Relay abnormality prediction method, medium, and device

Abstract

This invention relates to the field of relay monitoring, and in particular to a method, medium, and device for predicting relay anomalies. The method acquires voltage and current waveform data of the relay's operation process via an IO-Link interface, extracts features such as breaking arc, closing bounce, and steady-state contact resistance; determines health factors based on contact resistance, calculates single-instance damage values ​​by combining arc and bounce characteristics, and determines remaining lifespan by comparing cumulative damage values ​​with a threshold. This method shifts from counting incidents to counting damage, improving assessment accuracy through multi-dimensional damage quantification and adaptive aging of health factors; real-time online data acquisition avoids lag, ensuring prediction accuracy under different operating conditions, and providing technical support for industrial predictive maintenance.

Description

Technical Field

[0001] This invention relates to the field of relay monitoring, and in particular to a method, medium, and device for predicting relay anomalies. Background Technology

[0002] Relays, as electronic control switching devices widely used in industrial control, power systems, automotive electronics, and other fields, directly affect the safe and stable operation of the entire system due to their reliability. With the improvement of industrial automation and the popularization of predictive maintenance concepts, the need for online monitoring and dynamic prediction of relay remaining life is becoming increasingly urgent.

[0003] Currently, relay life prediction primarily employs statistical methods based on the number of operations. This method records the cumulative number of relay operations and issues a replacement warning when the number of operations approaches the manufacturer's rated electrical or mechanical lifespan. However, this fixed-threshold statistical method has significant shortcomings: firstly, the actual lifespan of a relay is affected by various factors such as load type, breaking current, and ambient temperature, resulting in significant differences in contact wear under different operating conditions for the same number of operations; secondly, as contacts age, their material properties change, and the damage under the same operating conditions gradually intensifies, a dynamic process that the fixed-threshold method cannot reflect.

[0004] To address the aforementioned issues, existing technologies have developed relay condition assessment methods based on electrical parameter monitoring. For example, relay health is assessed by monitoring changes in current and voltage in the contact circuit, or by detecting contact resistance. However, these methods typically focus on only a single parameter, failing to comprehensively consider the complete electrical behavior characteristics of the contact closing, opening, and stable conduction phases, making it difficult to fully quantify the cumulative effects of contact wear. Furthermore, most existing solutions employ offline detection or periodic inspection methods, failing to achieve real-time online monitoring, and lack effective identification and compensation mechanisms for differences in load types.

[0005] IO-Link (IEC 61131-9), as an intelligent point-to-point communication protocol, enables bidirectional data communication between sensors / actuators and the control layer, providing a technical foundation for acquiring high-precision voltage and current waveform data during relay operation. How to fully utilize IO-Link's data transmission capabilities, combined with the physical characteristics of relay contact operation, to construct a dynamic life prediction method that can adaptively predict aging conditions has become a pressing technical problem in this field. Summary of the Invention

[0006] To address one of the aforementioned technical problems, the present invention adopts the following technical solution: According to one aspect of the present invention, a method for predicting relay anomalies is provided, the method comprising the following steps: The voltage and current waveform data of the relay during each operation are obtained through the IO-Link communication interface. Each operation includes the contact closing process, the stable conduction process, and the contact opening process. Based on voltage waveform data and current waveform data, extract the action features corresponding to each action. The action features include at least the arc breaking feature, the closing bounce feature, and the steady-state contact resistance. The health factor of the current relay is determined based on the steady-state contact resistance; the health factor H satisfies the following relationship: ;in, This is the steady-state contact resistance measured during the current operation. The initial contact resistance of the new relay contact. This is the contact resistance threshold corresponding to the end of the relay's lifespan. Based on the characteristics of the broken arc, the characteristics of the closed bounce, and health factors, a single-instance damage value for this action is generated; among which, the first... Single-shot damage value of the action The following relationship must be satisfied: ;in, For the first The square integral of the breaking arc current of each action is used to characterize the degree of contact material loss caused by arc erosion during the contact disconnection process. For the first The square integral of the closing bounce current of each action is used to characterize the degree of contact material loss caused by the bounce arc during the contact closure process. These are the disjunctive injury coefficient function and the bounce injury coefficient function, respectively, which are related to the health factor H, and both are positively correlated with H; The individual damage values ​​are accumulated to the cumulative damage value, and the remaining life of the relay is determined based on the cumulative damage value and the preset total damage threshold.

