A gantry quality detection method and system

Abstract

This invention provides a mast quality inspection method and system, relating to the field of mast manufacturing technology. The mast quality inspection method includes: acquiring process data for each key component during the forklift mast production process, wherein the process data includes welding process data and assembly process data; performing anomaly detection on each process data to obtain anomaly degree values; conducting stability analysis under different usage modes based on the anomaly degree values ​​and the corresponding process weights to obtain stability indices; and determining the mast quality conformity based on the stability indices to complete the mast quality inspection. The inspection method and system provided by this invention can effectively improve the efficiency of quality assessment after mast production and ensure the reliability of mast quality conformity inspection results.

Description

Technical Field

[0001] This invention relates to the field of gantry manufacturing technology, and in particular to a method and system for gantry quality inspection. Background Technology

[0002] The core function of a forklift mast is to support and lift goods. Besides its structural design, the welding and assembly quality of its structure directly affects the forklift's load-bearing capacity and stability. The forklift mast consists of two parts: an inner mast and an outer mast, and its lifting function is achieved through a hydraulic system.

[0003] In the current mast production process, the manufactured masts are directly installed into the forklift system. However, because abnormalities that occur during the welding and assembly of the masts are difficult to identify accurately, the reliability of the masts during use is greatly reduced, thereby increasing the safety risks during use. Summary of the Invention

[0004] This invention provides a mast quality inspection method and system to solve the technical problem that in the prior art, masts are directly put into forklift systems for installation and use during the production process. However, due to the difficulty in accurately identifying abnormalities that occur during the welding and assembly of masts, the reliability of masts during use is greatly reduced, thereby increasing the safety risks during use.

[0005] To achieve the above and other related objectives, the present invention provides a mast quality inspection method, comprising: acquiring process data of key components during the production of a forklift mast, wherein the process data includes welding process data and assembly process data; performing anomaly detection on the process data to obtain anomaly degree values; performing stability analysis on different usage modes based on the anomaly degree values ​​and the corresponding process weights to obtain stability indices; and determining the mast quality qualification based on the stability indices to complete the mast quality inspection.

[0006] In one embodiment of the present invention, the welding process data includes the weld width and actual solder amount corresponding to different welding positions; anomaly detection is performed on the data of each process step to obtain the abnormality degree value of the step, including: finding the corresponding reference solder amount according to the weld width corresponding to different welding positions; comparing the actual solder amount corresponding to different welding positions with the corresponding reference solder amount; when the actual solder amount is less than the corresponding reference solder amount, the welding segment corresponding to the actual solder amount being less than the corresponding reference solder amount is regarded as an abnormal segment, and the difference between the reference solder amount and the actual solder amount is calculated to obtain the solder missing value at each position point in the abnormal segment; according to the segment length of each abnormal segment, the corresponding abnormal scoring factor is retrieved; according to the segment length of each abnormal segment, the abnormal scoring factor, the solder missing value, and the total welding length corresponding to the welding position, the first step abnormality degree value corresponding to each welding position is obtained.

[0007] In one embodiment of the present invention, the formula for calculating the abnormality value of the first stage is as follows: ;in, This indicates the degree of abnormality in the first stage. Indicates the starting position point in the abnormal partition segment. To the cutoff point The length of the partition segment, This indicates the actual amount of solder. Indicates the reference solder amount. Indicates each abnormal partition segment The corresponding abnormal scoring factor, This indicates the number of abnormal partitions corresponding to the welding position.

[0008] In one embodiment of the present invention, the assembly stage data includes component fastening data corresponding to different fastening positions and assembly adaptation data corresponding to different moving positions; anomaly detection is performed on the data of each process stage to obtain a stage anomaly degree value, including: obtaining a second stage anomaly degree value corresponding to each fastening position group based on the component fastening data corresponding to different fastening positions and the fastening position group corresponding to the fastening positions; obtaining a third stage anomaly degree value corresponding to each moving position group based on the assembly adaptation data corresponding to different moving positions and the moving position group corresponding to the moving positions.

[0009] In one embodiment of the present invention, the component fastening data includes torque-time curves of the fastened components at different fastening positions during the tightening process, the standardization of the fastening joint of the fastened components, and the first lubrication degree. Based on the component fastening data corresponding to different fastening positions and the fastening position groups corresponding to the fastening positions, a second-stage anomaly value is obtained for each fastening position group. This includes: comparing the similarity between the torque-time curve and the reference torque-time curve corresponding to the corresponding fastening position to obtain a fastening anomaly value; obtaining a fastening anomaly correction value based on the standardization of the fastening joint and the first lubrication degree; fusing the fastening anomaly value and the fastening anomaly correction value to obtain a second-stage anomaly component corresponding to each fastening position; and obtaining a second-stage anomaly value for each fastening position group based on the fastening position group, the second-stage anomaly component corresponding to each fastening position in the fastening position group, and the fastening position weight corresponding to each fastening position.

