Anti-toppling interlocking device monitoring system for cubicle trolley

Abstract

This invention discloses a monitoring system for the anti-tipping interlocking device of a centrally located switchgear trolley, relating to the field of device monitoring technology. It identifies abnormal data frames that cause occasional interlocking offsets, calculates the weighted proportion of abnormal data frames in each zone to obtain the time-series offset weighted density, and determines whether there is a steady-state interlocking anomaly in the corresponding coordinated linkage zone. When a steady-state interlocking anomaly is determined in a certain coordinated linkage zone, a standardized feature matrix is ​​constructed using an interlocking failure assessment model. This model comprehensively analyzes the topological relationship between the current circuit breaker center of gravity and the chassis support surface of the transport vehicle, jointly outputting a comprehensive hazard level assessment of the interlocking device. Based on this assessment, it controls the electrically controlled bistable actuator installed on the interlocking release mechanism to perform a pre-locking physical action. This monitoring system achieves intelligent monitoring of the anti-tipping interlocking during the entire process of centrally located switchgear trolley transport, significantly improving the level of operational safety.

Description

Technical Field

[0001] This invention relates to the field of device monitoring technology, specifically to a monitoring system for a centrally located cabinet trolley anti-tipping interlocking device. Background Technology

[0002] Medium-voltage switchgear trolleys with voltage levels of 12kV and above are prone to tipping over or derailment during transport or movement via inclined guide rails using transfer vehicles, which seriously threatens the safety of personnel and equipment.

[0003] Traditional interlocking devices primarily rely on rigid mechanical structures such as baffles and locking plates to achieve the five-proof logic. However, in actual working conditions, due to excessive operating torque (often exceeding 50 Nm) or long-term wear of components, passive interlocking is prone to failure due to structural yielding. Furthermore, existing technologies lack the ability to monitor the entire lifecycle of the vehicle during transport in real time, cannot detect minute deviations in the continuous spatial orientation of interlocking components, and struggle to provide effective early warnings of steady-state structural anomalies, often only able to remedy the situation after an accident has occurred. Summary of the Invention

[0004] The purpose of this invention is to provide a monitoring system for the anti-tipping interlocking device of the central cabinet handcart, so as to solve the problems in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a monitoring system for the anti-tipping interlocking device of a centrally located cabinet trolley, comprising:

[0006] Trajectory chain extraction module: Generates a structured topological association model, identifies and anchors the anti-tipping interlocking components of the handcart transfer vehicle, constructs the continuous spatial pose and deformation features of each anti-tipping interlocking component throughout the entire life cycle of the circuit breaker handcart transfer, and extracts multi-scale time-space pose trajectory chains;

[0007] Analysis module: Based on the time-space pose trajectory chain, the handcart transfer vehicle is decoupled and divided into multiple collaborative linkage partitions. The dynamic relative deviation features of each collaborative linkage partition in each frame are extracted and compared with the standard safe operation benchmark model. Abnormal data frames that cause occasional interlocking offsets are identified. The proportion of abnormal data frames in each partition is weighted and calculated to obtain the time-series offset weighted density. It is then determined whether there is a steady-state interlocking anomaly in the corresponding collaborative linkage partition.

[0008] Control module: When a steady-state interlocking anomaly is detected in a certain coordinated linkage zone, the interlocking failure assessment model is triggered to construct a standardized feature matrix, comprehensively analyze the topological relationship between the current circuit breaker center of gravity and the support surface of the transfer vehicle chassis, jointly output a comprehensive hazard level assessment of the interlocking device, and control the electronically controlled bistable actuator installed on the interlocking release mechanism to perform the pre-physical locking action.

[0009] Preferably, the trajectory chain extraction module introduces a hardware-triggered microsecond-level clock synchronization mechanism and synchronously attaches a timestamp, and uses coordinate system registration to map the local observation data of each heterogeneous sensor to the global coordinate system.

[0010] Preferably, when the trajectory chain extraction module generates a structured topological association model, the topological edge weight calculation model of the topological association model is defined as follows: ,in This is a correction factor for mechanical connections. These are the spatial association weight coefficients between node i and node j in the topological association model. and These are the coordinate vectors of the corresponding entity nodes in the three-dimensional feature space. This is a constant smoothing factor that controls the radial range of the Gaussian kernel function.

