A monitoring method and system of an intelligent power distribution cabinet

Abstract

This invention discloses a monitoring method and system for intelligent distribution cabinets, relating to the field of power distribution automation technology. It aims to solve the technical problem that traditional monitoring methods cannot directly and early diagnose plastic deformation and end fracture of closing springs. The method includes: acquiring force and displacement signals of the circuit breaker closing spring during energy storage compression; generating a real-time force-displacement curve based on the force and displacement signals; calculating the second-order rate of change of force with respect to displacement; capturing the inflection point of the closing spring at the end of energy storage due to the spring coil contact phenomenon, and determining the instantaneous displacement value corresponding to the inflection point as the real-time coil inflection point displacement; comparing the real-time coil inflection point displacement with the reference coil inflection point displacement under healthy conditions of the closing spring to obtain the drift amount; and determining the damage state of the closing spring based on the drift amount. This invention has the advantage of achieving accurate identification of spring damage and differentiated safety control by capturing the coil inflection point displacement drift.

Description

Technical Field

[0001] This invention relates to the field of power distribution automation technology, and more specifically, to a monitoring method and system for intelligent power distribution cabinets. Background Technology

[0002] As the core switching device in a distribution cabinet, the reliability of the circuit breaker's operating mechanism directly affects the safe operation of the power distribution network. The closing spring is a key energy storage component of the circuit breaker's operating mechanism, and its health determines whether the circuit breaker can reliably complete the closing operation. During long-term operation, the closing spring can undergo irreversible plastic tensile deformation due to continuous stress relaxation, fatigue creep, and abnormal mechanical impact, and may even suffer structural damage such as end hook breakage. This can lead to serious malfunctions such as insufficient energy storage, abnormal closing speed, or failure to operate.

[0003] Currently, monitoring methods for circuit breaker operating mechanisms mainly focus on acquiring the current waveforms of the opening and closing coils, contact travel-time curves, and recording the cumulative number of operations during the operation. Among these, the opening and closing coil current analysis is primarily used to diagnose the condition of the electromagnet and tripping mechanism, while the travel-time curve focuses on assessing the overall motion characteristics such as contact speed and overtravel. However, these indirect monitoring parameters do not directly characterize the changes in the mechanical properties of the closing spring itself, and in particular, they cannot effectively identify invisible plastic deformation within the spring or early fracture of the end connection structure. In practice, the plastic tensile deformation of the spring alters its free length and stiffness characteristics, causing subtle but definite anomalies in the mechanical behavior during energy storage. These anomalies are difficult to detect in a timely manner using conventional travel curves or current waveforms. When such damage accumulates to the stage of mechanical failure to operate, it often leads to serious power distribution accidents, and the subsequent investigation and repair costs are extremely high. Therefore, we propose a monitoring method and system for intelligent distribution cabinets. Summary of the Invention

[0004] The purpose of this invention is to provide a monitoring method and system for intelligent power distribution cabinets, so as to solve the technical problem that traditional monitoring methods cannot directly and early diagnose plastic deformation and end fracture of closing springs.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a monitoring method for an intelligent power distribution cabinet, comprising: Acquire the force and displacement signals of the circuit breaker closing spring during the energy storage compression process; Based on the force signal and displacement signal, a real-time force-displacement curve is generated, the second-order rate of change of force with respect to displacement is calculated, the inflection point of the closing spring in the final stage of energy storage due to the stiffness increase caused by the spring coil contact is captured, and the instantaneous displacement value corresponding to the inflection point is determined as the real-time coil inflection point displacement. The real-time inflection point displacement of the closing spring is compared with the reference inflection point displacement of the closing spring under healthy conditions to obtain the drift amount, and the damage state of the closing spring is determined based on the drift amount. If the drift exceeds the preset allowable range, a differentiated control command is generated to lock the closing operation circuit of the circuit breaker, prevent the energy storage motor of the closing spring from starting, and at the same time keep the tripping circuit of the circuit breaker in normal working condition.

[0006] Preferably, the calculation of the second-order rate of change of force with respect to displacement, capturing the inflection point of the sharp increase in stiffness, includes: The second-order difference value of force versus displacement is continuously calculated on the real-time force-displacement curve within adjacent sampling intervals. The sampling point where the second-order difference value first exceeds the preset stiffness increase threshold is taken as the stiffness increase start point. The turning point where the second-order difference value changes from a peak value to a decrease is determined as the inflection point of the phenomenon of sharp increase in stiffness.

[0007] Preferably, determining the damage state of the closing spring based on the drift amount includes: If the drift is positive and its absolute value exceeds the first damage threshold, it is determined that the closing spring has undergone plastic tensile deformation. If the drift is negative and its absolute value exceeds the second damage threshold, it is determined that the end hook of the closing spring has broken.

[0008] Preferably, the generation of differentiated control instructions includes: Disconnect the power supply circuit of the energy storage motor to prevent it from starting under any command; Only the power supply link of the closing operation circuit is disconnected, without making any changes to the electrical connection of the tripping circuit.

[0009] Preferred options also include: Record the real-time inflection point displacement of each energy storage process and generate a historical trend curve of the inflection point displacement. If the historical trend curve shows a continuous unidirectional drift trend and the current drift amount does not exceed the preset allowable range, a spring fatigue deterioration warning will be issued.

[0010] Preferred options also include: The damage diagnosis results of the closing spring, the execution status of the differentiated control command, the current opening and closing status of the circuit breaker, and the energy storage status of the closing spring are combined into a status message that conforms to the power distribution automation communication protocol and transmitted to the operation and maintenance master station.

[0011] Preferably, acquiring the force and displacement signals of the circuit breaker closing spring during the energy storage compression process includes: Force signals are collected by a force sensor located at the end of the closing spring; Displacement signals are collected by a displacement sensor located at the moving end of the closing spring.

