Real-time monitoring and fault diagnosis method and system for trailer production line

Abstract

The invention discloses a real-time monitoring and fault diagnosis method and system for a trailer production line, and relates to the technical field of production line monitoring. The real-time monitoring and fault diagnosis method comprises a production line diagnosis method and a workpiece diagnosis method. The workpiece diagnosis method comprises the steps of real-time monitoring and data acquisition, specifically, workpieces in a workpiece set are detected in real time through detection equipment, real-time data of the workpieces are acquired, and the workpiece set comprises initial workpieces and combined workpieces. The virtual model of the combined workpiece is obtained according to the virtual model of the initial workpiece and the structure change data, the diagnosis data of the initial workpiece is reflected on the virtual model of the combined workpiece, and the simulation fault diagnosis of the combined workpiece is realized through global simulation analysis, namely, the early warning of the fault is realized before the fault occurs, so that the fault diagnosis efficiency is improved. And the situation that the production efficiency of a trailer production line is affected by faults occurring after combination is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of production line monitoring, and in particular to a real-time monitoring and fault diagnosis method and system for a trailer production line. Background Art

[0002] As an important means of transportation, trailers have increasingly higher production efficiency and quality requirements. However, the equipment on the trailer production line is complex and diverse, the production process is cumbersome, and various faults and problems are prone to occur. Therefore, it is necessary to monitor the trailers in real time on the trailer production line to detect faults and ensure production efficiency and quality.

[0003] For example, the patent publication number "CN110146316A" is named "Fault diagnosis method and system for functional cabinets in automobile production lines". The fault diagnosis system of this invention detects the real-time relevant parameters of the functional cabinets when the production line is running in real time through the acquisition unit, and compares them with the preset warning values. When the real-time relevant parameters exceed the warning values, the specific problems of the functional cabinets are judged according to the empirical data recorded in the storage unit, and the display unit is used to push them so that the operator can quickly repair them without manual troubleshooting, which is conducive to improving the efficiency of automobile welding.

[0004] The above method uses the method of real-time related parameters exceeding the warning value to achieve early warning for subsequent maintenance. However, for the trailer structure on the trailer production line, each workpiece in the trailer structure is detected, but the workpieces are connected to each other, and then there will be some problems that will only occur when the workpieces are combined with each other or after the combination, that is, there is no early warning. For this reason, a real-time monitoring and fault diagnosis method and system for trailer production lines are invented. Summary of the invention

[0005] The object of the present invention is to provide a real-time monitoring and fault diagnosis method and system for a trailer production line to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above-mentioned object, the present invention provides the following technical solutions: the real-time monitoring and fault diagnosis method includes a production line diagnosis method and a workpiece diagnosis method; The workpiece diagnosis method comprises: Real-time monitoring and data acquisition: The workpieces in the workpiece set are inspected in real time by the inspection equipment to obtain the real-time data of the workpieces. The workpiece set includes the initial workpieces and the combined workpieces. The combined workpieces are regarded as a combination of several initial workpieces. The combination of the combined workpieces is obtained, and the structural data of the initial workpieces is obtained; Initial workpiece virtual model: a virtual model of the initial workpiece is established based on the real-time data of the initial workpiece; Preliminary fault diagnosis: perform fault diagnosis on the real-time data of the initial workpiece, obtain the diagnostic data of the initial workpiece, and map the diagnostic data of the initial workpiece to the virtual model of the initial workpiece; Establish and apply the artifact association model: Establish the artifact association model, obtain the association degree between each initial artifact in the combined artifact according to the artifact association model, and obtain the structural change data based on the association degree and the combination of the combined artifacts; Combined workpiece virtual model: The virtual model of the combined workpiece is obtained by simulating the virtual model of the initial workpiece and the structural change data; Virtual model analysis and diagnosis: based on the virtual model of the combined workpiece, the diagnostic data of the initial workpiece and the degree of association, the diagnostic data of the combined workpiece is obtained, the diagnostic data of the initial workpiece is reflected on the virtual model of the combined workpiece, and the virtual model of the combined workpiece is globally simulated and analyzed to simulate the impact of the diagnostic data on the virtual model of the combined workpiece, and obtain the simulated total diagnostic data; Early warning: Analyze the simulated total diagnostic data to obtain simulated fault data, and issue early warning based on the simulated fault data; Calibration: Perform fault diagnosis on the real-time data of the combined workpiece, compare the real-time data of the combined workpiece, the fault diagnosis structure of the combined workpiece and the simulated total diagnosis data of the corresponding virtual model of the combined workpiece, and obtain comparison data for modifying parameters in the virtual model analysis and diagnosis.

