Metal pipe transportation safety monitoring system based on big data

Abstract

The invention discloses a metal pipe transportation safety monitoring system based on big data, and relates to the technical field of metal pipe transportation. The method comprises the following steps: comparing a real-time image of a carriage with an initial image of the carriage to obtain the position offset of a metal pipe; if there is an offset dangerous point in the carriage of the transport vehicle at the corresponding moment, generating a scanning monitoring first abnormal signal; if the offset dangerous point does not exist, calculating a displacement comprehensive detection value, and if the displacement comprehensive detection value exceeds a threshold value, generating a scanning monitoring second abnormal signal; evaluating the deformation of the metal pipe, judging whether the metal pipe has plastic deformation or not, and if so, generating a measurement and monitoring first abnormal signal; when the measuring and monitoring first abnormal signal and the corresponding metal pipe serial number position are received, whether a preset vibration data threshold value is exceeded or not is judged, a compartment vibration detection value is calculated, and if the threshold value is exceeded, a scanning and monitoring third abnormal signal is generated; and when any abnormal signal is received, an alarm is generated and sent to the user interface module.

Description

Technical Field

[0001] The present invention belongs to the technical field of metal pipe transportation, and in particular relates to a metal pipe transportation safety monitoring system based on big data. Background Art

[0002] During the transportation of metal pipes, the bumps and vibrations of vehicles during driving may cause slight displacements of the pipes, which may cause deformation over a long period of time. If the road conditions on which the transport vehicles pass are poor, such as potholes and bumps, these will aggravate the mutual collision and vibration between the pipes. The bending and shaping deformation of the pipes will not only affect their appearance, but may also reduce their structural strength and performance, causing the pipes to fail to meet the specifications and be unable to be used normally. Severe bumps may also damage the internal structure of the pipes and reduce their service life. Deformation and damage will not only damage the pipes themselves, but may also cause safety hazards during installation and use. If the pipes are severely deformed during transportation, it may make installation difficult or impossible. If pipe damage is found at the construction site, it may also delay the construction progress and further increase economic losses. Summary of the invention

[0003] In order to overcome the shortcomings and deficiencies of the above-mentioned prior art, the present invention adopts the following technical solutions:

[0004] A metal pipe transportation safety monitoring system based on big data, including a data acquisition module, an image processing module, a position offset monitoring module, a vibration monitoring module, a metal pipe deformation assessment module, an abnormal signal generation and alarm module, and a user interface module;

[0005] Data acquisition module: used to collect the initial image of the interior of the carriage after loading is completed, and to collect real-time images of the interior of the carriage regularly during transportation, and to collect relevant data of the metal pipes; Image processing module: used to compare the real-time image of the carriage with the initial image, and identify the position changes of the metal pipes; Position offset monitoring module: used to compare the offset with the preset threshold, and classify the monitoring points into safe points, risk points and dangerous points; calculate the displacement comprehensive inspection value, and determine whether it exceeds the preset threshold; Vibration monitoring module: used to analyze real-time vibration data, determine whether it exceeds the preset threshold, calculate the total duration and the maximum single duration, and evaluate whether the carriage is in a vibration-damaged state; Metal pipe deformation assessment module: collects the spatial coordinate data of the outer surface of the metal pipe, fits the ellipse equation according to the coordinate data, and calculates the ellipse characteristic parameters; draws the ellipse center curve, calculates the maximum bending deformation deflection, determines the position coordinates of the maximum deviation, and determines whether plastic deformation occurs; Abnormal signal generation and alarm module: generates abnormal signals according to the monitoring results, and sends the abnormal signals to the user interface module; User interface module: receives and displays abnormal alarm information.

[0006] Preferably, the system workflow is as follows:

[0007] Step 1: Obtain the initial image of the carriage, the real-time image of the carriage and the metal pipe data;

[0008] Step 2: Compare the real-time image of the carriage with the initial image of the carriage to obtain the position offset of the m monitoring points with respect to the metal pipe; if there is an offset danger point Ai in the carriage of the transport vehicle at the corresponding moment, generate a first abnormal signal for scanning monitoring; if there is no offset danger point Ai, calculate the displacement comprehensive inspection value P, and if the displacement comprehensive inspection value P exceeds the threshold, generate a second abnormal signal for scanning monitoring;

[0009] Step 3: metal pipe deformation assessment, determining whether the metal pipe has plastic deformation, and if so, generating a first abnormal signal for measurement and monitoring;

[0010] Step 4: when the first abnormal signal of the measurement monitoring and its corresponding metal pipe number position are received, it is determined whether it exceeds the preset vibration data threshold, and the cabin vibration detection value is calculated. If the cabin vibration detection value exceeds the preset threshold, a third abnormal signal of the scanning monitoring is generated;

[0011] Step 5: When any abnormal signal among the scanning monitoring first abnormal signal, the scanning monitoring second abnormal signal, the scanning monitoring third abnormal signal, and the measuring monitoring first abnormal signal is received, an alarm is generated and sent to the user interface module.