[0012] A monitoring system for an intelligent power distribution cabinet includes: The signal acquisition unit is used to acquire the force and displacement signals of the circuit breaker closing spring during the energy storage compression process; The curve generation and feature extraction unit is used to generate real-time force-displacement curves based on force and displacement signals, calculate the second-order rate of change of force with respect to displacement, capture the inflection point of the closing spring in the final stage of energy storage where the stiffness increases sharply due to the contact of the spring coils, and determine the instantaneous displacement value corresponding to the inflection point as the real-time coil inflection point displacement. The diagnostic unit is used to compare the real-time inflection point displacement of the closing spring with the reference inflection point displacement of the closing spring under healthy conditions to obtain the drift amount, and to determine the damage state of the closing spring based on the drift amount. The control unit is used to generate differentiated control commands if the drift exceeds the preset allowable range, block the circuit breaker's closing operation circuit, prevent the energy storage motor of the closing spring from starting, and at the same time keep the circuit breaker's tripping circuit in normal working condition.

[0013] An electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement a monitoring method for an intelligent power distribution cabinet.

[0014] A computer-readable storage medium storing a computer program that, when executed by a processor, implements a monitoring method for an intelligent power distribution cabinet.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention captures the sharp increase in stiffness inflection point of the closing spring at the end of the energy storage stage, caused by the spring coils approaching complete contact, and determines the real-time coil inflection point displacement corresponding to this inflection point. By comparing this displacement with the reference coil inflection point displacement, it can directly identify whether the spring has undergone plastic tensile deformation or end hook breakage. This method transforms the invisible material damage inside the spring into a clear and measurable geometric position drift, overcoming the diagnostic lag and uncertainty caused by traditional methods that rely on the number of actions or stroke curves to indirectly infer the spring state. Because the coil inflection point displacement is extremely sensitive to minute changes in the spring's geometry, it can be accurately captured even in the early stages of spring plastic deformation, thus significantly improving the accuracy and timeliness of circuit breaker operating mechanism condition monitoring.

[0016] 2. When the invention detects that the displacement drift at the inflection point of the circuit breaker exceeds the allowable range, it generates a differentiated control command to block the closing operation circuit of the circuit breaker and prevent the energy storage motor from restarting, while maintaining the normal operation of the protection tripping circuit. This differentiated safety control strategy of "blocking closing and retaining tripping" avoids the risk of escalating accidents due to failure to close or slow closing caused by spring damage, while ensuring that the circuit breaker can still reliably perform its breaking protection function when a fault occurs in the power distribution network, achieving the best balance between safety and power supply continuity.

[0017] 3. This invention records the real-time inflection point displacement of each energy storage process and forms a historical trend curve. It can issue early warnings of spring fatigue degradation based on a continuous unidirectional drift trend before the drift exceeds the allowable range. This trend-based preventative maintenance mechanism allows maintenance personnel to schedule power outages for repair or replacement before the spring performance degrades to a dangerous critical point, avoiding unplanned outages caused by sudden mechanical failures. This significantly reduces maintenance costs and extends the overall service life of the distribution cabinet, realizing a shift from planned maintenance to condition-based maintenance. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall process of the present invention; Figure 2 This is a schematic diagram of the process for extracting stiffness features and determining the inflection point displacement of the loop in this invention; Figure 3 This is a schematic diagram of the spring damage state diagnosis and classification process of the present invention; Figure 4 This is a schematic diagram of the process for differentiated control execution and trend early warning processing of the present invention. Detailed Implementation

[0019] To facilitate understanding of the technical solution of the present invention by those skilled in the art, the technical solution of the present invention will now be further described in conjunction with the accompanying drawings.

[0020] Example 1, such as Figures 1-4 As shown, the present invention provides a monitoring method for an intelligent power distribution cabinet, comprising the following steps: Step S101: During the energy storage compression process of the closing spring, force signals characterizing the force state of the closing spring and displacement signals characterizing the deformation state of the closing spring are collected simultaneously, and real-time force-displacement curves of the closing spring during the current energy storage process are generated. Step S102: Extract stiffness features from the real-time force-displacement curve. By calculating the second-order rate of change of force with respect to displacement, capture the inflection point of the stiffness increase phenomenon of the closing spring at the end of the energy storage stage due to the spring coils tending to be fully fitted. Determine the instantaneous displacement value corresponding to the inflection point as the real-time coil inflection point displacement characterizing the geometric position of the closing spring in the energy storage position. Step S103: Compare the real-time parallel coil inflection point displacement with the reference parallel coil inflection point displacement that characterizes the closing spring in a healthy state. Based on the drift amount and drift direction of the real-time parallel coil inflection point displacement relative to the reference parallel coil inflection point displacement, determine the damage state of the closing spring and generate the corresponding spring health status diagnosis result. Step S104: When the health status diagnosis result of the spring indicates that the drift of the real-time coil inflection point displacement exceeds the preset allowable range, a differentiated control command is generated for the circuit breaker. The differentiated control command includes blocking the closing operation circuit of the circuit breaker and prohibiting the energy storage motor of the closing spring from restarting. Step S105: The indication information, which includes the health status diagnosis result of the spring and the execution status of the differentiated control command, is transmitted to the operation and maintenance master station through the power distribution network communication protocol to realize remote indication of the status of the switch device in the power distribution cabinet and remote control of the switch device's closing preparation function.

