A method and system for detecting the stress of a tension spring

Abstract

The application relates to the technical field of fault diagnosis, and provides a tension spring stress detection method and system, which comprises the following steps: in the normal operation state of an elevator door system, the normal working range of a tension spring stress value, the normal working range of a door machine driving motor working current value, and the expected correlation characteristics between the tension spring stress value and the door machine driving motor working current value are determined in advance; during the operation of the elevator door system, the tension spring stress value and the door machine driving motor working current value are synchronously collected; when the tension spring stress value exceeds the upper limit value of the normal working range, the fault source type of the tension spring stress abnormality is judged according to the tension spring stress value, the door machine driving motor working current value and the expected correlation characteristics determined in advance, and a tension spring stress abnormality judgment result is obtained. The application has the advantages of improving the accuracy of fault diagnosis, effectively preventing systematic damage, and improving the operation safety of the elevator.

Description

Technical Field

[0001] The present invention relates to the technical field of fault diagnosis, and in particular to a tension spring stress detection method and system. Background Art

[0002] In elevator door system operation, the tension spring is a key component, and its stress state directly affects the door's smooth opening and closing, as well as overall operational safety. Existing technologies typically monitor the spring's stress value using a stress sensor and assess its operating status based on pre-set judgment logic.

[0003] However, when an elevator door system faces an abnormal increase in external operating resistance, such as increased friction on the door rail due to foreign matter or changes in lubrication, the stress in the tension spring increases accordingly. Traditional stress detection methods struggle to accurately distinguish whether this stress anomaly is due to a decline in the spring's performance or increased external operating resistance. This lack of differentiation can cause the system to issue misleading warnings, preventing maintenance personnel from addressing the root cause of the problem during troubleshooting. This can ultimately cause other key mechanical components, such as the door operator's reducer, to fail due to prolonged abnormal loads, and expose the tension spring to an abnormally high, sustained stress state, posing a potential safety hazard to elevator operation.

[0004] In view of the above problems, the existing technology is in urgent need of improvement. Summary of the Invention

[0005] In order to address the deficiencies of the prior art, the present application provides a tension spring stress detection method and system, which has the advantage of being able to accurately distinguish the fault source type of abnormal tension spring stress, avoid misjudgment, and improve the accuracy of fault diagnosis, thereby effectively preventing systemic damage and improving elevator operation safety.

[0006] This application provides a method for detecting tension spring stress, the technical points of which are:

[0007] A method for detecting tension spring stress, comprising:

[0008] Under normal operating conditions of the elevator door system, the normal operating range of the tension spring stress value, the normal operating range of the door machine drive motor operating current value, and the expected correlation characteristics between the tension spring stress value and the door machine drive motor operating current value are predetermined;

[0009] During the operation of the elevator door system, the tension spring stress value and the door machine drive motor working current value are synchronously collected;

[0010] When the tension spring stress value exceeds the predetermined upper limit of the normal working range, the fault source type of the tension spring stress abnormality is judged based on the tension spring stress value, the working current value of the door machine drive motor and the predetermined expected correlation characteristics, and the tension spring stress abnormality judgment result is obtained.

[0011] Through the above scheme, the fault source type of abnormal tension spring stress can be distinguished to avoid misjudgment, thereby improving the accuracy of fault diagnosis and effectively preventing systemic damage caused by external resistance.

[0012] To further solve the problem, the present application further proposes that when the tension spring stress value exceeds a predetermined upper limit of a normal working range and the operating current value of the door machine drive motor exceeds a predetermined upper limit of a normal working range, the fault source type of the tension spring stress anomaly is determined, and the steps of obtaining the tension spring stress anomaly determination result include:

[0013] Obtain the rate of change of the tension spring stress value from the normal working range to the abnormal peak value to obtain the abnormal change rate of the tension spring; obtain the duration of the tension spring stress value in the abnormal state to obtain the abnormal duration of the tension spring;

[0014] Obtain the rate of change of the door machine drive motor operating current value from the normal operating range to the abnormal peak value to obtain the current abnormal change rate; obtain the duration of the door machine drive motor operating current value in the abnormal state to obtain the current abnormal duration;

[0015] According to the abnormal change rate of the tension spring, the abnormal duration of the tension spring, the abnormal change rate of the current and the abnormal duration of the current, it is judged that the fault source type of the abnormal tension spring stress is transient compensation of the internal drive system or continuous loading of the external running resistance.

[0016] Through the above scheme, by combining the rate of change and duration of the tension spring stress and the motor current, it is possible to more accurately identify whether the fault source is internal transient compensation or external continuous resistance, further improving the precision of diagnosis.

[0017] To improve the solution, the present application further proposes that, under normal operating conditions of the elevator door system, the steps of predetermining the normal operating range of the tension spring stress value, the normal operating range of the door machine drive motor operating current value, and the expected correlation characteristics between the tension spring stress value and the door machine drive motor operating current value include:

[0018] When the elevator door system is operating normally, the tension spring stress value and the door machine drive motor operating current value are continuously collected;

[0019] When the event of abnormal increase in external running resistance or transient compensation of the internal drive system does not occur, the collected tension spring stress value and door machine drive motor operating current value are used as baseline data;

[0020] Based on a preset period, trend analysis is performed on the baseline data accumulated within the preset period to identify the changing trends of the tension spring stress value and the door machine drive motor operating current value;

[0021] When the change trend shows that the tension spring stress value and the door machine drive motor operating current value both show a continuous and slow change in the same direction, the normal working range of the tension spring stress value, the normal working range of the door machine drive motor operating current value, and the expected correlation characteristics between the tension spring stress value and the door machine drive motor operating current value are adjusted and determined according to the change trend.

[0022] Through the above scheme, dynamic adaptive adjustment of the normal working range and related characteristics is achieved, so that the system can adapt to environmental changes or component performance degradation during long-term operation and maintain diagnostic accuracy.

[0023] To further solve the problem, the present application also proposes that, based on a preset period, trend analysis of the baseline data accumulated within the preset period is performed to identify the changing trends of the tension spring stress value and the door machine drive motor operating current value, including the following steps:

[0024] Based on a preset period, trend analysis is performed on the baseline data accumulated within the preset period to identify the changing trends of the tension spring stress value and the door machine drive motor operating current value;

[0025] Analyze the morphological characteristics of the changing trend; morphological characteristics include periodic characteristics or long-term cumulative characteristics;

[0026] Based on the morphological characteristics, it is determined whether the changing trend is caused by environmental factors or by the degradation of component performance.

[0027] Through the above solution, by analyzing the morphological characteristics of the trend, it is possible to further distinguish the root cause of the parameter change, whether it is environmental factors or component degradation, providing a more accurate basis for maintenance.

[0028] To improve the solution, this application also proposes that the steps of adjusting and determining the normal operating range of the tension spring stress value, the normal operating range of the door machine drive motor operating current value, and the expected correlation characteristics between the tension spring stress value and the door machine drive motor operating current value include:

[0029] Based on the change trend, calculate the target normal operating range of the tension spring stress value, the target normal operating range of the door crane drive motor operating current value, and the target expected correlation characteristics between the tension spring stress value and the door crane drive motor operating current value;

[0030] Comparing the difference between the target normal operating range and the normal operating range of the currently set tension spring stress value, the difference between the target normal operating range of the door machine drive motor operating current value and the normal operating range of the currently set door machine drive motor operating current value, and the difference between the target expected correlation characteristic and the expected correlation characteristic between the currently set tension spring stress value and the door machine drive motor operating current value, to obtain a range difference comparison result;

[0031] When any difference in the range difference comparison results exceeds a preset adjustment start threshold, incremental adjustments are made to the normal operating range of the currently set tension spring stress value, the normal operating range of the currently set door machine drive motor operating current value, and the expected correlation characteristic between the currently set tension spring stress value and the door machine drive motor operating current value at a preset adjustment step size;

[0032] Between two incremental adjustments, there is a preset adjustment period;

[0033] Continue to make incremental adjustments until all differences in the range difference comparison results are less than the corresponding preset adjustment completion threshold.