[0012] Preferably, in step 1, the initial image of the carriage, the real-time image of the carriage and the metal pipe data are obtained as follows:

[0013] When the loading of the metal pipes is completed, m monitoring points are set on the outer contour of the loaded goods inside the carriage, and the monitoring points include an image scanner and a laser precision measuring instrument;

[0014] Scan the interior of the carriage of the transport vehicle with an image scanner to obtain the image of the carriage loading; scan the metal pipes inside the carriage with a laser precision measuring instrument to obtain the metal pipe data;

[0015] When the loading of the metal pipes is completed, the interior of the carriage of the transport vehicle is scanned by an image scanner to obtain an initial image of the carriage; during the transportation process of the transport vehicle, the interior of the carriage of the transport vehicle is scanned by an image scanner to obtain a real-time image of the carriage.

[0016] Preferably, the specific process of step 2 is as follows:

[0017] When the position offset does not exceed the minimum value of the preset position offset threshold range, the corresponding monitoring point Ck is marked as an offset safety point Ck; wherein k=1, 2, 3, ..., m;

[0018] When the position offset is within the preset position offset threshold range, the corresponding monitoring point Bj is marked as an offset risk point Bj; wherein j = 1, 2, 3, ..., m;

[0019] When the position offset exceeds the maximum value of the preset position offset threshold range, the corresponding monitoring point Ai is marked as an offset danger point Ai; wherein i = 1, 2, 3, ..., m;

[0020] Among them, i≠j≠k;

[0021] If there is an offset danger point Ai in the carriage of the transport vehicle at the corresponding moment, a first abnormal signal of scanning monitoring is generated;

[0022] If there is no offset dangerous point Ai, further analysis is performed as follows: obtain the number of offset dangerous points Bj and the number of offset safe points Ck, and substitute them into the calculation formula to calculate the displacement comprehensive inspection value P. The calculation formula is as follows:

[0023]

[0024] Where T is the number of offset risk points Bj; N is the number of offset safe points Ck; β t and β n are the weight factors corresponding to the offset risk point Bj and the offset safety point Ck, and β t >β n ; R is the error correction factor;

[0025] If the displacement comprehensive inspection value P exceeds the preset displacement comprehensive inspection threshold, a second abnormal signal of scanning monitoring is generated.

[0026] Preferably, the process of step three is as follows:

[0027] S301, obtaining spatial coordinate data of the outer surface of the metal pipe along the axial direction;

[0028] Along the axial direction of the measuring pipe section, at a fixed length interval of nm, a laser precision measuring instrument is used to obtain the spatial coordinate data of the outer surface of the metal pipe along the axial direction; the spatial coordinate data point set Q = (x1, y1, z1), (x2, y2, z2), (x3, y3, z3), ..., (x m ,y m ,z m );

[0029] S302, calculating characteristic parameters of the ellipse equation of the metal pipe cross section;

[0030] The elliptical shape characteristics of each measured section are determined by spatial coordinate data, and the obtained adjacent section data points are projected onto the fitting section and brought into the ellipse equation to obtain characteristic parameters of the ellipse equation. The parameter characteristics include the radius parameters of the major and minor axes of the ellipse section and the coordinates of the center of the ellipse.

[0031] Specifically, the data point set Q is projected onto the same plane and an ellipse equation is fitted, which is as follows:

[0032]

[0033] Among them, (x0, y0) are the center coordinates of the elliptical cross section; a is the length of the semi-major axis of the elliptical cross section; b is the length of the semi-minor axis of the elliptical cross section;

[0034] S303, calculating the maximum bending deformation deflection, and determining the maximum bending deformation degree of the pipe;

[0035] S304, obtaining the position coordinates of the maximum deviation of the metal pipe;

[0036] S305, determining whether the metal pipe has undergone plastic deformation, and if so, generating a first abnormal measurement and monitoring signal.