[0021] In this embodiment of the invention, the above steps work together to construct a closed-loop monitoring system based on "precise sensing-diagnosis-control-communication based on physical stiffness characteristics." The core mechanism of this system lies in breaking away from the limitations of traditional methods that only focus on binary quantities such as motor current or end-position switches, and instead deeply analyzing the most essential mechanical property during the energy storage process of the closing spring, namely stiffness. When a helical spring is compressed, its coils gradually come together as they approach full compression. With each coil coming together, the effective working coils of the spring decrease by one, resulting in a non-linear and steep increase in its overall stiffness. This method uses the two most direct physical quantities, force and displacement, which are simultaneously acquired in step S101, to reconstruct the true mechanical characteristic curve of the spring; step S102 then uses mathematical methods to accurately capture the characteristic point where the second-order rate of change of force with respect to displacement changes drastically, that is, the mechanical inflection point where stiffness changes from a steady increase to a rapid surge. This inflection point displacement acts like a precise physical ruler for the spring's "energy storage in place." Any aging or damage that alters the spring's geometry or constitutive relationship will cause the reading of this ruler, the real-time inflection point displacement, to drift. Step S103 vectorizes and analyzes this drift, diagnosing whether it's overall "plastic stretching" or localized "end fracture" based on the drift direction, achieving a precise diagnosis at the mechanistic level. When the safety threshold set in step S104 is exceeded, the system no longer merely issues a passive alarm but actively generates differentiated control commands, fundamentally preventing the faulty spring from storing energy again and locking the circuit breaker, thus eliminating the possibility of the circuit breaker performing a dangerous closing operation due to insufficient spring energy or breakage. Finally, step S105 "transparently" presents the status of all this to the remote operation and maintenance master station through the power distribution network communication protocol, so that the operation and maintenance personnel, even though they are far away, can have a clear understanding of the health and control status of a spring inside the equipment, and can remotely verify whether the control measures have taken effect, which greatly improves the accuracy and timeliness of operation and maintenance.

[0022] In one embodiment, step S102 specifically includes: on the real-time force-displacement curve, with displacement as the independent variable and force as the dependent variable, continuously calculating the second-order difference value of force versus displacement within adjacent sampling intervals; determining the sampling point where the second-order difference value first exceeds a preset stiffness increase threshold as the starting point of the stiffness increase stage before the closing spring enters the coil-coil coupling phase; after this starting point, continuously monitoring the changing trend of the second-order difference value, determining the turning point where the second-order difference value changes from rapid increase to sharp decrease as the inflection point where the closing spring coil has basically completed contact, and recording the instantaneous displacement value corresponding to this inflection point on the displacement axis as the real-time coil-coil coupling inflection point displacement. The calculation of the second-order difference value is performed according to the following formula: ; in, The first force-displacement curve on this real-time force-displacement curve The force signal values ​​at each sampling point are evenly distributed along the displacement axis. Within the displacement range of the final energy storage stage, the following conditions will be met. Furthermore, the displacement value corresponding to the sampling point exhibiting local peak characteristics is determined as the real-time inflection point displacement. ,in This is the preset threshold for determining a sharp increase in stiffness. The physical essence of this method lies in the fact that the stiffness K of the closing spring is a local slope of its force-displacement curve, while its second-order rate of change directly reflects the rate of change of stiffness. In the initial stage of energy storage, the spring stiffness is approximately linear, and the second-order rate of change is close to zero; as the coils begin to gradually close, the effective number of coils decreases non-linearly, causing the stiffness K to begin to increase rapidly, manifesting as… It starts to rise from near zero and exceeds the threshold. This marks the point at which the rate of increase in stiffness has reached a level that cannot be ignored, signifying the beginning of the "sharp increase in stiffness stage." As the spring coil continues to adhere, the rate of increase in K reaches its peak, i.e. Reaching a local peak value, this is the moment of most dramatic change in stiffness; subsequently, with a large number of spring coils having completed their bonding, the increase in K begins to narrow. The energy level drops from the peak. This turning point from the peak to the current point physically corresponds precisely to the critical geometric position where most of the spring coils transition from a "free state" to a "closed state." Using this as the coil-closing inflection point provides extremely high physical directivity and repeatability, eliminating interference from local curve fluctuations caused by factors such as friction and sensor noise. This method allows the endpoint of spring energy storage to be precisely located from the "approximate area" determined by traditional position switches to a specific mechanical "event point."

[0023] As a specific implementation method, threshold The settings can be automatically completed through the factory calibration process. For example, in calibration mode, the force-displacement curve of a healthy spring is collected 10 times, and its performance in the region near the identified coil inflection point is calculated. The statistical average, then The value is set to 30%~50% of this average value to accommodate the differences in stiffness characteristics of springs of different specifications. Ensuring that sampling points are evenly distributed along the displacement axis can be achieved by interpolating and aligning the force signal using the displacement signal after isochronous sampling.

[0024] In one embodiment, regarding step S103 mentioned above, the process of determining the damage state of the closing spring in step S103 specifically includes: obtaining the reference coil inflection point displacement calibrated by the closing spring during the same energy storage process at the time of manufacture; calculating the displacement difference between the real-time coil inflection point displacement and the reference coil inflection point displacement, and using the displacement difference as the drift amount; when the drift amount is positive and the absolute value of the drift amount exceeds a first damage threshold, it is determined that the closing spring has undergone irreversible plastic tensile deformation, resulting in premature coil coiling; when the drift amount is negative and the absolute value of the drift amount exceeds a second damage threshold, it is determined that the end hook of the closing spring has broken, resulting in a relatively delayed coiling position. The drift amount Defined by the following formula: ; in, This is the real-time inflection point displacement. The displacement of the inflection point is taken as the reference. The criterion for determining this damage state is: if If so, it is determined to be plastic tensile deformation; if If so, it is determined that the end hook is broken. and These are the first and second damage thresholds, respectively. This judgment logic cleverly utilizes the monotonic mapping relationship between the physical damage of the closing spring and its parallel coil geometry. Plastic tensile deformation increases the spring's free height, causing the coils to contact earlier under the same compression stroke, thus shifting the parallel coil inflection point in the positive direction of the displacement axis. Conversely, end hook breakage is equivalent to shortening the axial length of the spring's compression-participating portion, requiring deeper compression for the coils to engage, causing the parallel coil inflection point to shift in the negative direction of the displacement axis. The sign of the drift precisely indicates the damage mode, achieving non-black-box, interpretable diagnosis. Furthermore, a dual threshold is employed. and Instead of a simple absolute range, tolerance for different damage modes can be set independently. For example, a stricter threshold can be set for damage modes such as end hooks that may cause catastrophic breakage.

