A method for monitoring the operating state and early warning of faults of a spring forming apparatus

Abstract

The present application belongs to the technical field of data processing, and particularly relates to a kind of spring forming equipment operating state monitoring and fault early warning method, its method includes: through the operating state data of key servo shaft, the torque stiffness is calculated, and the forming cycle is automatically divided into elastic contact, plastic forming and unloading demoulding phase;In the plastic forming phase, the influence of raw material hardness fluctuation is stripped by calculating the dynamic rheological resistance index of material and the upper limit of dynamic current;At the same time, the energy topology consistency coefficient containing position weighting function is calculated to capture the slight waveform distortion;Finally, a comprehensive fault early warning index is constructed based on the above index, and the equipment is warned or stopped in stages.The present application can effectively decouple material attribute fluctuation and mechanical failure, and improve the detection sensitivity of early failure.

Description

Technical Field

[0001] This invention relates to the field of data processing technology. More specifically, this invention relates to a method for monitoring the operating status and providing early warning of faults in spring forming equipment. Background Technology

[0002] As a basic mechanical component, the forming accuracy of springs directly affects the performance and lifespan of downstream products. In modern industrial production, CNC (Computer Numerical Control) spring forming machines are widely used, which rely on the coordinated motion of multi-axis servo motors to achieve the winding, bending and cutting of wires. In actual production, monitoring the operating status of the equipment and fault early warning are key links to ensure product quality and production safety.

[0003] Existing monitoring methods for spring forming equipment typically employ a simple threshold judgment method, which monitors whether the current or torque of the servo motor exceeds a set upper limit. However, the mechanical properties of raw materials such as spring steel wire, such as tensile strength and hardness, fluctuate between batches and even within the same roll. When the hardness of the raw material fluctuates within the normal tolerance range but is too high, the load torque required for forming will naturally increase. Traditional fixed threshold monitoring methods often misjudge this as equipment overload or tool wear, leading to frequent false alarms and reduced production efficiency.

[0004] On the other hand, real equipment failures, such as minor chipping of the forming tool or minor slippage of the wire feeding wheel, often manifest as distortion of waveform details rather than simply exceeding the amplitude limit. Relying solely on amplitude monitoring makes it difficult to detect early mechanical failures, which can easily lead to batch scrap or serious equipment damage.

[0005] Therefore, there is an urgent need for a monitoring method that can decouple material property fluctuations from equipment mechanical failures and is sensitive to minor faults. Summary of the Invention

[0006] To address the technical problem that existing monitoring methods cannot distinguish between raw material hardness fluctuations and equipment mechanical failures, resulting in high false alarm rates and insensitivity to early minor faults, this invention provides a method for monitoring the operating status and providing early warning of faults in spring forming equipment. The method includes: collecting operating status data of key servo axes, including angular position, angular velocity, and torque current, to calculate real-time torque stiffness; and automatically dividing a single forming cycle into an elastic contact phase, a plastic forming phase, and an unloading / demolding phase based on the evolution law of torque stiffness; within the plastic forming phase, calculating the dynamic rheological resistance index of the material, including integrating the second derivative of the torque current with respect to the angular position signal and multiplying it by a factor based on angular velocity and rated process reference. The system includes: a speed correction term for the speed ratio; a dynamic current upper limit calculated based on the material's dynamic rheological resistance index; an energy topology consistency coefficient calculated to characterize the similarity between the instantaneous power waveform of the plastic forming phase and the power waveform of the reference model within the current forming cycle; the calculation of the energy topology consistency coefficient includes a position weighting function, the value of which increases exponentially with the angular position from the start position to the end position of the plastic forming phase; and a comprehensive fault warning index calculated based on the energy topology consistency coefficient, the change amplitude of the material's dynamic rheological resistance index relative to the reference material resistance index, and a dynamic overload term constructed based on the peak torque current and the dynamic current upper limit of the forming cycle, and the execution of warning or shutdown operations.

[0007] This invention precisely pinpoints the key physical process of plastic deformation through phase segmentation using torque stiffness; it quantifies the processing hardness of raw materials by constructing a dynamic rheological resistance index, providing a benchmark for subsequent decoupling; it improves the sensitivity to faults in high-risk areas at the molding endpoint by introducing position-weighted energy topology analysis; and it automatically tolerates normal waveform fluctuations caused by material hardening by constructing a comprehensive fault warning index that includes decoupling terms, using the dynamic rheological resistance index as a suppression factor, while retaining high sensitivity to waveform distortions caused by equipment malfunctions. This effectively reduces the false alarm rate and improves the accuracy and reliability of monitoring.

