Method, device and system for monitoring mechanical state of electric chassis truck and medium

Abstract

The invention discloses an electric chassis vehicle mechanical state monitoring method, device and system and a medium, and the method comprises the steps: collecting the displacement and time data of an electric chassis vehicle under a rocking-in or rocking-out working condition, carrying out the segmented speed analysis of each operation stage, constructing a time-speed curve, and taking the total side length of the curve as a quantitative characteristic parameter, therefore, the mechanical state of the electric chassis can be accurately judged. Abnormal states such as clamping stagnation and loosening can be effectively identified, automatic monitoring and early warning of mechanical operation conditions are completed, the timeliness of fault detection and the intelligent level of equipment maintenance are remarkably improved, the problems that a traditional monitoring mode depends on artificial experience, judgment is subjective and early warning is lagged are solved, and the working efficiency is improved. And the operation stability and reliability of the high-voltage switch cabinet are powerfully ensured.

Description

Technical Field

[0001] This invention relates to the field of electric vehicle chassis testing technology, and in particular to a method, device, system and medium for monitoring the mechanical condition of an electric chassis vehicle. Background Technology

[0002] High-voltage switchgear is a critical piece of equipment in power systems, and the operational reliability of its electric chassis directly affects power supply safety and operational stability. As a sophisticated mechatronic device, the electric chassis is prone to malfunctions such as jamming or loosening in its transmission mechanism during long-term operation due to mechanical wear, structural deformation, or foreign object intrusion.

[0003] Currently, monitoring the mechanical condition of electric chassis vehicles mainly relies on operators' regular inspections and experience-based judgment, such as listening to operating noises and sensing abnormal vibrations. This traditional manual inspection method is highly subjective, cannot achieve real-time monitoring, and struggles to detect early, minor faults. Furthermore, it lacks timeliness, often only discovering faults when they significantly impact operation, potentially leading to equipment damage. In critical moments such as emergency tripping, the chassis vehicle's inability to operate properly can cause serious electrical accidents, posing significant safety hazards and affecting the safety and reliability of high-voltage switchgear operation. Summary of the Invention

[0004] In view of this, the present invention provides a method, device, system and medium for monitoring the mechanical condition of an electric chassis vehicle, in order to solve the technical problems of judgment lag and safety hazards caused by relying on human experience.

[0005] Firstly, a method for monitoring the mechanical condition of an electric chassis vehicle is provided, the method comprising: The displacement and time data of the electric chassis vehicle at different operating stages under moving conditions are obtained, where the moving conditions are either rocking in or rocking out. Based on displacement and time data, the operating speed of the electric chassis vehicle at each operating stage is generated; Based on the time data and operating speed of each operating phase, a time-speed curve of the electric chassis vehicle under mobile working conditions is constructed. Based on the total side length of the time-speed curve, the mechanical state of the electric chassis vehicle under mobile conditions is determined, wherein the mechanical state includes at least one of the following: stuck state, loose state, and normal state.

[0006] Secondly, a mechanical condition monitoring device for an electric chassis vehicle is provided, the device comprising: The acquisition module is used to acquire displacement and time data of the electric chassis vehicle at different operating stages under moving conditions, where the moving conditions are either rocking in or rocking out. The generation module is used to generate the operating speed of the electric chassis vehicle at each stage of operation based on displacement and time data. The module is used to build a time-speed curve of the electric chassis vehicle under mobile working conditions based on the time data and operating speed of each operating stage. The determination module is used to determine the mechanical state of the electric chassis vehicle under mobile conditions based on the total side length of the time-speed curve. The mechanical state includes at least one of the following: stuck state, loose state, and normal state. Thirdly, a mechanical condition monitoring system for an electric chassis vehicle is provided, the system comprising: The electric chassis vehicle mechanical condition monitoring device as described in the second aspect; Electric chassis vehicle; An array of markers is positioned between the outer surface of the bottom of the electric chassis vehicle and the vehicle's movement rails. The masking component is located on the bottom of the electric chassis vehicle and is tilted relative to the marking array. The masking component moves synchronously with the electric chassis vehicle, so that the marking array and the masking component form a visual window reflecting the real-time position of the electric chassis vehicle during the relative movement. An image acquisition device is positioned directly above the space formed by the marker array and the masking components, and is used to acquire location images at the nodes during the operation phase.

[0007] Fourthly, a computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the steps of the above-described electric chassis vehicle mechanical condition monitoring method.

[0008] The aforementioned solution for monitoring the mechanical condition of electric chassis vehicles, including the method, device, system, and storage medium, collects displacement and time data of the electric chassis vehicle during rocking-in or rocking-out operations. It then performs segmented speed analysis for each operational stage, constructs a time-speed curve, and uses the total side length of the curve as a quantitative feature parameter to accurately determine the mechanical condition of the electric chassis vehicle. This effectively identifies abnormal states such as jamming and loosening, achieving automated monitoring and early warning of mechanical operation. It significantly improves the timeliness of fault detection and the intelligence level of equipment maintenance, solving the problems of traditional monitoring methods relying on human experience, subjective judgment, and delayed early warning. This effectively ensures the stability and reliability of high-voltage switchgear operation. Attached Figure Description

[0009] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 This is a flowchart illustrating a method for monitoring the mechanical condition of an electric chassis vehicle according to an embodiment of the present invention. Figure 2 This is a time-speed curve of an electric chassis vehicle under rocking conditions according to an embodiment of the present invention; Figure 3 This is a time-speed curve of an electric chassis vehicle under rocking conditions according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of an electric chassis vehicle mechanical condition monitoring device according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of an electric chassis vehicle mechanical condition monitoring system according to an embodiment of the present invention.