[0025] As a specific implementation method, the first damage threshold Second damage threshold These are not fixed values, but parameters that can be configured in the system based on the spring's material, model, and operating environment. They can be stored in the diagnostic unit's non-volatile memory and written to by configuration software when the product leaves the factory or is deployed in the field.

[0026] In one embodiment, for a more detailed approach to generating the spring health status diagnosis result in step S103, step S103 further includes the following operation: when it is determined that the closing spring has undergone irreversible plastic tensile deformation, the degree of plastic deformation of the closing spring is further output based on the absolute value of the drift, whereby the degree of plastic deformation includes slight plastic deformation, moderate plastic deformation, and severe plastic deformation. Based on the absolute value of the drift Determine by the following formula: ; in, The preset plastic deformation level step size, This indicates the rounding up operation. The value of , , These correspond to slight plastic deformation, moderate plastic deformation, and severe plastic deformation, respectively. When When the value exceeds 3, it is still treated as a severe plastic deformation level. The beneficial effect of this classification mechanism is that it not only informs that the damage "exists," but also provides semi-quantitative information on the "degree" of the damage, providing maintenance personnel with a more refined decision-making basis for formulating differentiated maintenance strategies.

[0027] For example, circuit breakers with "slight plastic deformation" can be placed on a watchlist, with increased monitoring frequency, and can continue to serve in the short term; however, circuit breakers with "severe plastic deformation" must be replaced immediately with a power outage to prevent closing failure accidents. This level calculation relies solely on drift. and step length It consumes very few computing resources and can be completed quickly on the embedded diagnostic unit without sending data to the background for complex analysis.

[0028] As a specific implementation method, step size The setting can be based on engineering experience or fatigue test data for that type of spring. For example, for a certain type of circuit breaker closing spring, experimental data shows that when the plastic deformation reaches 0.6mm, its closing speed will drop to a critical value that cannot meet the national standard requirements. Therefore, the closing speed can be adjusted accordingly. If the value is set to 0.2mm, then drift amounts of 0.15mm, 0.35mm, and 0.55mm will fall into levels 1, 2, and 3, respectively.

[0029] In one embodiment, regarding step S104 mentioned above, the process of generating differentiated control instructions in step S104 specifically includes: presetting a drift allowable range consisting of multiple drift thresholds, wherein the upper limit of the drift allowable range corresponds to the maximum acceptable level of plastic tensile deformation, and the lower limit corresponds to the maximum acceptable level of end hook breakage; when the drift exceeds the upper or lower limit of the drift allowable range, the differentiated control logic is triggered. This differentiated control logic, while generating an instruction to block the circuit breaker closing operation circuit, forcibly disconnects the power supply circuit of the energy storage motor to prevent the energy storage motor from restarting under any remote instruction. The triggering condition of this differentiated control logic is expressed by the following formula: ; in, This represents the upper limit of the allowable range for the drift amount, and its value is [value missing]. , This is the lower limit of the allowable range for the drift amount, and its value is [value missing]. , This represents the maximum allowable drift corresponding to plastic tensile deformation. This represents the absolute value of the maximum permissible drift corresponding to the breakage of the end hook. This scheme constructs a direct path for "diagnostic trigger control." Once the diagnostic result falls into the danger zone, the control action will be executed immediately and automatically, eliminating the delay caused by manual decision-making and operation. More importantly, the control commands are "differentiated," which is reflected in the depth of blocking. Only locking the closing circuit means that the circuit breaker can only be prohibited from performing the action of connecting the circuit; while forcibly cutting off the power supply circuit of the energy storage motor completely eliminates the possibility of re-energy storage at a deeper energy source. This is a defense-in-depth design: even if the locking of the closing operation circuit fails for some reason (such as relay adhesion), the motor cannot obtain power to re-stretch a spring that is already in a dangerous state, preventing serious accidents such as spring breakage and flying fragments or mechanism jamming that may occur if the spring is forcibly compressed in a damaged state.

[0030] Based on the above embodiments, when the differentiated control command blocks the circuit breaker's closing operation circuit, it maintains the circuit breaker's protection tripping circuit in normal working condition. This allows the circuit breaker to still perform fault-breaking actions in the event of a power distribution network fault, achieving a differentiated safety control strategy of blocking closing while retaining protection tripping. This means that when the controller executes the blocking, it precisely disconnects only the power supply circuit of the closing coil or the drive signal of the closing control relay, without processing the tripping coil and its control circuit, which still maintains normal electrical connection with the protection device. Its greatest benefit is the "balance between safety and efficiency": while protecting the circuit breaker and distribution cabinet from the risk of closing failure caused by a faulty spring, the core protection function of the circuit breaker is not "sacrificed" due to this protection action. The circuit breaker remains ready to execute the tripping command to cut off any possible short-circuit faults downstream, maintaining the safety and stability of the entire power distribution network and preventing a local mechanical component damage problem from evolving into a systemic problem leading to protection failure.