[0034] Through the above scheme, a dynamic calibration mechanism based on difference comparison and incremental adjustment is provided, which ensures that the normal working range and associated characteristics can adapt to system changes smoothly and continuously, avoiding abrupt adjustments.

[0035] To further solve the problem, the present application further proposes that the steps of incrementally adjusting the normal working range of the currently set tension spring stress value, the normal working range of the currently set door machine drive motor operating current value, and the expected correlation characteristics between the currently set tension spring stress value and the door machine drive motor operating current value with a preset adjustment step size include:

[0036] Calculate the product of each difference in the range difference comparison result and the corresponding preset proportional coefficient to obtain a preset adjustment step size;

[0037] The normal working range of the currently set tension spring stress value, the normal working range of the currently set door machine drive motor working current value, and the expected correlation characteristics between the currently set tension spring stress value and the door machine drive motor working current value are incrementally adjusted with an adjustment step size.

[0038] Through the above scheme, an adaptive step size calculation based on the difference and proportional coefficient is introduced, which makes the adjustment process more flexible and accurate, and can be reasonably adjusted according to the actual deviation size.

[0039] To improve the solution, the present application further proposes that the steps of calculating the product of each difference in the range difference comparison result and the corresponding preset proportional coefficient to obtain the preset adjustment step size include:

[0040] Get the absolute value of each difference in the range difference comparison result;

[0041] According to the absolute value of the difference, the corresponding proportional coefficient is obtained from the preset lookup table;

[0042] Multiply the absolute value of the difference by the proportional coefficient to obtain the preset adjustment step size.

[0043] With the above solution, the proportional coefficient is obtained by looking up a table, which simplifies the process of determining the adjustment step size and improves efficiency and configurability.

[0044] To further solve the problem, the present application further proposes that the step of obtaining the corresponding proportional coefficient from a preset lookup table includes:

[0045] According to the absolute value of the difference, two preset difference values ​​adjacent to the absolute value of the difference are located in a preset lookup table, and proportional coefficients corresponding to the two adjacent preset difference values ​​are found;

[0046] According to the relative position relationship between the absolute value of the difference and two preset difference values, a proportional coefficient corresponding to the absolute value of the difference is obtained by interpolation calculation.

[0047] Through the above solution, interpolation calculation is adopted to make the acquisition of the proportional coefficient smoother and more accurate, avoiding the step adjustment that may be caused by simple table lookup.

[0048] To improve the solution, the present application further proposes that the steps of obtaining the proportional coefficient corresponding to the absolute value of the difference through interpolation calculation include:

[0049] According to the relative position relationship of the absolute value of the difference between two adjacent preset difference values, a linear interpolation method is used to calculate the corresponding proportional coefficient.

[0050] Through the above scheme, the use of linear interpolation method is clarified to ensure the simplicity and effectiveness of calculation.

[0051] A tension spring stress detection system is used to perform tension spring stress detection, comprising:

[0052] A normal range determination module is used to predetermine the normal operating range of the tension spring stress value, the normal operating range of the door machine drive motor operating current value, and the expected correlation characteristics between the tension spring stress value and the door machine drive motor operating current value under the normal operating state of the elevator door system;

[0053] The numerical synchronous acquisition module is used to synchronously acquire the tension spring stress value and the door machine drive motor operating current value during the operation of the elevator door system;

[0054] The tension spring abnormality judgment module is used to determine the fault source type of the tension spring stress abnormality based on the tension spring stress value, the working current value of the door machine drive motor and the predetermined expected correlation characteristics when the tension spring stress value exceeds the predetermined upper limit of the normal working range, and obtain the tension spring stress abnormality judgment result.

[0055] Through the above solution, a system for implementing a tension spring stress detection method is provided. Through modular design, it is easy to implement and deploy, and the integration and reliability of the system are improved.

[0056] In summary, the present application provides a method and system for detecting tension spring stress, which predetermines the normal operating range and expected correlation characteristics of the tension spring stress value and the door machine drive motor operating current value under normal operating conditions of the elevator door system, and synchronously collects data during operation. When the tension spring stress value exceeds the upper limit, the fault source type is judged based on multi-dimensional data, so that the fault source type of abnormal tension spring stress can be accurately distinguished, misjudgment can be avoided, the accuracy of fault diagnosis can be improved, systemic damage can be effectively prevented, and the safety of elevator operation can be improved. It has the advantages of being able to accurately distinguish the fault source type of abnormal tension spring stress, avoid misjudgment, improve the accuracy of fault diagnosis, thereby effectively preventing systemic damage and improving the safety of elevator operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a flow chart of a method for detecting tension spring stress in one embodiment of the present invention;

[0058] Figure 2 This is one of the flow charts of a method for detecting tension spring stress in another embodiment of the present invention;

[0059] Figure 3 This is a second flow chart of a method for detecting tension spring stress in another embodiment of the present invention;

[0060] Figure 4 This is a third flow chart of a method for detecting tension spring stress in another embodiment of the present invention;

[0061] Figure 5 This is a fourth flow chart of a method for detecting tension spring stress in another embodiment of the present invention;

[0062] Figure 6 This is a system block diagram of a tension spring stress detection system in another embodiment of the present invention;

[0063] Description of reference numerals:

[0064] 1. Tension spring stress detection system; 11. Normal range determination module; 12. Numerical synchronization acquisition module; 13. Tension spring abnormality judgment module. DETAILED DESCRIPTION

[0065] The technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. The components of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for which protection is claimed, but merely represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of this application.

[0066] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance.

[0067] In conventional elevator door systems, when an abnormal increase in tension spring stress occurs during operation, it's difficult to accurately distinguish whether the abnormality is due to a decline in the spring's inherent performance or an increase in external operating resistance. This lack of differentiation can cause the system to issue misleading warnings, preventing maintenance personnel from addressing the root cause of the problem. This can ultimately lead to the failure of other key mechanical components, such as the door operator's reducer, due to prolonged abnormal loads. This can also expose the tension spring to an abnormally high, sustained stress state, posing a potential safety hazard to elevator operation.

[0068] In this regard, the present application proposes a method for detecting tension spring stress, combining Figure 1 Shown, including:

[0069] S1, under the normal operating state of the elevator door system, predetermine the normal operating range of the tension spring stress value, the normal operating range of the door machine drive motor operating current value, and the expected correlation characteristics between the tension spring stress value and the door machine drive motor operating current value;

[0070] S2, during the operation of the elevator door system, synchronously collects the tension spring stress value and the door machine drive motor working current value;

[0071] S3, when the tension spring stress value exceeds the predetermined upper limit of the normal working range, the fault source type of the tension spring stress abnormality is determined according to the tension spring stress value, the working current value of the door machine drive motor and the predetermined expected correlation characteristics, and the tension spring stress abnormality judgment result is obtained.