[0010] in, Figure 5 The correspondence between the reference numerals and component names in the attached drawings is as follows: 1. Identifier array; 2. Occlusion component; 3. Image acquisition unit; 4. Binarization preprocessor; 5. Binary matrix converter; 6. Identifier unit quantity calculator; 7. Working condition node time converter; 8. Speed ​​converter; 9. Time-speed plotter; 10. Time-speed side length calculator; 11. Mechanical condition judge. Detailed Implementation

[0011] 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. It should be understood that the accompanying drawings in the present invention are only for illustrative and descriptive purposes and are not intended to limit the scope of protection of the present invention.

[0012] Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this invention illustrate operations implemented according to some embodiments of the invention. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or performed simultaneously. Moreover, those skilled in the art, guided by the content of this invention, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0013] Furthermore, the embodiments described herein are merely some, not all, of the embodiments of the invention. The components of the embodiments of the invention described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0014] It should be noted that the term "comprising" will be used in the embodiments of the present invention to indicate the presence of a feature subsequently declared, but does not exclude the addition of other features. It should also be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0015] The following is a detailed description of this case, in conjunction with the relevant accompanying drawings in the instruction manual.

[0016] Please see Figure 1 This specification provides a method for monitoring the mechanical condition of an electric chassis vehicle, specifically including the following steps: S10: Acquire displacement and time data of the electric chassis vehicle at different operating stages under mobile working conditions; Among them, the moving condition is either the rocking-in condition or the rocking-out condition.

[0017] It is understood that the executing entity of this invention can be an electric chassis vehicle mechanical condition monitoring device, a terminal, or a server; no specific limitation is made here. This embodiment of the invention will be described using a server as an example.

[0018] In this step, the electric chassis vehicle is one of the core components of the high-voltage switchgear. It carries the circuit breaker and controls its rocking-in or rocking-out operations to achieve the circuit breaker's opening and closing functions. The movement operation includes rocking-in and rocking-out operations. Rocking-in refers to sending the circuit breaker to the working position, and rocking-out refers to moving the circuit breaker to the isolation position. The electric chassis vehicle's rocking-in or rocking-out process includes multiple operating stages. Taking the rocking-in operation as an example, it includes a rocking-in start-up stage, a rocking-in stabilization stage, and a rocking-in deceleration stage. By acquiring the actual distance traveled by the electric chassis vehicle in each operating stage and the time taken to complete the stage displacement, the instantaneous speed change characteristics of different operating stages can be analyzed to achieve refined diagnosis of the mechanical condition and early fault warning.

[0019] In one embodiment of this application, a specific data acquisition scheme is provided. In S10, that is, acquiring displacement data and time data of the electric chassis vehicle at different operating stages under mobile conditions, the specific steps include the following S11-S15: S11: During the mobile operation of the electric chassis vehicle, acquire the rotational speed data of the electric chassis vehicle's drive motor.

[0020] S12: When the rotation data reaches the preset rotation threshold of any operating stage, generate the working condition node switching signal preset rotation threshold when the operating stage ends.

[0021] For steps S11-S12, when the electric chassis vehicle is detected to be performing a movement operation, the real-time rotation speed of the electric chassis vehicle's drive motor is acquired. When the real-time rotation speed reaches the preset rotation speed threshold for the current operating stage, the operating stage node is switched to enter the next operating stage. At this time, an operating stage node switching signal is generated to end the current operating stage. For example, in the rocking start-up operation, when the drive motor rotates 1000 times, the electric chassis vehicle needs to switch from the rocking start-up stage to the rocking stabilization stage. At this time, the rocking start-up stage ends, and an operating stage node switching signal is generated.

[0022] S13: Obtain the time and location information of the electric chassis vehicle at the working condition node switching signal.

[0023] In this step, the system responds to the working condition node switching signal and synchronously collects the time information and location information of the electric chassis vehicle when it completes the current operating phase.

[0024] In one embodiment of this application, a specific information acquisition scheme is provided. In S13, that is, acquiring the time information and location information of the electric chassis vehicle at the working condition node switching signal, the specific steps include the following steps S131-S133: S131: Obtain the time information of the electric chassis vehicle at the working condition node switching signal; S132: When the electric chassis vehicle is at the working condition node switching signal, acquire the position image of the electric chassis vehicle relative to the marker array on the movement path; The identifier array consists of multiple identifier units composed of alternating black and white blocks.

[0025] For steps S131-S132, for any operating stage, when the rotational speed data of the drive motor reaches the rotational speed threshold of that operating stage, the system responds to the working condition node switching signal that ends the operating stage, collects the time information of the electric chassis vehicle at the working condition node switching signal, and simultaneously collects a complete position image that includes the relative positional relationship between the marker array next to the running slide rail and the electric chassis vehicle.

[0026] S133: Based on the location image, determine the location information of the electric chassis vehicle at the working condition node switching signal.

[0027] In this step, the marker array is organized into marker units consisting of a large number of uniformly sized, alternating black and white blocks. Black and white represent the two extremes of the grayscale spectrum, and their alternating arrangement forms a regular, periodic visual signal. By detecting the instantaneous color transition (i.e., from black to white, or from white to black), the system converts this into a digital pulse signal, and by counting the number of such transitions, accurately obtains the number of marker units passed by the electric chassis vehicle. As the electric chassis vehicle moves, its relative position to the marker array changes continuously. By accurately counting the number of marker units passed in each stage of operation, the corresponding precise displacement data can be calculated.

[0028] Using the above method, the location image containing visual information is processed and calculated to convert it into a digital sequence representing the precise position of the electric chassis vehicle, and then the actual straight-line distance moved by the electric chassis vehicle from the starting position to the current node is calculated.