[0007] According to a second aspect of the present invention, a non-transitory computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the above-described relay anomaly prediction method.

[0008] According to a third aspect of the present invention, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described relay anomaly prediction method.

[0009] This invention has at least one of the following beneficial effects: To address the technical problem mentioned in the background art of how to fully utilize the data transmission capabilities of IO-Link, combine the physical characteristics of relay contact actions, and construct a dynamic life prediction method that can adapt to aging conditions, this invention provides a relay anomaly prediction method. This method acquires complete voltage and current waveform data of the contact closing process, stable conduction process, and contact opening process during each relay operation through the IO-Link communication interface, and extracts multi-dimensional action features such as breaking arc characteristics, closing bounce characteristics, and steady-state contact resistance. Based on this, the current relay health factor is dynamically determined according to the steady-state contact resistance, and the breaking damage coefficient function and bounce damage coefficient function are adaptively adjusted using this health factor to generate a single-damage value for this operation. Finally, the remaining life is determined by comparing the cumulative damage value with a preset total damage threshold. Thus, this invention achieves a fundamental shift from the traditional "counting" mode to a "damage counting" mode, effectively solving the problem that the fixed threshold method in the prior art cannot reflect differences in operating conditions and dynamic changes in aging.

[0010] Specifically, the present invention has the following beneficial effects: First, by comprehensively considering the arc erosion when the contact is disconnected, the bounce wear when it is closed, and the degradation of contact resistance when it is turned on, it achieves multi-dimensional quantification of the actual damage degree of each action. Compared with the method of monitoring only a single parameter in the prior art, it significantly improves the comprehensiveness and accuracy of damage assessment. Second, by introducing health factors to achieve aging adaptation of the damage assessment model, the aged contacts under the same electrical stress are given a higher single damage value, which overcomes the problem of underestimation of damage after aging caused by using a fixed damage coefficient in the prior art, and ensures that the prediction model can be adjusted in real time to follow the aging process of the contact.

[0011] Furthermore, this invention achieves real-time online acquisition of high-precision voltage and current waveform data through the IO-Link communication interface, avoiding the lag of offline detection or periodic inspection methods in the prior art; by accumulating the corrected single damage value to the cumulative damage value and comparing it with the preset total damage threshold, it realizes dynamic prediction of remaining life based on physical damage, and can maintain high prediction accuracy under different load conditions and different usage environments, providing reliable technical support for predictive maintenance of industrial equipment. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1This is a flowchart of a relay anomaly prediction method provided in an embodiment of the present invention. Detailed Implementation

[0014] 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 embodiments of the present invention, and not all embodiments. 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.

[0015] Before describing the method of this invention in detail, the hardware system architecture on which this method can be implemented is first described. In this embodiment, the method can run in an industrial control system that includes IO-Link smart relays, an IO-Link master station, and an edge computing gateway. Wherein: IO-Link Smart Relay: It integrates voltage and current sensors, and can collect the voltage across the contacts and the current flowing through the contacts in real time at a sampling rate of not less than 10kHz; it has a built-in microcontroller that supports the IO-Link communication protocol and can upload the collected waveform data through the IO-Link interface; some high-end models can have a built-in edge computing unit to directly extract feature values ​​and then upload them.

[0016] IO-Link Master Station: As a data aggregation node, it connects multiple IO-Link smart relays, supports multi-channel high-speed data acquisition, has edge computing capabilities, and can run feature extraction and lightweight damage calculation algorithms; it transmits the processed data to the upper-layer gateway.

[0017] Edge computing gateway / PLC: Receives data uploaded by the IO-Link master station, runs the core state estimation and lifetime prediction model, performs cumulative damage updates, remaining lifetime prediction, and early warning triggering; the results can be uploaded to the cloud for long-term storage and model optimization.

[0018] The main implementer of the method of this invention is an edge computing gateway or an IO-Link master station with strong computing capabilities. The method steps are described in detail below with reference to specific embodiments.