[0072] The normal operating range of tension spring stress values ​​refers to the range of stress values ​​expected under normal, trouble-free operation of the elevator door system. This range can be determined through statistical analysis of historical data, expert experience, or system model simulation. For example, upper and lower limits can be set by long-term monitoring of stress data during normal operation and calculating its average and standard deviation. This provides a benchmark for subsequent determination of abnormal tension spring stress. The normal operating range of the door drive motor operating current values ​​refers to the range of operating current values ​​expected under normal operation of the elevator door system. This range can be determined using similar methods as for tension spring stress values, such as by monitoring the current fluctuation range of the motor under normal load. This provides a benchmark for subsequent determination of abnormal motor load conditions. The expected correlation between tension spring stress values ​​and door drive motor operating current values ​​refers to the inherent, predictable relationship between tension spring stress values ​​and door drive motor operating current values ​​under normal operation of the elevator door system or under specific abnormal operating conditions. This characteristic can be established using mathematical models, empirical curves, or lookup tables. For example, regression analysis can be used to establish a functional relationship between the two, or experimental data can be used to plot a scatter plot and fit a trend line. This allows for comprehensive analysis of both data types and helps distinguish different fault sources. Synchronous data acquisition involves acquiring both the spring stress and the door operator drive motor operating current at the same time or within a very short time interval. This acquisition method can be implemented using dual-channel data acquisition devices, high-speed data buses, or timestamp alignment technologies. For example, by configuring sensors and data acquisition units to ensure consistent sampling frequencies and synchronized time stamping, the goal is to ensure temporal consistency between the two data types, providing an accurate data foundation for subsequent joint analysis. Determining the fault source type of abnormal spring stress involves identifying the specific cause or category of the abnormal spring stress. This determination can be achieved using methods such as rule-based reasoning, pattern recognition, or machine learning classification. For example, using pre-set logical rules, the interaction between spring stress and motor current can be used to distinguish between a spring problem and an external resistance problem. This improves the accuracy of fault diagnosis and avoids misdiagnosis.

[0073] In some preferred embodiments, the method is implemented as follows: First, during initial operation or after overhaul of the elevator door system, the system enters a baseline data acquisition mode. In this mode, stress sensors mounted on the tension springs and current sensors integrated into the door drive motor controller continuously collect tension spring stress and door drive motor operating current values. This data is transmitted to a data processing unit, which performs statistical analysis on the data, such as calculating the mean, standard deviation, and maximum and minimum values ​​over a large number of normal door opening and closing cycles, to determine the normal operating ranges of the tension spring stress and door drive motor operating current values. The data processing unit also analyzes historical data between the two and establishes a mathematical model reflecting their linkage, such as a linear regression equation or a polynomial fit curve, as the expected correlation characteristic. During routine operation of the elevator door system, the stress sensors and current sensors continuously and synchronously collect real-time data at a high frequency and transmit this data to the data processing unit. If the data processing unit detects that the real-time tension spring stress value exceeds the upper limit of the preset normal operating range, it immediately triggers an abnormality analysis process. During this process, the data processing unit simultaneously obtains the current operating current value of the door machine drive motor and inputs it, along with the real-time tension spring stress value, into a pre-established mathematical model for comparison. If the comparison results show that both the tension spring stress value and the door machine drive motor operating current value have increased abnormally, and the relationship between the two conforms to the external resistance increase pattern indicated by the expected correlation characteristics, the data processing unit determines that the fault source type is continuous loading of external operating resistance. Conversely, if the tension spring stress value increases abnormally, but the door machine drive motor operating current value remains within the normal range or does not change significantly, and does not conform to the expected correlation characteristics, the data processing unit determines that the fault source type is the performance degradation of the tension spring itself. Ultimately, this judgment result is sent to the elevator control system or remote monitoring platform for maintenance personnel to carry out targeted processing.

[0074] Optional, combined Figure 2 As shown, in S3, when the tension spring stress value exceeds the predetermined upper limit of the normal working range and the operating current value of the door machine drive motor exceeds the predetermined upper limit of the normal working range, the fault source type of the tension spring stress abnormality is determined, and the steps of obtaining the tension spring stress abnormality determination result include:

[0075] S31, obtaining the rate of change of the tension spring stress value from the normal working range to the abnormal peak value, and obtaining the abnormal change rate of the tension spring; obtaining the duration of the tension spring stress value in the abnormal state, and obtaining the abnormal duration of the tension spring;

[0076] S32, obtaining a rate of change of the working current value of the door machine drive motor from a normal operating range to an abnormal peak value, and obtaining a current abnormality change rate; obtaining a duration of the working current value of the door machine drive motor in an abnormal state, and obtaining a current abnormality duration;

[0077] S33: Determine, based on the abnormal change rate of the tension spring, the abnormal duration of the tension spring, the abnormal change rate of the current, and the abnormal duration of the current, whether the fault source of the abnormal tension spring stress is transient compensation of the internal drive system or continuous loading of the external running resistance.

[0078] The abnormal spring change rate refers to the rate of change when the spring stress value rapidly or slowly reaches an abnormal peak value from the normal operating range. This value can be obtained through time series analysis of continuously collected spring stress values, for example, by calculating the ratio of the difference between adjacent sampling points to the time interval. Its purpose is to reflect the urgency and dynamic characteristics of the spring stress anomaly. The abnormal spring duration refers to the length of time the spring stress value remains abnormal after exceeding the upper limit of the normal operating range. This value can be calculated by recording the time point when the spring stress value first exceeds the upper limit and the approximate time point when it last returns to the normal range. Its purpose is to assess the persistence and stability of the spring stress anomaly. The abnormal current change rate refers to the rate of change when the operating current value of the door operator drive motor rapidly or slowly reaches an abnormal peak value from the normal operating range. This value can be obtained through time series analysis of continuously collected door operator drive motor operating current values, for example, by calculating the ratio of the difference between adjacent sampling points to the time interval. Its purpose is to reflect the response speed of the door operator drive motor in adjusting its output to overcome resistance. Abnormal current duration refers to the length of time the door drive motor's operating current remains abnormal after exceeding the upper limit of its normal operating range. This duration can be calculated by recording the time the door drive motor's operating current first exceeds the upper limit and the approximate time it last returns to the normal range. Its purpose is to assess the duration of the door drive motor's high-load condition. Internal drive system transient compensation refers to the rapid, short-term, high-power output or torque adjustment made by the elevator door system's internal drive mechanism, such as the door drive motor or its control unit, to overcome transient, short-term operating resistance. This can manifest as a rapid increase and then a rapid decrease in the spring stress and door drive motor operating current over a short period of time. Continuous external operating resistance refers to the persistent resistance acting on the door during operation due to factors such as the external environment or component wear, such as increased friction in the door rail or door jamming. This can manifest as the spring stress and door drive motor operating current remaining at a high level or slowly increasing for an extended period of time.

[0079] In some preferred embodiments, when the elevator door system detects that both the tension spring stress value and the door operator drive motor operating current value simultaneously exceed their respective upper limits of the normal operating range, a data processing unit may be activated to perform further analysis. This data processing unit may be an embedded controller, such as an ARM-based microprocessor. First, the data processing unit acquires a high-frequency, real-time data stream from the connected stress and current sensors. To determine the abnormal rate of change of the tension spring, the data processing unit may record the tension spring stress value at a preset sampling period (e.g., 10 milliseconds), calculate the difference between the current value and the previous value within the normal operating range, and divide the difference by the corresponding time interval to obtain the instantaneous rate of change. The duration of the tension spring abnormality can be determined by recording the timestamp of the first time the tension spring stress value exceeds the upper limit and continuously monitoring until it returns to the normal range or the maximum monitoring time is reached. Similarly, the data processing unit acquires the door operator drive motor operating current value at the same sampling frequency and calculates the abnormal current rate of change and the duration of the current abnormality. Once these four dynamic characteristic data items are acquired, the data processing unit inputs them into a pre-trained classification model, which can be a rule-based expert system or a lightweight machine learning model such as a support vector machine or decision tree. The model outputs a judgment based on a combination of the input's rate of change and duration. For example, if the model identifies that both the tension spring stress value and the door operator drive motor operating current value increase rapidly (e.g., the rate of change exceeds a preset threshold A) within a very short period of time (e.g., less than 500 milliseconds) and the duration of the abnormal state is also very short (e.g., less than 1 second), it is determined to be transient compensation of the internal drive system. Conversely, if both values ​​increase slowly (e.g., the rate of change is less than a preset threshold B) and the duration is long (e.g., more than 3 seconds), it is determined to be continuous loading of the external operating resistance. In this way, the system can distinguish complex dual abnormality situations based on the dynamic characteristics of actual operating data.

