Power relay diagnosis method and system

Abstract

The invention provides a power relay diagnosis method and system, and relates to the technical field of power relay diagnosis. The method comprises the following steps: acquiring control signal state information of a to-be-diagnosed power relay and working state information of other electrical equipment adjacent to the physical position of the to-be-diagnosed power relay; determining a time window when the contact of the to-be-diagnosed power relay is in an off state and the external interference is lower than a preset threshold value; in the time window, controlling the multipath switching unit to connect the contact resistance measuring unit to two ends of a contact of the power relay to be diagnosed; after the contact resistance measuring unit is connected to the two ends of the contact, a resistance value between the two ends of the contact is collected; and judging the contact adhesion state of the to-be-diagnosed power relay according to the resistance value. According to the method, the accuracy of a measurement result is ensured, the state of the relay contact is accurately and quickly judged, and misjudgment is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of power relay diagnosis, and in particular to a power relay diagnosis method and system. Background Art

[0002] Control cabinets are a core component of modern industrial automation systems, housing numerous power relays. These relays perform critical tasks in controlling various actuators on the production line, such as driving motors, controlling valve opening and closing, and regulating the power of heating units. To maximize the use of limited space within the control cabinet, these power relays are typically designed to be compact and densely mounted on standard mounting rails. A typical industrial control cabinet may integrate hundreds or even more power relays, creating a complex electrical and physical environment.

[0003] The reliability of power relays is directly related to the continuity of production processes and the safety of equipment. Contact sticking is a common and serious failure mode of power relays. This occurs when the relay contacts fail to fully separate when they should open, remaining somewhat conductive. This failure can cause loss of control of the controlled equipment, leading to production accidents or equipment damage. Therefore, regular health assessment and fault diagnosis of the large number of power relays in control cabinets, especially the timely detection of contact sticking failures, is crucial to ensuring the stable operation of production systems.

[0004] Contact resistance measurement is an effective technique for diagnosing contact sticking in power relays. When the relay is normally disconnected, the moving and static contacts should be insulated from each other, exhibiting an extremely high open-circuit resistance (theoretically infinite, but in practice, an extremely high insulation resistance). If the measured resistance between the contacts is significantly lower than the normal open-circuit resistance, it indicates that the contacts may not be fully separated and are sticking. The resistance value exhibited varies depending on the degree of sticking, ranging from a low, finite resistance to a near-short-circuit resistance.

[0005] In real-world applications, where numerous power relays are densely installed within industrial control cabinets and require online or quasi-online diagnostics, the sheer number and density of relays makes it difficult to route individual measurement cables from each relay contact to a centralized diagnostic unit. To address this issue, a natural approach is to utilize shared measurement resources and multi-way switching. Specifically, one or a few diagnostic measurement units are designed and, through a multi-way switching system, are connected sequentially or as needed to the contacts of the relays to be diagnosed. This approach significantly reduces wiring, lowering installation complexity and costs.

[0006] However, sharing measurement resources and switching mechanisms presents new technical challenges in practical applications. When measuring the open-circuit contact resistance of a particular power relay, other adjacent power relays may be operating normally. For example, a neighboring relay may be closed, controlling a high-power load, with hundreds of amperes or even higher flowing through its contacts; or its coil may be energized, generating strong electromagnetic fields and heat. These operating relays and the loads they control can generate various forms of interference.

[0007] When the measurement circuit is connected to the open contacts of the relay under diagnosis through a switching system, electromagnetic fields generated by nearby operating relays (through spatial coupling), crosstalk between cables, and transient voltage / current changes in the power supply or grounding system (through conductive coupling) can all be induced into the measurement circuit. In particular, open-circuit contact resistance measurements are high-impedance measurements, and the measurement signal is typically very weak, making them extremely sensitive to external interference. This interference can cause significant fluctuations or deviations in the measured resistance value. It can even result in a lower resistance value when the contacts are actually open, leading to a false diagnosis of contact sticking.

[0008] Furthermore, if the diagnostic system measures relays in groups, when measuring a relay within a group or in adjacent groups, other relays in the same group or in adjacent groups may be in a specific electrical state (for example, their coils are driven by control signals, or the loads they control are switching). Such electrical connections and transient responses between relays and between relays and loads (such as voltage spikes when inductive loads are disconnected or current surges when capacitive loads are charged) may also be coupled into the measurement circuit through the switching system, common power paths, or common ground paths, causing distortion in the measurement results.

[0009] In industrial control cabinets, where space is limited and relays are densely installed, diagnosing contact sticking using a contact resistance measurement method based on shared measurement resources and a multi-channel switching mechanism requires addressing interference from adjacent relays and other electrical activities within the system on the open-circuit resistance measurement of high-impedance contacts. This ensures accurate measurement results, enables accurate and rapid judgment of relay contact status, and avoids misjudgments. Summary of the Invention

[0010] The purpose of the present invention is to provide a power relay diagnosis method and system, which aims to solve the interference problem caused by adjacent working relays and other electrical activities within the system on the open circuit resistance measurement of high-impedance contacts, ensure the accuracy of the measurement results, realize accurate and rapid judgment of the relay contact status, and avoid misjudgment.

[0011] In a first aspect, the present invention provides a power relay diagnosis method, comprising the following steps:

[0012] S1 obtains the control signal status information of the power relay to be diagnosed and the working status information of other electrical equipment physically adjacent to the power relay to be diagnosed;

[0013] S2. Based on the control signal status information of the power relay to be diagnosed and the working status information of other adjacent electrical equipment, it is determined that the power relay contacts to be diagnosed are in the off state and the time window of the external interference is below a preset threshold;

[0014] S3 within the time window, the control multi-way switching unit to connect the contact resistance measuring unit to both ends of the contact of the power relay to be diagnosed;

[0015] S4. After the contact resistance measurement unit is connected to both ends of the contact, the resistance value between the two ends of the contact is collected;

[0016] S5. Determine the contact adhesion state of the power relay to be diagnosed based on the resistance value.

[0017] The power relay diagnosis method provided by the present invention can effectively suppress the interference of adjacent working relays and other electrical activities within the system on high-impedance measurement during the brief period when the contacts of the relay to be diagnosed are disconnected, while meeting the efficiency requirements of rapid scanning diagnosis of a large number of relays and ensuring the accuracy of the diagnostic results.

[0018] In a second aspect, the present invention provides a power relay diagnostic system, comprising:

[0019] an acquisition module, configured to acquire control signal status information of the power relay to be diagnosed and operating status information of other electrical devices physically adjacent to the power relay to be diagnosed;

[0020] a determination module, configured to determine a time window in which the contacts of the power relay to be diagnosed are in an open state and the external interference is lower than a preset threshold value based on the control signal status information of the power relay to be diagnosed and the operating status information of other nearby electrical devices;

[0021] A control module is used to control the multi-way switching unit to connect the contact resistance measuring unit to both ends of the contacts of the power relay to be diagnosed within a time window;

[0022] an acquisition module, configured to acquire the resistance value between the two ends of the contact after the contact resistance measurement unit is connected to the two ends of the contact;

[0023] The judgment module is used to judge the contact adhesion state of the power relay to be diagnosed according to the resistance value.