[0007] Furthermore, the production line diagnosis method includes: Data acquisition: Obtain historical production data of equipment in the trailer production line; Real-time monitoring: Real-time monitoring of the equipment in the trailer production line and the trailer structure to obtain real-time data of the equipment and structure; Equipment division in the production line: The equipment in the production line is divided into individual real-time data and total real-time data according to the individual and total attributes of the equipment in the production line; Establish and apply production line association model: Establish production line association model, which establishes the degree of association between production line equipment based on historical production data; Establish and apply prediction models: Establish prediction models, use prediction models to predict real-time data of equipment, and obtain equipment prediction data; Apply continuous data: Use time series analysis technology and combine the degree of association to deeply mine the continuity of sub-real-time data and total real-time data, identify trends in the production process and continuity between production lines, and obtain continuous data between sub-real-time data and total real-time data; Establish and apply thresholds: Establish corresponding equipment thresholds based on historical production data, determine whether continuous data and equipment prediction data will exceed the corresponding thresholds, and issue an early warning if the thresholds are exceeded.

[0008] Furthermore, the structural change data includes physical connection, mechanical properties and vibration connection, the physical connection includes the connection method between initial workpieces in the combined workpiece, the mechanical properties include stress distribution and stiffness changes, and the vibration connection includes changes in resonance frequency and amplitude.

[0009] Furthermore, the method for obtaining the degree of association between equipment on the production line includes: analyzing the historical production data of the equipment in the trailer production line, determining whether there is an association between the equipment, establishing the association between the equipment, and establishing a production line association model for reflecting the interaction and dependency between the equipment. Through the production line association model, the degree of mutual influence between the equipment is analyzed, and the degree of mutual influence is expressed by quantitative indicators.

[0010] Furthermore, the method for obtaining the degree of association between each artifact in the trailer structure includes: analyzing the initial artifacts in the combined structure, obtaining the connection method between each initial artifact in the combined artifact, using the structural data and real-time operation data of the artifacts to establish an artifact association model that can reflect the physical connection, functional dependency and interaction between the artifacts, and analyzing the mutual influence and association degree between the artifacts through the artifact association model. The mutual influence and association degree between the artifacts are expressed by quantitative indicators.

[0011] Furthermore, based on the initial workpieces in the workpiece set, they are divided into long-span workpieces and non-long-span workpieces according to the length data in the structural data. The fault diagnosis method for the workpiece data of the long-span workpiece includes segmented monitoring, and the segmented monitoring includes dividing the long-span workpiece into several shorter sections, performing vibration monitoring and data collection on each section, and obtaining segmented data and position data of each section.

[0012] Furthermore, the fault diagnosis method of the long-span workpiece includes: The segmented data is established based on the position data and corresponds to the position on the long-span workpiece. After the position is matched, the detection point position of the long-span workpiece is calibrated, and the segmented data is time-aligned to obtain the overall data; Map the overall data into a virtual model, and personnel conduct auxiliary analysis; Perform signal processing on the overall data, and process the processed overall data to obtain characteristic information of the fault; The fault characteristic information is pattern recognized to determine the fault type. The location data and fault characteristics are combined to determine the specific location of the corresponding fault using a positioning algorithm.

[0013] A real-time monitoring and fault diagnosis system for a trailer production line adopts the above-mentioned real-time monitoring and fault diagnosis method for a trailer production line.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The real-time monitoring and fault diagnosis method and system of the trailer production line, through the establishment of virtual models, preliminary fault diagnosis and correlation models, first performs fault analysis on the initial workpiece before combining the workpieces, then establishes a virtual model of the initial workpiece, obtains the virtual model of the combined workpiece based on the virtual model of the initial workpiece and structural change data, reflects the diagnostic data of the initial workpiece on the virtual model of the combined workpiece and realizes simulated fault diagnosis of the combined workpiece through global simulation analysis, that is, realizes early warning of faults before they occur, and reduces the situation where the production efficiency of the trailer production line will be affected by faults occurring after the combination.