[0080] Optional, combined Figure 3 As shown, in S1, when the elevator door system is in normal operation, the steps of predetermining the normal working range of the tension spring stress value, the normal working range of the door machine drive motor operating current value, and the expected correlation characteristics between the tension spring stress value and the door machine drive motor operating current value include:

[0081] S11, when the elevator door system is in normal operation, continuously collect the tension spring stress value and the door machine drive motor working current value;

[0082] S12, when the event of abnormal increase of external running resistance or the event of transient compensation of the internal drive system does not occur, the collected tension spring stress value and the door machine drive motor operating current value are used as baseline data;

[0083] S13, based on a preset period, performing trend analysis on the baseline data accumulated within the preset period to identify the change trend of the tension spring stress value and the door machine drive motor operating current value;

[0084] S14. When the change trend shows that the tension spring stress value and the door machine drive motor operating current value both show a continuous slow change in the same direction, adjust and determine the normal working range of the tension spring stress value, the normal working range of the door machine drive motor operating current value, and the expected correlation characteristics between the tension spring stress value and the door machine drive motor operating current value according to the change trend.

[0085] Baseline data refers to the spring stress values ​​and door operator drive motor operating current values ​​collected when the elevator door system is operating normally and is not subject to external abnormal resistance or internal transient compensation events. This ensures that the data used for subsequent trend analysis is pure and truly reflects long-term changes in the system under stable conditions, thereby preventing abnormal events from interfering with the assessment of the normal operating range. A preset period refers to the time window used to accumulate baseline data and conduct trend analysis. This can be a fixed interval, such as daily, weekly, or monthly, or a period triggered when the data volume reaches a certain threshold. The goal is to provide sufficient data for effective trend analysis while balancing the timeliness of data updates with the consumption of computing resources. Trend analysis involves statistical or algorithmic processing of the baseline data accumulated during the preset period to identify patterns or directions in the temporal changes in the spring stress values ​​and door operator drive motor operating current values. Specifically, moving averages, linear regression, exponential smoothing, or more complex machine learning algorithms can be used to identify long-term drift, periodic fluctuations, or specific patterns in the data. The goal is to detect gradual changes in normal operating parameters caused by environmental factors or slow degradation of component performance during long-term system operation. The trend of change refers to the specific direction of the spring stress values ​​and the door operator drive motor operating current values ​​over time, as revealed by trend analysis. Specifically, this can manifest as a continuous increase, a continuous decrease, periodic fluctuations, or stability. Its purpose is to serve as a basis for determining whether the normal operating range needs to be adjusted. In particular, when these values ​​display a sustained, slow, and unidirectional change, it indicates that the system baseline state has drifted. Sustained, slow, and unidirectional change refers to the spring stress values ​​and the door operator drive motor operating current values ​​changing in the same direction (for example, simultaneously increasing or decreasing) at a slow and steady rate over a period of time. This is different from sudden, sharp fluctuations or changes in the opposite direction. The purpose is to identify gradual drifts in the system baseline state caused by environmental factors (such as temperature and humidity changes) or long-term component wear and aging (such as spring fatigue and decreased motor efficiency). These drifts require dynamic adjustments to the normal operating range to accommodate them. Adjustment and determination refers to correcting and updating the normal working range of the tension spring stress value, the normal working range of the door machine drive motor operating current value, and the expected correlation characteristics between the two based on the identified change trend. Specifically, the normal range and correlation characteristics can be redefined by calculating a new mean, standard deviation or regression model parameters. The purpose is to enable the predetermined normal working range to dynamically adapt to the benchmark drift that occurs during the long-term operation of the elevator door system, thereby improving the accuracy and reliability of the judgment of tension spring stress anomaly.

[0086] In some preferred embodiments, the present application is implemented as follows: During normal operation of the elevator door system, high-precision stress sensors and current sensors are configured to continuously collect tension spring stress values ​​and door drive motor operating current values. This data is acquired in real time at a frequency of 100 times per second by a data acquisition unit, such as an embedded controller, and transmitted to a data storage module, such as a non-volatile memory. A data processing module continuously monitors these data streams. When the system detects no abnormal door jamming or transient high current surges in the door drive motor, the currently collected tension spring stress and door drive motor operating current values ​​are marked as valid baseline data and stored in a dedicated baseline data buffer. Abnormal events can be detected by setting a threshold for the instantaneous rate of change of stress or current. For example, if the instantaneous rate of change of stress exceeds 0.5 N / mm / ms, an abnormal event is considered to have occurred. Based on a preset period, such as every 24 hours, a background analysis service or algorithm module is triggered. This module extracts all baseline data accumulated over the past 24 hours from the baseline data buffer. The module then performs linear regression analysis on these data to calculate the average drift slope of the spring stress values ​​and the door operator drive motor operating current values. The moving average and standard deviation of the data are also calculated to smooth short-term fluctuations and identify long-term trends. The analysis module further examines the calculated drift slopes of the spring stress values ​​and the door operator drive motor operating current values. If both slopes are non-zero, have the same direction, and their absolute values ​​are less than a preset "slow change" threshold (for example, a change of no more than 0.01 N / mm or 0.005 A per hour), the system determines that there is a sustained, slow, and consistent change in the same direction. Once this sustained, slow, and consistent change is identified, the system uses the calculated drift slopes to predict expected baseline values ​​for the spring stress values ​​and the door operator drive motor operating current values ​​over a period of time. Based on these predicted values, the system recalculates and updates the normal operating ranges for the spring stress values ​​and the door operator drive motor operating current values, for example, to the new mean ±3 standard deviations. At the same time, the system refits the regression model between the spring stress value and the door operator drive motor operating current value based on the new data, thereby adjusting and determining the new expected correlation characteristics. These new ranges and characteristics are stored and used for subsequent spring stress anomaly judgments.

[0087] Optionally, based on a preset period, the step of performing trend analysis on the baseline data accumulated within the preset period to identify the change trend of the tension spring stress value and the door machine drive motor operating current value includes:

[0088] Based on a preset period, trend analysis is performed on the baseline data accumulated within the preset period to identify the changing trends of the tension spring stress value and the door machine drive motor operating current value;

[0089] Analyze the morphological characteristics of the changing trend; morphological characteristics include periodic characteristics or long-term cumulative characteristics;

[0090] Based on the morphological characteristics, it is determined whether the changing trend is caused by environmental factors or by the degradation of component performance.

[0091] Morphological features refer to the specific patterns or structures exhibited by data trends in a time series. These can be identified using time series analysis methods such as Fourier transforms, wavelet analysis, or autocorrelation function analysis. Their purpose is to reveal the underlying patterns of trend change. Periodic features refer to patterns in data trends that recur at fixed or nearly fixed time intervals. Specifically, they can be identified through spectral analysis or seasonal decomposition methods, such as daily, weekly, or annual recurring patterns. Their purpose is to distinguish changes caused by external cyclical influences. Long-term cumulative features refer to persistent, non-periodic cumulative changes in data trends over a longer time span. Specifically, they can be identified through linear regression, exponential smoothing, or cumulative sum analysis, such as a sustained, slow rise or fall. Their purpose is to reflect the gradual aging or wear of internal system components. Environmental factors refer to conditions external to the elevator door system that are not caused by changes in the component's own performance but can affect its operating parameters. Specifically, they can include temperature, humidity, dust accumulation, detergent residue, or seasonal variations. Their purpose is to identify the impact of external interference on system operation. Among them, component performance degradation refers to the performance degradation of key mechanical or electrical components inside the elevator door system due to long-term use, wear or aging. Specifically, it may include tension spring fatigue, door machine drive motor bearing wear, increase in reducer gear clearance or sensor drift; its purpose is to identify the root cause of internal system failures.