[0024] As can be seen from the above, the power relay diagnostic method provided by the present invention can intelligently select and utilize time windows with relatively low interference for contact open-circuit resistance measurement in specific application scenarios where a large number of power relays are densely installed in industrial control cabinets, share measurement resources, and are subject to complex external interference. By coordinating with the real-time operating timing of the relay control system, this method effectively suppresses interference with high-impedance measurements caused by adjacent operating relays, high-power load switching, and other electrical activities within the system, greatly improving the accuracy of contact sticking diagnosis and reducing the rate of false positives.

[0025] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the embodiments of the present invention. The purposes and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A flow chart of a power relay diagnosis method provided by an embodiment of the present invention.

[0027] Figure 2 A schematic structural diagram of a power relay diagnostic system provided by an embodiment of the present invention.

[0028] Description of labels:

[0029] 100, acquisition module; 200, determination module; 300, control module; 400, acquisition module; 500, judgment module. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0031] 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 the present invention, the terms "first", "second", etc. are used only to distinguish the description and should not be understood as indicating or implying relative importance.

[0032] Reference Attachment Figure 1 The present invention provides a power relay diagnosis method, comprising the following steps:

[0033] S1 obtains the control signal status information of the power relay to be diagnosed and the working status information of other electrical equipment physically adjacent to the power relay to be diagnosed;

[0034] S2. Based on the control signal status information of the power relay to be diagnosed and the working status information of other adjacent electrical equipment, it is determined that the power relay contacts to be diagnosed are in the off state and the time window of the external interference is below a preset threshold;

[0035] S3 within the time window, the control multi-way switching unit to connect the contact resistance measuring unit to both ends of the contact of the power relay to be diagnosed;

[0036] S4. After the contact resistance measurement unit is connected to both ends of the contact, the resistance value between the two ends of the contact is collected;

[0037] S5. Determine the contact adhesion state of the power relay to be diagnosed based on the resistance value.

[0038] Acquiring control signal status information for the power relay under diagnosis and operating status information for other electrical equipment physically proximate to the power relay under diagnosis refers to obtaining signals reflecting the current or expected operating status of the relay under diagnosis, as well as data reflecting the current operating status of other electrical equipment physically proximate to the relay. This information can originate from feedback signals from the control system, sensors, communication interfaces, or the device itself. It primarily provides the foundational data needed to determine the timing of subsequent measurements. Determining the time window during which the contacts of the power relay under diagnosis are open and external interference is below a preset threshold involves predicting when the contacts of the relay under diagnosis are in a stable open state based on the acquired control signal status information and predicting the level of external interference based on the operating status information of neighboring electrical equipment. This allows identification of specific time periods during which the contacts of the relay under diagnosis are open and external interference is low. This determination process can be implemented by a processor-executed algorithm or by dedicated hardware logic. Its primary purpose is to identify a low-interference time window suitable for measuring high-impedance contact resistance.

[0039] This method operates based on a deep understanding of the electrical environment and relay operating sequences within industrial control cabinets. It uses intelligent timing control to mitigate interference and achieve online contact open-circuit resistance measurement. First, a timing information acquisition unit monitors the control signals and operating status of the relay under diagnosis and its adjacent critical electrical equipment (other relays, loads) in real time. Based on this real-time information and pre-defined rules, it accurately calculates and targets a brief time window during which the relay's contacts are open and the impact of nearby major interference sources (such as high-current switching and coil pull-in / out transients) is relatively minimal. When this "quiet" measurement window arrives, a high-speed multi-way switching unit is rapidly activated, precisely connecting a high-impedance contact resistance measurement unit to the open contacts of the target relay. The contact resistance measurement unit applies a weak test signal within a very short period of time, collects the response, and rapidly calculates the contact resistance value. The diagnostic judgment unit receives this resistance value and determines whether the contacts are sticking based on a preset threshold. This entire process is coordinated through scan management, enabling efficient and orderly scan diagnosis of a large number of relays within the control cabinet. By performing measurements when interference is minimal, the accuracy of high-impedance measurements is greatly improved, effectively solving the problem of misjudgment of interference in dense installation and online diagnosis scenarios.

[0040] The core innovation of this application is that, by comprehensively considering the control status of the power relay to be diagnosed and the working status of the adjacent electrical equipment, a time window in which the contact is in the disconnected state and the external interference is low is intelligently determined, and the contact resistance measurement is performed within this window, thereby effectively overcoming the influence of external interference on the accuracy of high impedance measurement in a dense installation environment.

[0041] Specifically, the method first obtains the control signal status information of the power relay to be diagnosed and the working status information of other electrical equipment in its physical proximity. Based on this information, the system analyzes and determines a specific time window that meets two conditions: the contacts of the power relay to be diagnosed are expected to be in a disconnected state, and the external interference generated by the adjacent electrical equipment is lower than a preset threshold. Once the time window is determined, the control logic drives the multi-way switching unit within the window to connect the contact resistance measurement unit to the two ends of the contact of the power relay to be diagnosed. After the connection is completed, the contact resistance measurement unit collects the resistance value between the two ends of the contact. Finally, based on the collected resistance value, it is determined whether the contacts of the power relay to be diagnosed are stuck. The entire process ensures the reliability of the measurement data by performing measurements at a time of low interference and contact disconnection.

[0042] As a preferred embodiment, the solution of the present application is specifically implemented as follows: obtaining the control signal status information can be achieved by reading the voltage or current signal of the relay coil drive circuit. The working status information of the adjacent electrical equipment can be obtained from the control interface of the equipment itself or by monitoring the current changes in its power supply line. Determining the time window can be completed by an embedded processor executing an algorithm, which judges its disconnection delay based on the relay control signal, and predicts the interference timing based on the type and status of the adjacent device, and then looks for the low-interference period after the two are superimposed. The multi-way switching unit can be constructed using a semiconductor switch or a small electromechanical relay array. The contact resistance measurement unit can be a combination of a constant current source circuit and a high-precision voltage measurement circuit. Determining the contact adhesion state can be performed by comparing the measured resistance value with a threshold stored in a memory.

[0043] Through the above scheme, this application can accurately measure the open-circuit resistance of power relay contacts in densely installed environments with external interference. By selecting a time window when the contacts are disconnected and external interference is low for measurement, the influence of interference signals on high-impedance measurements is effectively avoided, and the accuracy of resistance measurement results is improved. Based on the accurate resistance value, the judgment of the contact adhesion state is more reliable, the misdiagnosis rate is reduced, and the stable operation of the industrial control system is guaranteed.

[0044] In some embodiments, the specific steps in step S2 include:

[0045] S21. According to the control signal status information of the power relay to be diagnosed, it is determined whether the power relay to be diagnosed receives a disconnect instruction, and according to the disconnect instruction, the stabilization time required for the power relay contacts to be diagnosed to change from the energized state to the disconnected state is determined;

[0046] S22. Based on the working status information of other electrical equipment and the preset association rules, by identifying the first continuous time interval in which the external interference is below the preset threshold, the predicted period of transient interference generated by other electrical equipment is determined; the timing association rules include the association between the equipment type and the transient interference timing;

[0047] S23. According to the stabilization time required for the power relay contacts to be diagnosed to transition from the energized state to the disconnected state, the starting time point at which the power relay contacts to be diagnosed reach a stable disconnected state is determined;

[0048] S24. According to the starting time point and the transient interference prediction period, identifying the second continuous time interval after the power relay contacts to be diagnosed are stably disconnected and the external interference is lower than the preset threshold;

[0049] S25. According to the second continuous time interval and the preset contact resistance measurement time, select a time period that meets the measurement time requirement from the continuous time interval as the time window.