[0010] In one embodiment of the present invention, the formula for calculating the abnormality value of the second stage is as follows: ;in, This indicates the degree of abnormality in the second stage. Indicates the degree of tightness abnormality. Indicates the standard degree of fastening joints. Indicates the first correction factor. Indicates the first level of lubrication. Indicates the second correction factor. This represents the tightening error correction value corresponding to each tightening position. This represents the weight of each fastening position.

[0011] In one embodiment of the present invention, the assembly adaptation data includes the reaction force and time curve of the active component in the corresponding active stroke at each active position, the second lubrication degree of the active node corresponding to the active component, the clearance degree between components, and the parallelism between components. Based on the assembly adaptation data corresponding to different active positions and the active position group corresponding to the active position, a third-stage anomaly value corresponding to each active position group is obtained, including: comparing the reaction force and time curve with the baseline reaction force and time curve corresponding to the corresponding active position to obtain a first adaptation anomaly value; obtaining an adaptation anomaly correction value based on the second lubrication degree corresponding to the active position; obtaining a second adaptation anomaly value based on the clearance degree and parallelism corresponding to the active position; fusing the adaptation anomaly value, the adaptation anomaly correction value, and the second adaptation anomaly value to obtain a third-stage anomaly component corresponding to each active position; and obtaining a third-stage anomaly value corresponding to each active position group based on the active position group, the third-stage anomaly component corresponding to each active position in the active position group, and the active position weight corresponding to each active position.

[0012] In one embodiment of the present invention, the formula for calculating the abnormality value of the third stage is as follows: ;in, This indicates the degree of abnormality in the third stage. This indicates the first degree of misfit. Indicates the gap degree, Indicates the first abnormal increment. Indicates parallelism. This indicates the second abnormal increment. This indicates the degree of anomaly in the second adaptation. Indicates the second degree of lubrication. Indicates the correction factor. This represents the adaptation anomaly correction value corresponding to each activity location. This represents the activity position weight corresponding to each activity position.

[0013] In one embodiment of the present invention, stability analysis is performed on different usage modes based on the abnormality level value of each link and the corresponding link weight to obtain a stability index. This includes: retrieving a corresponding link reference table for each usage mode; outputting the key links corresponding to each usage mode based on the link reference table, where the key links include welding positions, fastening position groups, and moving position groups; calculating the stability index based on the stability benchmark index, the abnormality level value of each key link position, and the sub-weight corresponding to each key link position. The abnormality level value includes a first abnormality level value corresponding to each welding position, a second abnormality level value corresponding to each fastening position group, and a third abnormality level value corresponding to each moving position group. The sub-weights include a first sub-weight corresponding to the first abnormality level value, a second sub-weight corresponding to the second abnormality level value, and a third sub-weight corresponding to the third abnormality level value. The formula for calculating the stability index is: ;in, Indicates stability index, This is represented as a stability benchmark index. This indicates the degree of abnormality in the first stage corresponding to each welding position. This indicates the first weight. This indicates the degree of abnormality in the second stage corresponding to each fastening position. This indicates the second weighting. This indicates the degree of abnormality in the third stage corresponding to each activity location. This indicates the third weight.

[0014] To achieve the above and other related objectives, the present invention also provides a mast quality inspection system, comprising: an acquisition unit for acquiring process data of key components during the production of a forklift mast, wherein the process data includes welding process data and assembly process data; an anomaly detection unit for performing anomaly detection on the process data to obtain an anomaly degree value; a stability analysis unit for performing stability analysis on different usage modes based on the anomaly degree value and the corresponding process weight to obtain a stability index; and a result output unit for determining the mast quality qualification based on the stability index, thereby completing the mast quality inspection.

[0015] The beneficial effects of this invention are as follows: The mast quality inspection method and system proposed in this invention can achieve quantitative analysis of anomalies in each process step by acquiring welding data and assembly data during forklift production. Furthermore, the quantitative abnormality values ​​can be used to analyze the stability of the mast after welding and assembly, thereby determining whether the mast stability is qualified. This improves the efficiency of quality assessment after mast production and ensures the reliability of mast quality qualification test results. Attached Figure Description

[0016] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0017] In the attached diagram:

[0018] Figure 1 This is a flowchart illustrating the gantry quality inspection method provided in an embodiment of the present invention.

[0019] Figure 2 The diagram shown is a structural block diagram of a gantry quality inspection system provided in an embodiment of the present invention.

[0020] Figure 3 The diagram shown is a structural schematic of an electronic device according to an embodiment of the present invention.

[0021] The attached figures are labeled as follows:

[0022] Electronic device 1; gantry quality inspection system 11; memory 12; processor 13; acquisition unit 111; anomaly detection unit 112; stability analysis unit 113; result output unit 114. Detailed Implementation

[0023] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0024] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. The drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0025] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.

[0026] This invention provides a mast quality inspection method. By acquiring welding and assembly data during forklift production, it is possible to quantitatively analyze the anomalies corresponding to each process step. Furthermore, the quantified abnormality values ​​are used to analyze the stability of the mast after welding and assembly, thereby determining whether the mast's stability is up to standard. This improves the efficiency of quality assessment after mast production and ensures the reliability of mast quality qualification test results.