[0092] In some preferred embodiments, the present application is implemented as follows: First, the system continuously collects the tension spring stress values ​​and the door motor drive motor operating current values ​​during normal operation of the elevator door system and accumulates these values ​​as baseline data. For example, data can be collected every minute, and baseline data can be accumulated for a month. Next, trend analysis is performed on this accumulated baseline data based on a preset period, such as a week or a month. This trend analysis can use statistical methods such as moving average, exponential smoothing, or linear regression to identify the overall changing trends of the tension spring stress values ​​and the door motor drive motor operating current values. Furthermore, the system analyzes the morphological characteristics of these identified changing trends. For example, if Fourier transform or wavelet analysis reveals that the changing trends of the tension spring stress values ​​and the door motor drive motor operating current values ​​show obvious 24-hour periodic fluctuations, this can be identified as a periodic feature. This periodic feature may be related to the elevator's operating frequency at different times of day, the day-night variation in ambient temperature, or the periodic operation of the building's internal air conditioning system. For example, if cumulative sum analysis or long-term linear fitting reveals that the tension spring stress and door operator drive motor operating current values ​​exhibit a sustained, slow upward trend over several months, this can be identified as a long-term cumulative characteristic. This long-term cumulative characteristic may be related to the gradual decline in component performance, such as fatigue of the tension spring material, wear of the door operator drive motor bearings, or slight deformation of the door rail. Finally, based on the morphological characteristics analyzed, the system can determine the root cause of the changing trend. For example, if a periodic characteristic is identified, the system can determine that the trend is primarily due to environmental factors, such as seasonal temperature fluctuations or daily fluctuations in passenger volume. If a long-term cumulative characteristic is identified, the system can determine that the trend is primarily due to component performance degradation, such as aging of the tension spring or decreased efficiency of the door operator drive motor. In this way, the system can distinguish normal fluctuations caused by the external environment from performance degradation caused by internal component wear, providing a more accurate basis for subsequent parameter adjustments and maintenance decisions.

[0093] Optionally, the step of adjusting and determining a normal operating range of the tension spring stress value, a normal operating range of the door machine drive motor operating current value, and an expected correlation characteristic between the tension spring stress value and the door machine drive motor operating current value includes:

[0094] Based on the change trend, calculate the target normal operating range of the tension spring stress value, the target normal operating range of the door crane drive motor operating current value, and the target expected correlation characteristics between the tension spring stress value and the door crane drive motor operating current value;

[0095] Comparing the difference between the target normal operating range and the normal operating range of the currently set tension spring stress value, the difference between the target normal operating range of the door machine drive motor operating current value and the normal operating range of the currently set door machine drive motor operating current value, and the difference between the target expected correlation characteristic and the expected correlation characteristic between the currently set tension spring stress value and the door machine drive motor operating current value, to obtain a range difference comparison result;

[0096] When any difference in the range difference comparison results exceeds a preset adjustment start threshold, incremental adjustments are made to the normal operating range of the currently set tension spring stress value, the normal operating range of the currently set door machine drive motor operating current value, and the expected correlation characteristic between the currently set tension spring stress value and the door machine drive motor operating current value at a preset adjustment step size;

[0097] Between two incremental adjustments, there is a preset adjustment period;

[0098] Continue to make incremental adjustments until all differences in the range difference comparison results are less than the corresponding preset adjustment completion threshold.

[0099] Among them, the change trend refers to the analysis of the tension spring stress values ​​and the door machine drive motor working current values ​​collected during the long-term operation of the elevator door system. The two identified show a pattern of continuous and slow changes in the same direction. It can be identified by statistical regression analysis, moving average analysis or machine learning models. Its purpose is to provide a directional basis for the adaptive adjustment of system parameters; the target normal operating range refers to the ideal working range that the tension spring stress values ​​and the door machine drive motor working current values ​​should maintain in the future based on the identified change trend, obtained by calculation or model prediction. It can be achieved by dynamic calculation based on trend prediction algorithm or derivation of expert system rule base. Its purpose is to set a clear terminal for parameter adjustment. Point state; target expected correlation characteristics refer to the ideal corresponding relationship or function model between the tension spring stress value and the door machine drive motor working current value obtained by calculation or model prediction based on the identified change trend. It can be determined by methods such as historical data fitting, machine learning regression analysis or physical model correction. Its purpose is to ensure that the two key parameters can still maintain a coordinated and consistent working state after adjustment; range difference comparison results refer to comparing the calculated target normal working range with the normal working range of the tension spring stress value set by the current system, and comparing the target normal working range of the door machine drive motor working current value with the normal working range of the currently set door machine drive motor working current value, and at the same time comparing the target After comparing the expected correlation characteristics with the expected correlation characteristics between the currently set tension spring stress value and the door machine drive motor working current value, the quantified deviation values ​​can be expressed by indicators such as absolute difference, relative percentage difference or mean square error. Its purpose is to accurately measure the gap between the current system parameters and the ideal target; the preset adjustment start threshold refers to a minimum allowable deviation value set for each difference in the range difference comparison result before parameter adjustment. Only when any difference exceeds this threshold will the system start the adjustment process. It can be set by experience value, based on system stability test or determined through simulation optimization. Its purpose is to avoid unnecessary frequent adjustments to small fluctuations, thereby ensuring the accuracy of system adjustment. Stability; The preset adjustment step size refers to the fixed or dynamic value by which the currently set parameter value is modified in each incremental adjustment operation. It can be determined by a fixed value, a proportional coefficient based on the size of the difference, or an adaptive algorithm. Its purpose is to control the amplitude of each adjustment and prevent the parameter adjustment from being too fast or too slow, so as to ensure the stability and convergence of the adjustment process; Incremental adjustment refers to the process of gradually modifying the current system parameter setting value in a small and step-by-step manner so that it gradually approaches the target value. It can be achieved by algorithms such as iterative approximation, proportional integral differential (PID) control, or gradient descent. Its purpose is to make the system parameter adjustment process smoother and more controllable, and to avoid system oscillation or instability caused by a one-time large-scale adjustment;The preset adjustment period is the time interval between two consecutive incremental adjustments. It can be determined using a fixed time interval, system response speed, or a dynamic adjustment strategy. Its purpose is to provide the system with sufficient stabilization time after each adjustment to adapt to the new parameter settings, thereby ensuring the reliability and effectiveness of the adjustment. The preset adjustment completion threshold is the maximum allowable deviation value set for each difference in the range difference comparison results during the continuous incremental adjustment process. When all differences are less than or equal to this threshold, the system will terminate the current adjustment process and consider the parameters to have reached the ideal state. This threshold can be set using empirical values, based on system accuracy requirements, or determined through simulation optimization. Its purpose is to ensure the accuracy and final convergence of parameter adjustments and avoid endless fine-tuning.

[0100] In some preferred embodiments, the present application is specifically implemented as follows: When the elevator door system identifies through trend analysis that the tension spring stress value and the door machine drive motor operating current value both show a continuous and slow change in the same direction, for example, both are slowly increasing at a rate of 0.5% per month, the system will start the parameter adaptive adjustment process. First, based on this change trend, a parameter calculation module will calculate the target normal working range of the tension spring stress value, the target normal working range of the door machine drive motor operating current value, and the target expected correlation characteristics between the tension spring stress value and the door machine drive motor operating current value. For example, if the current tension spring stress normal range is [100N, 120N], and the trend shows that the stress is rising, the system may calculate that the target range should be [102N, 122N]. At the same time, if the current correlation characteristic is that the current increases linearly with the stress, the system may adjust the slope or intercept of the linear relationship according to the trend to reflect the new equilibrium state. Next, a difference comparison unit compares these calculated target values ​​with the currently stored normal operating ranges for the spring stress values, the normal operating ranges for the door operator drive motor current values, and the expected correlation between the spring stress values ​​and the door operator drive motor current values. For example, if the upper limit of the target spring stress range is 122N and the current setting is 120N, the difference is 2N. All these differences are aggregated to form a range difference comparison result. If the absolute value of any difference in the range difference comparison result exceeds a preset adjustment trigger threshold, for example, if the difference in any parameter exceeds 1% of its current setting (for example, 2N exceeds 1% of 120N), the system triggers an incremental adjustment. At this point, the system incrementally adjusts the normal operating ranges for the currently set spring stress values, the normal operating ranges for the currently set door operator drive motor current values, and the expected correlation between the currently set spring stress values ​​and the door operator drive motor current values, in preset adjustment steps of, for example, 10% of the current difference. For example, the upper limit of the tension spring stress range will be adjusted from 120N to 120N+(2N*10%)=120.2N. To ensure the smoothness of the adjustment, the system will interval a preset adjustment period between two incremental adjustments, for example, an adjustment every 24 hours. This periodic adjustment allows the system to have enough time to stabilize after each fine-tuning and collect new data to verify the adjustment effect. The system will continue to make such incremental adjustments until the absolute values ​​of all differences in the range difference comparison results are less than the corresponding preset adjustment completion threshold, for example, all differences are less than 0.1% of their current set values. Once this condition is reached, the system considers that the parameters have been adjusted in place and stops the current adjustment process, thereby ensuring that the elevator door system can maintain optimal performance and reliability under the new operating conditions.