[0050] Control signal status information refers to the electrical signal or logical state used to control the energization or de-energization of the power relay coil. For example, it can be the "high level" or "on" state when the control relay is energized, and the "low level" or "off" state when the control relay is disconnected. Settling time refers to the interval between when the power relay receives a control signal (e.g., a disconnect command) and when its contacts physically switch and reach a stable state. This time may be affected by various factors, such as the relay's own characteristics, service life, and environmental conditions. Operating status information for other electrical equipment refers to the current operating mode or state of other electrical equipment physically adjacent to the power relay to be diagnosed. For example, it can be "running," "standby," "starting," or "stopping." These states may be related to electromagnetic interference or transient electrical signals generated by the equipment. Pre-set association rules are sets of pre-established rules that describe the timing characteristics, intensity, or impact range of transient interference generated by a specific type of electrical equipment under specific operating conditions. These rules can be based on experimental data, theoretical models, or empirical knowledge and are used to predict the time period when interference will occur. The transient interference prediction period refers to the time interval, predicted based on association rules, during which transient interference from neighboring electrical equipment may affect contact resistance measurement. The first continuous time interval refers to the continuous period during which the predicted external interference is below a preset threshold, after accounting for potential transient interference from neighboring electrical equipment. The start time of the stable disconnection state refers to the moment when the relay contacts are physically completely disconnected and in a stable state, calculated based on the time the relay receives the disconnection command and its stabilization time. The second continuous time interval refers to the continuous period after the relay contacts reach the stable disconnection state, during which external interference is below a preset threshold. This interval is theoretically suitable for contact resistance measurement. The preset contact resistance measurement duration is the minimum time required to complete contact resistance acquisition and processing. This duration depends on the response speed of the measurement circuit, the sampling rate, and the data processing requirements. The time window refers to the time period ultimately selected from the second continuous time interval for actual contact resistance measurement that meets the measurement duration requirements.

[0051] This solution refines the steps for determining the measurement time window to more precisely identify a suitable time period for contact resistance measurement, thereby improving measurement accuracy and avoiding misjudgments. This is achieved through the following specific steps: First, based on the control signal status information of the power relay to be diagnosed, it is determined whether the relay has received a disconnection command, which is a prerequisite for measuring the contact disconnection state. Furthermore, based on the disconnection command, the stabilization time required for the relay contacts to transition from the closed state to the open state is determined. This step recognizes that a process is required from receiving the command until the contacts are physically separated and stabilized. By determining this stabilization time, measurements can be avoided when the contacts are not yet fully disconnected, ensuring that subsequent judgments are based on the contact disconnection state. Simultaneously, based on the operating status information of other electrical devices physically adjacent to the relay to be diagnosed and pre-set association rules, the time periods during which these devices are likely to generate transient interference are predicted. These association rules, particularly those relating the device type to the transient interference timing, enable more accurate prediction of the type, intensity, and duration of interference that a specific device may generate under a specific operating state. This allows identification of the first continuous time interval during which external interference is likely to exceed a pre-set threshold, providing a basis for avoiding measurement during these periods of interference. Next, the determined stabilization time required for the power relay contacts to transition from the energized to the disconnected state is used to calculate the starting time point when the relay contacts actually reach a stable disconnected state. This starting time point serves as a benchmark to ensure that measurements are performed after the relay contacts are physically and stably disconnected. Then, combining the stable disconnection starting time point and the predicted transient interference period, a continuous time interval is identified that satisfies two conditions: it begins after the stable disconnection starting time point of the relay contacts and avoids periods when external interference exceeds a preset threshold. This identified second continuous time interval is theoretically a "clean" period suitable for contact resistance measurement. Finally, based on the identified second continuous time interval and the preset required contact resistance measurement duration, a time period within the continuous time interval that meets the measurement duration requirement is selected as the final time window for contact resistance measurement. Through the above steps, this solution can more accurately determine a time window suitable for high-impedance contact resistance measurement, effectively addressing the challenges posed by relay response delays and transient interference from neighboring equipment on measurement accuracy in complex industrial environments. This more precise time window determination method, combined with the subsequent steps of measuring the contact resistance within the determined time window, collecting the resistance value, and determining the contact sticking state, enables the entire diagnostic process to be carried out under ideal conditions where the relay contacts are stably disconnected and external interference is minimized, thereby significantly improving the accuracy and reliability of contact sticking diagnosis and reducing the misjudgment rate.

[0052] In one specific embodiment, the method for determining the time window can be implemented as follows: First, the control signal of the power relay to be diagnosed is monitored. When a disconnect command is detected, the timestamp of the command issuance is recorded. Simultaneously, a more accurate estimate of the current stabilization time is calculated using a preset algorithm model based on the standard stabilization time parameters of the relay model, or in combination with historical operating data of the relay (e.g., cumulative operation times, historical switching time records), and current ambient temperature. Adding the command issuance timestamp to this stabilization time estimate yields the starting time point when the relay contacts reach a stable disconnected state. Simultaneously, the system continuously obtains operating status information of other electrical devices adjacent to the relay to be diagnosed. For example, if a frequency converter is starting up nearby, based on preset association rules (e.g., a certain frequency converter model generates electromagnetic interference lasting approximately 50 milliseconds within a specific frequency range upon startup), it can be predicted that transient interference exceeding a threshold may exist during and after the inverter startup. By analyzing the predicted interference periods of all adjacent devices, all consecutive time intervals in which the overall external interference is below a preset threshold can be identified. Then, the starting time point of the relay's stable disconnection is compared with these low-interference time intervals to find the longest continuous time period starting after the starting time point and completely within the low-interference interval. This is the second continuous time interval. Finally, based on the fixed time length (e.g., 10 milliseconds) required for the contact resistance measurement unit to complete a measurement, a time period of at least 10 milliseconds is selected from this second continuous time interval as the final measurement time window. For example, if the second continuous time interval is from 100 milliseconds to 250 milliseconds after the instruction is issued, and the measurement time length requires 10 milliseconds, then 100 milliseconds to 110 milliseconds after the instruction is issued can be selected as the time window, or 150 milliseconds to 160 milliseconds, or 240 milliseconds to 250 milliseconds, etc. It is preferred to select an earlier time period to complete the diagnosis as quickly as possible.

[0053] Through the above method, the present application can more accurately determine a time window suitable for high-impedance contact resistance measurement. This effectively solves the challenges posed by the time required for the relay contacts to be stably disconnected and the transient interference of adjacent devices to measurement accuracy. Measuring within a determined time window can ensure that the resistance value is collected in an environment where the relay contacts are physically stably disconnected and external interference is minimized, thereby significantly improving the accuracy and reliability of the contact resistance measurement and reducing the contact adhesion misjudgment rate caused by measurement errors.

[0054] It should be noted that the association relationship between the device type and the transient interference time series in the association rule and the construction of the association rule itself can be achieved through the following steps:

[0055] First, synchronously obtain the operating status information of electrical equipment that is physically nearby and corresponds to the time when the electrical signal is collected. The purpose of this step is to obtain the current operating status of electrical equipment (such as other relays, motors, valves, etc.) that may cause interference around the relay to be diagnosed. This status information is the basis for predicting the interference period. The acquisition method can be to directly monitor the control signal line of the device, read the status word of the device through the industrial communication bus, or monitor the actual load current or voltage of the device through current or voltage sensors to determine its operating status. Synchronous acquisition means that the time point of obtaining this status information corresponds to the time point of collecting the environmental electrical signal, so as to facilitate subsequent correlation analysis.