[0019] As one possible embodiment of the present invention, such as Figure 1 As shown, a relay anomaly prediction method is provided, which includes the following steps: S100: Obtains voltage and current waveform data of the relay during each operation via the IO-Link communication interface.

[0020] When the relay actuates (i.e., contacts close or open), the internal sensor of the intelligent relay is triggered, recording waveform data of the entire actuation process. To ensure data integrity, the acquisition window is extended by a certain duration before and after the actuation, for example, 5ms is reserved before contact closure and 5ms is reserved after contact opening, to avoid potential data omissions during sensor triggering. Each actuation process includes the contact closure process, the stabilization conduction process, and the contact opening process. Specifically: Contact closing process: from the moment the coil is energized, the contact begins to move until the contact makes its first contact, until the bounce ends and the circuit is stably connected; Stable conduction process: The time period during which the contacts are stably closed and conducting; Contact disconnection process: from the moment the coil is de-energized until the contact separates until the arc is extinguished and the current is completely cut off.

[0021] The sensor acquires voltage and current waveforms for the three processes described above at a sampling rate of no less than 10kHz, forming complete action waveform data. This data is transmitted in real time to the IO-Link master station or edge computing gateway via the IO-Link communication interface. IO-Link (IEC 61131-9) is a point-to-point communication protocol that supports bidirectional data exchange, ensuring reliable transmission of high-precision waveform data.

[0022] S200: Extract the action features corresponding to each action based on the voltage waveform data and current waveform data.

[0023] The action characteristics include at least the characteristics of the broken arc, the characteristics of the closed bounce, and the steady-state contact resistance. The specific extraction method is as follows: S210: Extract the characteristics of the broken arc, which include the square integral of the broken arc current. This feature is obtained by integrating the current waveform data from the moment the contacts separate to the moment the arc is extinguished. Wherein: Contact separation moment The voltage rise is determined by the moment when the voltage waveform spikes during the contact disconnection process. When the contacts separate, the gap breaks down, generating an electric arc. Since the arc voltage is usually much higher than the conduction voltage drop when the contacts are closed (e.g., a spike from tens of millivolts to 10-30 volts), the voltage waveform will show a distinct spike edge.

[0024] Arc extinction moment The value is determined by the moment when the current waveform drops to zero and no longer rises. When the arc is extinguished, the current is completely cut off, and the waveform returns to zero.

[0025] Integrating the square of the current within the above interval yields... The calculation formula is as follows: The electric arc generated when the contacts break is the primary cause of contact material loss. The energy of the arc is determined by both the arc voltage and arc current; however, directly measuring the arc voltage requires a differential probe located close to the contacts, which is costly and difficult to implement. In practical applications, the degree of material erosion caused by the arc is the product of the square of the arc current and the arcing time. There is a strong correlation because the thermal effect of the electric arc is mainly generated by the electric current, and the amount of material vaporization and splashing is directly proportional to the input heat. Therefore, choosing... As a characterization index of arc damage, it can effectively reflect the degree of arc erosion and avoid the difficulty of measuring arc voltage, thus having good engineering feasibility.

[0026] S220: Extract closed bounce features, including the square integral of the closed bounce current. This feature is obtained by integrating the current waveform data during the bounce period of the contact closure process. When the contacts close, due to mechanical impact, the contacts bounce multiple times, each bounce generating a brief electric arc, reflected in the current waveform as multiple on-off oscillations. The bounce period is the time from the first contact to the end of the bounce and stable conduction. Integrating the square of the current during this period yields the result. The calculation formula is as follows: Although the bouncing arc during contact closure is short-lived (typically microseconds to milliseconds), its instantaneous energy can be very high due to the impact current at the moment of closure. Repeated bouncing can cause micro-melting and transfer of the contact material, and long-term accumulation can also lead to surface deterioration of the contact. As a damage indicator for closed bounce, it is consistent with the broken arc indicator in form, which facilitates subsequent comprehensive modeling and can accurately reflect the damage to the contact points caused by the arc thermal effect during the bounce process.

[0027] S230: Extract steady-state contact resistance R c .