[0015] At the same time, through real-time monitoring and data acquisition, the equipment and workpieces on the trailer production line can be monitored comprehensively and in real time to ensure the stability and reliability of the production process. The real-time data of the initial workpiece can be used to simulate the subsequent combined workpieces, simulate the impact of diagnostic data on the virtual model of the combined workpiece, and discover potential fault points in advance. The combination of production line diagnostic methods and workpiece diagnostic methods makes fault diagnosis more comprehensive and accurate, and can promptly discover faults in production.

[0016] By monitoring long-span workpieces in segments, segmenting the long-span workpieces, and then time-aligning the segmented data, this method can more accurately obtain the vibration data and operating status of the workpiece, improve the accuracy and efficiency of fault diagnosis, and combine the virtual model of the long-span workpiece with personnel-assisted analysis to locate the fault point more quickly. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a schematic diagram of a workpiece diagnosis method of the present invention; Figure 2 is a flow chart of the workpiece diagnosis method of the present invention; Figure 3 The flowchart of the production line diagnosis method of the present invention is shown in FIG. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] like Figure 1 - Figure 3As shown, the present invention provides a technical solution: the real-time monitoring and fault diagnosis method includes a production line diagnosis method and a workpiece diagnosis method; Workpiece diagnostic methods include: Real-time monitoring and data acquisition: The workpieces in the workpiece set are inspected in real time by the inspection equipment to obtain the real-time data of the workpieces. The workpiece set includes the initial workpieces and the combined workpieces. The combined workpieces are regarded as a combination of several initial workpieces. The combination of the combined workpieces is obtained, and the structural data of the initial workpieces is obtained; Initial workpiece virtual model: a virtual model of the initial workpiece is established based on the real-time data of the initial workpiece; Preliminary fault diagnosis: perform fault diagnosis on the real-time data of the initial workpiece, obtain the diagnostic data of the initial workpiece, and map the diagnostic data of the initial workpiece to the virtual model of the initial workpiece; Establish and apply the artifact association model: Establish the artifact association model, obtain the association degree between each initial artifact in the combined artifact according to the artifact association model, and obtain the structural change data based on the association degree and the combination of the combined artifacts; Combined workpiece virtual model: The virtual model of the combined workpiece is obtained by simulating the virtual model of the initial workpiece and the structural change data; Virtual model analysis and diagnosis: based on the virtual model of the combined workpiece, the diagnostic data of the initial workpiece and the degree of association, the diagnostic data of the combined workpiece is obtained, the diagnostic data of the initial workpiece is reflected on the virtual model of the combined workpiece, and the virtual model of the combined workpiece is globally simulated and analyzed to simulate the impact of the diagnostic data on the virtual model of the combined workpiece, and obtain the simulated total diagnostic data; Early warning: Analyze the simulated total diagnostic data to obtain simulated fault data, and issue early warning based on the simulated fault data; Calibration: Perform fault diagnosis on the real-time data of the combined workpiece, compare the real-time data of the combined workpiece, the fault diagnosis structure of the combined workpiece and the simulated total diagnosis data of the corresponding virtual model of the combined workpiece, and obtain comparison data for modifying parameters in the virtual model analysis and diagnosis.

[0020] Production line diagnostic methods include: Data acquisition: Obtain historical production data of equipment in the trailer production line; Real-time monitoring: Real-time monitoring of the equipment in the trailer production line and the trailer structure to obtain real-time data of the equipment and structure; Equipment division in the production line: The equipment in the production line is divided into individual real-time data and total real-time data according to the individual and total attributes of the equipment in the production line; Establish and apply the production line association model: Establish a production line association model, which establishes the degree of association between equipment on the production line based on historical production data; Establish and apply prediction models: Establish prediction models, use prediction models to predict real-time data of equipment, and obtain equipment prediction data; Apply continuous data: Use time series analysis technology and combine the degree of association to deeply mine the continuity of sub-real-time data and total real-time data, identify trends in the production process and continuity between production lines, and obtain continuous data between sub-real-time data and total real-time data; Establish and apply thresholds: Establish corresponding equipment thresholds based on historical production data, determine whether continuous data and equipment prediction data will exceed the corresponding thresholds, and issue an early warning if the thresholds are exceeded.