[0029] In one embodiment of this application, a specific location information calculation scheme is provided. In S133, that is, based on the location image, the location information of the electric chassis vehicle at the working condition node switching signal is determined, which specifically includes the following steps: The location image is binarized to generate a binary image; Based on the binary image, determine the number of identification units at the working condition node switching signal of the electric chassis vehicle; Based on the length value and number of identification units, the position information of the electric chassis vehicle at the working condition node switching signal is obtained.

[0030] In this embodiment, the location image is binarized to generate a binary image containing only two contrasting color values. Subsequently, by counting the number of feature transitions in the binary image, the number of marker units passed by the electric chassis vehicle is determined. This number is then multiplied by the standard physical length of the marker unit to obtain the precise location information of the electric chassis vehicle at the working condition node switching signal.

[0031] In one embodiment of this application, a specific binary image generation scheme is provided, namely, binarizing a location image to generate a binary image, specifically including the following steps: Edge image processing is performed on the location image to obtain the pixel grayscale value of each pixel in the location image; Image regions in the location image whose pixel grayscale values ​​are less than or equal to a first preset threshold are processed into first binary logical values, and image regions in the location image whose pixel grayscale values ​​are greater than or equal to a second preset threshold are processed into second binary logical values ​​to generate a binary image.

[0032] In this embodiment, edge image processing is performed on the location image to weaken unnecessary textures and noise interference in the image, thereby improving the accuracy of subsequent binarization processing for target region segmentation. After edge processing, a matrix containing the grayscale values ​​of each pixel is obtained, which clearly reflects the boundary feature information of the identifier array. Subsequently, using two preset thresholds, dark and light regions in the image are identified and divided, thereby classifying different regions into corresponding color blocks and processing them into a first binary logical value and a second binary logical value, ultimately generating an image where all pixels are composed of binary logical values.

[0033] Optionally, a first preset threshold is set to 50 and a second preset threshold is set to 200. The grayscale value of each pixel in the edge contour image is compared with the first and second preset thresholds respectively. If the pixel grayscale value is ≤50, it is assigned a value of 0; if the pixel grayscale value is ≥200, it is assigned a value of 255. Subsequently, all pixels with a grayscale value of 0 are assigned a binary logic value of 0, and all pixels with a grayscale value of 255 are assigned a binary logic value of 1, thereby converting the position image into a sequence consisting only of binary logic values ​​0 and 1, generating a binary image.

[0034] In one embodiment of this application, a specific scheme for determining the number of identification units is provided, that is, determining the number of identification units of an electric chassis vehicle at the working condition node switching signal based on a binary image, specifically including the following steps: Traverse the binary image to determine the number of transitions in the binary logic values ​​within the image; The number of marker units traversed by the electric chassis vehicle is determined based on the number of jumps.

[0035] In this embodiment, the binary image is scanned pixel by pixel along the direction of movement of the electric chassis vehicle, detecting the binary logic value (0 represents black, 1 represents white) of each pixel. During the traversal, whenever the logic value of two adjacent pixels changes (e.g., from 0 to 1, or from 1 to 0), it is recorded as a transition, and the system counter increments accordingly. By counting the total number of transitions, the number of color block boundaries traversed can be determined, and thus the cumulative number of identification units traversed by the electric chassis vehicle at the current working condition node signal can be obtained.

[0036] S14: Based on the difference in the timing information of the switching signals between two adjacent working condition nodes, the time data of the electric chassis vehicle in each operating stage is obtained.

[0037] S15: Based on the difference in position information of the switching signals of two adjacent working condition nodes, the displacement data of the electric chassis vehicle in each operating stage is obtained.

[0038] For steps S14-S15, after synchronously collecting the time and location information of the switching signals of the operating nodes at the end of each operating phase, the time data of each operating phase is obtained by calculating the difference in time information between two adjacent switching signals. Further, after calculating the location information at each switching signal, the displacement data of each operating phase is obtained by calculating the difference in location information between two adjacent switching signals.

[0039] S20: Based on displacement and time data, generate the operating speed of the electric chassis vehicle at each operating stage.

[0040] In this step, any abnormality in the electric chassis vehicle (such as jamming or loosening) will be immediately reflected in the abnormal speed value. By dividing the acquired stage displacement by the stage time, the operating speed of each operating stage is obtained, thereby transforming the raw spatiotemporal data into speed parameters with clear diagnostic value. This enables the system to accurately identify abnormal conditions that occur during movement, ensuring the accuracy and timeliness of condition monitoring.

[0041] S30: Based on the time data and operating speed of each operating phase, construct the time-speed curve of the electric chassis vehicle under mobile working conditions.

[0042] In this step, after calculating the operating speed of the electric chassis vehicle at each stage of its movement, a time-speed curve is plotted by comparing the stage duration with the corresponding stage speed, visually demonstrating the speed change over time. This integrates discrete data points into a graphical representation of the overall motion state of the vehicle, and by analyzing the morphological characteristics of this graph, quantitative diagnosis and anomaly identification of the mechanical condition can be achieved.