[0037] Preferably, the specific process of step 4 is as follows:

[0038] When the first abnormal measurement and monitoring signal and its corresponding metal pipe number position are received, the vibration data in the car at the current moment is analyzed to determine whether it exceeds the preset vibration data threshold: if the vibration data exceeds the preset vibration data threshold, it is determined that the car is in a vibration-damaging state at this time, and the total duration of the car in the vibration-damaging state during the vibration period and the maximum duration of a single time are calculated, and the car vibration detection value is obtained; if the car vibration detection value exceeds the preset car vibration detection threshold, a third abnormal scanning monitoring signal is generated.

[0039] Preferably, in S303, the maximum bending deformation deflection is calculated to determine the maximum bending deformation degree of the pipe, and the specific process is as follows:

[0040] According to the obtained coordinates of the center of the ellipse at different cross sections (x1, y1), (x2, y2), (x3, y3), ..., the starting position is (x0, y0), connect all the coordinates of the center of the ellipse, and draw the center curve L1 of the pipe ellipse;

[0041] Draw a straight line y=y0 that passes through the starting point (x0, y0) and is parallel to the original direction of the metal pipe, and mark the reference straight line y=y0 as the reference straight line L2;

[0042] Find the point (x m ,y m ), so that |ym -y0|maximum and mark it as h max ;h max is the maximum vertical distance between the ellipse center curve L1 and the reference straight line L2, that is, the chord height at the maximum deformation;

[0043] The horizontal distance d from the starting point (x0, y0) to the maximum deformation is calculated by the formula as follows:

[0044] d = x m -x0;

[0045] The maximum bending deformation deflection F is calculated by the formula, and the calculation formula is as follows:

[0046] F=h max +d.

[0047] Preferably, in S304, the position coordinates of the maximum deviation of the metal pipe are obtained, and the specific process is as follows:

[0048] The major and minor axis radii of the cross section of the metal pipe at different positions are a i and b i , where i is the metal pipe position number;

[0049] For each metal pipe with position number i, calculate its deviation E i ; The calculation formula is as follows:

[0050]

[0051] Compare the deviation E of all position numbers i , the deviation E i The cross-sectional position i corresponding to the maximum value max , position i max The coordinates of are taken as the coordinates of the maximum flattening deformation position and marked as the starting point coordinates of the metal pipe;

[0052] Through the above steps, determine the location where the metal pipe has the maximum flattening deformation max .

[0053] Preferably, the specific process of S305 is as follows:

[0054] Tensile strain ε is used to indicate the degree of elongation or shortening of metal steel due to stress. The calculation formula is as follows:

[0055]

[0056] Among them, L arcis the arc length of the bent part of the metal pipe; L0 is the chord length; the arc length refers to the curve length of the bent part of the metal pipe; the chord length refers to the straight-line distance between the two end points of the bent part of the metal pipe;

[0057] Tensile stress refers to the tensile force per unit area of ​​a metal pipe. The tensile stress is calculated by the formula as follows:

[0058] σ=E·ε;

[0059] Where, E is the elastic modulus of the metal pipe;

[0060] σ y is the yield strength of the metal pipe, when σ>σ y When , it is considered that the metal pipe with position number i has undergone plastic deformation, it is marked as a defective metal pipe, and the first abnormal signal of measurement and monitoring is generated.

[0061] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0062] 1. The present invention integrates multiple modules such as data acquisition, image processing, position offset monitoring, vibration monitoring, metal pipe deformation assessment, abnormal signal generation and alarm, user interface, etc., to achieve all-round and real-time monitoring of the metal pipe transportation process. By using big data technology, the collected data is processed and analyzed, thus improving the accuracy and timeliness of monitoring.

[0063] 2. The present invention uses image processing technology to accurately identify the position changes of metal pipes during transportation, and conducts safety assessments based on preset thresholds; the vibration monitoring module analyzes the vibration data in the car in real time, evaluates whether the vibration may cause damage to the metal pipe, and provides a more detailed monitoring dimension; a laser precision measuring instrument is introduced to collect the spatial coordinate data of the outer surface of the metal pipe, and the deformation of the metal pipe is evaluated by fitting the elliptical equation and calculating the characteristic parameters; by calculating the maximum bending deformation deflection and the maximum deviation position coordinates, it can accurately determine whether the metal pipe has undergone plastic deformation, which is difficult to achieve with traditional monitoring methods.