[0021] The structural change data includes physical connection, mechanical properties and vibration connection. The physical connection includes the connection method between the initial workpieces in the combined workpiece, the mechanical properties include stress distribution and stiffness changes, and the vibration connection includes the changes in resonance frequency and amplitude.

[0022] The method for obtaining the degree of association between equipment on the production line includes: analyzing the historical production data of the equipment in the trailer production line, determining whether there is an association between the equipment, establishing the association between the equipment, and establishing a production line association model for reflecting the interaction and dependency between the equipment. Through the production line association model, the degree of mutual influence between the equipment is analyzed, and the degree of mutual influence is expressed by quantitative indicators.

[0023] The method for obtaining the degree of association between each artifact in the trailer structure includes: analyzing the initial artifacts in the combined structure, obtaining the connection mode between each initial artifact in the combined artifact, using the structural data and real-time operation data of the artifacts to establish an artifact association model that can reflect the physical connection, functional dependence and interaction between the artifacts, and analyzing the mutual influence and association degree between the artifacts through the artifact association model. The mutual influence and association degree between the artifacts are expressed by quantitative indicators.

[0024] Based on the initial workpieces in the workpiece set, they are divided into long-span workpieces and non-long-span workpieces according to the length data in the structural data. The fault diagnosis method for the workpiece data of the long-span workpiece includes segmented monitoring. The segmented monitoring includes dividing the long-span workpiece into several shorter sections, performing vibration monitoring and data collection on each section, and obtaining segmented data and position data of each section.

[0025] Fault diagnosis methods for long-span workpieces include: The segmented data is established based on the position data and corresponds to the position on the long-span workpiece. After the position is matched, the detection point position of the long-span workpiece is calibrated, and the segmented data is time-aligned to obtain the overall data; Map the overall data into a virtual model, and personnel conduct auxiliary analysis; Perform signal processing on the overall data, and process the processed overall data to obtain characteristic information of the fault; The fault characteristic information is pattern recognized to determine the fault type. The location data and fault characteristics are combined to determine the specific location of the corresponding fault using a positioning algorithm.

[0026] A real-time monitoring and fault diagnosis system for a trailer production line adopts the above-mentioned real-time monitoring and fault diagnosis method for a trailer production line.

[0027] The present application performs real-time detection of the equipment in the production line, performs real-time detection of the trailer structure on the production line, predicts the operating status of the equipment in the production line, and then detects the equipment in the production line and performs predictive diagnosis of faults, performs fault diagnosis on the trailer structure on the production line, performs diagnostic analysis on the workpiece, and obtains the fault condition of the workpiece. The real-time data of the initial workpiece includes real-time size detection of the initial workpiece and detection of the initial workpiece by a detection device, so as to facilitate subsequent fault diagnosis.

[0028] At the same time, real-time data of the combined workpiece is obtained. Since the combined workpiece has been actually manufactured, the data difference between the combined workpiece and the virtual model of the combined workpiece is analyzed. The data difference includes size difference and the difference between actual diagnostic data and simulated total diagnostic data, etc., which can optimize various parameters in the virtual model analysis and diagnosis.

[0029] Among them, continuity refers to whether the production is continuous, the threshold value of continuous data refers to whether the data of the production line can be continuously produced according to the continuous data, the combination situation in the combined workpiece is known data, the combination situation refers to the mutual connection of each initial structure, etc., the combination situation of the combined workpiece includes obtaining the initial workpiece data of each initial workpiece in the combined workpiece, and obtaining the way in which each initial workpiece is connected to each other. The overall structure of the trailer is regarded as a combination of several combined workpieces. In practical applications, the mutual connection requirements in the overall structure of the trailer are not high, and the allowable error range is large, so it is not described in this application. The sub-total attributes of the equipment in the production line refer to whether the equipment is installed on a sub-line or on the main production line. The operating status and value of the equipment in the production line are detected, and whether the operating status of the equipment in the production line is normal to ensure that the equipment in the production line can operate normally and judge, the continuous data of the sub-line and the main production line during production, wherein the continuous data includes the workpiece feeding speed on the sub-line, the combination time of the workpiece on the sub-line, the moving speed of the workpiece on the main production line, the combination time of the workpiece on the main production line, and the time coordination between the sub-line and the main production line, and the time coordination includes the production continuity between the sub-line and the main production line.