[0101] Optionally, the step of incrementally adjusting the normal operating range of the currently set tension spring stress value, the normal operating range of the currently set door machine drive motor operating current value, and the expected correlation characteristic between the currently set tension spring stress value and the door machine drive motor operating current value with a preset adjustment step size includes:

[0102] Calculate the product of each difference in the range difference comparison result and the corresponding preset proportional coefficient to obtain a preset adjustment step size;

[0103] The normal working range of the currently set tension spring stress value, the normal working range of the currently set door machine drive motor working current value, and the expected correlation characteristics between the currently set tension spring stress value and the door machine drive motor working current value are incrementally adjusted with an adjustment step size.

[0104] Among them, each difference in the range difference comparison result refers to the difference between the target normal working range of the tension spring stress value and the current set range, the difference between the target normal working range of the door machine drive motor working current value and the current set range, and the difference between the target expected correlation characteristics between the tension spring stress value and the door machine drive motor working current value and the current set expected correlation characteristics. Its purpose is to quantify the degree of deviation between the current system parameters and the ideal target parameters; the preset proportional coefficient refers to a set of values ​​pre-set according to the characteristics, importance or expected adjustment response speed of each difference, which can be stored and obtained by lookup table, function relationship or empirical value, etc., with the purpose of providing differentiated adjustment weights for different types of differences; the adjustment step size refers to the specific value calculated by multiplying the each difference in the range difference comparison result by the corresponding preset proportional coefficient, which is used to incrementally adjust the system parameters. Its purpose is to achieve adaptive and refined parameter adjustment.

[0105] In some preferred embodiments, after the system obtains range difference comparison results—for example, the difference in the normal operating range of the tension spring stress values ​​is ΔS, the difference in the normal operating range of the door operator drive motor operating current values ​​is ΔC, and the difference in the expected correlation characteristic between the tension spring stress values ​​and the door operator drive motor operating current values ​​is ΔA—to calculate the adaptive adjustment step size, the system can first obtain the absolute values ​​of these differences. For example, if ΔS is negative, its positive value is taken. Next, based on the absolute values ​​of these differences, the system retrieves the corresponding proportionality coefficients from a preset lookup table. The lookup table may pre-store a series of difference value ranges and their corresponding proportionality coefficients. For example, when the absolute value of the difference is between 0 and X1, the proportionality coefficient is K1; when the absolute value of the difference is between X1 and X2, the proportionality coefficient is K2, and so on. To obtain a more precise proportionality coefficient, the system can employ interpolation. For example, if the absolute value of a difference falls between two preset difference values, the system can calculate a precise proportionality coefficient based on their relative positions using linear interpolation or other interpolation algorithms. Once the corresponding proportionality coefficients are obtained, the system multiplies the absolute value of each difference by the respective proportionality coefficient to determine the adjustment step size for that difference. For example, the adjustment step size for the tension spring stress value can be calculated as |ΔS|*K_S, the adjustment step size for the door operator drive motor operating current value can be calculated as |ΔC|*K_C, and the adjustment step size for the expected correlation characteristic can be calculated as |ΔA|*K_A. K_S, K_C, and K_A are proportionality coefficients calculated from a lookup table or through interpolation based on the absolute values ​​of their respective differences. Finally, the system applies these calculated adjustment step sizes to the currently set normal operating range of the tension spring stress value, the currently set normal operating range of the door operator drive motor operating current value, and the currently set expected correlation characteristic between the tension spring stress value and the door operator drive motor operating current value, making incremental adjustments. For example, if the current normal operating range of the tension spring stress value needs to be increased, the calculated adjustment step size is added to it; if it needs to be decreased, the adjustment step size is subtracted. In this way, the system can make adjustments with appropriate step sizes based on the actual degree of deviation, ensuring the smoothness and convergence of the adjustment process.

[0106] Optional, combined Figure 4 As shown, the step of calculating the product of each difference in the range difference comparison result and the corresponding preset proportional coefficient to obtain the preset adjustment step size includes:

[0107] A1, obtains the absolute value of each difference in the range difference comparison result;

[0108] A2, based on the absolute value of the difference, obtains the corresponding proportional coefficient from the preset lookup table;

[0109] A3 multiplies the absolute value of the difference by the proportional coefficient to obtain the preset adjustment step size.

[0110] Among them, the preset lookup table refers to a data structure that pre-stores the mapping relationship between the absolute value of the difference and the proportional coefficient. It can be implemented in the form of an array, a hash table or a multi-dimensional matrix. Its purpose is to quickly retrieve and determine the corresponding proportional coefficient according to the size of the input difference; the proportional coefficient refers to the weight factor used to adjust the step size calculation. Its numerical value directly affects the speed and accuracy of the adjustment. By dynamically obtaining the proportional coefficient, adaptive control of the adjustment process can be achieved.

[0111] In some preferred embodiments, calculating the product of each difference in the range difference comparison result and the corresponding preset proportional coefficient to obtain the preset adjustment step size can be specifically implemented as follows: First, the system obtains the absolute value of the difference between each difference in the range difference comparison result. For example, if the difference between the currently set normal operating range of the tension spring stress and the target range is -15 units, then the absolute value of the difference is 15. Next, based on this absolute value of the difference, the system retrieves the corresponding proportional coefficient from a preset lookup table. The lookup table can be configured with multiple discrete difference intervals and their corresponding proportional coefficients. For example, when the absolute value of the difference is between 0 and 5, the proportional coefficient is set to 0.05; when the absolute value of the difference is between 5 and 20, the proportional coefficient is set to 0.1; when the absolute value of the difference is between 20 and 50, the proportional coefficient is set to 0.2; and when the absolute value of the difference is greater than 50, the proportional coefficient is set to 0.3. In this example, since the absolute value of the difference is 15, the system retrieves the corresponding proportional coefficient of 0.1 from the lookup table. Finally, the system multiplies the absolute value of the difference (15) by the proportional coefficient (0.1), resulting in a preset adjustment step size of 1.5. This adjustment step size is then used to incrementally adjust the relevant parameters to gradually approach the target value.

[0112] Optional, combined Figure 5 As shown, the step of obtaining the corresponding proportional coefficient from the preset lookup table in step A2 includes:

[0113] A21, based on the absolute value of the difference, locates two preset difference values ​​adjacent to the absolute value of the difference in a preset lookup table, and finds proportional coefficients corresponding to the two adjacent preset difference values;

[0114] A22, according to the relative position relationship between the absolute value of the difference and two preset difference values, obtain a proportional coefficient corresponding to the absolute value of the difference through interpolation calculation.

[0115] Among them, interpolation calculation refers to a mathematical method of estimating the numerical value of unknown data points between known data points based on these data points. It can be implemented using various mathematical models such as linear interpolation, polynomial interpolation, and spline interpolation. Its purpose is to infer continuous or more precise data points based on limited discrete data points, thereby improving the accuracy of data acquisition.