[0043] In practical application scenarios, such as Figure 2As shown, this is a time-velocity curve of an electric chassis vehicle under the rocking-in condition. The horizontal axis represents time data, and the vertical axis represents velocity data. Q0 is the working condition node switching signal at the start of the rocking-in condition. At this time, the time and displacement of the electric chassis vehicle are both zero, so the coordinates of point Q0 are (0, 0). Subsequently, the electric chassis vehicle enters the rocking-in start-up stage (rocking-in stage I). Q1 is the working condition node switching signal at the end of the rocking-in start-up stage. The time data x(1) and velocity data y(1) of the electric chassis vehicle in the curve can be calculated through the time information and position information corresponding to this point. After that, the electric chassis vehicle enters the rocking-in stabilization stage (rocking-in stage II). Q2 is the working condition node switching signal at the end of the rocking-in stabilization stage. x(2) is calculated through the difference between the time information of Q2 and Q1. Based on the difference between the position information of the electric chassis vehicle at Q2 and the position information at Q1, the displacement data of the electric chassis vehicle in the rocking-in stabilization stage is calculated. Then, the running speed y(2) of this stage is obtained through the time data and displacement data. Afterwards, the electric chassis vehicle enters the rocking deceleration stage (rocking stage III). Q3 is the working condition node switching signal at the end of the rocking deceleration stage. Similarly, x(3) is calculated by the difference between the time information of Q3 and Q2. The displacement data of the electric chassis vehicle in the rocking deceleration stage is calculated by the difference between the position information of the electric chassis vehicle at Q3 and the position information at Q2. Then, y(3) is obtained by using the time data and displacement data. This is to fully describe the speed change of each operating stage under the rocking working condition. Figure 3The figure shows the time-speed curve of the electric chassis vehicle under the rocking-out condition. The horizontal axis represents time data and the vertical axis represents speed data. To clearly distinguish between the rocking-in and rocking-out conditions, the time and speed coordinate values ​​are converted to negative numbers when plotting the rocking-out condition curve. Q4 is the working condition node switching signal at the start of the rocking out working condition. At this time, the time and displacement of the electric chassis vehicle are both zero, so the coordinates of point Q4 (x(4), y(4)) are (0, 0). Subsequently, the electric chassis vehicle enters the rocking out start-up stage (rocking out section I). Q5 is the working condition node switching signal at the end of the rocking out start-up stage. The time data x(5) and speed data y(5) of the electric chassis vehicle in the curve can be calculated through the time information and position information corresponding to this point. After that, the electric chassis vehicle enters the rocking out stabilization stage (rocking out section II). Q6 is the working condition node switching signal at the end of the rocking out stabilization stage. x(6) is calculated through the difference between the time information of Q6 and Q5. Based on the difference between the position information of the electric chassis vehicle at Q6 and the position information at Q5, the displacement data of the electric chassis vehicle in the rocking out stabilization stage is calculated. Then, the running speed y(6) of this stage is obtained through the time data and displacement data. Afterwards, the electric chassis vehicle enters the rocking out deceleration stage (rocking out stage III). Q7 is the working condition node switching signal at the end of the rocking out deceleration stage. Similarly, x(7) is calculated by the difference between the time information of Q7 and Q6. The displacement data of the electric chassis vehicle in the rocking in deceleration stage is calculated by the difference between the position information of the electric chassis vehicle at Q7 and the position information at Q6. Then, y(7) is obtained by using the time data and displacement data. This is to fully describe the speed change of each operating stage under the rocking out working condition.

[0044] S40: Determine the mechanical state of the electric chassis vehicle under mobile conditions based on the total side length of the time-velocity curve; The mechanical state includes at least one of the following: stuck state, loose state, and normal state.

[0045] In this step, the time-velocity curve is formed by connecting line segments corresponding to each operating stage under the moving condition, and the total side length is the sum of the lengths of all the line segments constituting the graph. Any mechanical fault will disrupt the normal motion pattern, causing the curve to distort and thus triggering a quantitative change in the total side length. For example, a jamming fault causes the graph to stretch and deform, increasing the total side length; a loosening fault causes the graph to shrink, decreasing the total side length. By analyzing and comparing the total side length of the graph with a preset threshold, it is possible to clearly determine whether the electric chassis vehicle has jamming or loosening faults under the moving condition, thereby achieving automatic diagnosis and classification of the mechanical condition.

[0046] In one embodiment of this application, a specific mechanical state determination scheme is provided. In S40, the mechanical state of the electric chassis vehicle under mobile conditions is determined based on the total side length of the time-velocity curve. Obtain the total side length of the time-velocity curve; If the total side length is greater than the first preset side length threshold, the electric chassis vehicle is determined to be stuck in the moving condition. If the total side length is less than or equal to the first preset side length threshold and greater than or equal to the second preset side length threshold, the electric chassis vehicle is determined to be in a normal state under mobile working conditions. If the total side length is less than the second preset side length threshold, the electric chassis vehicle is determined to be in a loose state under moving conditions.

[0047] In this embodiment, the time-velocity curve is a polygonal graph formed by sequentially connecting nodes of each running stage. Its total side length is the sum of the lengths of all hypotenuses and the base of the time axis. The hypotenuses connect adjacent time-velocity data points, representing the velocity changes in different running stages; the base length corresponds to the total time taken to complete the entire movement process. The length of each segment is calculated using the distance formula between two points, and these lengths are summed to obtain the total side length of the polygon.

[0048] Furthermore, the calculated total side length is compared with multiple preset side length thresholds to determine the mechanical state of the electric chassis vehicle throughout the movement process. If the total side length > the first preset side length threshold, the electric chassis vehicle is determined to be in a stuck state during movement; if the second preset side length threshold ≤ the total side length ≤ the first preset side length threshold, the electric chassis vehicle is determined to be in a normal state during movement; if the total side length < the second preset side length threshold, the electric chassis vehicle is determined to be in a loose state during movement. When abnormal speed (stuck or loose) is detected during the rocking-in or rocking-out process of the electric chassis vehicle, it indicates that there may be a problem with the mechanical transmission part, which requires timely maintenance to avoid failure and serious consequences during emergency operations.