[0031] In one embodiment, step S105 specifically includes: combining the spring health status diagnosis result, the execution confirmation signal of the differentiated control command, the current opening / closing status of the circuit breaker, and the energy storage status of the closing spring into a status indication message conforming to the power distribution automation communication protocol; and sending the status indication message to the maintenance master station via a remote communication network, so that maintenance personnel can formulate corresponding maintenance plans based on the spring health status diagnosis result and the execution status of the differentiated control command in the status indication message, and remotely confirm the execution status of the differentiated control command. This solution constructs an information-rich and closed-loop remote interaction scenario. The message not only sends "what disease was diagnosed," but also "what control measures were taken," "whether the measures have taken effect," and "what is the current actual status of the equipment," forming a complete chain of information evidence.

[0032] For example, the message simultaneously includes information such as "determined to be plastic tensile deformation," "differentiated control command executed," "closing circuit confirmed as locked," and "energy storage circuit de-energized." Maintenance personnel can remotely confirm from the main station whether the circuit breaker is truly in a safe, open, and non-energy-storage-capable state due to a spring problem. This allows for highly reliable planning of an emergency repair schedule to replace the spring the following day, eliminating the need for phone confirmation or on-site verification, significantly improving the efficiency and accuracy of maintenance command and dispatch.

[0033] As a specific implementation method, the status indication message fully complies with mainstream power distribution automation communication protocols such as IEC61850 or DNP3.0. The spring health diagnosis results are modeled as newly added logical node data objects, and the execution status of differentiated control commands is mapped to the relevant control block status words to ensure seamless integration with the existing power distribution automation master station system.

[0034] In one embodiment, regarding the aforementioned step S101, the process of synchronously acquiring signals in step S101 specifically includes: directly acquiring the force signal through a force sensor located at the end of the closing spring; and directly acquiring the displacement signal through a displacement sensor located at the moving end of the closing spring. This arrangement of sensors at the "end" and "moving end" ensures that the acquired force signal is the actual full-axial force experienced by the closing spring, avoiding errors and lags caused by indirect measurements (such as converting torque through motor current); simultaneously, the displacement sensor directly follows the movement of the spring compression end, and the measured displacement is the actual compression stroke of the spring. The two are physically directly corresponding, ensuring the authenticity and accuracy of the generated real-time force-displacement curve from the source, laying a solid physical foundation for all subsequent high-order analyses based on this curve.

[0035] In one embodiment, the monitoring method also performs a proactive early warning function, which includes: recording the real-time coil inflection point displacement determined during each energy storage process to form a historical trend curve of the coil inflection point displacement of the closing spring; when the historical trend curve of the coil inflection point displacement shows a continuous unidirectional drift trend, and the drift amount has not exceeded the preset allowable range, an early warning indication of spring fatigue deterioration is issued in advance, and the early warning indication is transmitted to the operation and maintenance master station through the power distribution network communication protocol to prompt operation and maintenance personnel to perform preventive maintenance. The continuous unidirectional drift trend is determined by calculating the linear fitting slope of the historical trend curve of the coil inflection point displacement, and the linear fitting slope... It is given by the following formula: ; in, This is the sequence number of the energy storage cycles. For the first The real-time inflection point displacement obtained during the energy storage process. This represents the total number of energy storage iterations involved in the fitting process. When... Greater than the preset trend determination threshold and When the sign remains stable, it is determined that a continuous unidirectional drift trend has occurred. This early warning function shifts the diagnosis from post-failure handling to pre-failure prediction, forming full-state monitoring throughout the life cycle. Spring fatigue and slight plastic deformation are a gradual process, and the small amplitude of unidirectional drift at the inflection point displacement is an early "indicator" of this process. The linear fitting slope is calculated using the least squares method on historical data points. This allows for the filtering out of random noise from single measurements, accurately capturing this slow but clearly directional degradation trend. Even though the current absolute value of the drift is far from reaching the threshold for triggering a latching command, a significant... The slope, however, indicates that it will inevitably "cross the line" in the near future. Notifying the maintenance master station of this warning in advance allows maintenance to shift from reactive emergency repairs to proactive planned maintenance, which helps reduce losses from unplanned power outages and optimizes spare parts inventory management.

[0036] It should be noted that in some optional implementations, the force sensor can be a piezoelectric, piezoresistive, or strain gauge type, and the displacement sensor can be a wire-type displacement sensor, a magnetostrictive displacement sensor, or a displacement sensor based on a photoelectric encoder, as long as it meets the requirements for the pressure on the end face of the closing spring and the internal installation space of the equipment. Before entering the subsequent processing unit, the displacement sensor signal and the force sensor signal need to pass through a signal conditioning circuit, including instrumentation amplifier filtering, differential amplification, and analog-to-digital conversion, ultimately becoming a digital signal that enters the microprocessor. A sharp increase in stiffness is determined by a threshold. In addition to factory calibration, an adaptive update can be performed after each major circuit breaker overhaul via a specific "health status benchmark recalibration" procedure. This compensates for minor, acceptable systematic deviations in spring characteristics caused by normal break-in and long-term operation, thereby ensuring the accuracy of subsequent diagnostics. The preset plastic deformation level step size... First damage threshold Second damage threshold Key parameters are stored in the storage unit during production, but the ability to remotely and securely modify them via the communication interface is retained, allowing for optimization based on feedback from operating data of a wider range of similar devices.