[0008] Preferably, the method for determining the start and end times of the plastic forming phase is as follows: when the detected torque stiffness is less than... When this state persists for more than 5 sampling periods, it is marked as the start time of the plastic forming phase. The average value of the torque stiffness of the elastic contact phase; when the torque current drops sharply from the peak point and the magnitude exceeds 10% of the peak current, it is marked as the termination time of the plastic forming phase; before the start time belongs to the elastic contact phase, and after the termination time belongs to the unloading and demolding phase.

[0009] Preferably, the formula for calculating the dynamic rheological resistance index of the material is: In the formula, The dynamic rheological resistance index of the material; The duration of the plastic forming phase, and ; , These represent the start and end times of the plastic forming phase, respectively. , , They are time points Torque current, angular position, and angular velocity; This is the second derivative of the torque current with respect to the angular position; Indicates taking the absolute value; This is the rated process reference speed for the equipment.

[0010] By introducing a material dynamic rheological resistance index that includes the second derivative integral and a velocity correction term, this invention can separate friction and inertial forces from the total torque output by the motor, and quantify the work hardening characteristics of the material. The velocity correction term takes into account the strain rate sensitivity of the material, preventing the increased yield strength of the material during high-speed processing from being mistakenly identified as abnormal equipment resistance, thereby ensuring the consistency and accuracy of monitoring indicators at different processing speeds.

[0011] Preferably, the formula for calculating the upper limit of the dynamic current is: In the formula, This is the upper limit of the dynamic current. The rated alarm current is based on the reference material. The dynamic rheological resistance index of the material; The drag index is used as the reference material.

[0012] Preferably, the formula for calculating the energy topology consistency coefficient is: In the formula, The energy topology consistency coefficient; , These represent the start and end times of the plastic forming phase, respectively. , They are time points Torque current and angular velocity; This represents the real-time instantaneous power of the motor. , These are the times in the baseline model. Torque current and speed; Power of the baseline model; For a moment The position-weighted function.

[0013] The energy topology consistency coefficient proposed in this invention can capture fault features hidden in waveform details by comparing the waveform morphology differences between real-time power flow and the benchmark model, thereby identifying soft faults that have not exceeded the amplitude limit but whose waveforms are distorted, thus making up for the blind spots of traditional amplitude monitoring methods.

[0014] Preferably, the formula for calculating the position weighting function is: In the formula, For a moment Position-weighted function; For a moment Angular position; , These represent the angular positions at the start and end times of the plastic forming phase, respectively. It is a natural exponential function.

[0015] Preferably, the calculation method for the dynamic overload term constructed based on the peak torque current and the upper limit of dynamic current in the molding cycle is as follows: calculate the difference between the peak torque current and the upper limit of dynamic current in the current molding cycle, and calculate the ratio of the difference to the upper limit of dynamic current; when the ratio is greater than 0, the ratio is used as the dynamic overload term, otherwise the dynamic overload term is always equal to 0.

[0016] This invention constructs an overload quantification index based on a dynamic benchmark. By calculating only the difference ratio of the portion exceeding the dynamic current upper limit, it ensures that the fault contribution value is only included when the load actually exceeds the range allowed by the current material hardness. This further enhances the algorithm's anti-interference capability and ensures that the triggering of alarm signals is entirely attributable to equipment abnormalities rather than reasonable fluctuations in the process or materials.

[0017] Preferably, the formula for calculating the comprehensive fault early warning index is: In the formula, This is a comprehensive fault early warning index; The energy topology consistency coefficient; , The dynamic rheological resistance index of the material. The drag index is used as the benchmark material. For dynamic overload items; This indicates taking the absolute value.

[0018] The calculation formula of the comprehensive fault early warning index constructed in this invention includes a suppression factor based on the amplitude of material resistance change, thereby realizing automatic gain control: when a drastic fluctuation in material resistance is detected, the algorithm automatically reduces the sensitivity of the fault index to prevent false alarms caused by waveform differences due to sudden changes in material; while when the material is stable, the system maintains high sensitivity; thus balancing the robustness and sensitivity of the monitoring system.