[0011] Preferably, the trajectory chain extraction module constructs the continuous spatial pose and deformation features of each anti-tipping interlocking component, and the dynamic evolution of displacement and deformation is described by continuous time series integration. Where S(t) is the composite pose and deformation cumulative state vector of the component at time t. This is the absolute reference state vector of the component in its initial static state. For time The structural deformation gradient tensor acquired at each time step. This is the instantaneous velocity vector of three-dimensional space extracted at the corresponding moment.

[0012] Preferably, the trajectory chain extraction module extracts multi-scale temporal-spatial pose trajectory chains, and the multi-scale trajectory chain feature fusion operator is defined as follows: ,in The output is the final multi-scale time-space pose trajectory chain feature matrix, where N is the total number of anchored and monitored interlocking components. Let be the temporal pose function of the k-th component in a three-dimensional continuous spatial motion. This is the characteristic function of the solid dynamics structural deformation of the component. As the feature weighting factor for pose space information, As the weighting factor for deformation physical information characteristics, This is a concatenation and join function for feature tensors of multimodal data.

[0013] Preferably, for any collaboratively linked partition, the analysis module calculates the deviation using the following expression: ,in Let be the dynamic relative deviation feature scalar of the k-th coordinated partition in the f-th frame. This represents the homogeneous transformation matrix of the measured spatial pose of the corresponding partition in the current observation frame. This is the ideal pose homogeneous transformation matrix preset in the standard safe operation baseline model. This refers to the Frobenius norm operation of a matrix.

[0014] Preferably, the analysis module calculates the time-series offset weighted density for each collaborative partition within a set sliding observation time window, and obtains the time-series offset weighted density of the k-th collaborative partition within a given time-series observation window T. An adaptive threshold evolution function is introduced when judging interlocking anomalies in steady state. When the criterion is met When this occurs, a steady-state interlocking anomaly is determined to exist.

[0015] Preferably, the interlocking failure assessment model of the control module extracts multi-physics parameters of the abnormal zone and its surroundings, including the slippage of the caster locking mechanism, the mechanical shear stress of the height adjustment mechanism, the static jamming resistance of the interlocking release mechanism, and the overall center of gravity offset induced by the force distortion of the anti-tipping support mechanism. A nonlinear normalized mapping function is introduced to uniformly transform the multi-dimensional physical parameters into a standardized space.

[0016] Preferably, in the interlocking failure assessment model, the expression for calculating the topological steady-state margin of the anti-tipping balance is: ,in The topological steady-state margin coefficient for the anti-tipping balance of the transfer vehicle. This is the real-time two-dimensional projection vector of the current system's centroid onto the ground plane. and Let be the position vector of the j-th physical boundary line of the effective support polygon of the transport vehicle chassis and the corresponding planar unit normal vector, respectively, and h{cg} be the absolute spatial height of the current system's center of gravity. The determinant value of the stiffness penalty matrix [cite:61] The combined calculation expression for the comprehensive hazard level assessment index is as follows: ,in The system's overall hazard level assessment index is the result of joint output. This is a column vector of physical destructive force weight coefficients for the protection subsystem. A unit column vector of all 1s with the same dimension as the column vector. This is a column vector representing the system's real-time safety coefficients. This represents the Hadamard product.

[0017] Preferably, the trajectory chain extraction module identifies and anchors the anti-tipping interlocking components of the handcart transfer vehicle, including a docking locking mechanism, a height adjustment mechanism, a track transition mechanism, a handcart limit mechanism, an interlock release mechanism, and an anti-tipping support mechanism.

[0018] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0019] 1. By continuously tracking the spatial pose and deformation of the anti-tipping interlocking components throughout their entire life cycle and extracting multi-scale time-space pose trajectory chains, a high-precision structured data foundation is provided for subsequent analysis, effectively solving the problem that traditional transport vehicles rely solely on simple mechanical hooks for connection and are prone to tipping over due to accidental disengagement.

[0020] 2. Based on the trajectory chain, the transfer vehicle is decoupled into multiple coordinated linkage partitions. By comparing the frame-by-frame dynamic relative deviation features with the standard safe operation benchmark model, the abnormal data frames of occasional interlocking offsets are calibrated. And by using the time-series offset weighted density calculation, steady-state interlocking anomalies are identified. Compared with the traditional method that relies on human experience to judge, the sensitivity and accuracy of anomaly identification are greatly improved, and the shortcomings of existing interlocking devices that cannot monitor the interlocking status offset in real time during the movement of the handcart are made up for.