[0028] The voltage drop across the contacts and the load current during the stable conduction phase are determined. The stable conduction phase is the period from the end of the bounce period after contact closure to the start of contact opening. Within this period, a stable time window is selected, and the average voltage drop is calculated. and average current Steady-state contact resistance: As relays are used more frequently, oxide films, carbides, or material transfer form on the contact surface due to factors such as electric arcing and environmental oxidation, leading to increased contact resistance. Increased contact resistance intensifies heat generation during conduction, further accelerating aging and creating a vicious cycle. Therefore, steady-state contact resistance is a direct indicator of the degree of contact surface degradation and a crucial basis for predicting remaining lifespan. Real-time monitoring of R... cChanges in these changes can be used to dynamically assess the health status of the contacts.

[0029] The three dimensions of features extracted from S210 to S230 are: the breaking arc feature, which is directly related to the material ablation when the contact is broken; the closing bounce feature, which reflects the impact wear when the contact is closed; and the steady-state contact resistance, which characterizes the long-term degradation of the contact surface. The combination of these three features, compared to existing technologies that only monitor a single parameter (such as only counting the number of actions or only detecting contact resistance), can more comprehensively reflect the actual damage to the contact caused by each action.

[0030] For example, a single large current interruption may produce significant [damage / damage]. A single instance of mechanical jamming may manifest as a prolonged bounce time, leading to... An increase in contact resistance, and a slow rise in contact resistance, reflect a long-term aging trend. These three characteristics characterize the contact state from different perspectives, providing a rich data foundation for subsequent damage quantification.

[0031] S300: Determine the current relay's health factor based on the steady-state contact resistance. The health factor H is used to quantify the degree of aging of the contact points, and its calculation formula is as follows: ;in: This represents the steady-state contact resistance measured during the current action. The initial contact resistance of the new relay contacts can be obtained through factory calibration or first operation measurement and stored in the device; The contact resistance threshold corresponding to the end of the relay's lifespan is generally set to 1.5 to 2 times the initial value based on experimental data.

[0032] This formula normalizes the change in contact resistance to the [0,1] interval. When H=0, it means the contact is brand new, and when H=1, it means the contact has reached the end of its lifespan.

[0033] The advantages of using linear normalization are twofold: firstly, the health factor has a linear relationship with the contact resistance, facilitating the subsequent construction of the damage coefficient function; secondly, normalization eliminates the influence of differences in the initial resistance of different relays, making the health factor comparable across devices. By calculating H in real time, the aging process of the contacts can be dynamically sensed, laying the foundation for subsequent adaptive damage calculation.

[0034] S400: Generates the single-injury value for this action based on the characteristics of the broken arc, the characteristics of the closed bounce, and health factors.

[0035] Single-shot damage value of the i-th action Calculated by the following formula: ;in, These are the segmental injury coefficient function and the bounce injury coefficient function, respectively, which are related to the health factor H, and both are monotonically increasing functions of H.

[0036] Arc breaking and contact bounce are the two main physical processes causing contact damage. Their contributions to contact wear are independent, and both can be controlled by... Quantification. The above calculation formula uses a linear combination form that conforms to the superposition principle of damage accumulation, making it easy to understand and implement.

[0037] As contacts age, their material properties change (e.g., melting point decreases, heat capacity decreases), resulting in greater actual damage from the same arc energy. Using a fixed coefficient would lead to an underestimation of damage in the later stages of aging. Introducing a coefficient function positively correlated with H addresses this issue. This allows the damage model to adapt to the aging process: when the contact is new (H is small), the coefficient is close to the base value; when the contact ages (H increases), the coefficient increases accordingly, and the same arc energy is assigned a higher damage value. This mechanism is the core of the adaptive prediction achieved in this invention.

[0038] In this embodiment, Using linear function form: ;in: The basic damage coefficient is obtained through laboratory calibration. For example, under rated resistive load and rated current, the average damage coefficient of each operation of a new relay is measured. And normalize the single damage value to 1, thereby inferring . This is the aging correction factor, obtained through accelerated aging experiments. For example, life tests are performed on the same model of relay, and the aging values ​​at different stages are recorded. The coefficients were determined by regression analysis with respect to the actual remaining lifespan.