[0037] Example 2: The present invention also provides a monitoring system for an intelligent power distribution cabinet, used to execute the monitoring method in any of the above embodiments. The system includes: The signal acquisition unit is used to simultaneously acquire force signals characterizing the force state of the closing spring and displacement signals characterizing the deformation state of the closing spring during the energy storage compression process of the closing spring in the circuit breaker operating mechanism. The curve generation and feature extraction unit is connected to the signal acquisition unit and is used to generate the real-time force-displacement curve of the closing spring during the current energy storage process. By calculating the second-order rate of change of force with respect to displacement, the inflection point of the closing spring in the final stage of energy storage, where the stiffness increases sharply due to the spring coils tending to be fully engaged, is captured. The instantaneous displacement value corresponding to the inflection point is determined as the real-time coil inflection point displacement. The diagnostic unit, connected to the curve generation and feature extraction unit, is used to store the reference parallel coil inflection point displacement that characterizes the closing spring in a healthy state, compare the real-time parallel coil inflection point displacement with the reference parallel coil inflection point displacement, determine the damage state of the closing spring based on the drift amount and drift direction, and generate a spring health status diagnostic result. The control unit, connected to the diagnostic unit, is used to generate a differentiated control command when the spring health status diagnostic result indicates that the drift of the real-time coil inflection point displacement exceeds the preset allowable range. The differentiated control command includes blocking the closing operation circuit of the circuit breaker and prohibiting the energy storage motor of the closing spring from restarting. The communication unit, connected to the diagnostic unit and the control unit, is used to transmit the indication information, including the diagnostic results of the spring's health status and the execution status of the differentiated control command, to the operation and maintenance master station via the power distribution network communication protocol, thereby realizing remote indication of the status of the switchgear in the power distribution cabinet and remote control of the switchgear's closing preparation function.

[0038] Each of the above-mentioned units corresponds to a step. The curve generation and feature extraction unit, the circuit breaker unit, and the control unit can be integrated into an embedded hardware platform based on a microprocessor or digital signal processor. They work together to analyze the millisecond-level changes in the spring mechanical state that occur inside the circuit breaker into intuitive health diagnosis results, transform them into reliable control actions, and package them into standard communication messages. Together, they constitute a highly integrated and intelligent "perception-diagnosis-decision-communication" front-end intelligent terminal.

[0039] In the context of this invention, the following provides a clear explanation of some core terms: Closing spring: As the monitored target, it is a key elastic element in the circuit breaker operating mechanism responsible for storing the mechanical energy required for closing, and is usually a cylindrical helical compression spring.

[0040] Real-time force-displacement curve: refers to a two-dimensional curve formed by the one-to-one correspondence between synchronously acquired force signals and displacement signals during a single complete energy storage compression process. It intuitively represents the dynamic relationship between the spring's elastic stiffness and the compression stroke.

[0041] Stiffness feature extraction: Specifically refers to the process of identifying feature values ​​or feature points related to stiffness changes from force-displacement curves using mathematical methods. This invention focuses on the high-order feature of the second-order rate of change of force with respect to displacement.

[0042] Real-time coil inflection point displacement: This is the core monitoring parameter created by the present invention. It refers to the displacement value corresponding to the inflection point in the physical process at the end of the closing spring energy storage, when the coils begin to come into contact in large quantities, resulting in a decrease in the effective number of spring coils and a sharp increase in stiffness. This value accurately marks the true geometric position when the spring is in place.

[0043] Reference coil inflection point displacement: This is the reference value of the real-time coil inflection point displacement obtained by calibrating the closing spring through the same energy storage process when it leaves the factory or is confirmed to be in a fully healthy state.

[0044] Drift amount: It is the deviation value of the real-time coil inflection point displacement relative to the reference coil inflection point displacement. Its magnitude and positive or negative direction are the key indicators for this invention to determine whether the spring is damaged and the type of damage.

[0045] Differentiated control commands refer to asymmetric protective control commands issued based on different spring health diagnosis results. Their significant feature is that they can selectively lock out some functions (such as closing) while retaining other key functions (such as protection tripping), which is completely different from the traditional one-size-fits-all locking.

[0046] Example 3: An electronic device includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement a monitoring method for an intelligent power distribution cabinet.

[0047] Example 4: A computer-readable storage medium storing a computer program, which, when executed by a processor, implements a monitoring method for an intelligent power distribution cabinet.

[0048] Example 5 provides a monitoring method for an intelligent distribution cabinet, using an indoor high-voltage vacuum circuit breaker with a rated voltage of 12kV and a rated current of 1250A as the implementation object. The closing spring of its operating mechanism is a cylindrical helical compression spring with a spring wire diameter of 10mm, 12 effective turns, and a free height of 180mm. A spoke-type tension / compression sensor is used, with a range of 0 to 5000N and an accuracy class of 0.05%, installed on the fixed end of the closing spring. A wire-type displacement sensor is used, with a range of 0 to 150mm and a linearity of 0.1%, with the wire end fixed to the moving end of the closing spring. The sampling frequency is set to 2kHz, and the displacement axis sampling interval is uniformly set to 0.05mm after interpolation.

[0049] At the time of manufacture, the circuit breaker underwent 10 complete energy storage operations, simultaneously acquiring force and displacement signals to generate corresponding real-time force-displacement curves. The statistical results of the peak force signal and final displacement signal acquired during the 10 energy storage processes are shown in the table below: Table 1: Statistical Table of Signal Acquisition During 10 Energy Storage Processes in the Factory Calibration Phase

[0050] As shown in Table 1, the standard deviation of the peak value of the force signal during the 10 energy storage processes was 1.49 N, the standard deviation of the final value of the displacement signal was 0.018 mm, and the correlation coefficient of the force-displacement curves all exceeded 0.999. This indicates that the sensor system has excellent repeatability and linearity under the same working conditions, and the generated real-time force-displacement curves are stable and reliable.

[0051] Using the data collected during the 5th energy storage process in the above factory calibration stage, on the real-time force-displacement curve, with displacement as the independent variable and force as the dependent variable, the second-order difference value of force versus displacement in adjacent sampling intervals is continuously calculated along the displacement axis at equal intervals of 0.05 mm.