[0030] On the trailer production line, there are not only devices for detecting the equipment in the production line, but also several detection devices for detecting workpieces. Workpieces refer to the various structural parts of the trailer, and are uniformly represented by workpieces here. The initial workpiece does not necessarily have only a single structure inside, but only refers to the workpiece when the production line has not yet been installed with other workpieces. On the trailer production line, the initial workpieces are combined with each other to obtain combined workpieces, and the combined workpieces are connected to obtain trailers. For fault diagnosis and analysis of the initial workpiece, since the initial workpiece has no correlation with other initial workpieces at this time, the workpiece can be directly detected and fault diagnosis and analysis can be performed, and the analysis result of the initial workpiece is more reliable at this time.

[0031] The structural data of the workpiece has been recorded in the database. A virtual workpiece is simulated through the structural data of the workpiece. The real-time data of the long-span workpiece and the long-span combined workpiece are input into the corresponding virtual workpiece. The real-time data is used to simulate the reaction of the real-time data in the virtual workpiece in the computer to obtain virtual simulation data. Personnel can watch it through the display screen and perform fault diagnosis methods with the assistance of personnel. When the initial workpiece with a long span is inspected, it is inconvenient to perform diagnosis and analysis directly through real-time data due to its long span. For example, long-span bearings, suspension systems, etc. may be more susceptible to stress concentration and fatigue damage. In addition, due to the long span, the long-span workpiece is not easy to detect in real time due to its long span. At the same time, the span problem makes the analysis of the real-time data inconvenient. There may be complex correlations between different parts of the long-span workpiece. Therefore, a fault diagnosis method for long-span workpieces is adopted.

[0032] Divide the long-span workpiece into several shorter sections. The length of each section should be determined according to the specific working conditions and monitoring requirements. Perform vibration monitoring on each section separately, and collect vibration signals in real time through sensors and other equipment. Data collection should ensure comprehensiveness and accuracy to reflect the true state of the workpiece. The monitoring equipment obtains segmented data of each section, including key parameters such as vibration frequency and amplitude. At the same time, the position data of each section is recorded for subsequent data processing and fault location. The signal processing includes filtering, denoising and smoothing.

[0033] The segmented data is established based on the position data and the position correspondence on the long-span workpiece, the monitoring point position is calibrated to ensure the accuracy and consistency of the data, and time alignment is performed to eliminate the errors caused by the asynchronous data collection time, so as to obtain the overall data and map the overall data to the virtual model, which helps personnel to more intuitively understand the status of the workpiece and possible problems. Personnel combine the virtual model with the actual data to conduct auxiliary analysis and preliminarily judge whether the workpiece has a fault and the possible location of the fault. The overall data is processed by signal, such as filtering and denoising, to improve the quality of the data, and extracted through signal processing methods. The characteristic information of the fault, such as frequency change, amplitude abnormality, etc., is classified and identified by pattern recognition technology. The fault type, such as cracks, wear, looseness, etc., is determined according to the identification result. The location data and fault characteristic information are combined and the positioning algorithm is used to determine the specific location of the fault. The long-span workpiece is monitored in a segmented manner. The long-span workpiece is segmented and then the segmented data is time-aligned. This method can more accurately obtain the vibration data and operating status of the workpiece, improve the accuracy and efficiency of fault diagnosis, and combine the virtual model of the long-span workpiece and personnel-assisted analysis to locate the fault point more quickly.

[0034] Positioning algorithms are usually based on the principles of pattern recognition or template matching. They use known fault types and characteristic information to compare and analyze real-time monitored data to determine the specific location of the fault. Combining location data and fault characteristics, they can accurately point out the fault point, providing an important basis for subsequent maintenance and fault handling. Commonly used positioning algorithms include determining the fault location by measuring signal strength and comparing the signal strength differences at different locations, calculating the fault location by using the time difference of signal propagation at different locations, and identifying and predicting the fault location by training machine learning models.