[0021] 3. After determining the steady-state interlocking anomaly, a standardized feature matrix is ​​constructed through the interlocking failure assessment model. Combined with the topological relationship between the circuit breaker's center of gravity and the support surface of the transfer vehicle chassis, a comprehensive hazard level assessment is conducted. This controls the subsequent actions of the interlocking release mechanism, which not only avoids the tipping accident of the handcart due to interlocking failure, but also solves the risk of tipping over of heavy handcarts such as 12kV due to their high and rearward center of gravity on inclined guide rails or during transfer. It also prevents excessive intervention from affecting the normal maintenance process. The entire process realizes intelligent and refined monitoring of the anti-tipping interlocking during the transfer of the central switchgear handcart, which significantly improves the level of operation and maintenance safety and the standardization of operation. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0023] Figure 1 This is a flowchart of the monitoring system of the present invention.

[0024] Figure 2 This is a schematic diagram of the overall structure of an existing interlocking device.

[0025] In the diagram: 1-cabinet; 2-handcart / transfer cart; 3-circuit breaker. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] The structure of the anti-tipping interlocking device for the central cabinet handcart is as follows: Figure 2 As shown, the device includes a handcart transfer cart 2. A push handle is fixedly installed on the top of the end of the handcart transfer cart 2 away from the cabinet 1. A track transition mechanism is installed at the end of the handcart transfer cart 2 close to the cabinet 1. A caster locking mechanism is also installed at the bottom caster of the handcart transfer cart 2 to lock the casters. An anti-tipping support mechanism is installed at the end of the handcart transfer cart 2 away from the cabinet 1.

[0028] A docking seat is also fixedly installed on the side of the cabinet 1 near the handcart transfer trolley 2. The docking seat is used to cooperate with the docking locking mechanism at the front end of the handcart transfer trolley 2 to realize the positioning and locking between the handcart transfer trolley 2 and the central cabinet 1. The docking locking mechanism is used to guide the handcart transfer trolley 2 to be aligned with the docking seat of the cabinet 1, and to restrict the handcart transfer trolley 2 from shifting forward, backward or left and right relative to the cabinet 1 after docking.

[0029] A height adjustment mechanism is also provided on one side of the handcart transfer cart 2. The height adjustment mechanism is used to adjust the height of the handcart transfer cart 2 track so that the handcart transfer cart 2 track is on the same horizontal plane or within the allowable error range as the handcart guide rail in the central cabinet, thereby facilitating the placement of the circuit breaker 3 into the cabinet 1.

[0030] The track transition mechanism is used to form a continuous transition channel between the handcart guide rail and the handcart transfer car 2 rail inside the cabinet after the handcart transfer car 2 is locked to the cabinet 1. The handcart transfer car 2 is also equipped with a handcart limiting mechanism, which is used to limit the handcart transfer car 2 in front and behind and laterally after the circuit breaker 3 handcart enters the handcart transfer car 2.

[0031] The handcart transfer trolley 2 is also equipped with an interlocking release mechanism, which works in conjunction with the docking locking mechanism, the track transition mechanism, the handcart limit mechanism, and the caster locking mechanism to restrict the sequence of actions of docking, track transition, handcart removal, handcart limit, and caster release. When the handcart transfer trolley 2 is not reliably locked to the cabinet 1, the interlocking release mechanism restricts the circuit breaker 3 from moving out. When the circuit breaker 3 is not fully inserted into the handcart transfer trolley 2 and is limited and locked, the interlocking release mechanism restricts the caster locking mechanism from being released.

[0032] Example: This example provides a monitoring system for the anti-tipping interlocking device of the centrally located cabinet trolley. Please refer to [link / reference]. Figure 1 As shown, it includes:

[0033] The trajectory chain extraction module collects dynamic operation video and multi-dimensional sensor data during the interaction between the handcart and the central control cabinet, and simultaneously attaches high-precision timestamps and three-dimensional spatial coordinates. The acquired multi-source data is cleaned, denoised, and reconstructed to generate a structured topological association model. In the topological association model, the anti-tipping interlocking components of the handcart (including docking locking mechanism, height adjustment mechanism, track transition mechanism, handcart limit mechanism, interlock release mechanism, and anti-tipping support mechanism) are identified and anchored. The continuous spatial pose and deformation features of each component in the entire life cycle of the circuit breaker handcart transfer (including pushing in, centering, locking, transition, and removal stages) are constructed, and multi-scale time-space pose trajectory chains are extracted. The time-space pose trajectory chains are sent to the analysis module.