[0027] Figure 1 A flowchart of a gantry quality inspection method according to an exemplary embodiment of this application is shown, applied to a gantry quality inspection system, including steps S10-S40. The following will be combined with... Figure 1 The technical solution of this application will be described in detail below.

[0028] First, execute step S10 to obtain process data for each key component in the forklift mast production process. The process data includes welding process data and assembly process data.

[0029] During the production of forklift masts, data from key components, including welding and assembly processes, can be sent to the mast quality inspection system. Alternatively, the mast quality inspection system can proactively acquire process data, including welding and assembly data, to analyze mast stability and determine whether the mast is up to standard. This improves the efficiency of mast quality inspection and ensures the reliability of the mast during its use.

[0030] Next, step S20 is executed to detect anomalies in the data of each process step and obtain the anomaly level value of each step.

[0031] After acquiring process data, including welding and assembly data, the gantry quality inspection system will also perform anomaly detection on the corresponding process based on the process data for each process, thereby determining the degree of anomaly for each process. This enables reliability combination analysis for different usage modes, ultimately determining whether the gantry quality is up to standard.

[0032] Specifically, in the process of calculating the degree of abnormality, the degree of abnormality of the first stage corresponding to different welding positions can be calculated by using welding stage data; the degree of abnormality of the second stage corresponding to different fastening position groups and the degree of abnormality of the third stage corresponding to different moving position groups can also be calculated by using assembly stage data.

[0033] Preferably, the welding process data may further include the weld width and actual solder amount corresponding to different welding positions. In determining the weld width and actual solder amount corresponding to different welding positions, the actual solder amount for each position under fixed welding parameters can be determined based on welding parameters during the welding process (such as welding speed). Alternatively, the weld width corresponding to different welding positions can be determined by taking images of the weld at the welding position using an imaging device before welding and identifying the weld width in the captured images.

[0034] In step S20, when the process step data is welding process data, anomaly detection is performed on the data of each process step to obtain the abnormality level value of the step, which may further include:

[0035] Find the corresponding reference amount of solder based on the weld width corresponding to different welding positions;

[0036] Compare the actual solder amount corresponding to different welding positions with the corresponding reference solder amount;

[0037] When the actual solder amount is less than the corresponding reference solder amount, the welding section corresponding to the actual solder amount being less than the corresponding reference solder amount is regarded as an abnormal section, and the difference between the reference solder amount and the actual solder amount is calculated to obtain the solder missing value at each position point within the abnormal section.

[0038] Based on the segment length of each abnormal segment, retrieve the corresponding abnormal scoring factor;

[0039] Based on the segment length, anomaly scoring factor, solder missing value, and total welding length corresponding to each welding position, the first-stage anomaly level value corresponding to each welding position is obtained.

[0040] During anomaly detection, a correspondence table between weld width and reference solder quantity can be used, along with the weld width corresponding to different welding positions in the welding process data. The reference solder quantity for each weld width can be found in the table. Then, the reference solder quantity for each weld width is compared with the actual solder quantity at the corresponding weld position. If the actual solder quantity is greater than the reference quantity, it indicates that the current actual solder quantity meets the stability requirements of welding quality and does not need to be recorded. However, if the actual solder quantity is less than the reference quantity, it indicates that the insufficient actual solder quantity will affect the welding quality stability of the corresponding section. Therefore, the welding section consisting of adjacent positions where the actual solder quantity is less than the reference quantity can be marked as an anomaly section. Then, based on the difference between the actual solder quantity and the reference solder quantity for each position in the anomaly section, the missing solder value for each position within the anomaly section is calculated. Subsequently, the segment length of each abnormal segment corresponding to each welding position is calculated to establish a correspondence table between the segment length and the abnormal scoring factor, and to find the abnormal scoring factor corresponding to each segment length. Finally, using the obtained segment length, abnormal scoring factor, solder missing value, and total welding length corresponding to each welding position, the abnormality degree value of the first stage corresponding to each welding position is calculated using the calculation formula of the first stage abnormality degree value.

[0041] Specifically, the formula for calculating the abnormality level of the first stage can be expressed as:

[0042] ;

[0043] in, This indicates the degree of abnormality in the first stage. Indicates the starting position point in the abnormal partition segment. To the cutoff point The length of the partition segment, This indicates the actual amount of solder. Indicates the reference solder amount. Indicates each abnormal partition segment The corresponding abnormal scoring factor, This indicates the number of abnormal partitions corresponding to the welding position.

[0044] In the process of calculating the anomaly level value in the first stage, we can first determine the anomaly segment length based on the anomaly segment. Find the corresponding anomaly scoring factor in the pre-configured table of correspondence between partition length and anomaly scoring factor, and then calculate the actual solder amount at different locations in the corresponding anomaly segment. Compared with the reference solder amount Perform difference calculations to find the actual amount of solder. Less than the reference solder amount The corresponding solder missing value at that time. Then, based on the solder missing value and the corresponding anomaly scoring factor, at the starting position point... To the cutoff point Segment length The process involves integration to obtain the first-stage anomaly component for each abnormal segment at different welding positions. Finally, the summation of these first-stage anomaly components for each abnormal segment yields the degree of anomaly for each welding position. It is worth noting that each welding position can be a critical location affecting the stability of the gantry under different usage modes.