[0035] By performing fault diagnosis and analysis through virtual simulation data, personnel can conduct auxiliary analysis and simulate real-time data in the computer through virtual workpieces. Since the simulation process can be displayed on the display screen, personnel can make auxiliary diagnosis and analysis through the simulation screen on the display screen. Through the vibration of the simulation screen, the operating status of the equipment can be intuitively understood, and the frequency, amplitude, phase and other characteristics of the vibration can be analyzed. These characteristics are often associated with specific fault types. Through the establishment of virtual models, preliminary fault diagnosis and correlation models, the initial workpiece is first analyzed for faults before the workpieces are combined, and then a virtual model of the initial workpiece is established. The virtual model of the combined workpiece is obtained based on the virtual model of the initial workpiece and the structural change data. The diagnostic data of the initial workpiece is reflected on the virtual model of the combined workpiece and analyzed through global simulation to achieve simulated fault diagnosis of the combined workpiece, that is, to achieve early warning of faults before they occur, thereby reducing the situation where the production efficiency of the trailer production line will be affected by faults that occur after the combination.

[0036] The overall size of the combined workpiece changes. When different initial workpieces are combined together, the overall size of the combined workpiece may change due to the matching, connection or stacking between the workpieces. The mass distribution of the initial workpieces will change during the combination process, which will in turn affect the overall mass distribution of the combined workpiece. After the workpieces are combined, the stiffness and strength of the combined workpiece may change due to the mutual support, constraint or reinforcement. This change may cause the combined workpiece to show different anti-deformation and load-bearing capacities when subjected to force. For combined workpieces that need to move, such as transmission parts or motion mechanisms in mechanical systems, the combination of workpieces will affect their motion characteristics. In some cases, the combination of workpieces will also affect the thermal characteristics of the combined workpiece, such as thermal conductivity, heat capacity or thermal expansion coefficient.

[0037] Professional testing equipment (such as crack detectors, stress analyzers, and ultrasonic flaw detectors) conduct in-depth testing and analysis of the preliminary structure and combined structure in the trailer. The test and analysis results of the preliminary structure are used to eliminate some defective products, and the remaining qualified ones will be put into production line for production. However, the initial workpieces put into the production line are only of qualified quality and may not be discovered or deemed qualified when tested separately. However, when these initial workpieces are combined into combined workpieces, these defects may interact with each other, resulting in a decline in overall performance or safety hazards. At the same time, when the initial workpieces are connected to each other, especially during welding and other connection processes, internal stress concentration may occur due to thermal deformation and uneven cooling of the material, which will cause problems in the combined workpiece. Through real-time monitoring and data acquisition, the equipment and workpieces on the trailer production line can be fully and real-time monitored to ensure the stability and reliability of the production process. The real-time data of the initial workpiece is used to simulate the subsequent combined workpiece, simulate the impact of diagnostic data on the virtual model of the combined workpiece, and discover potential fault points in advance. The combination of production line diagnostic methods and workpiece diagnostic methods makes fault diagnosis more comprehensive and accurate, and can timely discover faults in production.

[0038] There are existing technologies for predicting numerical trends. The specific principles of the predictive model are not explained here. The specific equipment is different, so the corresponding equipment will use different predictive models. The prediction of numerical values ​​is achieved through the predictive model. Feature information extraction is one of the key steps in fault diagnosis. By extracting fault feature information from the processed overall data, it can provide strong support for subsequent fault identification and classification. Feature information extraction is usually based on the time domain, frequency domain or time-frequency domain characteristics of the signal. By calculating and analyzing these characteristics, feature information related to the fault can be extracted, such as amplitude, frequency, phase, energy, etc. Common feature extraction methods include: time domain feature extraction: extract statistical indicators such as the mean, variance, maximum, and minimum values ​​of the signal to reflect the overall waveform characteristics and amplitude changes of the signal; frequency domain feature extraction: convert the signal from the time domain to the frequency domain through methods such as Fourier transform or wavelet transform, and extract spectrum features, such as spectrum energy, spectrum peak frequency, etc.; time-frequency domain feature extraction: combine the characteristics of the time domain and frequency domain to extract the time-frequency characteristics of the signal, such as wavelet packet decomposition coefficients, IMF components of empirical mode decomposition, etc.