[0052] The threshold for detecting a sharp increase in stiffness is set at the factory calibration time for this model of closing spring. It is 8N. Within the displacement range of the final stage of energy storage, it will satisfy... Furthermore, the displacement values ​​corresponding to sampling points exhibiting local peak characteristics are determined as real-time inflection point displacements. The distribution of the calculation results within the displacement range of 85mm to 92mm is shown in the table below: Table 2: Distribution of Second-Order Difference Values ​​of Force-Displacement Curves in the Displacement Interval of the Energy Storage Terminal Segment

[0053] As shown in Table 2, at a displacement of 89.00 mm, the second-order differential value first exceeds the threshold of 8, reaching 9, marking the beginning of the sharp increase in stiffness of the closing spring before coil merging. At a displacement of 90.50 mm, the second-order differential value reaches a local peak of 24, indicating that the rate of stiffness increase reaches its maximum at this point. Subsequently, at a displacement of 91.00 mm, the second-order differential value drops sharply to 15, constituting a turning point from rapid increase to sharp decrease. Therefore, the displacement value of 91.00 mm corresponding to this point is determined as the real-time coil merging inflection point displacement of this energy storage process. Using the same method, calculations were performed on 10 energy storage processes, and the average real-time coil merging inflection point displacement corresponding to each energy storage process was obtained as 91.02 mm. This value is recorded as the baseline coil merging inflection point displacement. .

[0054] After the circuit breaker is put into operation in the distribution network, the monitoring system continuously records the real-time inflection point displacement of each energy storage process and periodically determines the damage status.

[0055] In this embodiment, the setting is It is 0.30mm. It is 0.25mm.

[0056] The monitoring data from four typical time points during the operation are now selected for analysis. The data for each time point are shown in the table below:

[0057] Table 3 shows that in the initial stage of operation, the drift was +0.01 mm, which was within the normal fluctuation range. After one year of operation, the drift increased to +0.13 mm, which, although positive, did not exceed the first damage threshold of 0.30 mm and was considered normal. After two years of operation, the drift reached +0.36 mm, which was positive and exceeded the first damage threshold, indicating that the closing spring had undergone irreversible plastic tensile deformation. To verify the diagnostic logic of end hook fracture, the damage condition of deep cracks in the spring end hook was simulated by machining in a laboratory environment. The real-time displacement of the coil inflection point was measured to be 90.74 mm, and the drift was -0.28 mm, which was negative and the absolute value exceeded the second damage threshold of 0.25 mm. The system accurately determined that the end hook was fractured. The above results show that the two-parameter determination method based on the sign and magnitude of the drift can effectively distinguish between two typical spring damage modes.

[0058] After determining that the closing spring has undergone plastic tensile deformation, a quantitative calculation of the degree of plastic deformation is further performed.

[0059] The measured drift data from different operational phases were selected for grading and verification. The results are shown in the table below: Table 4: Verification Table for Classification of Plastic Deformation Degree

[0060] Table 4 shows that Sample 1, with a drift of 0.08 mm, is classified as having slight plastic deformation; Sample 2, with a drift of 0.22 mm, is classified as having moderate plastic deformation; Sample 3, with a drift of 0.36 mm after two years of operation, is classified as having severe plastic deformation; and Sample 4, with a drift of 0.52 mm, exceeds the third level but is still treated as having severe plastic deformation. This classification result matches the maintenance strategies adopted in actual engineering for different degrees of plastic deformation, verifying the rationality and practicality of the classification formula.

[0061] When the diagnostic results indicate that the drift exceeds the preset allowable range, a differentiated control command is generated.

[0062] Plastic tensile deformation and drift were diagnosed after two years of operation. In the case of mm, satisfying The triggering conditions are as follows. The differentiated control command generated by the system simultaneously blocks the circuit breaker closing operation circuit and forcibly disconnects the power supply circuit of the energy storage motor, while maintaining the circuit breaker's protection tripping circuit in normal operating condition. The state comparison before and after the control command execution is shown in the table below: Table 5: Verification Record of Differentiated Control Command Execution Effect

[0063] To verify that the circuit breaker can correctly respond to protection trip commands even under differentiated blocking conditions, a simulated overcurrent fault signal was injected into the circuit breaker protection device via a relay protection tester after the control command was executed. The protection device operated correctly and issued a trip command, and the circuit breaker completed the opening operation within 62ms, with the breaking process proceeding normally. This test was repeated three times, with consistent results, verifying that the differentiated safety control strategy of "blocking closing and retaining tripping" was correctly executed.

[0064] After successful execution of the differentiated control command, the spring health status diagnosis result, the execution status of the differentiated control command, the current opening and closing status of the circuit breaker, and the energy storage status of the closing spring are combined into a status indication message conforming to the IEC61850 communication protocol and sent to the operation and maintenance master station through the station control layer network. The message content and reception confirmation are shown in the table below: Table 6: Status Indication Message Content and Remote Confirmation Record Table

[0065] Upon receiving the message, the maintenance personnel confirmed that the circuit breaker in the feeder bay had been automatically locked and energy storage prohibited due to severe plastic tensile deformation of the closing spring, but the protection tripping function remained intact. Based on this, the maintenance personnel immediately formulated a maintenance plan for replacing the closing spring the following day and sent a confirmation receipt to the field monitoring system via the remote communication network. The entire process, from fault diagnosis and automatic control to maintenance decision-making, formed a closed loop, verifying the completeness and timeliness of the remote status indication and remote confirmation functions.

[0066] During the long-term operation of the circuit breaker, the monitoring method also performs a proactive early warning function. It records the real-time inflection point displacement of the closing spring during each energy storage process, forming a historical trend curve of the inflection point displacement of the closing spring.