[0019] Preferably, the execution of the early warning or shutdown operation includes: based on the comprehensive fault early warning index. Execute a tiered response: If A yellow alert is triggered, prompting a check of lubrication and tool wear; if This triggers a red stop, initiating an emergency stop or rollback action.

[0020] Preferably, the calculation of real-time torque stiffness is achieved using the five-point difference method, based on angular position and torque current.

[0021] The beneficial effects of this invention are as follows:

[0022] This invention precisely pinpoints the key physical process of plastic deformation through phase segmentation using torque stiffness; it quantifies the processing hardness of raw materials by constructing a dynamic rheological resistance index, providing a benchmark for subsequent decoupling; it improves the sensitivity to faults in high-risk areas at the molding endpoint by introducing position-weighted energy topology analysis; and it automatically tolerates normal waveform fluctuations caused by material hardening by constructing a comprehensive fault warning index that includes decoupling terms, using the dynamic rheological resistance index as a suppression factor, while retaining high sensitivity to waveform distortions caused by equipment malfunctions. This effectively reduces the false alarm rate and improves the accuracy and reliability of monitoring. Attached Figure Description

[0023] Figure 1 This is a flowchart illustrating a method for monitoring the operating status and providing early warning of faults in a spring forming equipment according to the present invention;

[0024] Figure 2 This schematically illustrates the current data acquisition and phase segmentation results for a single molding cycle under three working conditions;

[0025] Figure 3 It schematically illustrates the statistical comparison results of key indicators under three working conditions;

[0026] Figure 4 This is an illustrative comparison of the alarm effects of this solution and the traditional fixed threshold method. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0029] This invention discloses a method for monitoring the operating status and providing early warning of faults in a spring forming equipment, referring to... Figure 1 This includes steps S1 to S4:

[0030] S1: Collects the operating status data of key servo axes, calculates the real-time torque stiffness, and automatically divides a single molding cycle into an elastic contact phase, a plastic forming phase, and an unloading and demolding phase based on the evolution law of torque stiffness.

[0031] First, in order to achieve millisecond-level monitoring of the operating status of the spring forming equipment and capture minute mechanical changes, the system first utilizes the underlying data interface of the CNC controller to synchronously acquire the operating status data of key servo axes at a high sampling frequency of 1ms via the EtherCAT industrial real-time Ethernet bus. This includes the angle position feedback from the motor encoder at each moment during a single forming cycle. angular velocity of the motor and the torque current of the servo drive The torque current is proportional to the output torque; at the same time, in order to eliminate electromagnetic noise interference, the time sequence composed of the original data is subjected to sliding Kalman filtering.

[0032] Then, the torque stiffness at each moment is calculated using the five-point difference method, which serves as the criterion for phase segmentation. The specific calculation formula is as follows:

[0033]

[0034] In the formula, For a moment Torque stiffness; , , , They are time points , , , Torque current; , , , They are time points , , , The angular position; this calculation formula utilizes the five-point difference principle, which can effectively smooth noise and accurately calculate the rate of change of torque relative to angle.

[0035] Furthermore, since the continuous molding process includes different physical stages such as elastic contact, plastic deformation, and unloading, directly analyzing the entire process would obscure key characteristics. Therefore, it is necessary to automatically divide a single molding cycle into an elastic contact phase, a plastic forming phase, and an unloading and demolding phase based on the evolution law of torque stiffness: when a significant decrease in torque stiffness is detected, i.e., torque stiffness... When this state persists for more than 5 sampling periods, it is marked as the start time of the plastic forming phase. ,in, This represents the average torque stiffness of the elastic contact phase; the termination point of the plastic forming phase is marked when the torque current drops sharply from its peak value, exceeding 10% of the peak value. ; the onset time of the plastic forming phase The termination time of the previously elastic contact phase and the plastic forming phase The next phase is the unloading and demolding phase.

[0036] For example, Figure 2 The data acquisition and phase segmentation results for a single molding cycle under three working conditions are presented; among them, Figure 2 (1) shows the current data acquisition and phase segmentation results for a single molding cycle under the reference working condition. Figure 2 (2) shows the current data acquisition and phase segmentation results for a single molding cycle under material hardening conditions. Figure 2 (3) shows the current data acquisition and phase segmentation results of a single molding cycle under equipment failure; the single molding cycle is divided into elastic contact phase, plastic molding phase and unloading demolding phase.

[0037] S2: Calculate the dynamic rheological resistance index of the material within the plastic forming phase.