[0039] Time series analysis is a statistical method specifically used to process data series that change over time. It aims to discover the inherent patterns, trends, periodicity and other characteristics in the data, and make future predictions and decisions based on these characteristics. Time series analysis arranges data in chronological order and uses statistical methods to analyze the relationships and changing patterns between data. It relies on the continuity and correlation of data in time to analyze the data. At the same time, time series analysis is used to monitor the changing trends and periodic fluctuations of the workpiece transportation speed on each assembly line, evaluate the consistency and synchronization of the speed, and thus ensure the synchronization of workpiece production on the entire assembly line.

[0040] Imbalance judgment: By analyzing the vibration data of the equipment, especially the high-frequency components in the vibration spectrum, it can be determined whether the equipment has an imbalance problem. Imbalance usually causes periodic vibration of the equipment during operation, and the vibration amplitude will increase with the increase of speed. Misalignment includes shaft misalignment and angle misalignment. By analyzing the equipment's axis centerline deviation, vibration data, and temperature data, it can be determined whether the equipment has an asymmetry problem. Equipment looseness usually leads to an increase in vibration amplitude, a wider vibration spectrum, and the appearance of non-periodic vibration components. By analyzing the equipment's vibration data and spectrum characteristics, it can be determined whether the equipment has a loose problem. Wear is a common form of failure during equipment operation. By analyzing the equipment's vibration data, oil analysis data, and operating time, it can be determined whether the equipment has a wear problem. The above can not only realize the judgment of the equipment, but also realize the judgment of the initial workpiece in the trailer.

[0041] After the warning is issued, personnel can carry out maintenance or adjust equipment parameters, which will not be explained here. The types of equipment in the production line are different, so the threshold settings of the corresponding equipment will be different. The degree of mutual influence is expressed by quantitative indicators, that is, the degree of influence between equipment is expressed by numerical values. The virtual model of the combined workpiece is obtained by simulating the virtual model of the initial workpiece and the structural change data. Since the length of the combined workpiece is affected by the initial workpiece and different connection methods will directly affect the size data of the combined workpiece, the virtual model of the combined workpiece needs to be combined with the virtual model of the initial workpiece and the structural change data.

[0042] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is limited by the attached embodiments and their equivalents.

Claims

1. A real-time monitoring and fault diagnosis method for a trailer production line, characterized in that: The real-time monitoring and fault diagnosis method includes a production line diagnosis method and a workpiece diagnosis method; The workpiece diagnosis method comprises: Real-time monitoring and data acquisition: The workpieces in the workpiece set are inspected in real time by the inspection equipment to obtain the real-time data of the workpieces. The workpiece set includes the initial workpieces and the combined workpieces. The combined workpieces are regarded as a combination of several initial workpieces. The combination of the combined workpieces is obtained, and the structural data of the initial workpieces is obtained; Initial workpiece virtual model: a virtual model of the initial workpiece is established based on the real-time data of the initial workpiece; Preliminary fault diagnosis: perform fault diagnosis on the real-time data of the initial workpiece, obtain the diagnostic data of the initial workpiece, and map the diagnostic data of the initial workpiece to the virtual model of the initial workpiece; Establish and apply the artifact association model: Establish the artifact association model, obtain the association degree between each initial artifact in the combined artifact according to the artifact association model, and obtain the structural change data based on the association degree and the combination of the combined artifacts; Combined workpiece virtual model: The virtual model of the combined workpiece is obtained by simulating the virtual model of the initial workpiece and the structural change data; Virtual model analysis and diagnosis: based on the virtual model of the combined workpiece, the diagnostic data of the initial workpiece and the degree of association, the diagnostic data of the combined workpiece is obtained, the diagnostic data of the initial workpiece is reflected on the virtual model of the combined workpiece, and the virtual model of the combined workpiece is globally simulated and analyzed to simulate the impact of the diagnostic data on the virtual model of the combined workpiece, and obtain the simulated total diagnostic data; Early warning: Analyze the simulated total diagnostic data to obtain simulated fault data, and issue early warning based on the simulated fault data; Calibration: Perform fault diagnosis on the real-time data of the combined workpiece, compare the real-time data of the combined workpiece, the fault diagnosis structure of the combined workpiece and the simulated total diagnosis data of the corresponding virtual model of the combined workpiece, and obtain comparison data for modifying parameters in the virtual model analysis and diagnosis.