[0067] The effectiveness of the trend warning function is verified using data from the first three periodic monitoring sessions after the circuit breaker was put into operation. The average real-time inflection point displacement of the circuit breaker during the five energy storage processes within each of the three consecutive monitoring cycles is taken as the representative value for that cycle. The data is shown in the table below:

[0068] Based on the data in Table 7, take... , , , , Substitute into the linear fitting slope formula to calculate: Molecular part: ; ; Numerator = 1638.807 - 1638.714 = 0.093 Denominator part: ; ; Denominator = 42 - 36 = 6; ; Find the slope of the linear fit The trend determination threshold is 0.0155 mm / cycle. In this embodiment, the preset trend determination threshold is 0.01 mm / cycle. Currently... Greater than 0.01, and The sign is positive and remains stable, indicating a continuous unidirectional drift trend. Although the current drift is only +0.036mm, far below the damage assessment threshold of 0.30mm, the system issued an early warning of spring fatigue deterioration, prompting maintenance personnel to include the circuit breaker in the key observation list, thus realizing the shift from planned maintenance to condition-based maintenance.

[0069] The embodiments disclosed in this invention are preferred embodiments, but are not limited thereto. Those skilled in the art can easily understand the spirit of this invention based on the above embodiments and make different extensions and variations, but as long as they do not depart from the spirit of this invention, they are all within the protection scope of this invention.

Claims

1. A monitoring method of an intelligent power distribution cabinet, characterized in that, include: Acquire the force and displacement signals of the circuit breaker closing spring during the energy storage compression process; Based on the force signal and displacement signal, a real-time force-displacement curve is generated, the second-order rate of change of force with respect to displacement is calculated, the inflection point of the closing spring in the final stage of energy storage due to the stiffness increase caused by the spring coil contact is captured, and the instantaneous displacement value corresponding to the inflection point is determined as the real-time coil inflection point displacement. The real-time inflection point displacement of the closing spring is compared with the reference inflection point displacement of the closing spring under healthy conditions to obtain the drift amount, and the damage state of the closing spring is determined based on the drift amount. If the drift exceeds the preset allowable range, a differentiated control command is generated to lock the closing operation circuit of the circuit breaker, prevent the energy storage motor of the closing spring from starting, and at the same time keep the tripping circuit of the circuit breaker in normal working condition.

2. The monitoring method of an intelligent power distribution cabinet according to claim 1, characterized in that, The calculation of the second-order rate of change of force with respect to displacement captures the inflection point of the sharp increase in stiffness, including: The second-order difference value of force versus displacement is continuously calculated on the real-time force-displacement curve within adjacent sampling intervals. The sampling point where the second-order difference value first exceeds the preset stiffness increase threshold is taken as the stiffness increase start point. The turning point where the second-order difference value changes from a peak value to a decrease is determined as the inflection point of the phenomenon of sharp increase in stiffness.

3. The monitoring method for an intelligent power distribution cabinet according to claim 1, characterized in that, The step of determining the damage state of the closing spring based on the drift amount includes: If the drift is positive and its absolute value exceeds the first damage threshold, it is determined that the closing spring has undergone plastic tensile deformation. If the drift is negative and its absolute value exceeds the second damage threshold, it is determined that the end hook of the closing spring has broken.

4. The monitoring method for an intelligent power distribution cabinet according to claim 1, characterized in that, The generation of differentiated control instructions includes: Disconnect the power supply circuit of the energy storage motor to prevent it from starting under any command; Only the power supply link of the closing operation circuit is disconnected, without making any changes to the electrical connection of the tripping circuit.

5. The monitoring method for an intelligent power distribution cabinet according to claim 1, characterized in that, Also includes: Record the real-time inflection point displacement of each energy storage process and generate a historical trend curve of the inflection point displacement. If the historical trend curve shows a continuous unidirectional drift trend and the current drift amount does not exceed the preset allowable range, a spring fatigue deterioration warning will be issued.

6. The monitoring method for an intelligent power distribution cabinet according to claim 1, characterized in that, Also includes: The damage diagnosis results of the closing spring, the execution status of the differentiated control command, the current opening and closing status of the circuit breaker, and the energy storage status of the closing spring are combined into a status message that conforms to the power distribution automation communication protocol and transmitted to the operation and maintenance master station.

7. The monitoring method for an intelligent power distribution cabinet according to claim 1, characterized in that, The acquisition of force and displacement signals of the circuit breaker closing spring during the energy storage compression process includes: Force signals are collected by a force sensor located at the end of the closing spring; Displacement signals are collected by a displacement sensor located at the moving end of the closing spring.

8. A monitoring system for an intelligent power distribution cabinet, characterized in that, include: The signal acquisition unit is used to acquire the force and displacement signals of the circuit breaker closing spring during the energy storage compression process; The curve generation and feature extraction unit is used to generate real-time force-displacement curves based on force and displacement signals, calculate the second-order rate of change of force with respect to displacement, capture the inflection point of the closing spring in the final stage of energy storage where the stiffness increases sharply due to the contact of the spring coils, and determine the instantaneous displacement value corresponding to the inflection point as the real-time coil inflection point displacement. The diagnostic unit is used to compare the real-time inflection point displacement of the closing spring with the reference inflection point displacement of the closing spring under healthy conditions to obtain the drift amount, and to determine the damage state of the closing spring based on the drift amount. The control unit is used to generate differentiated control commands if the drift exceeds the preset allowable range, block the circuit breaker's closing operation circuit, prevent the energy storage motor of the closing spring from starting, and at the same time keep the circuit breaker's tripping circuit in normal working condition.

9. An electronic device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the monitoring method of the intelligent power distribution cabinet as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The system stores a computer program, which, when executed by a processor, implements the monitoring method for the intelligent power distribution cabinet as described in any one of claims 1 to 7.

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