[0038] It should be noted that in the plastic forming phase, the load torque mainly comes from the internal resistance of the material to plastic flow; however, the output torque of the servo motor includes friction, inertial force and material deformation resistance, and the material is strain rate sensitive, that is, the faster the deformation speed, the higher the yield strength. In order to prevent the normal load increase caused by material hardening from being misjudged as equipment failure, it is necessary to separate the pure material properties and construct a second derivative integral index that includes speed correction, namely the material dynamic rheological resistance index.

[0039] Specifically, within the plastic forming phase, the dynamic rheological resistance index of the material is calculated using the following formula:

[0040]

[0041] In the formula, The dynamic rheological resistance index of the material; The duration of the plastic forming phase is used for normalization, and ; , These represent the start and end times of the plastic forming phase, respectively. For a moment Torque current; For a moment Angular position; The second derivative of the torque current with respect to the angular position represents the trend of work hardening rate. Indicates taking the absolute value; For a moment angular velocity; This is the rated process reference speed for the equipment.

[0042] Among them, the material dynamic rheological resistance index The higher the value, the more difficult the raw material is to process at the current processing moment, indicating that the material is harder or hardens faster; the second derivative term in its calculation formula... The linearly varying frictional components were filtered out, focusing instead on the nonlinear plastic deformation resistance; velocity correction term. The drag characteristics at high speeds were then corrected and amplified.

[0043] S3: Calculate the energy topology consistency coefficient including the location weighting function.

[0044] It should be noted that equipment failures are often hidden in the details of waveform morphology. For example, tool wear can cause the impact at the moment of contact to become blunt, and wire slippage can cause phase lag in energy integration. In order to monitor the health status of the equipment actuator and improve the sensitivity to the high-risk area of ​​the forming end point, which is most prone to chipping or slippage, this invention introduces a position weighting function and constructs an energy topology consistency coefficient. The equipment status is quantified by comparing the waveform morphology difference between the real-time energy flow and the benchmark model.

[0045] Specifically, we first define a position-weighted function, which adopts an exponential growth form, and the specific calculation formula is as follows:

[0046]

[0047] In the formula, For a moment Position-weighted function; For a moment Angular position; , These represent the angular positions at the start and end times of the plastic forming phase, respectively. It is a natural exponential function; this function makes the weight of the forming endpoint greater than the weight of the starting point, thus amplifying the impact of the end-point anomaly.

[0048] It should be noted that by introducing an exponentially increasing position weighting function, the weight of the molding endpoint position in fault determination is amplified. Since faults such as chipping or slippage are most likely to occur at the molding endpoint where the load is greatest during the spring molding process, this weighting mechanism improves the system's ability to capture fault signals in high-risk areas, realizes key monitoring of critical molding stages, and improves the signal-to-noise ratio of fault warning.

[0049] Furthermore, the weighted energy topological consistency coefficient is calculated, specifically using the following formula:

[0050]

[0051] In the formula, The energy topology consistency coefficient; , These represent the start and end times of the plastic forming phase, respectively. For a moment Torque current; For a moment angular velocity; This represents the real-time instantaneous power of the motor. , These are the times in the baseline model. Torque current and speed; Power of the baseline model; For a moment The position-weighted function.

[0052] The baseline model is the mean curve calculated by collecting the torque current and speed curves of continuously qualified products during the equipment commissioning phase or after the most recent maintenance, and then aligning them through dynamic time warping.

[0053] The numerator is the weighted total energy deviation, and the denominator is the geometric mean of the total energy of the real-time signal and the total energy of the reference signal, which is the energy normalization factor. This calculation formula is essentially a comprehensive measure of weighted Pearson correlation and amplitude difference. When the equipment is operating smoothly, the energy topology consistency coefficient... The energy topology consistency coefficient approaches 1; when mechanical failure causes waveform distortion, the energy topology consistency coefficient... The value will drop rapidly.

[0054] For example, Figure 3The statistical comparison results of key indicators under three operating conditions include the statistical comparison results of material dynamic rheological resistance index and energy topology consistency coefficient: For the baseline operating condition, the material dynamic rheological resistance index is moderate and the energy topology consistency coefficient is close to 1, indicating that the waveform is consistent; For the material hardening operating condition, the material dynamic rheological resistance index increases significantly, reflecting the material hardening, while the energy topology consistency coefficient is still very high, close to 1, indicating that the waveform shape has not changed, the equipment is fault-free, and the material properties have been decoupled; For the equipment failure, the material dynamic rheological resistance index does not change much compared to the baseline operating condition, but the energy topology consistency coefficient decreases significantly, indicating that the waveform topology is distorted and the fault characteristics have been captured.