[0049] By employing the above methods, mechanical faults that are difficult to capture intuitively are transformed into quantifiable graphical features for comparative analysis, making diagnostic conclusions objective and accurate, and effectively identifying early potential faults. The final output of clear status classifications (stuck, loose, normal) significantly lowers the technical threshold for operation and maintenance work, providing solid technical support for predictive maintenance and safe and reliable operation of high-voltage switchgear.

[0050] As can be seen, in the above scheme, by collecting displacement and time data of the electric chassis vehicle during the rocking-in or rocking-out operation, segmented speed analysis is performed on each operating stage to construct a time-speed curve. The total side length of the curve is used as a quantitative feature parameter to achieve accurate judgment of the mechanical state of the electric chassis vehicle. This effectively identifies abnormal states such as jamming and loosening, completing automated monitoring and early warning of mechanical operation. It significantly improves the timeliness of fault detection and the level of intelligent equipment maintenance, solving the problems of traditional monitoring methods relying on human experience, subjective judgment, and delayed early warning, thus effectively ensuring the stability and reliability of high-voltage switchgear operation.

[0051] In one embodiment, a mechanical condition monitoring device for an electric chassis vehicle is provided, which corresponds one-to-one with the mechanical condition monitoring method for an electric chassis vehicle described in the above embodiments. For example... Figure 4 As shown, the electric chassis vehicle mechanical condition monitoring device 100 includes: an acquisition module 101, a generation module 102, a construction module 103, and a determination module 104. Detailed descriptions of each functional module are as follows: The acquisition module 101 is used to acquire displacement data and time data of the electric chassis vehicle at different operating stages under moving conditions, wherein the moving conditions are rocking in or rocking out conditions. The generation module 102 is used to generate the running speed of the electric chassis vehicle at each operating stage based on displacement data and time data. Module 103 is used to construct a time-speed curve of the electric chassis vehicle under mobile working conditions based on the time data and operating speed of each operating stage. The determination module 104 is used to determine the mechanical state of the electric chassis vehicle under mobile conditions based on the total side length of the time-speed curve, wherein the mechanical state includes at least one of the following: stuck state, loose state, and normal state.

[0052] In one embodiment, the acquisition module 101 is specifically used for: During the mobile operation of the electric chassis vehicle, the rotational speed data of the drive motor of the electric chassis vehicle is acquired; When the revolution count data reaches the preset revolution count threshold for any operating stage, a condition node switching signal is generated to end that operating stage. Acquire the time and location information of the electric chassis vehicle at the working condition node switching signal; Based on the difference in the timing information of the switching signals between two adjacent working condition nodes, the time data of the electric chassis vehicle in each operating stage is obtained. The displacement data of the electric chassis vehicle in each operating stage is obtained based on the difference in position information of the switching signals of two adjacent working condition nodes.

[0053] In one embodiment, the acquisition module 101 is further configured to: The steps for obtaining the time and location information of the electric chassis vehicle at the working condition node switching signal and the preset speed threshold specifically include: Obtain the time information of the electric chassis vehicle at the working condition node switching signal; When the electric chassis vehicle is at the working condition node switching signal, the position image of the electric chassis vehicle relative to the marker array on the movement path is acquired. The marker array includes multiple marker units composed of alternating black and white blocks. Based on the location image, the position information of the electric chassis vehicle at the working condition node switching signal is determined.

[0054] In one embodiment, the acquisition module 101 is further configured to: The location image is binarized to generate a binary image; Based on the binary image, determine the number of identification units at the working condition node switching signal of the electric chassis vehicle; Based on the length value and number of identifier units in the identifier array, the position information of the electric chassis vehicle at the working condition node switching signal is obtained.

[0055] In one embodiment, the acquisition module 101 is further configured to: Edge image processing is performed on the location image to obtain the pixel grayscale value of each pixel in the location image; Image regions in the location image whose pixel grayscale values ​​are less than or equal to a first preset threshold are processed into first binary logical values, and image regions in the location image whose pixel grayscale values ​​are greater than or equal to a second preset threshold are processed into second binary logical values ​​to generate a binary image.

[0056] In one embodiment, the acquisition module 101 is further configured to: Traverse the binary image to determine the number of transitions in the binary logic values ​​within the image; The number of marker units traversed by the electric chassis vehicle is determined based on the number of jumps.

[0057] In one embodiment, the determining module 104 is specifically used for: Obtain the total side length of the time-velocity curve; If the total side length is greater than the first preset side length threshold, the electric chassis vehicle is determined to be stuck in the moving condition. If the total side length is less than or equal to the first preset side length threshold and greater than or equal to the second preset side length threshold, the electric chassis vehicle is determined to be in a normal state under mobile working conditions. If the total side length is less than the second preset side length threshold, the electric chassis vehicle is determined to be in a loose state under moving conditions.

[0058] The electric chassis vehicle mechanical condition monitoring device 100 provided by this invention collects displacement and time data of the electric chassis vehicle during rocking in and rocking out operations, performs segmented speed analysis on each operating stage, constructs a time-speed curve, and uses the total side length of the curve as a quantitative feature parameter to achieve accurate identification of the mechanical condition of the electric chassis vehicle. It can effectively identify abnormal states such as jamming and loosening, complete automated monitoring and early warning of mechanical operation, significantly improve the timeliness of fault detection and the level of intelligent equipment maintenance, and solve the problems of traditional monitoring methods relying on human experience, subjective judgment, and delayed early warning, effectively ensuring the stability and reliability of high-voltage switchgear operation.