[0039] By introducing a health factor H and using it for dynamic adjustment of the damage coefficient, the model can be adjusted in real time to follow the contact aging process. When the contact health factor increases from 0.2 to 0.8, Possibly from Increase to (Assuming) ) makes the same The corresponding damage value increased by 80%, effectively reflecting the accelerated aging effect. This mechanism overcomes the problem of underestimation of post-aging damage caused by using a fixed damage coefficient in existing technologies, and always maintains an accurate reflection of the true degree of damage.

[0040] S500: The single damage value is added to the cumulative damage value, and the remaining life of the relay is determined based on the cumulative damage value and the preset total damage threshold to generate multi-level abnormal early warning information.

[0041] Cumulative damage value Where N represents the number of actions taken. The preset total damage threshold. The total damage capacity corresponding to the relay under rated operating conditions can be obtained through accelerated life testing, such as operating under rated resistive load and rated current until failure, and calculating the sum of all single damage values ​​throughout the entire life cycle.

[0042] The S500 procedure further includes the following sub-steps: S510: Obtain the single damage value of a preset number of actions backward from the current time point, and calculate its moving average value. The preset number of times can be set according to actual needs, such as taking the most recent 50 or 100 actions. The formula for calculating the moving average is: Where M is the preset quantity and i is the current number of actions. Using a moving average instead of a single value for prediction is to smooth out the impact of short-term fluctuations on the prediction results. For example, a sudden surge in damage value due to an accidental high-current interruption might lead to an overly pessimistic prediction of remaining life if that value is used directly to predict the remaining life; the moving average, however, reflects recent damage trends, making the prediction more robust.

[0043] S520: Determine the remaining equivalent number of actions based on the cumulative damage value, total damage threshold, and sliding average. The calculation formula is as follows: This formula is based on the principle of "remaining damage capacity divided by the current damage rate". Wherein, Indicates the remaining damage capacity. This represents the average damage consumed per action under the current operating conditions. Dividing the two values ​​yields the remaining number of actions. This method represents a fundamental shift from traditional "counting actions" to "counting damage": traditional methods assume that each action consumes the same amount of lifespan, while this invention dynamically adjusts the damage value of each action based on actual operating conditions, thus providing more accurate predictions. For example, when a relay switches from light load to heavy load, The lifespan will increase, and the remaining life prediction value will decrease accordingly, so as to reflect the impact of changes in operating conditions on lifespan in a timely manner.

[0044] By accumulating the physical damage from each action and comparing it to a total damage threshold, different degrees of wear corresponding to the same number of actions under different operating conditions can be effectively distinguished. The use of moving averages smooths out short-term fluctuations, making the prediction results more robust. For example, in a real-world scenario: a relay operates 8000 times under light load, accumulating damage... 60,000 (based on standard movement), total injury threshold Then switch to overload, and calculate the sliding average of the most recent 50 actions. (That is, each action is equivalent to 2 standard actions). Therefore, the remaining lifetime is predicted to be (10000−6000) / 2=2000 actions, while traditional counting methods would incorrectly predict 10000−8000=2000 actions (assuming 8000 actions have been performed). However, due to increased load, the remaining lifetime should actually be 1000 actions (if counted as standard actions) or less. The method of this invention promptly reflects the impact of load changes on lifetime.

[0045] S600: Generate multi-level abnormal warning information based on the remaining equivalent number of actions and the preset warning threshold.

[0046] To provide maintenance personnel with clear decision-making support, this embodiment sets up a three-level early warning threshold, specifically including: S610: Attention-level warning generated when or A warning at the attention level is generated, indicating that the relay status has entered the deterioration zone, and it is recommended to pay closer attention.

[0047] The reasoning behind setting the warning level threshold is as follows: Cumulative damage exceeding 70% means the relay's lifespan is largely exhausted; a health factor exceeding 0.5 indicates the contact resistance has deteriorated to approximately half of its lifespan's end value. Both conditions indicate the relay has entered a stable deterioration phase, requiring attention but not yet necessitating maintenance. Setting this warning level can remind maintenance personnel to include it in their upcoming inspection schedule.