[0034] By deploying high-frame-rate industrial cameras and multi-dimensional sensor arrays such as high-frequency inertial measurement units (IMUs) and high-precision laser ranging, and by pre-setting strain gauge arrays or fiber Bragg grid (FBG) sensors on the surface of the load-bearing components of the handcart (such as guide rail support arms, docking pins, and anti-tipping bracket load points), high-frequency micro-strain data is acquired synchronously, and dynamic running images and multi-dimensional physical quantities are continuously acquired. In order to eliminate the systematic delay error caused by asynchronous data streams, the trajectory chain extraction module introduces a hardware-triggered microsecond-level clock synchronization mechanism and synchronously attaches a high-precision timestamp.

[0035] In one embodiment disclosed in this application, the specific deployment of the aforementioned multi-dimensional sensor array is as follows: a high frame rate industrial camera is installed at the center of the top pusher beam of the handcart transfer vehicle, with the lens looking down to globally cover the docking locking area between the transfer vehicle and the central cabinet; a high-frequency inertial measurement unit (IMU) is rigidly fixed at the geometric center of the chassis of the handcart transfer vehicle to accurately sense the overall three-dimensional attitude and tilt angle changes of the chassis; a high-precision laser rangefinder is installed on both sides of the front end of the handcart transfer vehicle, facing the docking seat of the central cabinet, to measure the docking parallelism in real time; and a fiber Bragg grid (FBG) sensor is attached axially to the bottom bearing surface of the track transition mechanism and the surface of the force-bearing diagonal bar of the anti-tipping support mechanism to accurately collect micro-strain data.

[0036] During the three-dimensional spatial coordinate mounting process, coordinate system registration is used to map the local observation data of various heterogeneous sensors to the global coordinate system. The spatial rigid body transformation logic is expressed as follows: ,in This is a set of three-dimensional spatial points in a global coordinate system. This is the original set of observation points in the local coordinate system of each sensor. To represent the orthogonal rotation matrix of the rotation dimension, To characterize the translation vector of spatial position offset, isolated data collected by multi-source heterogeneous sensors are uniformly transformed into an absolute physical space reference, providing an unbiased geometric base for subsequent spatial scene reconstruction and pose estimation.

[0037] To address the distortion of sensor signals caused by complex electromagnetic interference and mechanical vibration, an adaptive nonlinear filtering and point cloud removal algorithm is employed to clean, denoise, and reconstruct the original multidimensional sensor data. Based on the extraction of high-dimensional geometric features, a structured topological correlation model is constructed using graph neural network (GNN) topological analysis. In this graph, the transfer vehicle, the central cabinet, and various mechanical interference zones are abstracted as graph nodes, while physical connections are abstracted as graph edges. To quantify the dynamic correlations between various mechanical structures, a topological edge weight calculation model is defined as follows: ,in For mechanical connection correction coefficients, binarization or weighting is performed based on whether there are physical hinges or rigid connections between components to incorporate mechanical kinematic constraints. These are the spatial association weight coefficients between node i and node j in the topological association model. and These are the coordinate vectors of the corresponding entity nodes in the three-dimensional feature space. To control the constant smoothing factor of the radial range of the Gaussian kernel function, the spatial topological compactness and structural synergy between the physical components of the device are objectively characterized by calculating the Euclidean distance of the multi-dimensional eigenvectors and performing Gaussian mapping.

[0038] Supported by a structured topological association model, the machine vision feature matching algorithm is used to identify and anchor the anti-tipping interlocking components of the handcart transfer vehicle (including docking locking mechanism, height adjustment mechanism, track transition mechanism, handcart limit mechanism, interlock release mechanism and anti-tipping support mechanism). For the entire life cycle of circuit breaker handcart transfer (pushing in, centering, locking, transition and removal stages), the module continuously calculates the continuous spatial pose and micro-deformation characteristics of each component.

[0039] The dynamic evolution of displacement and deformation is described by continuous time series integration. Where S(t) is the composite pose and deformation cumulative state vector of the component at time t. This is the absolute reference state vector of the component in its initial static state. For time The structural deformation gradient tensor acquired at each time step. This is the instantaneous velocity vector of three-dimensional space extracted at the corresponding moment.