[0055] S4: Calculate the upper limit of dynamic current based on the material dynamic rheological resistance index; calculate the comprehensive fault warning index based on the energy topology consistency coefficient, the change of the material dynamic rheological resistance index relative to the reference material resistance index, and the dynamic overload term constructed based on the peak torque current and the upper limit of dynamic current during the molding cycle, and execute the warning or shutdown operation.

[0056] It should be noted that, in order to completely solve the problem of false alarms caused by material fluctuations, it is necessary to decouple the increased load caused by excessively hard materials from the waveform distortion caused by equipment wear. If the energy topology is distorted, but the material resistance characteristics also change drastically, this usually means that it is a normal material fluctuation and the alarm should be suppressed. Conversely, if the material characteristics are stable but the energy topology is distorted independently, it should be judged as an equipment failure. At the same time, in order to prevent hard materials from damaging the equipment, a current hard threshold that dynamically fluctuates with the material hardness should be retained.

[0057] Specifically, a dynamic current upper limit is defined that fluctuates with the material hardness, and the specific calculation formula is as follows:

[0058]

[0059] In the formula, This is the upper limit of the dynamic current. The rated alarm current is based on the reference material. The dynamic rheological resistance index of the material; The drag index is used as the reference material.

[0060] It should be noted that, unlike traditional fixed alarm thresholds, this invention constructs a dynamic current upper limit that fluctuates in real time with the material hardness. When the material hardening is detected, i.e., the material's dynamic rheological resistance index is... When the load increases, the system automatically raises the alarm limit to tolerate normal load increases; conversely, it lowers the limit. This adaptive adjustment mechanism minimizes false alarms caused by fluctuations in raw material tolerances while ensuring that the load does not exceed the limit, thereby improving the production efficiency of the equipment.

[0061] Furthermore, the comprehensive fault early warning index is calculated, and the specific calculation formula is as follows:

[0062]

[0063] In the formula, This is a comprehensive fault early warning index; The energy topology consistency coefficient; , which represents the change in the dynamic rheological drag index of the current material relative to the drag index of the reference material; This represents the peak torque current of the current molding cycle. This is the upper limit of the dynamic current. Indicates taking the absolute value; This indicates taking the maximum value.

[0064] The first term in the calculation is the decoupling term, and the denominator is... As a suppressive factor, when the material fluctuates drastically, the denominator increases, automatically reducing the comprehensive fault warning index. The value of is used to tolerate waveform changes caused by material variations; the second term of the calculation formula is a dynamic overload term constructed based on the peak torque current and dynamic current upper limit of the molding cycle. The fault contribution is only included when the current exceeds the upper limit allowed by the current material hardness.

[0065] Ultimately, based on the comprehensive fault early warning index Execute a tiered response: If A yellow alert is triggered, prompting a check of lubrication and tool wear; if This triggers a red stop, initiating an emergency stop or rollback action.

[0066] For example, Figure 4 This is a comparison of the alarm performance of this solution with that of the traditional fixed threshold method; Figure 4 (1) shows the alarm effect of the traditional fixed threshold method. Figure 4 (2) shows the alarm effect of this solution; for the material hardening condition, the traditional fixed threshold method generates false alarms because the current peak exceeds the fixed threshold of 57.5A. However, in this solution, although the dynamic rheological resistance index of the material increases, the denominator of the comprehensive fault warning index is suppressed. The dynamic current limit, which is dynamically adjusted, keeps the overall fault warning index below 0.3, successfully avoiding false alarms. For equipment fault conditions, the traditional fixed threshold method misses the alarm because the peak value does not significantly exceed the limit, while the overall fault warning index of this solution quickly rises to over 0.7, triggering a red shutdown and accurately identifying mechanical faults.