[0056] Second, transient interference feature extraction. This step involves analyzing the collected ambient electrical signals to identify and quantify the transient interference components they contain. Ambient electrical signals may originate from the measurement circuit itself or its vicinity and contain various coupled-in noise and transients. Feature extraction involves identifying transient events from the original signal and calculating their properties, such as the transient signal's amplitude, duration, rate of change, and intensity within a specific frequency range. These features describe the type, intensity, and duration of transient interference and are fundamental to understanding its nature.

[0057] Third, the interference features are associated with the device status. This step establishes a correspondence between the transient interference features extracted in the second step and the operating status information of the adjacent electrical equipment obtained synchronously in the first step. For example, it is recorded that at a specific point in time, a nearby motor changes from a stopped state to a started state, and at the same time, a certain specific transient interference feature is detected in the measurement circuit signal. By recording a large number of such correspondences, a data set can be established on "what type of equipment may produce what type of transient interference when its state changes." This association is the basis for subsequent learning of interference timing patterns.

[0058] Fourth, transient interference timing regularity learning and rule generation. This step is based on the interference feature and device state association data set established in the third step, and uses analysis methods to find the regularity therein. The focus of the analysis is to determine what kind of regularity there is in the timing of the typical transient interference generated by a specific type of adjacent device when a specific working state changes relative to the time point of the state change instruction or event. For example, through analysis, it was found that after a certain model of motor receives a start instruction, the strongest interference it generates usually occurs after a fixed delay time after the instruction is issued and lasts for a fixed period of time. These discovered timing regularities, such as the relative start time and duration of the interference, are converted into structured rules and stored to form a rule base. These rules describe a method for predicting interference periods when the state of a known adjacent device changes.

[0059] Fifth, rule updating and optimization. This step maintains and improves the rules for associating device types with transient interference timings generated in step 4. As the diagnostic system operates over a long period of time at industrial sites, it continuously collects new environmental electrical signals and information about the operating status of adjacent devices, extracting and correlating interference features. This new data can be used to verify and correct existing rules. For example, if a deviation is found between the actual interference timing of a device and the rule prediction, the delay time or duration parameters in the rule can be adjusted based on the new data. Rule updates and optimizations ensure that the rule base reflects actual changes in the on-site electrical environment and improve the accuracy of interference period predictions.

[0060] In some embodiments, in step S21, the step of determining the stabilization time required for the contact of the power relay to be diagnosed to change from the energized state to the disconnected state according to the disconnection instruction includes:

[0061] Obtain the operating condition data of the power relay to be diagnosed; the operating condition data includes standard stabilization time, historical operating data and current environmental parameter information; the historical operating data includes service life or cumulative number of operations, and actual time data of historical contact state switching;

[0062] According to the working condition data, the current stabilization time estimate required for the power relay contacts to be diagnosed to change from the energized state to the disconnected state is calculated and used as the stabilization time required for the power relay contacts to be diagnosed to change from the energized state to the disconnected state.

[0063] This solution introduces the concept of "operating condition data," a data set used to comprehensively reflect the current operating status and performance characteristics of the power relay under diagnosis. Operating condition data encompasses multiple aspects of information: "Standard stabilization time" typically refers to the relay's stabilization time parameter measured at the factory or under standard test conditions; "Historical operating data" records the relay's cumulative operating conditions and performance changes since commissioning, such as its total service life or the number of switching operations, as well as the actual delay time measured during past contact state transitions (particularly from energized to deenergized); and "Current environmental parameter information" refers to the real-time physical quantities of the relay's environment during diagnostic measurements, such as ambient temperature and humidity. By acquiring and comprehensively analyzing this operating condition data, this solution calculates a "current stabilization time estimate" that better reflects the relay's current reality. This estimate takes into account potential performance degradation due to long-term use (reflected by historical operating data) and the impact of current environmental conditions on its performance (reflected by current environmental parameter information), making it more accurate than a single standard stabilization time estimate. The estimated value obtained by this dynamic calculation is used as the time required to determine the stable disconnection of the contact, which provides a more reliable basis for the subsequent determination of the starting time point of stable disconnection.

[0064] This solution obtains operating data from the power relay to be diagnosed and, based on this data, calculates an estimated stabilization time that reflects the relay's current actual state. This operating data covers the relay's standard performance parameters, historical usage, and current environmental conditions. Historical operating data, such as years of use or cumulative operating cycles, can reflect the relay's aging, while historical contact state switching times provide direct evidence of how relay performance changes over time. Current environmental parameters, such as temperature, directly affect the relay coil's response speed and the mechanical properties of the contacts. By comprehensively analyzing this information, a model or algorithm can be developed to predict the relay's actual stabilization time under current operating conditions. For example, historical data can be used to analyze the growth trend of stabilization time with usage or age, and the standard stabilization time can be adjusted based on the current temperature. The calculated current stabilization time estimate is used to determine the actual time required for the relay contacts to transition from the closed state to the open state. This more accurate stabilization time is used in subsequent steps to determine the starting time when the contacts reach a stable open state. Because the stabilization time is more accurately determined, the resulting stable open start time is also more accurate. Based on this accurate starting time point, combined with the analysis of the external interference prediction period, the continuous time interval after the contact is stably disconnected and the external interference is lower than the preset threshold can be more reliably identified. Finally, a period that meets the time required for contact resistance measurement is selected from this reliable time interval as the measurement window. This method of dynamically adjusting the stabilization time based on operating condition data enables the diagnostic system to adapt to individual differences, aging, and environmental changes of the relay, ensuring that measurements are performed during the period when the contact is indeed stably disconnected and external interference is minimal. This is combined with the steps in the aforementioned scheme of judging whether a disconnection instruction has been received and determining the stabilization time (possibly a fixed value) based on the control signal status information, forming a more robust and accurate time window determination mechanism, thereby significantly improving the accuracy and reliability of the contact resistance measurement results, and effectively solving the problem of accurately determining the relay stabilization time in complex industrial environments.

[0065] Furthermore, the step of calculating an estimated value of a current stabilization time required for the contacts of the power relay to be diagnosed to change from an energized state to an energized state based on the operating condition data includes:

[0066] Analyze the actual delay characteristics of the power relay contacts to be diagnosed from the energized state to the disconnected state based on historical working data;

[0067] Determine the environmental impact of environmental factors on stabilization time based on current environmental parameter information;

[0068] Based on the standard stabilization time parameters, the actual delay characteristic analysis results and the environmental impact, the estimated current stabilization time required for the power relay contacts to be diagnosed to change from the energized state to the disconnected state is calculated.