[0116] In some preferred embodiments, when it is necessary to obtain the proportional coefficient corresponding to the absolute value of the difference from the preset lookup table, specifically, the system can first search the preset lookup table based on the absolute value of the difference currently calculated to locate the two preset difference values ​​that are closest to the absolute value of the difference and are on the left and right. For example, if there are preset difference values ​​10, 20, and 30 in the lookup table, and the current absolute value of the difference is 15, the system will locate the preset difference values ​​10 and 20. Then, the system will read the proportional coefficients corresponding to the two preset difference values ​​(for example, 10 and 20) from the lookup table (for example, the preset difference value 10 corresponds to a proportional coefficient of 0.5, and the preset difference value 20 corresponds to a proportional coefficient of 0.8). Then, the system can use a linear interpolation method to calculate the proportional coefficient corresponding to the absolute value of the difference based on the relative position relationship between the absolute value of the difference (15) and the two adjacent preset difference values ​​(10 and 20). The specific calculation formula can be: proportional coefficient = proportional coefficient 1 + (absolute value of difference - preset difference value 1) * (proportional coefficient 2 - proportional coefficient 1) / (preset difference value 2 - preset difference value 1). In this way, even if the absolute value of the difference is not exactly listed in the lookup table, a smooth and accurate proportional coefficient can be obtained, thereby ensuring that the subsequent adjustment step size calculation is more accurate.

[0117] Optionally, the step of obtaining the proportional coefficient corresponding to the absolute value of the difference through interpolation calculation includes:

[0118] According to the relative position relationship of the absolute value of the difference between two adjacent preset difference values, a linear interpolation method is used to calculate the corresponding proportional coefficient.

[0119] The relative position relationship of the absolute difference value between two adjacent preset difference values ​​refers to the absolute difference value being numerically located between the two known preset difference values ​​and the proportional relationship of its distance to each of the two preset difference values. This can be determined by calculating the difference between the absolute difference value and the smaller preset difference value, as well as the total difference between the two preset difference values, in order to provide an accurate weight factor for subsequent interpolation calculations.

[0120] Among them, the linear interpolation method refers to a method of estimating the numerical value of an unknown data point through known data points. Specifically, it assumes that the data change between two known data points presents a linear relationship. It can be calculated using the formula y=y1+(x-x1)*((y2-y1) / (x2-x1)), where x is the absolute value of the difference, x1 and x2 are two adjacent preset difference values, y1 and y2 are the proportional coefficients corresponding to x1 and x2, and y is the proportional coefficient to be calculated. Its purpose is to accurately estimate the proportional coefficient corresponding to any intermediate value between a limited number of lookup table data points, thereby improving the accuracy of the calculation.

[0121] In some preferred embodiments, when the system needs to calculate the proportional coefficient corresponding to the absolute difference value through interpolation, it can first obtain the current absolute difference value. For example, the absolute difference value may be 0.07. Next, the system locates two preset difference values ​​adjacent to the absolute difference value in a preset lookup table. Assume that the lookup table contains preset difference values ​​0.05 and 0.10, which correspond to proportional coefficients 0.2 and 0.4, respectively. At this time, the system determines the relative position relationship of the absolute difference value 0.07 between 0.05 and 0.10. Specifically, the difference between the absolute difference value 0.07 and the smaller preset difference value 0.05 can be calculated to be 0.02, and the total difference between the two preset difference values ​​0.05 and 0.10 can be calculated to be 0.05. The system can then use a linear interpolation formula for calculation. For example, the formula can be used: proportional coefficient to be calculated = proportional coefficient corresponding to the smaller preset difference value + (absolute difference value - smaller preset difference value) * ((proportional coefficient corresponding to the larger preset difference value - proportional coefficient corresponding to the smaller preset difference value) / (larger preset difference value - smaller preset difference value)). Substituting these values, we obtain the following: The calculated proportional coefficient = 0.2 + (0.07 - 0.05) * ((0.4 - 0.2) / (0.10 - 0.05)) = 0.2 + 0.02 * (0.2 / 0.05) = 0.2 + 0.08 = 0.28. In this way, the system can accurately calculate that the proportional coefficient corresponding to the absolute difference of 0.07 is 0.28. The entire calculation process can be performed by the main controller or a dedicated signal processing unit in the elevator door system, ensuring real-time and accurate calculations.

[0122] A tension spring stress detection system is used to perform tension spring stress detection, combined with Figure 6 As shown, the tension spring stress detection system 1 includes:

[0123] The normal range determination module 11 is used to predetermine the normal operating range of the tension spring stress value, the normal operating range of the door machine drive motor operating current value, and the expected correlation characteristics between the tension spring stress value and the door machine drive motor operating current value under the normal operating state of the elevator door system;

[0124] The numerical synchronous acquisition module 12 is used to synchronously acquire the tension spring stress value and the door machine drive motor operating current value during the operation of the elevator door system;

[0125] The tension spring abnormality judgment module 13 is used to judge the fault source type of the tension spring stress abnormality based on the tension spring stress value, the working current value of the door machine drive motor and the predetermined expected correlation characteristics when the tension spring stress value exceeds the upper limit of the predetermined normal working range, and obtain the tension spring stress abnormality judgment result.

[0126] Among them, the normal range determination module refers to a functional unit used to establish benchmark data of the tension spring stress value and the door machine drive motor working current value and the correlation between them under the normal operation of the elevator door system. It can be implemented by a combination of a processor, a memory and a related sensor interface, and its purpose is to provide a reference basis for subsequent abnormality detection; the numerical synchronization acquisition module refers to a functional unit used to obtain the tension spring stress value and the door machine drive motor working current value in real time during the operation of the elevator door system. It can be implemented by a combination of a stress sensor, a current sensor, a data acquisition interface and a data processing unit, and its purpose is to ensure the real-time and correlation of the data, and provide accurate data support for subsequent fault diagnosis; the tension spring abnormality judgment module refers to a functional unit used to identify and classify the source of the tension spring stress abnormality fault based on the collected data and preset correlation characteristics. It can be implemented by a combination of an embedded processor, a logic judgment algorithm and a data analysis model, and its purpose is to accurately judge the root cause of the tension spring stress abnormality and avoid misjudgment and unnecessary maintenance work.

[0127] In some preferred embodiments, the present application is implemented as follows: The normal range determination module may consist of a main controller (e.g., an industrial-grade PLC or embedded microprocessor) and its associated storage unit. The main controller may be connected to the elevator door system's sensor network. During initial installation and commissioning of the elevator door system or during regular maintenance, the main controller continuously collects data from the tension spring stress sensor and the door operator drive motor current sensor by executing a series of preset door opening and closing cycles. This data is stored in the storage unit and statistically analyzed by the main controller, such as calculating the mean and standard deviation, and establishing a regression model for the tension spring stress and motor current under normal operating conditions, thereby determining their respective normal operating ranges and expected correlation characteristics.

[0128] The synchronous data acquisition module can consist of an independent stress sensor, a current sensor, and a high-speed data acquisition unit. The stress sensor can be mounted directly on the tension spring, providing real-time output of the spring's stress value. The current sensor can be connected in series with the door operator's drive motor's power supply to monitor the motor's operating current in real time. The high-speed data acquisition unit can be configured to synchronously read the analog or digital signals from these two sensors at a millisecond frequency and transmit the collected data to the tension spring anomaly detection module via a bus (e.g., CAN bus or Ethernet).