Claims

1. A method for monitoring the operating status and providing early warning of faults in a spring forming equipment, characterized in that, include: Collect operating status data of key servo axes, including angular position, angular velocity and torque current, to calculate real-time torque stiffness, and based on the evolution law of torque stiffness, automatically divide a single molding cycle into elastic contact phase, plastic forming phase and unloading demolding phase; Within the plastic forming phase, the dynamic rheological resistance index of the material is calculated, including integrating the second derivative of the torque current with respect to the angular position signal and multiplying it by a velocity correction term based on the ratio of angular velocity to the rated process reference velocity. Calculate the upper limit of dynamic current based on the material's dynamic rheological resistance index; The energy topology consistency coefficient is calculated to characterize the similarity between the instantaneous power waveform of the plastic forming phase and the power waveform of the reference model within the current forming cycle. The calculation of the energy topology consistency coefficient includes a position weighting function, the value of which increases exponentially with the angular position from the start position to the end position of the plastic forming phase. Based on the energy topology consistency coefficient, the variation of the material dynamic rheological resistance index relative to the reference material resistance index, and the dynamic overload term constructed based on the peak torque current and dynamic current upper limit of the molding cycle, a comprehensive fault warning index is calculated, and a warning or shutdown operation is executed.

2. The method for monitoring the operating status and providing early warning of faults in a spring forming equipment according to claim 1, characterized in that, The method for determining the start and end times of the plastic forming phase is as follows: When the detected torque stiffness is less than When this state persists for more than 5 sampling periods, it is marked as the start time of the plastic forming phase. The average value of the torque stiffness of the elastic contact phase; when the torque current drops sharply from the peak point and the magnitude exceeds 10% of the peak current, it is marked as the termination time of the plastic forming phase; before the start time belongs to the elastic contact phase, and after the termination time belongs to the unloading and demolding phase.

3. The method for monitoring the operating status and providing early warning of faults in a spring forming equipment according to claim 1, characterized in that, The formula for calculating the dynamic rheological resistance index of the material is: ； In the formula, The dynamic rheological resistance index of the material; The duration of the plastic forming phase, and ; , These represent the start and end times of the plastic forming phase, respectively. , , They are time points Torque current, angular position, and angular velocity; This is the second derivative of the torque current with respect to the angular position; Indicates taking the absolute value; This is the rated process reference speed for the equipment.

4. The method for monitoring the operating status and providing early warning of faults in a spring forming equipment according to claim 1, characterized in that, The formula for calculating the upper limit of the dynamic current is: ； In the formula, This is the upper limit of the dynamic current. The rated alarm current is based on the reference material. The dynamic rheological resistance index of the material; The drag index is used as the reference material.

5. The method for monitoring the operating status and providing early warning of faults in a spring forming equipment according to claim 1, characterized in that, The formula for calculating the energy topology consistency coefficient is: ； In the formula, The energy topology consistency coefficient; , These represent the start and end times of the plastic forming phase, respectively. , They are time points Torque current and angular velocity; This represents the real-time instantaneous power of the motor. , These are the times in the baseline model. Torque current and speed; Power of the baseline model; For a moment The position-weighted function.

6. The method for monitoring the operating status and providing early warning of faults in a spring forming equipment according to claim 1, characterized in that, The formula for calculating the position weighting function is: ； In the formula, For a moment Position-weighted function; For a moment Angular position; , These represent the angular positions at the start and end times of the plastic forming phase, respectively. It is a natural exponential function.

7. The method for monitoring the operating status and providing early warning of faults in a spring forming equipment according to claim 1, characterized in that, The calculation method for the dynamic overload term constructed based on the peak torque current and the upper limit of dynamic current in the molding cycle is as follows: calculate the difference between the peak torque current and the upper limit of dynamic current in the current molding cycle, and calculate the ratio of the difference to the upper limit of dynamic current. When the ratio is greater than 0, the ratio is used as the dynamic overload term; otherwise, the dynamic overload term is always equal to 0.

8. The method for monitoring the operating status and providing early warning of faults in a spring forming equipment according to claim 1, characterized in that, The formula for calculating the comprehensive fault early warning index is: ； In the formula, This is a comprehensive fault early warning index; The energy topology consistency coefficient; , The dynamic rheological resistance index of the material. The drag index is used as the benchmark material. For dynamic overload items; This indicates taking the absolute value.

9. The method for monitoring the operating status and providing early warning of faults in a spring forming equipment according to claim 1, characterized in that, The execution of the warning or shutdown operation includes: According to the comprehensive fault early warning index Execute a tiered response: If A yellow alert is triggered, prompting a check of lubrication and tool wear; if This triggers a red stop, initiating an emergency stop or rollback action.

10. The method for monitoring the operating status and providing early warning of faults in a spring forming equipment according to claim 1, characterized in that, The real-time torque stiffness is calculated using the five-point difference method, based on angular position and torque current.

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