[0069] Historical operating data refers to a collection of data that records the operating status and performance of the power relay under diagnosis over a period of time. This data may include information such as the relay's cumulative operating hours, cumulative switching times, historical fault records, or historical switching time data measured under specific test conditions. The actual delay characteristic refers to the time delay between the power relay contacts receiving a disconnect command and actually completing the disconnection action. This characteristic is affected by long-term factors such as wear of the relay's internal mechanical structure, contact material loss, and spring fatigue. This characteristic can be obtained through statistical analysis, trend prediction, or aging modeling of historical operating data. Current environmental parameter information refers to the real-time physical parameters of the local or global environment in which the power relay under diagnosis is located during diagnostic measurements. This information may include information such as ambient temperature, humidity, air pressure, the presence of external vibration, and electromagnetic field strength. The environmental impact variable is a quantitative representation of the transient or continuous effect of the current environmental parameters on the contact stabilization time of the power relay under diagnosis. This impact variable can be determined by consulting the environmental adaptability information in the relay's technical manual, conducting experimental calibration to determine the relationship between environmental factors and stabilization time, or establishing a correction model based on environmental parameters. The standard stabilization time parameter refers to the reference value of the time required for the contacts of the power relay under diagnosis to transition from the energized to the disconnected state, measured at the factory or under specific standard test conditions. This parameter is typically provided by the manufacturer and reflects the relay's performance under ideal or nominal conditions. The current estimated stabilization time required for the contacts of the power relay under diagnosis to transition from the energized to the disconnected state is a prediction of the time required for the contacts to complete a stable disconnection, taking into account both the relay's long-term state and the transient effects of the external environment. This prediction can be obtained by using the standard stabilization time parameter as a benchmark and applying corrections or superposition based on actual delay characteristic analysis results and environmental influences, or by establishing a comprehensive model for calculation.

[0070] By executing the above steps, this solution comprehensively considers the various factors that affect the stable-opening time of power relay contacts, thereby obtaining a stable-time estimate that is closer to actual operating conditions. First, based on historical operating data, the actual delay characteristics of the power relay contacts transitioning from the energized to the disconnected state are analyzed. This analysis step utilizes the relay's long-term operating data to reveal inherent performance changes due to factors such as aging and wear, providing an important basis for subsequent calculations to reflect the relay's current state. Next, based on current environmental parameter information, the environmental impact of environmental factors on the stable-time estimate is determined. This step captures the impact of external environmental factors such as temperature and humidity on the relay's transient performance and quantifies the deviations caused by these external conditions. Finally, based on the standard stable-time parameters, the actual delay characteristics analysis results, and the environmental impact, an estimate of the current stable-time estimate required for the power relay contacts to transition from the energized to the disconnected state is calculated. This calculation step organically combines the relay's nominal performance at factory delivery, its long-term variations, and external transient influences. Through a comprehensive calculation process, it generates an estimate that more comprehensively and accurately reflects the relay's stable-time estimate under current operating conditions. The estimated stabilization time obtained through the above steps can more accurately predict when the contacts will actually reach a stable disconnected state, compared to methods that rely solely on standard parameters or simple historical corrections. This provides a more reliable input for subsequently determining the starting time point for stable contact disconnection based on the stabilization time. This, in turn, allows for more accurate selection of measurement timing when determining the time window in which external interference falls below a preset threshold, ensuring resistance measurements are taken when the contacts are fully and stably disconnected and interference is low. This effectively avoids measurement errors and misjudgments caused by inaccurate stabilization time estimates, improving the accuracy and reliability of the entire power relay contact sticking diagnosis method.

[0071] In one specific embodiment, analyzing the actual delay characteristics of the power relay under diagnosis transitioning from the energized to the energized state based on historical operating data can be accomplished by accessing the relay's historical operating log stored in the device management system database. This log records the timestamp from each control command issued to the actual completion of the relay state switch. The system can perform statistical analysis on this historical switching time data, such as calculating the average delay, standard deviation of the delay, or establishing a delay trend model based on age or cumulative operating times, to obtain an analysis of the actual delay characteristics reflecting the relay's current aging level. The environmental impact of environmental factors on the stabilization time can be determined based on current environmental parameter information. This can be achieved by using temperature and humidity sensors deployed within the control cabinet or near the relay under diagnosis to collect real-time ambient temperature and humidity data. The system can pre-store a relationship table or function model between environmental parameters and stabilization time corrections. For example, when ambient temperature increases, stabilization time may increase; when humidity increases, stabilization time may decrease. By consulting this relationship table or inputting the real-time collected environmental parameters into the function model, the environmental impact of the current environmental conditions on the stabilization time can be calculated. The current stabilization time estimate is calculated based on the standard stabilization time parameters, the actual delay characteristic analysis results, and the environmental impact factors. Specifically, this can be achieved by using the standard stabilization time parameters provided by the relay manufacturer as a baseline value. The actual delay characteristic analysis results (e.g., a delay increment) obtained through historical data analysis and the environmental impact factors (e.g., an environmental correction factor) determined based on the current environmental parameters are then superimposed on this baseline value to obtain a current stabilization time estimate that comprehensively considers multiple factors. For example, the estimated value = standard stabilization time + actual delay increment + environmental correction factor. Alternatively, a machine learning model can be trained whose inputs include the standard stabilization time, historical operating data analysis results, current environmental parameters, etc., and whose output is the current stabilization time estimate.

[0072] By comprehensively considering the actual delay characteristics of the power relay to be diagnosed due to long-term operation and the transient impact of current environmental factors on the stabilization time, and combining the standard stabilization time parameters of the relay, this solution can calculate an estimate that more accurately reflects the time required for the relay contacts to transition from the energized state to the disconnected state under the current actual operating conditions. This more accurate stabilization time estimate provides a more reliable basis for subsequently determining the starting time point for the stable disconnection of the contacts, allowing the system to more accurately determine when the relay contacts have truly reached a stable disconnected state. This ensures that when the contact resistance measurement time window is subsequently selected, the measurement operation is performed when the contacts are completely separated and stable, effectively avoiding low measurement values ​​and misjudgments caused by the contacts not being stably disconnected, and significantly improving the accuracy and reliability of power relay contact adhesion diagnosis.

[0073] In some embodiments, the specific steps in step S22 include:

[0074] S221 obtains the type and physical location information of other electrical devices physically adjacent to the power relay to be diagnosed;

[0075] S222. Based on the working status information, type, physical location information and association rules of other electrical devices, determine the predicted period of transient interference generated by other electrical devices by identifying the first continuous time interval in which the external interference is lower than the preset threshold.

[0076] Physical location information refers to data describing the spatial location of electrical equipment. It can be expressed in the form of coordinates, relative distances and directions, or numbers (e.g., cabinet numbers, floor numbers, slot numbers) within a specific installation structure (e.g., cabinets, rails). Association rules are models or sets that establish the relationship between the type, operating status, and physical location of electrical equipment and the transient interference characteristics (e.g., timing, intensity, waveform) generated by the equipment, as well as the interference propagation and attenuation patterns. These can be implemented using lookup tables, mathematical models, empirical formulas, or statistical models based on historical data.

[0077] By obtaining and utilizing information about the type and physical location of other electrical devices physically adjacent to the power relay to be diagnosed, and combining it with more sophisticated association rules, the method of the present application can more accurately predict the time period of transient interference generated by other electrical devices. This more accurate interference prediction helps to more reliably identify the time interval when external interference is below a preset threshold, thereby providing a more reliable basis for the subsequent selection of the measurement time window for the power relay contact resistance. This effectively reduces the impact of external interference on the measurement of the open-circuit resistance of high-impedance contacts, improves the accuracy of the measurement results, and thus improves the reliability of the judgment of the adhesion state of the power relay contacts, reducing the occurrence of misjudgments.