[0040] After completing dynamic feature capture, the high-frequency acquired microscopic transient jitter and the low-frequency macroscopic translation trajectory are decoupled in the multi-resolution domain to extract multi-scale time-space pose trajectory chains. This process concatenates the discrete pose coordinates of each interlocking mechanism with the temporal deformation data into a high-dimensional continuous trajectory cluster. The multi-scale trajectory chain feature fusion operator is defined as follows: ,in The output is the final multi-scale time-space pose trajectory chain feature matrix, where N is the total number of anchored and monitored interlocking components. Let be the temporal pose function of the k-th component in a three-dimensional continuous spatial motion. This is the characteristic function of the solid dynamics structural deformation of the component. As the feature weighting factor for pose space information, As the weighting factor for deformation physical information characteristics, This is a concatenation and join function for feature tensors of multimodal data.

[0041] Analysis module: Based on the time-space pose trajectory chain, the handcart transfer vehicle is decoupled and divided into multiple collaborative linkage zones (such as the container docking locking zone, the track height transition zone, and the chassis anti-tipping load zone). The dynamic relative deviation features of each collaborative linkage zone in each frame are extracted (such as the coaxiality of the docking seat and the docking mechanism, the horizontal height difference of the track transition mechanism, etc.), and compared with the standard safe operation benchmark model to identify the abnormal data frames that cause occasional interlocking offsets.

[0042] The geometric deviation and signal acquisition confidence score of each coordinated linkage partition in each frame are extracted as weight coefficients. The proportion of abnormal data frames in each partition is weighted and calculated to obtain the time offset weighted density. Based on the time offset weighted density and an adaptive threshold judgment mechanism, the instantaneous interference caused by operation vibration is filtered out, and it is determined whether there is a steady-state interlocking abnormality in the corresponding coordinated linkage partition (i.e., the device has indeed experienced continuous structural deviation or logical failure). The judgment result is sent to the control module.

[0043] Based on the multi-scale time-space pose trajectory chain transmitted upstream, the analysis module decouples the overall rigid body motion of the handcart transfer vehicle into multiple independent collaborative linkage zones (including the container docking and locking zone, the track height transition zone, and the chassis anti-tipping load zone, etc.).

[0044] In the local coordinate system after dimensionality reduction and projection, the system extracts the dynamic relative deviation features of each collaborative linkage partition frame by frame. When extracting features, the system performs feature-level fusion of the pose offset calculated by vision and the mechanical deformation tensor obtained by the strain sensor array. When calculating the temporal offset weighted density, the system dynamically adjusts the adaptive judgment threshold in combination with the current full life cycle stage of the vehicle (such as centering, locking, and transition stages) to filter out normal mechanical vibration interference in specific stages. Its feature calibration process strictly follows the spatial geometric analytical logic.

[0045] For any collaborative partition, the expression for calculating the deviation is: ,in Let be the dynamic relative deviation feature scalar of the k-th coordinated partition in the f-th frame. This represents the homogeneous transformation matrix of the measured spatial pose of the corresponding partition in the current observation frame. This is the ideal pose homogeneous transformation matrix preset in the standard safe operation baseline model. This refers to the Frobenius norm operation of a matrix.

[0046] The method for constructing the standard safe operation benchmark model and its preset ideal pose homogeneous transformation matrix Bk(f) is as follows:

[0047] In a controlled, standardized substation laboratory, highly qualified professional maintenance personnel strictly followed operating procedures, using fully functional handcarts and transfer vehicles of the same model to perform no fewer than 100 standardized cabinet entry and exit transfer operations. The system collected sensor data frames throughout the entire lifecycle of these 100 normal operations, used the Dynamic Time Warping (DTW) algorithm to align the time series, and performed weighted averaging on the aligned spatial pose homogeneous transformation matrix to remove outliers and noise. The result was then solidified into the ideal pose homogeneous transformation matrix Bk(f) for this model of equipment and stored in the system database.