[0059] In one embodiment, a mechanical condition monitoring system for an electric chassis vehicle is provided to implement the aforementioned mechanical condition monitoring method for an electric chassis vehicle. For example... Figure 5 As shown, the mechanical condition monitoring system for this electric chassis vehicle includes: Electric chassis vehicle; Identifier array 1 is positioned between the outer surface of the bottom of the electric chassis vehicle and the movement rail of the electric chassis vehicle; The shielding component 2 is located on the bottom of the electric chassis vehicle and is tilted relative to the marking array 1. The shielding component moves synchronously with the electric chassis vehicle, so that the marking array 1 and the shielding component form a visible window reflecting the real-time position of the electric chassis vehicle during the relative movement. Image acquisition device 3 is positioned directly above the space formed by the marker array 1 and the masking component, and is used to acquire position images at the nodes during the operation phase; Binarization preprocessor 4 is used to binarize the pixel grayscale values ​​of the location image to obtain a binary image; Binary matrix converter 5 is used to obtain the binary matrix of a binary image; The marker unit number calculator 6 is used to determine the number of marker units passed by the electric chassis vehicle based on a binary matrix, and to determine the displacement data of the electric chassis vehicle in each operating stage based on the number of marker units and the marker unit length value. The working condition node time converter 7 is used to obtain the time information of the working condition node switching signal at the working condition node signal, and determine the time data of the electric chassis vehicle in each operating stage based on the time information of the switching signals of two adjacent working condition nodes. Speed ​​converter 8 is used to obtain the operating speed of the electric chassis vehicle at each operating stage based on time data and displacement data; Time-speed plotter 9 is used to plot the time-speed curve of the electric chassis vehicle under mobile working conditions based on the running speed and time data of each operating stage. Time-velocity side length calculator 10, used to obtain the total side length of a time-velocity curve; Mechanical state determiner 11 is used to determine the mechanical state of the electric chassis vehicle under moving conditions based on the total side length.

[0060] In this embodiment, the electric chassis vehicle, as a mechatronic device primarily composed of mechanical components, exhibits jamming and loosening as its main failure modes. Due to the limited interior space and the already complex existing mechanical and electric motor system, adding a system for directly detecting mechanical faults would be difficult to implement. To address this issue, this application proposes a position encoding mechanism using a marker array 1 and a masking component 2, encoding position information using visual images. Specifically, the marker array 1 consists of pairs of black and white blocks arranged on a prefabricated grid surface. In the figure, blocks labeled "a" are all black, and blocks labeled "b" are all white. The marker array is attached between the interior floor surface and the slide rails of the electric chassis vehicle for indirect detection of displacement. The masking component 2 is located above the marker array 1 at a certain angle and moves synchronously with the electric chassis vehicle, achieving indirect displacement detection through interaction with the marker array 1. The relative movement between the tilted movable baffle (i.e., the masking component 2) and the fixed black and white grid (i.e., the marker array 1) creates a triangular visible area where the edge of the tilted baffle intersects with the black and white grid. This, combined with the image acquisition unit 3 positioned above the space formed by the masking component 2 and the marker array 1, generates a unique image that changes with the user's position upon receiving a working condition node switching signal. After acquiring the image containing the marker array 1 and the masking component 2, edge contour processing is performed, and the pixel grayscale values ​​within the contour area are extracted. When the motor encoder detects that the drive motor's rotation speed has reached the threshold for the current operating stage, it sends a signal to the controller. The controller then generates a working condition node switching signal, triggering the image acquisition unit 3 to acquire the position image.

[0061] Furthermore, the system also includes: a binarization preprocessor 4, used to receive the pixel grayscale values ​​of the position image acquired by the image acquisition unit 3, perform binarization processing on them, and obtain the corresponding binary logic value (Bivalent Logic); a binary matrix converter 5, used to receive the binary logic value (Bivalent Logic) from the binarization preprocessor 4 to obtain the relevant binary matrix sequence; an identifier unit number calculator 6, used to receive the binary matrix sequence from the binary matrix converter to obtain the number of identifier units passed by the electric chassis vehicle (Number), indirectly detecting the position information of the electric chassis vehicle; a working condition node time converter 7, used to obtain the time information at the working condition node signal, and determine the time data of the electric chassis vehicle in each operating stage based on the time information at the switching signals of two adjacent working condition nodes; and a speed converter 8, used to receive the identifier unit number calculator 6 and the working condition node time converter according to the working condition node signal. Device 7 provides the number of identification units (Number) and time data to obtain the operating speed; Time-speed plotter 9 receives the time data and operating speed to provide a quadrilateral curve graph of time and speed for the rocking-in or rocking-out conditions, and then transmits it to the host computer; Time-speed side length calculator 10 receives the time data and operating speed to obtain the total side length of the time-speed curve graph for the rocking-in or rocking-out conditions; Mechanical state judge 11 receives the total side length of the time-speed curve graph to quantitatively determine whether the electric chassis vehicle is in a stuck, loose, or normal mechanical state during the rocking-in or rocking-out conditions, and the result is transmitted to the host computer.

[0062] Among them, the binarization preprocessor 4 performs binarization processing on the pixel grayscale value VS, as follows: When the pixel grayscale value VS of the image within the edge contour is ≤50, set it to 0; When the pixel grayscale value VS of the image within the edge contour is ≥200, set it to 255.

[0063] Furthermore, the binary logic value performs the following: If the pixel grayscale value VS is 0, the binary logic value Bivalent Logic is set to 0; If the pixel grayscale value VS is 255, then the binary logic value Bivalent Logic is set to 1.

[0064] Here, the binary sequence Sequence is a sequence containing 1s and 0s generated by the binary matrix transformer 5. The binary sequence Sequence is executed according to the following formula:

[0065] When the grayscale value of the color block is 255, ak =1; when the grayscale value of the color block is 0, a k =0.