[0045] Preferably, the assembly stage data may further include component fastening data corresponding to different fastening positions and assembly adaptation data corresponding to different moving positions. For component fastening data, some data may be obtained during the component fastening process, such as the fixed position of the lead screw and bolt during fastening; other fastening components and methods may also be included. A portion may be obtained after assembly through image capture and comparative analysis. For assembly adaptation data, some data may be obtained during component assembly or bench testing; another portion may be obtained after assembly through image capture and comparative analysis.

[0046] In step S20, when the process step data is assembly step data, anomaly detection is performed on the data of each process step to obtain the abnormality level value of the step. This may further include:

[0047] Based on the component fastening data corresponding to different fastening positions and the fastening position groups corresponding to the fastening positions, the second-stage abnormality value corresponding to each fastening position group is obtained;

[0048] Based on the assembly adaptation data corresponding to different activity positions and the activity position groups corresponding to the activity positions, the abnormality value of the third stage corresponding to each activity position group is obtained.

[0049] When the process data is assembly data, the abnormality level value can include a second abnormality level value corresponding to each fastening position group and a third abnormality level value corresponding to each moving position group. The second abnormality level value for different fastening position groups can be calculated using the component fastening data and the corresponding fastening position groups for different fastening positions. Similarly, the third abnormality level value for different moving position groups can be calculated using the assembly adaptation data and the corresponding moving position groups for different moving positions. This allows for stability analysis under different usage modes using the first, second, and third abnormality level values, comprehensively assessing the gantry quality and improving the efficiency of post-production quality inspection of the gantry.

[0050] Among them, the fastening data of the accessories may further include the torque and time curves of the fastened accessories during the tightening process corresponding to different fastening positions, the standardization of the fastening joints of the fastened accessories, and the first lubrication.

[0051] When acquiring fastening data for components, the gantry quality inspection system can collect the torque-time relationship sensed by the torque wrench during the tightening process, specifically the torque change before reaching a preset torque value. A torque-time curve is then constructed based on this relationship. Alternatively, the system can use torque-time data collected from other automated fastening equipment. Before tightening, the system can also capture images of the corresponding fastening joints using imaging equipment to obtain real-time images. The threaded areas of the fastening joints in these real-time images are identified and compared with standard thread images to determine the similarity between the current fastening joint thread and the standard fastening joint, serving as the standard for the fastening joint. Furthermore, the system can determine the initial lubrication level of the fastened component by comparing the glossiness of the real-time image with images of fastening joints corresponding to different lubrication levels. The torque-time curves of the fastened components during the tightening process, the standardization of the fastening joints of the fastened components, and the first lubrication level are then uploaded to the gantry quality inspection system. Alternatively, the gantry quality inspection system can actively collect the torque-time curves, the standardization of the fastening joints of the fastened components, and the first lubrication level to calculate the degree of abnormality in the second stage corresponding to different fastening position groups.

[0052] Once the torque-time curve of the fastened component during the tightening process, the standardization of the fastening joint, and the initial lubrication are determined, based on the component tightening data corresponding to different tightening positions and the corresponding tightening position groups, the second-stage abnormality value corresponding to each tightening position group is obtained, which may further include:

[0053] The similarity between the torque and time curve and the reference torque and time curve corresponding to the fastening position is compared to obtain the fastening abnormality value;

[0054] Based on the standard degree of the fastening joint corresponding to the fastening position and the first degree of lubrication, the correction value for fastening abnormality is obtained;

[0055] The tightening anomaly degree value and the tightening anomaly correction value are fused together to obtain the second-stage anomaly component corresponding to each tightening position;

[0056] Based on the fastening position group, the second-stage abnormality component corresponding to each fastening position in the fastening position group, and the fastening position weight corresponding to each fastening position, the abnormality degree value of the second stage corresponding to each fastening position group is obtained.

[0057] In calculating the second-stage anomaly value, the torque-time curve corresponding to each fastening position can first be compared with the reference torque-time curve to determine the fastening similarity value. This similarity value, combined with a preset fastening factor, is then used to determine the fastening anomaly value during the fastening process. It's worth noting that the reference torque-time curve can also be a pre-configured standard fastening joint and a base torque-time curve without lubrication. Then, based on the standard degree of the fastening joint and the first lubrication level corresponding to the fastening position determined by the photograph, a fastening anomaly correction value is calculated. For each fastening position, the obtained fastening anomaly value and the fastening anomaly correction value can be superimposed to determine the second-stage anomaly component corresponding to each fastening position. Finally, based on the fastening position group, multiple corresponding second-stage anomaly components are found. Combined with the pre-set fastening position weights based on experience, the second-stage anomaly value used to evaluate the anomaly at each fastening position is calculated using the formula for calculating the second-stage anomaly value.