[0048] This spatial deviation scalar is continuously compared with the set static tolerance domain to accurately filter and identify abnormal data frames that cause sporadic interlocking offsets. After completing frame-by-frame deviation feature extraction, to avoid misjudgment caused by single-point data drift due to electromagnetic pulses or local occlusion, a hardware-based signal-to-noise ratio evaluation mechanism is introduced to extract signal acquisition confidence scores. Based on these confidence scores, the module performs time-series offset weighted density calculations for each collaborative linkage partition within a set sliding observation time window. The mathematical model is expressed as follows: ,in This represents the time-series offset weighted density of the k-th collaborative partition within a given time-series observation window T. The weights for the objective signal confidence of the f-th frame are derived from the sensor received signal strength and the physical characteristics of the point cloud covariance matrix. The Boolean state feature parameter of the frame (takes a value of 1 when the f-th frame is determined to be an abnormal data frame by geometric logic, and a value of 0 otherwise) uses the quality of the original data as a penalty and incentive factor to perform a weighted integral on the frequency of occurrence of dangerous frames in the discrete time series. From a purely mathematical perspective, it suppresses the interference of low-quality incomplete data on the overall anomaly assessment and outputs a smooth density distribution that reflects the real physical offset.

[0049] After obtaining the time-series offset weighted density, an adaptive threshold determination mechanism is further introduced to make a final judgment on steady-state interlocking anomalies. Given that there may be high-frequency vibrations caused by heavy equipment passage or uneven ground in the switch room, the judgment baseline must have environmental dynamic robustness. The adaptive threshold evolution function is defined as follows: ,in The adaptive decision threshold within the current time window T. This is a rigid tolerance baseline objectively set by the system based on the yield limit of the interlocking mechanical mechanism. The environmental compensation gain coefficient is pre-calibrated through modal analysis testing. The formula is for the variance of background vibration energy in the non-operational environment during the current period, which is separated by fast Fourier transform. Its function is to dynamically stretch or compress the safety tolerance boundary based on the real-time monitored external mechanical vibration conditions, and effectively filter out the spurious deviation signal caused by instantaneous physical impact.

[0050] When the criterion is met When the system is certain that the coordinated linkage partition has experienced a persistent structural deviation or logical failure of the device, which has eliminated instantaneous interference, it determines that there is a steady-state interlocking anomaly and sends the absolute determination result and the anomaly spatial coordinate array to the control module with low latency.

[0051] Control Module: When a steady-state interlocking anomaly is detected in a certain coordinated linkage zone, the interlocking failure assessment model is triggered. This model extracts multi-physics parameters of the abnormal zone and its surroundings, and maps the slippage of the caster locking mechanism, the shear stress of the height adjustment mechanism, the jamming resistance of the interlocking release mechanism, and the overall center of gravity offset caused by the force on the anti-tipping support mechanism into a standardized space for normalization. By constructing a standardized feature matrix, the topological relationship between the current circuit breaker center of gravity and the support surface of the transfer vehicle chassis is comprehensively analyzed. The actual damage of the steady-state anomaly to the transfer vehicle docking position restriction, limit unlocking release logic, and anti-tipping balance is verified. The comprehensive hazard level assessment of the output device is combined, and based on this, the electronically controlled bistable actuator installed on the interlocking release mechanism is controlled to perform the pre-physical locking action.

[0052] In one embodiment disclosed in this application, an electrically controlled bistable actuator is horizontally mounted on the side wall support of the interlocking release mechanism. A high-strength wedge-shaped locking pin is integrally formed at the end of its output push rod. Simultaneously, a physical locking groove matching the wedge-shaped locking pin is formed on the corresponding movement trajectory of the original mechanical interlocking plate's side wall. When the system determines that the comprehensive hazard assessment index Erisk exceeds the limit, the control module outputs a positive drive pulse to the actuator, switching the magnetic circuit of the permanent magnet inside the actuator. The output push rod pops out instantly, allowing the wedge-shaped locking pin to precisely insert into the locking groove of the mechanical interlocking plate, forming rigid mechanical interference, thus completely locking the interlocking release lever. When the system state returns to within the safety threshold, the control module outputs a reverse pulse, causing the push rod to retract and exit the locking groove, releasing the pre-locking physical lock.

[0053] When the analysis module determines that there is a steady-state interlocking anomaly in a certain coordinated linkage zone, the control module immediately triggers the interlocking failure assessment model at the bottom layer. This model extracts the multi-physics characteristic parameters of the abnormal zone and its spatial neighborhood, specifically including the slippage of the caster locking mechanism, the mechanical shear stress of the height adjustment mechanism, the static jamming resistance of the interlocking release mechanism, and the overall center of gravity offset induced by the force distortion of the anti-tipping support mechanism.