[0078] In some of the above-mentioned embodiments of the present application, it is proposed to determine the predicted time period when other electrical devices generate transient interference based on the working status information of other nearby electrical devices and preset association rules by identifying the first continuous time interval in which the external interference is lower than the preset threshold value to assist in determining the time window suitable for contact resistance measurement. For example, an association rule table can be preset to record the approximate time period and intensity range of different types of electrical equipment that may generate interference under specific working conditions. When the working status information of the neighboring device is obtained, the table can be queried to predict the time period when it may generate interference. In this way, the time period when interference may exist can be preliminarily screened out. However, in a scenario where space is limited and relays are densely installed, the relays in adjacent work and other electrical activities within the system will generate various forms of interference, which will affect the contact measurement point of the power relay to be diagnosed through spatial coupling, cable crosstalk, power supply or grounding system conduction coupling, etc. Simply predicting interference timing based on device type and operating status may not accurately reflect the combined effects of multiple interference sources at the measurement point, nor the attenuation and variations caused by the interference propagation path. This leads to inaccurate judgment of the actual overall interference level at the measurement point, affecting the accuracy of identifying time intervals when the interference is below the preset threshold, and thus the accuracy of contact resistance measurement. Therefore, a more sophisticated and accurate method is needed to predict the overall external interference at the measurement point of the power relay contact to be diagnosed, so as to reliably identify low-interference periods.

[0079] To address the above issues, this application provides a method for determining the predicted period of transient interference generated by other electrical devices. This method analyzes the interference of each adjacent device individually, taking into account the diversity, complexity, and spatial location of adjacent electrical devices, and the impact on interference propagation. This method more accurately identifies and quantifies the transient interference characteristics generated by various types of adjacent devices under different operating conditions. Specifically, the steps in step S222 include:

[0080] A1. For each adjacent electrical device, determine the timing characteristics of the standard transient interference that the device may generate in its current operating state based on its type, current operating status, and association rules.

[0081] A2. For each adjacent electrical device, determine the interference propagation parameter based on its physical location information. Based on the interference propagation parameter, calculate the extent to which the interference generated by the device will affect the contact measurement point of the power relay to be diagnosed.

[0082] A3. For each adjacent electrical device, determine the predicted duration and intensity of transient interference generated by that device on the contact measurement point of the power relay being diagnosed, taking into account its standard transient interference timing characteristics and the degree of impact on the measurement point.

[0083] A4. Comprehensively calculate the predicted period and intensity of transient interference generated by all adjacent electrical equipment on the power relay contact measurement point to be diagnosed, and superimpose and / or analyze the predicted period and intensity of the overall external interference at the power relay contact measurement point to be diagnosed;

[0084] A5. Based on the predicted period and predicted intensity of the overall external interference, identify a first continuous time interval and use it as the predicted period during which transient interference will be generated by other electrical equipment.

[0085] In step A1, the standard transient interference timing characteristics refer to the typical pattern or waveform of the transient interference signal generated by a specific type of electrical equipment under specific working conditions and standard conditions, which changes over time. It can be represented by a model established by pre-measurement, simulation or empirical data.

[0086] In step A2, interference propagation parameters describe the changes in the characteristics of the interference signal as it propagates from the source device to the measurement point. These parameters may include the effects of factors such as spatial distance, dielectric properties, coupling path impedance, and shielding effects on the interference signal's amplitude, waveform, and delay. The degree of impact is a quantitative representation of the amplitude, energy, or impact of the interference signal generated by a single adjacent electrical device on the measurement point after it propagates to the measurement point. This can be an attenuation coefficient, a transfer function, or a value calculated based on the propagation parameters.

[0087] In step A3, the predicted period and predicted intensity of transient interference refer to the predicted time range of the transient interference signal generated at the contact measurement point of the power relay to be diagnosed under a specific working state of a single adjacent electrical device, and the interference amplitude or energy within the time range.

[0088] In step A4, superposition and / or analysis refers to the process of comprehensively processing the predicted results of transient interference generated by multiple adjacent electrical devices at the measurement point. Superposition can refer to linear or nonlinear superposition of the predicted interference waveforms in the time domain, and analysis can refer to statistical, logical, or other forms of comprehensive evaluation of the predicted results of multiple interference sources to obtain overall interference information. The predicted time period and predicted intensity of the overall external interference refer to the predicted time-varying pattern of the sum of transient interference generated by all adjacent electrical devices at the measurement point of the power relay contact to be diagnosed within a specific time period, including the time range of the interference occurrence and the total interference amplitude or energy within that time range.

[0089] In step A5, identifying the first continuous time interval refers to finding a continuous time period in which the overall interference intensity is lower than a preset threshold according to the predicted period and predicted intensity of the overall external interference.

[0090] The above method combines the characteristics of individual interference sources with the influence of the propagation path to predict the actual transient interference generated by a single neighboring device at the measurement point. By superimposing or comprehensively analyzing the predicted interference from all individual neighboring devices at the measurement point, it can accurately predict the sum of all external interference experienced at the measurement point at any given moment, taking into account the cumulative effect of multiple interference sources and thus more realistically reflecting the actual interference environment at the measurement point. After obtaining the overall interference prediction at the measurement point, continuous time intervals where the overall interference intensity is below the threshold can be accurately identified based on a preset interference threshold. These intervals are periods of low external interference and are ideal time windows for measuring high-impedance contact resistance. Identifying these low-interference periods indirectly determines the predicted periods of transient interference generated by other electrical devices (i.e., non-low-interference periods), providing an accurate basis for subsequently selecting appropriate measurement time windows. This method utilizes multi-dimensional information such as the type, operating status, physical location, and interference propagation characteristics of neighboring devices. Through refined modeling and comprehensive analysis, it overcomes the limitations of simple association rule methods and is particularly suitable for applications in complex electromagnetic environments such as industrial control cabinets.

[0091] In a specific embodiment, assume that the power relay R1 to be diagnosed is installed in an industrial control cabinet and is physically located near two other electrical devices: a small relay R2 and a large contactor C1. To predict the external interference at the measurement point of the R1 contact, the above steps can be performed as follows:

[0092] First, for R2 and C1, the typical transient interference timing characteristics that they might generate in their current state are determined based on their respective types (small relay, large contactor), current operating states (for example, R2 in the closed state and C1 in the open state), and preset association rules. For example, the association rule library stores typical interference waveform data generated by different types of relays and contactors during closing and opening operations.

[0093] Next, obtain the physical location information of R2 and C1 relative to the R1 contact measurement point, such as the linear distance between them, their relative orientation, and their relative position to the control cabinet's internal structures (such as metal partitions and cable harnesses). Based on this physical location information, combined with a pre-defined interference propagation model or empirical data, determine the propagation parameters of the interference from R2 and C1 to the R1 measurement point, and calculate the impact of the interference generated by each of them at the R1 measurement point. For example, the closer the distance and the less shielding, the greater the impact.

[0094] Then, the standard transient interference timing characteristics of R2 are combined with the degree of its influence at the measurement point of R1 to predict the period and intensity of the transient interference generated by R2 at the measurement point of R1. Similarly, the standard transient interference timing characteristics of C1 are combined with the degree of its influence at the measurement point of R1 to predict the period and intensity of the transient interference generated by C1 at the measurement point of R1.

[0095] The predicted duration and intensity of the transient interference generated by R2 and C1 at the R1 measurement point are then combined. If the timing of the R2 and C1 operations is known, their respective predicted interference waveforms can be aligned and superimposed in the time domain to obtain the overall predicted interference waveform at the R1 measurement point. By analyzing this overall waveform, the predicted duration and intensity of the overall external interference can be determined, for example, identifying the time and duration of the interference peak.