[0058] Preferably, the formula for calculating the degree of abnormality in the second stage can be expressed as:

[0059] ;

[0060] in, This indicates the degree of abnormality in the second stage. Indicates the degree of tightness abnormality. Indicates the standard degree of fastening joints. Indicates the first correction factor. Indicates the first level of lubrication. Indicates the second correction factor. This represents the tightening error correction value corresponding to each tightening position. This represents the weight of each fastening position.

[0061] In calculating the degree of abnormality in the second stage, the correction value for tightening abnormalities can be calculated first. Specifically, this is done by utilizing the standard degree of the tightening joint. and the first correction factor To determine the abnormal increase correction value when correcting for fastening abnormalities. Then, by utilizing the first lubrication and the second correction factor To determine the abnormal reduction correction value when correcting for fastening abnormalities. Subsequently, the abnormal increase correction value and the abnormal decrease correction value are superimposed and merged to determine the fastening abnormality correction value corresponding to each fastening position. Furthermore, the first and second correction factors can be pre-set factors based on experience, such as the relationship between the fastening joint standard, the first lubrication level, and the correction amount. Then, the abnormality value of the second stage is corrected using the tightening abnormality correction value to obtain the abnormality component of the second stage corresponding to each tightening position. Finally, this is combined with the tightening position weights corresponding to each tightening position in the pre-set tightening position group. This allows for the calculation of the second-stage anomaly value corresponding to each fastening position group. .

[0062] In addition, the assembly adaptation data may further include the reaction force and time curve of the active component in the corresponding active stroke in each active position, the second lubrication of the active node corresponding to the active component, the clearance between components, and the parallelism between components.

[0063] When acquiring assembly and adaptation data, the gantry quality inspection system can do so after assembly by repeatedly pushing the movable component against the fixed component to collect the parameter relationship of the reaction force over time, constructing a reaction force versus time curve, and uploading it to the gantry quality inspection system. Alternatively, the gantry quality inspection system can actively collect the data. It's worth noting that after assembly, a robotic arm equipped with a pressure sensor can be used to push the movable component back and forth to obtain the reaction force. Alternatively, the movement of the movable component can be tested on a test bench to determine the correlation between the reaction force and time. The fixed component can be the outer gantry, and the movable component can be the inner gantry, or a combination of other fixed and movable components in the gantry system. Furthermore, before assembly, images of the movable component can be captured using imaging equipment, and the captured images can be compared with reference images corresponding to different lubrication levels to find the most similar reference image. The lubrication level corresponding to this reference image is then used as the second lubrication level. After assembly, images of the fit between fixed and moving parts can be captured using imaging equipment. These images are then compared with a reference fit image to determine the differences in clearance and linearity between the two. The clearance difference is used as the clearance degree, and the linearity difference as the parallelism. Finally, the second lubrication degree, clearance degree, and parallelism are uploaded to the gantry quality inspection system, or actively collected by the gantry quality inspection system, to calculate the anomaly degree value of the third stage corresponding to the moving position group.

[0064] Once the reaction force versus time curve of the active component in its corresponding active stroke, the second lubrication degree of the active node corresponding to the active component, the clearance between components, and the parallelism between components are determined, the abnormality value of the third stage corresponding to each active position group is obtained based on the assembly adaptation data corresponding to different active positions and the active position groups corresponding to the active positions. This can further include:

[0065] The similarity between the active reaction force and time curve and the benchmark active reaction force and time curve corresponding to the active position is compared to obtain the first fitting anomaly value.

[0066] Based on the second lubrication degree corresponding to the active position, the adaptation anomaly correction value is obtained;

[0067] The second adaptation anomaly value is obtained based on the gapness and parallelism corresponding to the activity position;

[0068] The anomaly degree value, the anomaly correction value, and the second anomaly degree value are fused together to obtain the third-stage anomaly component corresponding to each activity position;

[0069] Based on the activity location group, the abnormal component of the third stage corresponding to each activity location in the activity location group, and the activity location weight corresponding to each activity location, the abnormality value of the third stage corresponding to each activity location group is obtained.

[0070] When calculating the anomaly degree value of the third stage, the similarity between the active reaction force and time curves corresponding to different active positions and the baseline active reaction force and time curves in the gantry fit mode without lubrication and with standard clearance and straightness can be compared to determine the fit similarity value. This fit similarity value, combined with a preset fit preset factor, is then used to calculate the first fit anomaly degree value. Subsequently, using the second lubrication degree corresponding to the active position, the fit anomaly correction value can be calculated to correct the fit anomaly. Using the clearance and parallelism corresponding to the active position, further incremental corrections can be made to assembly anomalies other than active reaction force anomalies, resulting in the second fit anomaly degree value superimposed on the first fit anomaly degree value. Then, by fusing the fit anomaly degree value, the fit anomaly correction value, and the second fit anomaly degree value, the third stage anomaly component corresponding to each active position can be calculated. Finally, using the active positions in the active position group, the third stage anomaly component corresponding to each active position, and the active position weight corresponding to each active position, the third stage anomaly degree value corresponding to different active position groups can be calculated using the formula for calculating the third stage anomaly degree value.