[0054] To eliminate the dimensional barriers between heterogeneous physical quantities, the system introduces a nonlinear normalization mapping function to uniformly transform multidimensional physical parameters into a normalized space. The mathematical model of this mapping is expressed as follows: ,in Let i be the scalar of the i-th characteristic physical parameter after mapping to the normalized space. The actual observed value of the i-th multiphysics parameter acquired in real time by the sensor. The critical failure threshold of the physical parameter in the field of materials mechanics or kinematics is calibrated. The absolute physical quantity is nonlinearly compressed to the standardized range of [0,1] by an exponential decay function, so as to objectively quantify the true severity of each independent physical field parameter approaching the physical yield or rigid body failure limit.

[0055] After normalizing the multiphysics data, a high-dimensional normalized feature matrix is ​​constructed based on the extracted normalized scalars. This matrix is ​​then used to comprehensively assess the three-dimensional topological relationship between the current circuit breaker center of gravity and the support surface of the transport vehicle chassis. In dynamic space, the expression for calculating the topological steady-state margin of the anti-tipping equilibrium is: ,in The topological steady-state margin coefficient for the anti-tipping balance of the transfer vehicle. This is the real-time two-dimensional projection vector of the center of mass of the rigid body system consisting of the current circuit breaker and the transfer vehicle onto the ground plane. and Let be the position vector of the j-th physical boundary line of the polygon effectively supporting the chassis of the transport vehicle, and its corresponding planar unit normal vector. The absolute spatial height of the current system's center of gravity. The determinant value of the stiffness penalty matrix, which is derived from the above-mentioned standardized feature matrix, is calculated by approximating the shortest normal safety margin of the overturning boundary of the support surface through dynamic centroid projection, and the dynamic penalty calculation is performed on it using the system stiffness decay state, thereby objectively verifying the deterioration boundary and overturning instability critical point of the actual anti-tipping bearing capacity of the chassis.

[0056] Based on the above topological relationship calculation results, the evaluation model further quantitatively verifies the actual destructive force of this steady-state anomaly on the three major protective lines of the transfer vehicle docking restriction, limit unlocking and release logic, and anti-tipping balance, and combines it with the comprehensive hazard level assessment of the output device.

[0057] The joint calculation expression for the global hazard assessment index is as follows: ,in The system's overall hazard level assessment index is the result of joint output. This is the transpose matrix of the column vector of physical destructive force weight coefficients for the three major protection subsystems: docking, unlocking logic, and anti-tilt balance. A unit column vector of all 1s with the same dimension as the column vector. This is a column vector containing the system's real-time safety coefficients, including docking fault tolerance, limit unlocking smoothness, and topological steady-state margin. The Hadamard product (i.e., element-wise multiplication of a matrix or vector) is represented in Euclidean space. By performing a weighted square root operation on the sum of squared decreases in the safety factors of each subsystem, it aggregates the cumulative destructive effect of steady-state anomalies of local mechanisms on the overall linkage logic, generating a single objective quantitative index characterizing the global failure risk of the system.

[0058] Ultimately, the control module uses this... The index-controlled interlock release action specifically involves adding an electrically controlled bistable permanent magnet actuator with a power-off retention function inside the interlock release mechanism. When the hazard assessment exceeds the limit, the control module drives the output push rod of the actuator to physically couple it with the original mechanical interlock plate or limit pin. The strong mechanical obstruction restricts the rotation of the interlock release lever, thereby blocking the limit unlocking and handcart removal actions in the pre-stage, achieving a hard physical cut-off of the risk of tipping failure.

[0059] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0060] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A monitoring system for the anti-tipping interlocking device of a centrally located cabinet trolley, characterized in that: include: Trajectory chain extraction module: Generates a structured topological association model, identifies and anchors the anti-tipping interlocking components of the handcart transfer vehicle, constructs the continuous spatial pose and deformation features of each anti-tipping interlocking component throughout the entire life cycle of the circuit breaker handcart transfer, and extracts multi-scale time-space pose trajectory chains; Analysis module: Based on the time-space pose trajectory chain, the handcart transfer vehicle is decoupled and divided into multiple collaborative linkage partitions. The dynamic relative deviation features of each collaborative linkage partition in each frame are extracted and compared with the standard safe operation benchmark model. Abnormal data frames that cause occasional interlocking offsets are identified. The proportion of abnormal data frames in each partition is weighted and calculated to obtain the time-series offset weighted density. It is then determined whether there is a steady-state interlocking anomaly in the corresponding collaborative linkage partition. Control module: When a steady-state interlocking anomaly is detected in a certain coordinated linkage zone, the interlocking failure assessment model is triggered to construct a feature matrix, determine the topological relationship between the current circuit breaker center of gravity and the support surface of the transfer vehicle chassis, and output the comprehensive hazard level of the interlocking device, and then automatically control the subsequent actions of the interlocking release mechanism.