[0096] Finally, the predicted duration and intensity of the overall external interference are compared with a preset interference threshold to identify consecutive time intervals where the overall interference intensity is below the threshold. These identified low-interference time intervals are then designated as suitable time windows for contact resistance measurement. Time periods outside these intervals are then identified as predicted periods of transient interference from other electrical equipment.

[0097] The above method enables a more refined and accurate prediction of the overall external interference at the contact measurement point of the power relay under diagnosis. This enables the system to reliably identify the first continuous time interval in which the external interference is below a preset threshold, thereby improving the accuracy of determining the time window suitable for contact resistance measurement and, in turn, the accuracy of contact resistance measurement.

[0098] In some embodiments, the specific steps in step A4 include:

[0099] A41. Generate a predicted transient interference waveform at the measurement point based on the transient interference prediction period and predicted intensity of each adjacent electrical device;

[0100] A42. Align and superimpose each predicted transient interference waveform in the time domain to obtain the overall predicted interference waveform at the measurement point of the power relay contact to be diagnosed;

[0101] A43. By analyzing the overall predicted interference waveform, identifying the peak intensity and duration of the overall predicted interference waveform;

[0102] A44. Determine the predicted period and predicted intensity of the overall external interference at the measurement point of the power relay contact to be diagnosed based on the peak intensity and duration of the overall predicted interference waveform.

[0103] A transient interference waveform refers to the amplitude or intensity curve of an interference signal that varies over time. This can be achieved using a preset waveform model, a waveform template based on historical data, or waveform data obtained through simulation calculations. Generating a predicted transient interference waveform at a measurement point refers to constructing or selecting a prediction model that reflects the temporal variation of the transient interference generated by the interference source at the measurement point, based on the characteristics of the interference source, the propagation path, and the receiving characteristics of the measurement point. This can be achieved using a typical waveform library based on device type and operating status, a propagation model that considers distance and dielectric attenuation, or a prediction algorithm that incorporates electromagnetic compatibility theory. Time domain alignment and superposition refers to precisely aligning the predicted transient interference waveforms generated by different interference sources on a common time axis based on their respective predicted occurrence times. The amplitudes of all waveforms at the same time point are then summed to obtain a single superimposed waveform that reflects the combined effect of all interference sources. This can be achieved using time synchronization technology, waveform interpolation technology, and a linear superposition algorithm. The overall predicted interference waveform refers to a composite waveform formed by aligning and superimposing the predicted transient interference waveforms generated by all adjacent electrical equipment at the measurement point in the time domain. This waveform reflects the temporal trend and intensity of the overall interference generated at the measurement point by the combined action of all interference sources during the prediction period. It can be represented by discrete time series data or a continuous function model. Analyzing the overall predicted interference waveform refers to processing the superimposed overall predicted interference waveform to extract its key features, such as the highest point of the waveform, the time range in which the waveform exceeds a certain threshold, etc. This can be achieved using a peak detection algorithm, a threshold crossing detection algorithm, or a waveform integral analysis algorithm. Identifying the peak intensity and duration of the overall predicted interference waveform refers to analyzing the overall predicted interference waveform to determine the maximum amplitude value of the waveform and the length of time from the beginning to the end or from exceeding a certain threshold to falling below the threshold. This can be achieved using an automatic peak search algorithm, a duration calculation method based on the waveform envelope, or a duration estimation method based on energy integration. Determining the predicted period and predicted intensity of the overall external interference means finally determining a predicted period representing the overall external interference and a representative intensity value within the period based on information such as the peak intensity and duration obtained from the analysis of the overall predicted interference waveform. The result is used for subsequent judgment on whether there is a low-interference time window. It can be achieved by using the waveform duration as the predicted period and the peak intensity as the predicted intensity, or by using the waveform energy as equivalent to a rectangular pulse to determine the period and intensity.

[0104] The method provided in this application generates a predicted transient interference waveform at the measurement point based on the predicted duration and predicted intensity of transient interference from each adjacent electrical device. This refines the description of interference from simple duration and intensity information to waveform data with time-dynamic characteristics, enabling more precise capture of the interference characteristics generated by different devices. Subsequently, each predicted transient interference waveform is aligned and superimposed in the time domain to obtain an overall predicted interference waveform at the measurement point of the power relay contact to be diagnosed. This key step simulates the real-world superposition effect of multiple interference sources acting simultaneously at the measurement point, taking into account the phase, shape, and temporal overlap between the waveforms, thereby obtaining an overall interference waveform that is closer to the actual situation. By analyzing the overall predicted interference waveform and identifying its peak intensity and duration, the most critical interference characteristics, namely the maximum intensity and duration of the overall interference, can be extracted from the complex superimposed waveform. Finally, based on the peak intensity and duration of the overall predicted interference waveform, the predicted duration and intensity of the overall external interference at the measurement point of the power relay contact to be diagnosed are determined. This final prediction result is based on more precise waveform superposition and analysis, and is therefore more accurate than the simple superposition of duration and intensity. The entire process forms a complete prediction chain, from waveform prediction of a single interference source to superposition of multiple sources, and then to extraction of overall characteristics, ultimately resulting in an accurate overall interference prediction result. This method, based on waveform superposition and analysis, can more accurately reflect the overall interference situation under the combined influence of multiple interference sources. Especially when the interference waveforms are complex or there is significant time overlap, it can effectively avoid the prediction bias that may be caused by simple superposition, thereby providing more reliable basic data for subsequent identification of time periods when external interference falls below the preset threshold.

[0105] For example, when generating a predicted transient interference waveform at a measurement point based on the predicted transient interference period and predicted intensity of each adjacent electrical device, typical transient interference waveform templates can be preset for different types of electrical equipment (such as motor starters, solenoid valves, switching power supplies, etc.). These templates can be adjusted based on the device type, power level, and distance from the measurement point. For example, when a high-power inductive load is disconnected, it may generate a voltage spike waveform with a steep rise and slowly decaying oscillation, while a switching power supply may generate a high-frequency periodic ripple and transient pulse waveform. When aligning and superimposing each predicted transient interference waveform in the time domain, the corresponding predicted waveforms can be precisely synchronized on the time axis based on the predicted operating state switching time of each device. The amplitude values ​​of these waveforms at each time point are then summed to obtain a superimposed discrete time series representing the overall predicted interference waveform. When analyzing the overall predicted interference waveform to identify its peak intensity and duration, the time series of the superimposed waveforms can be traversed to find the point with the largest amplitude as the peak intensity, and the time range in which the waveform amplitude continuously exceeds a certain noise threshold can be determined as the duration. Finally, when determining the predicted period and predicted intensity of the overall external interference at the contact measurement point of the power relay to be diagnosed based on the peak intensity and duration of the overall predicted interference waveform, the identified duration can be used as the predicted period of the overall external interference, and the peak intensity can be used as the predicted intensity of the overall external interference.

[0106] This method more accurately predicts the overall transient interference generated by the combined effects of multiple adjacent electrical devices at the contact measurement point of the power relay being diagnosed. This improves the accuracy of the overall interference prediction by taking into account the waveform characteristics and time-domain superposition effects of different interference sources. This more accurate overall interference prediction allows for more reliable identification of time intervals when external interference falls below a preset threshold, enabling the selection of the optimal time window for power relay contact resistance measurement. This effectively avoids measurement errors and misjudgments caused by interference, improving the reliability of contact sticking diagnosis.