[0066] Furthermore, an additional term is added to the binary sequence Sequence: Number = Number + 1, with the initial value of Number, which indicates the number of units, being 0.

[0067] The time data x(i) at the working condition node switching signal is generated by the working condition node time converter 7 based on the working condition node switching signal. The time data x(i) is processed as follows: Let i be the set {0, 1, 2, 3, 4, 5, 6, 7}. Where i=0, it is the moment of the start signal Q0 node; When i=1, it is the time of the Q1 node of the switching signal between the I-II stages of the rocking process; When i=2, it is the time of the Q2 node of the switching signal between segments II and III; When i=3, it is the time of the Q3 node signal for the end of the roll-in; When i=4, it is the time when the start signal Q4 is generated; When i=5, it is the time of the Q5 node when the switching signal between segments I and II is generated; When i=6, it is the time of the Q6 node when the switching signal between segments II and III is generated; When i=7, it is the time when the end signal Q7 is generated.

[0068] The running speed y(i) is generated by speed converter 8 based on the time data x(i) and the number of identifier units Number. The running speed y(i) is executed as follows:

[0069] Where d is the width of each black and white block grid.

[0070] Furthermore, the time-velocity curve Ps is generated by the time-velocity plotter 9 and plotted using the plotting function plot(x,y).

[0071] Total side length of the figure ΣL k It is generated by the time-speed-side-length calculator 10, specifically: Calculate the side lengths for each operating stage under the rocking-in condition: The lengths of the segments advancing into segment I, segment II, and segment III are L1, L2, and L3, respectively. The formula for calculating the lengths of these three segments is:

[0072] Among them, the line segment serial number k = 1, 2, 3; the time sampling serial number i = 0, 1, 2, 3; The length L4 of the x-axis projection line segment of the rocking-in is calculated by the formula:

[0073] The formula for calculating the graphic side length value ΣL1 in the rocking-in condition is: ΣL1 = L1 + L2 + L3 + L4; Among them, L1, L2, L3, and L4 are the x-axis projection side lengths of the first stage, the second stage, the third stage, and the rocking-in stage of the rocking-in respectively.

[0074] Perform the calculation of the side length in the rocking-out condition: The lengths of the first stage, the second stage, and the third stage line segments of the rocking-out are L5, L6, and L7 respectively. The formulas for calculating the lengths of the three line segments are:

[0075] Among them, the line segment serial number k = 5, 6, 7; the time sampling serial number i = 4, 5, 6, 7; The length L8 of the x-axis projection line segment of the rocking-out is calculated by the formula:

[0076] The formula for calculating the graphic side length value ΣL2 in the rocking-out condition is: ΣL2 = L5 + L6 + L7 + L8; Among them, L5, L6, L7, and L8 are the x-axis projection side lengths of the first stage, the second stage, the third stage, and the rocking-out stage of the rocking-out respectively.

[0077] Furthermore, the mechanical state of the electric chassis truck is determined by the mechanical state detector 11: If ΣL k > LS, it is determined as the stuck state; If LS ≥ ΣL k ≥ LH, it is displayed as the normal state; If ΣL k < LH, it is displayed as the loose state; Among them, LH is the preset value of the stuck side length, and LS is the preset value of the loose side length; when k = 1, it is the rocking-in condition; when k = 2, it is the rocking-out condition.

[0078] The electric chassis mechanical condition monitoring system provided by this invention has no direct mechanical contact among all monitoring components, avoiding errors introduced by wear, slippage, and mechanical deformation, and boasts advantages such as long lifespan and high reliability. The entire system has a flat structure, perfectly fitting into the narrow space at the bottom of the electric chassis compartment, effectively solving the problem of installing sensors in complex electromechanical structures. Its core components (color blocks, baffles, and cameras) are all simple physical structures and universal vision components, requiring no major modifications to existing mature and expensive electric chassis mechanical structures, resulting in extremely low cost. Using the simplest vision principles and mechanical structure, it achieves a low-cost, high-reliability solution for monitoring the condition of precision moving parts in confined spaces.

[0079] Specific limitations regarding the mechanical condition monitoring system for electric chassis vehicles can be found in the above-described limitations on the mechanical condition monitoring method for electric chassis vehicles, and will not be repeated here. Each module in the aforementioned mechanical condition monitoring system for electric chassis vehicles can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in the electronic device, or stored in the memory of the electronic device as software, so that the processor can call and execute the corresponding operations of each module.

[0080] In one embodiment, a computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the above-described method for monitoring the mechanical condition of an electric chassis vehicle.

[0081] It should be noted that the functions or steps that the computer-readable storage medium can achieve are described in the relevant descriptions of the server side and client side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0082] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0083] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0084] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for monitoring the mechanical condition of an electric chassis vehicle, characterized in that, include: The displacement and time data of the electric chassis vehicle at different operating stages under moving conditions are obtained, wherein the moving conditions are rocking in or rocking out. Based on the displacement data and the time data, the operating speed of the electric chassis vehicle in each operating stage is generated; Based on the time data and operating speed of each operating stage, a time-speed curve of the electric chassis vehicle under the mobile working condition is constructed. Based on the total side length of the time-speed curve, the mechanical state of the electric chassis vehicle under the moving condition is determined, wherein the mechanical state includes at least one of the following: stuck state, loose state, and normal state.