2. The method for real-time monitoring and fault diagnosis of a trailer production line according to claim 1, characterized in that: The production line diagnosis method comprises: Data acquisition: Obtain historical production data of equipment in the trailer production line; Real-time monitoring: Real-time monitoring of the equipment in the trailer production line and the trailer structure to obtain real-time data of the equipment and structure; Equipment division in the production line: The equipment in the production line is divided into individual real-time data and total real-time data according to the individual and total attributes of the equipment in the production line; Establish and apply the production line association model: Establish a production line association model, which establishes the degree of association between equipment on the production line based on historical production data; Establish and apply prediction models: Establish prediction models, use prediction models to predict real-time data of equipment, and obtain equipment prediction data; Apply continuous data: Use time series analysis technology and combine the degree of association to deeply mine the continuity of sub-real-time data and total real-time data, identify trends in the production process and continuity between production lines, and obtain continuous data between sub-real-time data and total real-time data; Establish and apply thresholds: Establish corresponding equipment thresholds based on historical production data, determine whether continuous data and equipment prediction data will exceed the corresponding thresholds, and issue an early warning if the thresholds are exceeded.

3. The method for real-time monitoring and fault diagnosis of a trailer production line according to claim 1, characterized in that: The structural change data includes physical connection, mechanical properties and vibration connection. The physical connection includes the connection mode between the initial workpieces in the combined workpiece. The mechanical properties include stress distribution and stiffness change. The vibration connection includes the change of resonance frequency and amplitude.

4. The method for real-time monitoring and fault diagnosis of a trailer production line according to claim 1, characterized in that: The method for obtaining the degree of association between equipment on the production line includes: analyzing the historical production data of the equipment in the trailer production line, determining whether there is an association between the equipment, establishing the association between the equipment, and establishing a production line association model for reflecting the interaction and dependency between the equipment. Through the production line association model, the degree of mutual influence between the equipment is analyzed, and the degree of mutual influence is expressed by quantitative indicators.

5. The method for real-time monitoring and fault diagnosis of a trailer production line according to claim 1, characterized in that: The method for obtaining the degree of association between each artifact in the trailer structure includes: analyzing the initial artifacts in the combined structure, obtaining the connection mode between each initial artifact in the combined artifact, using the structural data and real-time operation data of the artifacts to establish an artifact association model that can reflect the physical connection, functional dependence and interaction between the artifacts, and analyzing the mutual influence and association degree between the artifacts through the artifact association model. The mutual influence and association degree between the artifacts are expressed by quantitative indicators.

6. The method for real-time monitoring and fault diagnosis of a trailer production line according to claim 1, characterized in that: Based on the initial workpieces in the workpiece set, they are divided into long-span workpieces and non-long-span workpieces according to the length data in the structural data. The fault diagnosis method for the workpiece data of the long-span workpiece includes segmented monitoring. The segmented monitoring includes dividing the long-span workpiece into several shorter sections, performing vibration detection and data collection on each section, and obtaining segmented data and position data of each section.

7. The method for real-time monitoring and fault diagnosis of a trailer production line according to claim 6, characterized in that: Fault diagnosis methods for long-span workpieces include: The segmented data is established based on the position data and corresponds to the position on the long-span workpiece. After the position is matched, the detection point position of the long-span workpiece is calibrated, and the segmented data is time-aligned to obtain the overall data; Map the overall data into a virtual model, and personnel conduct auxiliary analysis; Perform signal processing on the overall data, and process the processed overall data to obtain characteristic information of the fault; The fault characteristic information is pattern recognized to determine the fault type. The location data and fault characteristics are combined to determine the specific location of the corresponding fault using a positioning algorithm.

8. A real-time monitoring and fault diagnosis system for a trailer production line, characterized in that: A real-time monitoring and fault diagnosis method for a trailer production line as described in any one of claims 1 to 7 is adopted.

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