consumption during the tire vulcanization process provided in the above embodiments.

[0144] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0145] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0146] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for monitoring abnormal energy consumption during tire vulcanization, characterized in that, Applied to a steam monitoring server, the method includes: Acquire the steam supply flow rate sequence of the air inlet pipe, the pressure data sequence inside the vulcanizing chamber, and the temperature data sequence at the outlet of the steam trap of the vulcanizing machine under pressure during the pressure holding and vulcanizing stage. Based on the steam supply flow rate data sequence and the temperature data sequence, the steam supply interval and the condensate removal action interval are marked within the continuous monitoring period. The monitoring time period between adjacent steam supply intervals is taken as the pressure natural decay interval; Within the natural pressure decay range, the absolute value of the slope of the pressure data sequence as a function of time is calculated and used as the pressure decay rate. The time overlap ratio between each steam supply interval and the condensate removal action interval in the time domain is used as the synchronization coupling coefficient. When the target steam supply interval meets the preset invalid penetration condition, the target steam supply interval is determined to be an invalid penetration supply interval. The invalid penetration condition includes: the synchronization coupling coefficient is greater than the preset coupling threshold, and the ratio of cumulative steam flow to total steam consumption exceeds the preset abnormal ratio threshold. Based on the pressure decay rate of the pressure natural decay range, determine the energy consumption anomaly type of the invalid penetration supply range and output the energy consumption anomaly signal.

2. The method according to claim 1, characterized in that, The step of marking the steam supply interval and the condensate removal operation interval within a continuous monitoring period based on the steam supply flow rate data sequence and the temperature data sequence specifically includes: A first-order difference calculation was performed on the temperature data sequence at the outlet of the steam trap to obtain the temperature change rate sequence. The start and end times of condensation drainage are identified based on the temperature change rate sequence and the preset temperature change threshold. The time period between the start time of the drainage and the end time of the drainage is marked as the drainage action interval; The time periods in which the steam supply flow rate data sequence is greater than a preset flow rate benchmark value are marked as steam supply intervals.

3. The method according to claim 2, characterized in that, Before using the time overlap ratio between each of the steam replenishment intervals and the condensate removal operation intervals in the time domain as the synchronization coupling coefficient, the method further includes: Each of the steam supply intervals and the nearest exhaust / condensate action interval on the time axis are respectively regarded as associated units; Calculate the time difference between the start time of the steam supply interval and the start time of the condensate discharge interval in each of the associated units, and use it as the response lag time. When the absolute value of the response lag time is less than the preset associated time window, the step of calculating the synchronization coupling coefficient is performed; If the absolute value of the response lag time is greater than or equal to the preset associated time window, then the synchronization coupling coefficient is not calculated.

4. The method according to claim 2, characterized in that, The step of determining the energy consumption anomaly type of the ineffective penetration replenishment interval based on the pressure holding attenuation rate of the pressure natural attenuation interval, and outputting an energy consumption anomaly signal, specifically includes: Obtain the pressure holding attenuation rate of the pressure natural attenuation interval immediately preceding the invalid penetration replenishment interval timing; If the pressure holding attenuation rate is greater than or equal to the preset attenuation threshold, the current anomaly type is determined to be a system physical leak, and a first-level alarm signal is output. If the pressure attenuation rate is less than the preset attenuation threshold, the current abnormality type is determined to be a direct discharge of the steam trap, and a secondary alarm signal is output.

5. The method according to claim 1, characterized in that, Within the natural pressure decay range, the absolute value of the slope of the pressure data sequence changing over time is calculated as the pressure decay rate, specifically including: Obtain the start and end times of the natural pressure decay interval; A fitting start point is obtained by delaying the preset denoising time after the start time, and a fitting end point is obtained by advancing the preset denoising time before the end time. The pressure data sequence between the fitting start point and the fitting end point is then extracted. A linear regression fit is performed on the extracted pressure data sequence to obtain a pressure fitting line; The absolute value of the slope of the pressure fitting line is determined as the pressure holding attenuation rate.

6. The method according to claim 5, characterized in that, After calculating the absolute value of the slope of the pressure data sequence changing over time as the pressure holding decay rate, the method further includes: The pressure fitting line is extended backward along the time axis to the end of the target steam supply interval to form a theoretical attenuation baseline. The integral of the absolute value of the difference between the pressure data sequence within the target steam replenishment interval and the theoretical attenuation baseline is calculated as the pressure recovery response area; The time integral of the steam supply flow rate data sequence within the target steam supply interval is used as the total steam consumption of the interval. The ratio of the pressure recovery response area to the total steam consumption in the interval is determined as the replenishment and boosting efficiency index.

7. The method according to claim 6, characterized in that, When the target steam supply interval meets the preset invalid penetration condition, the target steam supply interval is determined to be an invalid penetration supply interval, specifically including: When the synchronization coupling coefficient of the target steam supply interval is greater than the preset coupling threshold, and the ratio of cumulative steam flow to total steam consumption exceeds the preset abnormal ratio threshold, it is determined whether the supply boosting efficiency index of the target steam supply interval is less than the preset efficiency threshold. If so, then the target steam supply interval is confirmed as an invalid penetration supply interval.

8. A steam monitoring server, characterized in that, The steam monitoring server includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the steam monitoring server to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium storing computer instructions, characterized in that, When the computer instructions are executed on the steam monitoring server, the steam monitoring server performs the method as described in any one of claims 1-7.

10. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are run on the steam monitoring server, the steam monitoring server performs the method as described in any one of claims 1-7.

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