[0129] The spring anomaly detection module can consist of a high-performance edge computing unit or cloud server. This module receives real-time data from the synchronous data acquisition module. When the received spring stress value exceeds the upper limit preset by the normal range determination module, the spring anomaly detection module immediately initiates a diagnostic routine. This routine executes pre-set judgment logic based on the current spring stress value, the door operator drive motor operating current value, and the expected correlation characteristic model provided by the normal range determination module. For example, if the spring stress increases and the door operator drive motor current also increases significantly, and their trends conform to the correlation characteristics of increasing external resistance (for example, a positive correlation between current and stress and a rapid rate of change), the fault is determined to be caused by increased external operating resistance. If the spring stress increases but the door operator drive motor current does not change significantly or does not conform to the expected correlation characteristics, the fault is determined to be caused by degradation of the spring itself. The judgment result is immediately transmitted to the elevator control system or remote monitoring platform via a communication interface, triggering an alarm or maintenance instruction.

[0130] The above description is merely an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, various modifications and variations of the present application are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for detecting tension spring stress, characterized in that: include: Under normal operating conditions of the elevator door system, the normal operating range of the tension spring stress value, the normal operating range of the door machine drive motor operating current value, and the expected correlation characteristics between the tension spring stress value and the door machine drive motor operating current value are predetermined; During the operation of the elevator door system, the tension spring stress value and the door machine drive motor working current value are synchronously collected; When the tension spring stress value exceeds the upper limit of the predetermined normal working range, the fault source type of the tension spring stress abnormality is determined based on the tension spring stress value, the working current value of the door machine drive motor and the predetermined expected correlation characteristics, and the tension spring stress abnormality judgment result is obtained; When the tension spring stress value exceeds a predetermined upper limit of a normal operating range and the operating current value of the door machine drive motor exceeds a predetermined upper limit of a normal operating range, the step of determining the fault source type of the tension spring stress abnormality and obtaining the tension spring stress abnormality determination result comprises: Obtaining the rate of change of the tension spring stress value from the normal working range to the abnormal peak value to obtain the abnormal change rate of the tension spring; obtaining the duration of the tension spring stress value in the abnormal state to obtain the abnormal duration of the tension spring; Obtaining the rate of change of the working current value of the door machine drive motor from the normal working range to the abnormal peak value to obtain the current abnormal change rate; obtaining the duration of the working current value of the door machine drive motor in the abnormal state to obtain the current abnormality duration; According to the abnormal change rate of the tension spring, the abnormal duration of the tension spring, the abnormal change rate of the current, and the abnormal duration of the current, it is determined that the fault source type of the abnormal tension spring stress is transient compensation of the internal drive system or continuous loading of the external running resistance; The step of predetermining the normal operating range of the tension spring stress value, the normal operating range of the door machine drive motor operating current value, and the expected correlation characteristics between the tension spring stress value and the door machine drive motor operating current value under the normal operating state of the elevator door system includes: When the elevator door system is operating normally, the tension spring stress value and the door machine drive motor operating current value are continuously collected; When the event of abnormal increase in external running resistance or transient compensation of the internal drive system does not occur, the collected tension spring stress value and door machine drive motor operating current value are used as baseline data; Based on a preset period, trend analysis is performed on the baseline data accumulated within the preset period to identify the change trend of the tension spring stress value and the door machine drive motor operating current value; When the change trend shows that the tension spring stress value and the door machine drive motor working current value both show a continuous and slow change in the same direction, the normal working range of the tension spring stress value, the normal working range of the door machine drive motor working current value, and the expected correlation characteristics between the tension spring stress value and the door machine drive motor working current value are adjusted and determined according to the change trend.

2. A tension spring stress detection method according to claim 1, characterized in that: The step of performing trend analysis on the baseline data accumulated within the preset period based on the preset period to identify the change trend of the tension spring stress value and the door machine drive motor working current value includes: Based on a preset period, trend analysis is performed on the baseline data accumulated within the preset period to identify the change trend of the tension spring stress value and the door machine drive motor operating current value; Analyzing the morphological characteristics of the change trend; the morphological characteristics include periodic characteristics or long-term cumulative characteristics; Based on the morphological characteristics, it is determined that the change trend is caused by environmental factors or by component performance degradation.

3. A tension spring stress detection method according to claim 1, characterized in that: The step of adjusting and determining the normal operating range of the tension spring stress value, the normal operating range of the door machine drive motor operating current value, and the expected correlation characteristics between the tension spring stress value and the door machine drive motor operating current value includes: Calculating, based on the change trend, a target normal operating range of the tension spring stress value, a target normal operating range of the door machine drive motor operating current value, and a target expected correlation characteristic between the tension spring stress value and the door machine drive motor operating current value; Comparing the difference between the target normal operating range and the normal operating range of the currently set tension spring stress value, the difference between the target normal operating range of the door machine drive motor operating current value and the normal operating range of the currently set door machine drive motor operating current value, and the difference between the target expected correlation characteristic and the expected correlation characteristic between the currently set tension spring stress value and the door machine drive motor operating current value, to obtain a range difference comparison result; When any difference in the range difference comparison results exceeds a preset adjustment start threshold, incremental adjustments are made to the normal operating range of the currently set tension spring stress value, the normal operating range of the currently set door machine drive motor operating current value, and the expected correlation characteristic between the currently set tension spring stress value and the door machine drive motor operating current value at a preset adjustment step size; Between two incremental adjustments, there is a preset adjustment period; The incremental adjustment is continued until all differences in the range difference comparison result are smaller than the corresponding preset adjustment completion threshold.

4. A tension spring stress detection method according to claim 3, characterized in that: The step of incrementally adjusting the normal working range of the currently set tension spring stress value, the normal working range of the currently set door machine drive motor operating current value, and the expected correlation characteristic between the currently set tension spring stress value and the door machine drive motor operating current value with a preset adjustment step size includes: Calculating the product of each difference in the range difference comparison result and the corresponding preset proportional coefficient to obtain a preset adjustment step size; With the adjustment step, incremental adjustments are made to the normal working range of the currently set tension spring stress value, the normal working range of the currently set door machine drive motor working current value, and the expected correlation characteristics between the currently set tension spring stress value and the door machine drive motor working current value.

5. A tension spring stress detection method according to claim 4, characterized in that: The step of calculating the product of each difference in the range difference comparison result and the corresponding preset proportional coefficient to obtain the preset adjustment step size includes: Obtaining the absolute value of each difference in the range difference comparison result; According to the absolute value of the difference, a corresponding proportional coefficient is obtained from a preset lookup table; The absolute value of the difference is multiplied by the proportional coefficient to obtain a preset adjustment step size.

6. A tension spring stress detection method according to claim 5, characterized in that: The step of obtaining the corresponding proportional coefficient from a preset lookup table includes: According to the absolute value of the difference, two preset difference values ​​adjacent to the absolute value of the difference are located in a preset lookup table, and proportional coefficients corresponding to the two adjacent preset difference values ​​are found; According to the relative position relationship between the absolute value of the difference and two preset difference values, a proportional coefficient corresponding to the absolute value of the difference is obtained through interpolation calculation.

7. A tension spring stress detection method according to claim 6, characterized in that: The step of obtaining the proportional coefficient corresponding to the absolute value of the difference by interpolation calculation includes: According to the relative position relationship of the absolute value of the difference between two adjacent preset difference values, a linear interpolation method is used to calculate the corresponding proportional coefficient.

8. A tension spring stress detection system, used to perform the tension spring stress detection method according to claim 1, characterized in that: include: A normal range determination module is used to predetermine the normal operating range of the tension spring stress value, the normal operating range of the door machine drive motor operating current value, and the expected correlation characteristics between the tension spring stress value and the door machine drive motor operating current value under the normal operating state of the elevator door system; The numerical synchronous acquisition module is used to synchronously acquire the tension spring stress value and the door machine drive motor operating current value during the operation of the elevator door system; The tension spring abnormality judgment module is used to determine the fault source type of the tension spring stress abnormality based on the tension spring stress value, the working current value of the door machine drive motor and the predetermined expected correlation characteristics when the tension spring stress value exceeds the predetermined upper limit of the normal working range, and obtain the tension spring stress abnormality judgment result.

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