[0048] S620: Warning-level alert generation when or When the lifespan is nearing its end, a warning level alert will be generated, indicating that the product is close to its end and suggesting that maintenance be scheduled and spare parts be prepared.

[0049] The reasoning behind setting the warning level threshold is as follows: cumulative damage exceeding 85% means the remaining lifespan is less than 15%, and a health factor exceeding 0.8 indicates that the contact resistance has deteriorated to more than 80% of the end-of-life value. At this point, the contact condition has significantly deteriorated and may fail at any time. Setting this level of warning is to allow maintenance personnel sufficient preparation time to arrange replacement during the equipment downtime window.

[0050] S630: Emergency Warning Generated when If the steady-state contact resistance changes by more than the preset sudden change threshold in a single jump, an emergency warning will be generated, indicating that a sudden fault such as contact welding may occur, and the machine should be stopped immediately for inspection.

[0051] The reasoning behind setting emergency thresholds is as follows: Cumulative damage exceeding 95% signifies that the relay is nearing the end of its lifespan, and any action could lead to failure. A single jump in contact resistance exceeding a preset threshold (e.g., an increase of more than 50% compared to the previous measurement) usually indicates abnormal changes on the contact surface, such as material fusion or severe erosion, which are precursors to sudden failures. Therefore, once an emergency warning is triggered, immediate measures should be taken to prevent the fault from escalating and causing greater losses.

[0052] By setting three progressive warning levels, frequent false alarms caused by a single threshold (such as alarms for minor over-limits) are avoided, and differentiated maintenance suggestions are provided under different risk levels, thus achieving an effective connection from condition monitoring to maintenance decision-making.

[0053] S700: Identifies the type of load driven by the current action based on voltage and current waveform data.

[0054] This step is another preferred embodiment of the present invention, used to further improve prediction accuracy. Specifically, it includes the following sub-steps: S710: Determine the power factor angle φ between voltage and current based on the voltage and current waveforms during the stable conduction phase of the contacts.

[0055] During the stable conduction phase, the voltage waveform within a certain time window is captured. and current waveform Calculate the phase difference between the two. A specific method could be: Detecting the zero-crossing point of the voltage and the moment when the current crosses zero Calculate the time difference Calculate the power factor angle based on the power frequency f (usually 50Hz or 60Hz). Determined based on whether voltage or current leads. Positive and negative: When current lags voltage >0 (inductive load), current leads voltage when <0 (capacitive load).

[0056] S720: Determine the load type based on the magnitude of the power factor angle.

[0057] In this embodiment, a preset power factor angle threshold is set. ,For example The judgment rules are as follows: when When identified as a resistive load; when When the load is inductive, it is identified as such.

[0058] The impedance characteristics of a load determine the phase relationship between voltage and current. Purely resistive loads (such as heaters and resistance wires) have voltage and current in phase, with a power factor angle close to 0°; inductive loads (such as motors and contactor coils) have current lagging behind voltage, with a positive power factor angle, typically between 30° and 60°; capacitive loads have current leading voltage, with a negative power factor angle. Since inductive loads are most common in industrial settings, while capacitive loads are relatively rare, this embodiment primarily distinguishes between resistive and inductive loads, but the method can also be extended to capacitive load identification. To avoid misjudgment caused by measurement noise, as long as the absolute value of the power factor angle is within 5°, it is considered a resistive load.

[0059] S800: Determine the corresponding load type coefficient based on the load type. The load type coefficient is used to quantify the amplification effect of different loads on contact damage. In this embodiment, the load type coefficient is set as follows: Resistive load: , as the baseline load type; Inductive load: The value range is [1.5, 3], and the specific value is determined according to the load inductance.

[0060] Inductive loads, due to their inductance, generate higher arc energy when the contacts break, causing significantly more damage to the contacts than resistive loads under the same current. Typically, for a typical inductive load (e.g., power factor 0.3–0.5), the damage from a single operation is approximately 1.5–3 times that of a resistive load. Therefore, by introducing a load type coefficient, the damage under different loads can be normalized to the same benchmark.