[0107] Reference Attachment Figure 2 The present invention provides a power relay diagnostic system, comprising:

[0108] An acquisition module 100 is configured to acquire control signal status information of the power relay to be diagnosed and operating status information of other electrical devices physically adjacent to the power relay to be diagnosed;

[0109] A determination module 200 is configured to determine a time window in which the contacts of the power relay to be diagnosed are in an open state and the external interference is lower than a preset threshold value based on the control signal status information of the power relay to be diagnosed and the operating status information of other nearby electrical devices;

[0110] The control module 300 is used to control the multi-way switching unit to connect the contact resistance measurement unit to both ends of the contacts of the power relay to be diagnosed within the time window;

[0111] The acquisition module 400 is used to acquire the resistance value between the two ends of the contact after the contact resistance measurement unit is connected to the two ends of the contact;

[0112] The judgment module 500 is used to judge the contact adhesion state of the power relay to be diagnosed according to the resistance value.

[0113] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any actual relationship or order between these entities or operations.

[0114] The foregoing description is merely an embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A power relay diagnostic method, characterized in that: The following steps are involved: S1 obtains the control signal status information of the power relay to be diagnosed and the working status information of other electrical equipment physically adjacent to the power relay to be diagnosed; S2. Based on the control signal status information of the power relay to be diagnosed and the working status information of other adjacent electrical equipment, it is determined that the power relay contacts to be diagnosed are in the off state and the time window of the external interference is below a preset threshold; S3 within the time window, the control multi-way switching unit to connect the contact resistance measuring unit to both ends of the contact of the power relay to be diagnosed; S4. After the contact resistance measurement unit is connected to both ends of the contact, the resistance value between the two ends of the contact is collected; S5. Determine the contact adhesion state of the power relay to be diagnosed based on the resistance value.

2. The power relay diagnosis method according to claim 1, characterized in that: The specific steps in step S2 include: S21. According to the control signal status information of the power relay to be diagnosed, it is determined whether the power relay to be diagnosed receives a disconnect instruction, and according to the disconnect instruction, the stabilization time required for the power relay contacts to be diagnosed to change from the energized state to the disconnected state is determined; S22. Based on the working status information of other electrical equipment and the preset association rules, by identifying the first continuous time interval in which the external interference is below the preset threshold, the predicted period of transient interference generated by other electrical equipment is determined; the timing association rules include the association between the equipment type and the transient interference timing; S23. According to the stabilization time required for the power relay contacts to be diagnosed to transition from the energized state to the disconnected state, the starting time point at which the power relay contacts to be diagnosed reach a stable disconnected state is determined; S24. According to the starting time point and the transient interference prediction period, identifying the second continuous time interval after the power relay contacts to be diagnosed are stably disconnected and the external interference is lower than the preset threshold; S25. According to the second continuous time interval and the preset contact resistance measurement time, select a time period that meets the measurement time requirement from the continuous time interval as the time window.

3. The power relay diagnosis method according to claim 2, characterized in that: In step S21, the step of determining the stabilization time required for the contacts of the power relay to be diagnosed to change from the energized state to the disconnected state according to the disconnection instruction includes: Obtaining the operating condition data of the power relay to be diagnosed; According to the working condition data, the current stabilization time estimate required for the power relay contacts to be diagnosed to change from the energized state to the disconnected state is calculated and used as the stabilization time required for the power relay contacts to be diagnosed to change from the energized state to the disconnected state.

4. The power relay diagnosis method according to claim 3, characterized in that: The working condition data includes standard stabilization time, historical working data and current environmental parameter information.

5. The power relay diagnosis method according to claim 4, characterized in that: The historical working data includes the service life or the cumulative number of working times, as well as the actual time data of the historical contact state switching.

6. The power relay diagnosis method according to claim 4, characterized in that: The steps of calculating an estimated value of a current stabilization time required for a contact of a power relay to be diagnosed to change from an energized state to an energized state according to the operating condition data include: Analyze the actual delay characteristics of the power relay contacts to be diagnosed from the energized state to the disconnected state based on historical working data; Determine the environmental impact of environmental factors on stabilization time based on current environmental parameter information; Based on the standard stabilization time parameters, the actual delay characteristic analysis results and the environmental impact, the estimated current stabilization time required for the power relay contacts to be diagnosed to change from the energized state to the disconnected state is calculated.

7. The power relay diagnosis method according to claim 2, characterized in that: The specific steps in step S22 include: S221 obtains the type and physical location information of other electrical devices physically adjacent to the power relay to be diagnosed; S222. Based on the working status information, type, physical location information and association rules of other electrical devices, determine the predicted period of transient interference generated by other electrical devices by identifying the first continuous time interval in which the external interference is lower than the preset threshold.

8. The power relay diagnosis method according to claim 7, characterized in that: The specific steps in step S222 include: A1. For each adjacent electrical device, determine the timing characteristics of the standard transient interference that the device may generate in its current operating state based on its type, current operating status, and association rules. A2. For each adjacent electrical device, determine the interference propagation parameter based on its physical location information. Based on the interference propagation parameter, calculate the extent to which the interference generated by the device will affect the contact measurement point of the power relay to be diagnosed. A3. For each adjacent electrical device, determine the predicted duration and intensity of transient interference generated by that device on the contact measurement point of the power relay being diagnosed, taking into account its standard transient interference timing characteristics and the degree of impact on the measurement point. A4. Comprehensively calculate the predicted period and intensity of transient interference generated by all adjacent electrical equipment on the power relay contact measurement point to be diagnosed, and superimpose and / or analyze the predicted period and intensity of the overall external interference at the power relay contact measurement point to be diagnosed; A5. Based on the predicted period and predicted intensity of the overall external interference, identify a first continuous time interval and use it as the predicted period during which transient interference will be generated by other electrical equipment.

9. The power relay diagnosis method according to claim 8, characterized in that: The specific steps in step A4 include: A41. Generate a predicted transient interference waveform at the measurement point based on the transient interference prediction period and predicted intensity of each adjacent electrical device; A42. Align and superimpose each predicted transient interference waveform in the time domain to obtain the overall predicted interference waveform at the measurement point of the power relay contact to be diagnosed; A43. By analyzing the overall predicted interference waveform, identifying the peak intensity and duration of the overall predicted interference waveform; A44. Determine the predicted period and predicted intensity of the overall external interference at the measurement point of the power relay contact to be diagnosed based on the peak intensity and duration of the overall predicted interference waveform.

10. A power relay diagnostic system, characterized in that: include: an acquisition module, configured to acquire control signal status information of the power relay to be diagnosed and operating status information of other electrical devices physically adjacent to the power relay to be diagnosed; a determination module, configured to determine a time window in which the contacts of the power relay to be diagnosed are in an open state and the external interference is lower than a preset threshold value based on the control signal status information of the power relay to be diagnosed and the operating status information of other nearby electrical devices; A control module is used to control the multi-way switching unit to connect the contact resistance measuring unit to both ends of the contacts of the power relay to be diagnosed within a time window; an acquisition module, configured to acquire the resistance value between the two ends of the contact after the contact resistance measurement unit is connected to the two ends of the contact; The judgment module is used to judge the contact adhesion state of the power relay to be diagnosed according to the resistance value.

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