2. The monitoring system for the anti-tipping interlocking device of the central cabinet handcart according to claim 1, characterized in that: the analysis module performs time-series offset weighted density calculation on each coordinated linkage partition within a set sliding observation time window, and obtains the time-series offset weighted density of the k-th coordinated linkage partition within a given time-series observation window T. An adaptive threshold evolution function is introduced when determining interlocking anomalies in steady-state conditions. When the criterion is met When this occurs, a steady-state interlocking anomaly is determined to exist.

3. The monitoring system for the anti-tipping interlocking device of the central cabinet handcart according to claim 1, characterized in that: the expression for calculating the topological edge weights of the topological association model is: ,in, This is a correction factor for mechanical connections. These are the spatial association weight coefficients between node i and node j in the topological association model. and These are the coordinate vectors of the corresponding entity nodes in the three-dimensional feature space. This is a constant smoothing factor that controls the radial range of the Gaussian kernel function.

4. The monitoring system for the anti-tipping interlocking device of the central cabinet handcart according to claim 3 is characterized in that: the trajectory chain extraction module uses continuous time series integration to describe the continuous spatial pose and deformation characteristics of each anti-tipping interlocking component.

5. The monitoring system for the anti-tipping interlocking device of the central cabinet handcart according to claim 3, characterized in that: the time-space pose trajectory chain calculation expression is: ,in This represents the feature matrix of the multi-scale time-space pose trajectory chain, where N is the total number of interlocking components being anchored and monitored. Let be the three-dimensional continuous motion attitude function of the k-th interlocking component in time sequence. For the corresponding solid dynamic structural deformation characteristic function, For pose space information feature weighting factors, and The weighting factor is the physical information feature of deformation.

6. The monitoring system for the anti-tipping interlocking device of the central cabinet handcart according to claim 1, characterized in that: the analysis module calculates the dynamic relative deviation characteristic scalar for any coordinated linkage zone.

7. The monitoring system for the anti-tipping interlocking device of the central cabinet handcart according to claim 3 is characterized in that: the trajectory chain extraction module maps the local observation data of each heterogeneous sensor to the global coordinate system by means of the coordinate system registration function.

8. The monitoring system for the anti-tipping interlocking device of the central cabinet handcart according to claim 1, characterized in that: the interlocking failure assessment model extracts multi-physics field parameters of the abnormal zone, including slippage, mechanical shear stress, static jamming resistance and center of gravity offset.

9. The monitoring system for the anti-tipping interlocking device of the centrally located cabinet trolley according to claim 8, characterized in that: in the interlocking failure assessment model, the expression for calculating the topological steady-state margin of the anti-tipping balance is: ,in The topological steady-state margin coefficient for the anti-tipping balance of the transfer vehicle. This is the real-time two-dimensional projection vector of the current system's centroid onto the ground plane. and These are the position vector of the j-th physical boundary line of the effective support polygon of the chassis and the corresponding plane unit normal vector, respectively. The height of the system's center of gravity in space. Given the determinant of the stiffness penalty matrix, the joint calculation expression for the comprehensive hazard level assessment index is as follows: ,in The system's overall hazard level assessment index is the result of joint output. This is the transpose of the column vector of physical destructive force weight coefficients of the protection subsystem. A unit column vector with all 1s of the same dimension as the column vector. Let be the column vector of the system's real-time safety coefficients, and This represents the Hadamard product.

10. The monitoring system for the anti-tipping interlocking device of the central cabinet handcart according to claim 1, characterized in that: the trajectory chain extraction module identifies the anti-tipping interlocking components of the lower handcart transfer car, the anti-tipping interlocking components including a docking locking mechanism, a height adjustment mechanism, a track transition mechanism, a handcart limit mechanism, an interlock release mechanism, and an anti-tipping support mechanism.

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