[0071] Preferably, the formula for calculating the abnormality level value of the third stage can be expressed as:

[0072] ;

[0073] in, This indicates the degree of abnormality in the third stage. This indicates the first degree of misfit. Indicates the gap degree, Indicates the first abnormal increment. Indicates parallelism. This indicates the second abnormal increment. This indicates the degree of anomaly in the second adaptation. Indicates the second degree of lubrication. Indicates the correction factor. This represents the adaptation anomaly correction value corresponding to each activity location. This represents the activity position weight corresponding to each activity position.

[0074] In calculating the degree of abnormality in the third stage, the clearance between components can be used as a reference. and the first abnormal increment The abnormal value of the gap between the parts was calculated. Through parallelism Second abnormal increment It can calculate the parallelism anomaly value between parts. Therefore, the degree of second fit anomaly can be determined based on the gap anomaly and the parallelism anomaly. The second anomaly score is combined with the first anomaly score. This allows us to determine the overall degree of adaptation anomaly. Subsequently, through a second lubrication... and correction factor To determine the corresponding adaptation anomaly correction value Then, the overall adaptation anomaly value is corrected to obtain the third-stage anomaly component corresponding to each activity position. Finally, based on the activity locations corresponding to each activity location group, the abnormal components of the third stage corresponding to each activity location are combined with the corresponding activity location weights. In order to achieve the corresponding abnormality value of the third stage. The calculations are performed. Among them, the first abnormal increment, the second abnormal increment, the correction factor, and the activity position weight corresponding to each activity position are all obtained in advance based on experience.

[0075] Next, step S30 is executed, and stability analysis of different usage modes is performed based on the abnormality level value of the link and the link weight corresponding to the abnormality level value of the link, so as to obtain the stability index.

[0076] After acquiring the anomaly levels at each stage, the gantry quality inspection system can combine the corresponding stage weights with the anomaly levels to perform stability analysis on the gantry under different usage modes. This allows for the determination of stability indicators for each usage mode, enabling rapid assessment of whether the finished gantry product meets quality standards. The gantry usage modes can include forward tilting, backward tilting, and lifting under load, as well as other modes.

[0077] In step S30, stability analysis is performed on different usage modes based on the abnormality level value and the corresponding weight of the abnormality level value to obtain a stability index, which may further include:

[0078] For each usage mode, retrieve the corresponding process reference table;

[0079] Based on the link comparison table, the key links corresponding to the usage mode are output. The key links include welding positions, fastening position groups, and moving position groups.

[0080] The stability index is calculated based on the stability benchmark index, the abnormality value of the key position of the link, and the sub-weight of each key position. The abnormality value of the link includes the first abnormality value corresponding to each welding position, the second abnormality value corresponding to each fastening position group, and the third abnormality value corresponding to each moving position group. The sub-weight includes the first sub-weight corresponding to the first abnormality value, the second sub-weight corresponding to the second abnormality value, and the third sub-weight corresponding to the third abnormality value.

[0081] During stability analysis, a correspondence table between usage modes and process reference tables can be used to locate the process reference table for each usage mode. Then, based on the data information of key process locations recorded in the process reference table for the corresponding usage mode, the abnormality value corresponding to each key process location is retrieved. Combining this with the preset stability benchmark index for each usage mode and the weighted average of each key process location, the stability index can be calculated using the stability index calculation formula. Key process locations can include welding positions, fastening position groups, and moving position groups; other key locations are also possible. The abnormality value includes a first abnormality value corresponding to each welding position, a second abnormality value corresponding to each fastening position group, and a third abnormality value corresponding to each moving position group; other abnormality values ​​are also possible for other key locations.

[0082] The formula for calculating the stability index is:

[0083] ;

[0084] in, Indicates stability index, This is represented as a stability benchmark index. This indicates the degree of abnormality in the first stage corresponding to each welding position. This indicates the first weight. This indicates the degree of abnormality in the second stage corresponding to each fastening position. This indicates the second weighting. This indicates the degree of abnormality in the third stage corresponding to each activity location. This indicates the third weight.

[0085] Next, step S40 is executed to determine the qualification of the gantry quality based on the stability index, so as to complete the gantry quality inspection.

[0086] After determining the stability indicators, the gantry quality inspection system compares these indicators with the threshold values ​​for the corresponding usage modes of the gantry. When the stability indicators for all usage modes are within the threshold range, the gantry is considered to be of acceptable quality. Conversely, if the stability indicators for one or more usage modes exceed the threshold values, the gantry is considered to be of unacceptable quality. This method allows for rapid acceptance testing of gantry quality, improving testing efficiency while ensuring the reliability of the acceptance test results.