2. The method for monitoring the mechanical condition of an electric chassis vehicle according to claim 1, characterized in that, The steps for acquiring displacement and time data of the electric chassis vehicle at different operating stages under mobile conditions specifically include: During the mobile operation of the electric chassis vehicle, the rotational speed data of the drive motor of the electric chassis vehicle is acquired; When the revolution count data reaches a preset revolution count threshold for any operating stage, a condition node switching signal is generated to end that operating stage. Obtain the time and location information of the electric chassis vehicle at the working condition node switching signal; The time data of the electric chassis vehicle in each operating stage is obtained based on the difference in the time information of the switching signals of two adjacent working condition nodes. The displacement data of the electric chassis vehicle in each operating stage is obtained based on the difference in position information of the switching signals of two adjacent working condition nodes.

3. The method for monitoring the mechanical condition of an electric chassis vehicle according to claim 2, characterized in that, The step of obtaining the time information and location information of the electric chassis vehicle at the working condition node switching signal specifically includes: Obtain the time information of the electric chassis vehicle at the working condition node switching signal; When the electric chassis vehicle is at the working condition node switching signal, the position image of the electric chassis vehicle relative to the marker array on the movement path is acquired, wherein the marker array includes multiple marker units composed of alternating black and white blocks; Based on the location image, the location information of the electric chassis vehicle at the working condition node switching signal is determined.

4. The method for monitoring the mechanical condition of an electric chassis vehicle according to claim 3, characterized in that, The step of determining the position information of the electric chassis vehicle at the working condition node switching signal based on the position image specifically includes: The location image is binarized to generate a binary image; Based on the binary image, determine the number of identification units at the working condition node switching signal of the electric chassis vehicle; Based on the length value of the identifier unit in the identifier array and the number of identifier units, the position information of the electric chassis vehicle at the working condition node switching signal is obtained.

5. The method for monitoring the mechanical condition of an electric chassis vehicle according to claim 4, characterized in that, The step of binarizing the location image to generate a binary image specifically includes: Edge image processing is performed on the location image to obtain the pixel grayscale value of each pixel in the location image; The image regions in the location image whose pixel grayscale values ​​are less than or equal to a first preset threshold are processed into first binary logical values, and the image regions in the location image whose pixel grayscale values ​​are greater than or equal to a second preset threshold are processed into second binary logical values, so as to generate the binary image.

6. The method for monitoring the mechanical condition of an electric chassis vehicle according to claim 4, characterized in that, The step of determining the number of identification units at the working condition node switching signal of the electric chassis vehicle based on the binary image specifically includes: Traverse the binary image to determine the number of transitions in the binary logic values ​​of the binary image; Based on the number of transitions, the number of marker units passed by the electric chassis vehicle is determined.

7. The method for monitoring the mechanical condition of an electric chassis vehicle according to claim 1, characterized in that, The step of determining the mechanical state of the electric chassis vehicle under the mobile condition based on the total side length of the time-velocity curve specifically includes: Obtain the total side length of the time-velocity curve; If the total side length is greater than the first preset side length threshold, the electric chassis vehicle is determined to be stuck in the moving condition; If the total side length is less than or equal to the first preset side length threshold and greater than or equal to the second preset side length threshold, the electric chassis vehicle is determined to be in a normal state under the mobile working condition. If the total side length is less than the second preset side length threshold, the electric chassis vehicle is determined to be in a loose state under the moving condition.

8. A mechanical condition monitoring device for an electric chassis vehicle, characterized in that, include: The acquisition module is used to acquire displacement data and time data of the electric chassis vehicle at different operating stages under mobile conditions, wherein the mobile conditions are rocking in or rocking out. A generation module is used to generate the operating speed of the electric chassis vehicle in each operating stage based on the displacement data and the time data. A construction module is used to construct a time-speed curve of the electric chassis vehicle under the mobile working condition based on the time data and the operating speed of each operating stage. The determination module is used to determine the mechanical state of the electric chassis vehicle under the moving condition based on the total side length of the time-speed curve, wherein the mechanical state includes at least one of the following: stuck state, loose state, and normal state.

9. A mechanical condition monitoring system for an electric chassis vehicle, characterized in that, include: The electric chassis vehicle mechanical condition monitoring device as described in claim 8; Electric chassis vehicle; An array of markers is disposed between the outer surface of the bottom of the electric chassis and the movement rail of the electric chassis. A masking component is disposed on the outer bottom of the electric chassis vehicle and is inclined relative to the marking array. The masking component moves synchronously with the electric chassis vehicle, so that the marking array and the masking component form a visual window reflecting the real-time position of the electric chassis vehicle during the relative movement. An image acquisition device is positioned directly above the space formed by the marker array and the masking component, and is used to acquire location images at the nodes during the operation phase. A binarization preprocessor is used to binarize the pixel grayscale values ​​of a location image to obtain a binary image. Binary matrix converter, used to obtain the binary matrix of a binary image; The marker unit quantity calculator is used to determine the number of marker units passed by the electric chassis vehicle based on a binary matrix, and to determine the displacement data of the electric chassis vehicle in each operating stage based on the number of marker units and the marker unit length value. The working condition node time converter is used to obtain the time information of the working condition node switching signal at the working condition node signal, and determine the time data of the electric chassis vehicle in each operating stage based on the time information of the switching signals of two adjacent working condition nodes. A speed converter is used to obtain the operating speed of an electric chassis vehicle at each stage of operation based on time and displacement data. The time-speed plotter is used to draw time-speed curves of electric chassis vehicles under mobile working conditions based on the operating speed and time data of each operating stage. Time-velocity side length calculator, used to obtain the total side length of a time-velocity curve; The mechanical state determiner is used to determine the mechanical state of an electric chassis vehicle under mobile working conditions based on the total side length.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the electric chassis vehicle mechanical condition monitoring method as described in any one of claims 1 to 7.

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