[0061] The specific calibration of the load type coefficient can be performed through the following experiment: Select the same model of relay and operate it until failure under different load types and the same current level, recording the total damage value over the entire life cycle. Let the total damage under resistive load be... The total damage under inductive load is Then the load type coefficient for inductive loads can be calibrated as follows: (This is a reciprocal relationship; in practical applications, it needs to be determined based on the normalization direction of the damage calculation formula.) In the formula of this embodiment, As a multiplier, it directly affects the damage value; therefore, the inductive load corresponds to... It should be greater than 1.

[0062] S900: Uses load type coefficient to correct the single damage value.

[0063] Corrected single-shot damage value The following relationship must be satisfied: Revised Will replace the original This is used for subsequent cumulative damage updates and remaining lifetime predictions.

[0064] By introducing load type identification and correction, the model can automatically adapt to load changes. For example, when the same relay controls a heater (resistive) and a motor (inductive) at different time periods, each action under inductive load will be assigned a larger damage value, thus more accurately reflecting the actual lifespan consumption. Without this correction, the damage under inductive load would be underestimated, leading to an overestimation of the predicted remaining lifespan and potentially missing the optimal maintenance window. When the relay switches from controlling the heater to controlling the motor, The value of a single damage event is increased by adjusting the value from 1 to 2, which avoids underestimating the lifespan consumption and maintains high prediction accuracy in different application scenarios.

[0065] In summary, this embodiment fully utilizes the high-precision data acquisition capabilities of IO-Link, and through multi-dimensional feature extraction, adaptive health factors, cumulative damage prediction, and load type correction, it effectively solves the problems of low accuracy and inability to adapt to aging and changes in operating conditions in existing relay life prediction methods, providing reliable technical support for predictive maintenance of industrial equipment.

[0066] Furthermore, although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0067] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, mobile terminal, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0068] In an exemplary embodiment of this disclosure, an electronic device capable of implementing the above-described method is also provided.

[0069] Those skilled in the art will understand that various aspects of the present invention can be implemented as systems, methods, or program products. Therefore, various aspects of the present invention can be specifically implemented in the following forms: entirely in hardware, entirely in software (including firmware, microcode, etc.), or in a combination of hardware and software, collectively referred to herein as “circuit,” “module,” or “system.”

[0070] An electronic device according to this embodiment of the invention. The electronic device is merely an example and should not be construed as limiting the functionality or scope of the embodiments of the invention.

[0071] Electronic devices are manifested in the form of general-purpose computing devices. Components of an electronic device may include, but are not limited to: at least one processor, at least one memory, and buses connecting different system components (including memory and processor).

[0072] The memory stores program code that can be executed by a processor, causing the processor to perform the steps described in the "Exemplary Methods" section above, according to various exemplary embodiments of the present invention.

[0073] The storage may include readable media in the form of volatile storage, such as random access memory (RAM) and / or cache memory, and may further include read-only memory (ROM).

[0074] The storage may also include programs / utilities having a set (at least one) of program modules, including but not limited to: an operating system, one or more applications, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0075] A bus can represent one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus that uses any of the various bus architectures.

[0076] The electronic device can also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable a user to interact with the electronic device, and / or any device that enables the electronic device to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication can be performed via input / output (I / O) interfaces. Furthermore, the electronic device can communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter. The network adapter communicates with other modules of the electronic device via a bus. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0077] In exemplary embodiments of this disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the methods described above is stored. In some possible embodiments, various aspects of the present invention may also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps of the various exemplary embodiments of the present invention described in the "Exemplary Methods" section above.