[0087] Please see Figure 2 The present invention also provides a mast quality inspection system 11, comprising: an acquisition unit 111 for acquiring process data of key components during the production of a forklift mast, wherein the process data includes welding process data and assembly process data; an anomaly detection unit 112 for performing anomaly detection on the process data to obtain an anomaly degree value; a stability analysis unit 113 for performing stability analysis on different usage modes based on the anomaly degree value and the corresponding process weight to obtain a stability index; and a result output unit 114 for determining the quality qualification of the mast based on the stability index to complete the mast quality inspection.

[0088] It should be noted that the gantry quality inspection system 11 provided in the above embodiments and the gantry quality inspection method provided in the above embodiments belong to the same concept. The specific operation methods of each module and unit have been described in detail in the method embodiments and will not be repeated here. In practical applications, the gantry quality inspection system 11 provided in the above embodiments can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. This is not a limitation here.

[0089] Please see Figure 3 The electronic device 1 may include a memory 12, a processor 13, and a bus, and may also include a computer program stored in the memory 12 and executable on the processor 13, such as a gantry quality inspection program.

[0090] The memory 12 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 12 can be an internal storage unit of the electronic device 1, such as a portable hard drive of the electronic device 1. In other embodiments, the memory 12 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 1. Furthermore, the memory 12 can include both internal and external storage units of the electronic device 1. The memory 12 can be used not only to store application software and various types of data installed on the electronic device 1, such as gantry quality inspection codes, but also to temporarily store data that has been output or will be output.

[0091] In some embodiments, the processor 13 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips. The processor 13 is the control unit of the electronic device 1, connecting various components of the electronic device 1 through various interfaces and lines. It executes programs or modules (such as gantry quality inspection programs) stored in the memory 12, and calls data stored in the memory 12 to perform various functions and process data of the electronic device 1.

[0092] The processor 13 executes the operating system of the electronic device 1 and various installed applications. The processor 13 executes the applications to implement the steps in the above-described gantry quality inspection method.

[0093] For example, the computer program may be divided into one or more modules, which are stored in the memory 12 and executed by the processor 13 to complete this application. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the electronic device 1. For example, the computer program may be divided into units in a gantry quality inspection system.

[0094] The integrated unit implemented as a software functional module described above can be stored in a computer-readable storage medium, which can be non-volatile or volatile. The software functional module, stored in the storage medium, includes several instructions to cause a computer device (which may be a personal computer, a computer device, or a network device, etc.) or a processor to execute some functions of the gantry quality inspection method described in the various embodiments of this application.

[0095] In summary, the mast quality inspection method and system disclosed in this invention, by acquiring welding and assembly data during forklift production, can quantitatively analyze anomalies corresponding to each process step. Furthermore, by utilizing the quantified anomaly severity values, the stability of the mast after welding and assembly can be analyzed to determine whether the mast's stability is up to standard. This improves the efficiency of post-production quality assessment of masts and ensures the reliability of mast quality compliance test results. Therefore, this invention effectively overcomes the various shortcomings of existing technologies and has high industrial application value.

[0096] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A gantry mass detection method, characterized in that, include: Acquire process data for each key component in the production of forklift mast, wherein the process data includes welding process data and assembly process data; Anomaly detection is performed on the data of each process step to obtain the anomaly degree value of each step; Stability analysis of different usage modes is performed based on the abnormality level value of the link and the link weight corresponding to the abnormality level value of the link, and a stability index is obtained. Based on the stability indicators, the qualification of the gantry quality is determined to complete the gantry quality inspection; The welding process data includes the weld width and actual amount of solder corresponding to different welding positions; Anomaly detection is performed on the data of each process step to obtain the anomaly degree value, including: Based on the weld width corresponding to different welding positions, find the corresponding reference amount of solder; Compare the actual amount of solder corresponding to different welding positions with the corresponding reference amount of solder. When the actual solder amount is less than the corresponding reference solder amount, the soldering section corresponding to the actual solder amount being less than the corresponding reference solder amount is regarded as an abnormal section, and the difference between the reference solder amount and the actual solder amount is calculated to obtain the solder missing value at each position point in the abnormal section. Based on the segment length of each abnormal segment, retrieve the corresponding abnormal scoring factor; Based on the segment length, the anomaly scoring factor, the solder missing value, and the total welding length corresponding to the welding position for each of the abnormal segments, the first stage anomaly degree value corresponding to each welding position is obtained; The assembly process data includes component fastening data corresponding to different fastening positions and assembly adaptation data corresponding to different moving positions. Anomaly detection is performed on the data of each process step to obtain the anomaly degree value, including: Based on the fastening data of the accessories corresponding to different fastening positions and the fastening position groups corresponding to the fastening positions, the second link abnormality value corresponding to each fastening position group is obtained; Based on the assembly adaptation data corresponding to different activity positions and the activity position groups corresponding to the activity positions, the abnormality value of the third stage corresponding to each activity position group is obtained.

2. The gantry mass detection method of claim 1, wherein, The formula for calculating the abnormality level of the first stage is: ； in, This indicates the degree of abnormality in the first stage. Indicates the starting position point in the abnormal partition segment. To the cutoff point The length of the partition segment, This indicates the actual amount of solder. Indicates the reference solder amount. Indicates each abnormal partition segment The corresponding abnormal scoring factor, This indicates the number of abnormal partitions corresponding to the welding position.