[0078] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0079] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0080] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0081] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0082] Furthermore, the accompanying drawings are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention and are not intended to be limiting. It is readily understood that the processes shown in the above drawings do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0083] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0084] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for predicting relay anomalies, characterized in that, The method includes the following steps: The voltage and current waveform data of the relay during each operation are obtained through the IO-Link communication interface, wherein each operation includes the contact closing process, the stable conduction process, and the contact opening process. Based on the voltage waveform data and current waveform data, the action features corresponding to each action are extracted. The action features include at least the arc breaking feature, the closing bounce feature, and the steady-state contact resistance. Based on the steady-state contact resistance, the current health factor of the relay is determined; the health factor H satisfies the following relationship: ;in, This is the steady-state contact resistance measured during the current operation. The initial contact resistance of the new relay contact. This is the contact resistance threshold corresponding to the end of the relay's lifespan. Based on the characteristics of the broken arc, the characteristics of the closed bounce, and the health factors, a single-instance damage value for this action is generated; wherein, the first Single-shot damage value of the action The following relationship must be satisfied: ;in, For the first The square integral of the breaking arc current of each action is used to characterize the degree of contact material loss caused by arc erosion during the contact disconnection process. For the first The square integral of the closing bounce current of each action is used to characterize the degree of contact material loss caused by the bounce arc during the contact closure process. These are the disjunctive injury coefficient function and the bounce injury coefficient function, respectively, which are related to the health factor H, and both are positively correlated with H; The single damage values ​​are accumulated to a cumulative damage value, and the remaining life of the relay is determined based on the cumulative damage value and a preset total damage threshold to generate an abnormal warning message.

2. The method according to claim 1, characterized in that, The square integral of the interrupted arc current is obtained by integrating the current waveform data from the moment the contacts separate to the moment the arc is extinguished; wherein, the moment the contacts separate is determined based on the moment when the voltage waveform suddenly rises during the contact disconnection process, and the moment the arc is extinguished is determined based on the moment when the current waveform drops to zero and no longer rises; The square integral of the closed bounce current is obtained by integrating the current waveform data during the bounce period in the contact closure process; wherein, the bounce period is determined by the period during which the current waveform exhibits multiple on-off oscillations after the contact is closed. The steady-state contact resistance is determined based on the contact voltage drop and load current during the stable conduction phase of the contact; wherein, the stable conduction phase is the period from the end of the bounce period after the contact is closed to the start of contact opening.

3. The method according to claim 1, characterized in that, The segmental damage coefficient function and the bounce damage coefficient function They are linear functions, satisfying the following relationship: ;in, Based on the damage coefficient, This is the aging correction factor.

4. The method according to claim 1, characterized in that, The step of determining the remaining lifespan of the relay based on the cumulative damage value and a preset total damage threshold includes: Obtain the single damage value of a preset number of actions backward from the current time point, and calculate the sliding average of the single damage values ​​of the preset number of actions. Based on the cumulative damage value, the preset total damage threshold, and the sliding average value, the remaining equivalent number of actions is determined, satisfying the following relationship: ;in, The remaining equivalent number of actions, The preset total damage threshold, This represents the current cumulative damage value. The moving average of the damage value per action for a preset number of actions.

5. The method according to claim 4, characterized in that, The method further includes: Based on the remaining equivalent number of actions and the preset warning threshold, multi-level abnormal warning information is generated; Among them, when At that time, an attention-level warning will be generated; when At that time, a warning level alert will be generated; when An emergency warning is generated when the steady-state contact resistance changes by more than a preset sudden change threshold in a single instance.

6. The method according to any one of claims 1 to 5, characterized in that, The method further includes: Based on the voltage waveform data and current waveform data, the load type driven by the current action is identified; the load type includes inductive load and resistive load. Determine the corresponding load type coefficient based on the load type; The load type coefficient is used to perform load correction on the single damage value, resulting in a corrected single damage value. The following relationship must be satisfied: ;in, This is the load type coefficient; the load type coefficient for inductive loads is greater than that for resistive loads.

7. The method according to claim 6, characterized in that, The identification of the load type driven by the current action includes: Determine the power factor angle between voltage and current based on the voltage and current waveforms during the stable conduction phase of the contacts. ; when When identified as a resistive load; when When identified as an inductive load; among them, This is the preset power factor angle threshold.

8. The method according to claim 6, characterized in that, The load type coefficient is preset according to the load type, wherein the load type coefficient corresponding to inductive load is 1.5 to 3, and the load type coefficient corresponding to resistive load is 1.

9. A non-transitory computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements a relay anomaly prediction method as described in any one of claims 1 to 8.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements a relay anomaly prediction method as described in any one of claims 1 to 8.

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