3. The gantry mass detection method of claim 1, wherein, The component fastening data includes the torque and time curves of the fastened components at different fastening positions during the tightening process, the standardization of the fastening joints of the fastened components, and the first degree of lubrication. Based on the fastening data of the components corresponding to different fastening positions and the fastening position groups corresponding to the fastening positions, a second-stage abnormality value is obtained for each fastening position group, including: The similarity between the torque and time curve and the reference torque and time curve corresponding to the fastening position is compared to obtain the fastening anomaly value; Based on the standard degree of the fastening joint corresponding to the fastening position and the first lubrication degree, the fastening abnormality correction value is obtained; The fastening anomaly degree value and the fastening anomaly correction value are fused and calculated to obtain the second-stage anomaly component corresponding to each fastening position; Based on the fastening position group, the second link abnormality component corresponding to each fastening position in the fastening position group, and the fastening position weight corresponding to each fastening position, the second link abnormality value corresponding to each fastening position group is obtained.

4. The gantry mass detection method of claim 3, wherein, The formula for calculating the degree of abnormality in the second stage is: ； in, This indicates the degree of abnormality in the second stage. Indicates the degree of tightness abnormality. Indicates the standard degree of fastening joints. Indicates the first correction factor. Indicates the first level of lubrication. Indicates the second correction factor. This represents the tightening error correction value corresponding to each tightening position. This represents the weight of each fastening position.

5. The gantry mass detection method of claim 1, wherein, The assembly adaptation data includes the reaction force and time curve of the active component in the corresponding active stroke at each active position, the second lubrication degree of the active node corresponding to the active component, the clearance between components, and the parallelism between components; Based on the assembly adaptation data corresponding to different activity positions and the activity position groups corresponding to those activity positions, a third-stage anomaly degree value is obtained for each activity position group, including: The similarity curve of the active reaction force and time is compared with the benchmark active reaction force and time curve corresponding to the active position to obtain the first adaptation anomaly value. Based on the second lubrication degree corresponding to the active position, the adaptation anomaly correction value is obtained; The second adaptation anomaly value is obtained based on the gap degree and parallelism corresponding to the activity position; The adaptation anomaly degree value, the adaptation anomaly correction value, and the second adaptation anomaly degree value are fused together to obtain the third-stage anomaly component corresponding to each activity position; Based on the activity location group, the abnormal component of the third stage corresponding to each activity location in the activity location group, and the activity location weight corresponding to each activity location, the abnormality value of the third stage corresponding to each activity location group is obtained.

6. The gantry mass detection method of claim 1, wherein, The formula for calculating the abnormality level of the third stage is as follows: ； in, This indicates the degree of abnormality in the third stage. This indicates the first degree of misfit. Indicates the gap degree, Indicates the first abnormal increment. Indicates parallelism. This indicates the second abnormal increment. This indicates the degree of anomaly in the second adaptation. Indicates the second degree of lubrication. Indicates the correction factor. This represents the adaptation anomaly correction value corresponding to each activity location. This represents the activity position weight corresponding to each activity position.

7. The gantry mass detection method of claim 1, wherein, Stability analysis is performed on different usage modes based on the abnormality level value of the aforementioned link and the link weight corresponding to the abnormality level value, resulting in stability indices, including: Based on each usage mode, retrieve the corresponding process reference table; Based on the link lookup table, the key links corresponding to the usage mode are output. The key links include welding positions, fastening position groups, and moving position groups. The stability index is calculated based on the stability benchmark index, the abnormality value of the key position of the link, and the weight of each key position of the link. The abnormality value of the link includes a first abnormality value corresponding to each welding position, a second abnormality value corresponding to each fastening position group, and a third abnormality value corresponding to each moving position group. The weights include a first weight corresponding to the first abnormality value, a second weight corresponding to the second abnormality value, and a third weight corresponding to the third abnormality value. The formula for calculating the stability index is: ； in, Indicates stability index, This is represented as a stability benchmark index. This indicates the degree of abnormality in the first stage corresponding to each welding position. This indicates the first weight. This indicates the degree of abnormality in the second stage corresponding to each fastening position. This indicates the second weighting. This indicates the degree of abnormality in the third stage corresponding to each activity location. This indicates the third weight.

8. A gantry quality inspection system applying the gantry quality inspection method according to any one of claims 1-7, characterized in that, include: The acquisition unit is used to acquire process data of key components in the production process of forklift mast, wherein the process data includes welding process data and assembly process data; An anomaly detection unit is used to perform anomaly detection on the data of each process step to obtain the anomaly degree value of the step. A stability analysis unit is used to perform stability analysis on different usage modes based on the abnormality level value of the link and the link weight corresponding to the abnormality level value, and to obtain a stability index; and The result output unit is used to determine the qualification of the gantry quality based on the stability index, so as to complete the gantry quality inspection.

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