[0064] 3. The present invention not only monitors position offset and vibration, but also conducts a comprehensive assessment based on the deformation of the metal pipe to generate different types of abnormal signals. The generation of abnormal signals is based on monitoring results in multiple dimensions, thereby improving the reliability and accuracy of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0066] Figure 1 A module diagram of a metal pipe transportation safety monitoring system based on big data of the present invention is shown;

[0067] Figure 2 The working flow chart of the system of the present invention is shown;

[0068] Figure 3 The flowchart of the metal pipe deformation evaluation according to the present invention is shown. DETAILED DESCRIPTION

[0069] 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.

[0070] In addition, the described features, structures or characteristics may be combined in one or more example embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the example embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or other methods, components, steps, etc. may be adopted. In other cases, well-known structures, methods, implementations or operations are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0071] This embodiment provides a metal pipe transportation safety monitoring system based on big data. Figure 1 is a module diagram of a metal pipe transportation safety monitoring system based on big data in an embodiment of the present invention, such as Figure 1 As shown, the system includes a data acquisition module, an image processing module, a position offset monitoring module, a vibration monitoring module, a metal pipe deformation evaluation module, an abnormal signal generation and alarm module, and a user interface module.

[0072] Data acquisition module: includes a carriage initial image acquisition submodule, a carriage real-time image acquisition submodule and a metal pipe data acquisition submodule; the carriage initial image acquisition submodule is used to acquire the initial image of the interior of the carriage after loading is completed; the carriage real-time image acquisition submodule is used to regularly acquire real-time images of the interior of the carriage during transportation; the metal pipe data acquisition submodule is used to acquire relevant data of metal pipes using a laser precision measuring instrument.

[0073] Image processing module: used to compare the real-time image of the carriage with the initial image and identify the position changes of metal pipes.

[0074] Position offset monitoring module: used to compare the offset with the preset threshold, classify the monitoring points into safe points, risk points and dangerous points; calculate the displacement comprehensive inspection value to determine whether it exceeds the preset threshold.

[0075] Vibration monitoring module: used to analyze real-time vibration data, determine whether it exceeds the preset threshold, calculate the total duration and the maximum duration of a single time, and evaluate whether the car is in a state of vibration damage.

[0076] Metal pipe deformation assessment module: collects spatial coordinate data of the outer surface of the metal pipe, fits the ellipse equation according to the coordinate data, and calculates the ellipse characteristic parameters; draws the ellipse center curve, calculates the maximum bending deformation deflection, determines the position coordinates of the maximum deviation, and determines whether plastic deformation occurs.

[0077] Abnormal signal generation and alarm module: generates abnormal signals according to monitoring results and sends the abnormal signals to the user interface module.

[0078] User interface module: receives and displays abnormal alarm information.

[0079] Figure 2 This is a workflow diagram of a metal pipe transportation safety monitoring system based on big data according to an embodiment of the present invention. Figure 2 As shown, the system workflow includes the following steps:

[0080] Step 1: Obtain the initial image of the carriage, the real-time image of the carriage and the metal pipe data.

[0081] When the loading of the metal pipes is completed, m monitoring points are set on the outer contour of the loaded goods inside the carriage, and the monitoring points include an image scanner and a laser precision measuring instrument.

[0082] The interior of the carriage of the transport vehicle is scanned by an image scanner to obtain the image of the carriage loading; the metal pipes inside the carriage are scanned by a laser precision measuring instrument to obtain the metal pipe data.

[0083] When the loading of the metal pipes is completed, the interior of the carriage of the transport vehicle is scanned by an image scanner to obtain an initial image of the carriage; during the transportation process of the transport vehicle, the interior of the carriage of the transport vehicle is scanned by an image scanner to obtain a real-time image of the carriage.

[0084] Step 2: Compare the real-time image of the carriage with the initial image of the carriage to obtain the position offset of m monitoring points with respect to the metal pipe.

[0085] When the position offset does not exceed the minimum value of the preset position offset threshold range, the corresponding monitoring point Ck is marked as an offset safety point Ck; wherein k=1, 2, 3, ..., m.

[0086] When the position offset is within the preset position offset threshold range, the corresponding monitoring point Bj is marked as an offset risk point Bj; wherein j=1, 2, 3, ..., m.

[0087] When the position offset exceeds the maximum value of the preset position offset threshold range, the corresponding monitoring point Ai is marked as an offset danger point Ai; wherein i=1, 2, 3, ..., m.

[0088] Among them, i≠j≠k.

[0089] If there is an offset danger point Ai in the carriage of the transport vehicle at the corresponding moment, a first abnormal signal of scanning monitoring is generated;

[0090] If there is no offset dangerous point Ai, further analysis is performed as follows: obtain the number of offset dangerous points Bj and the number of offset safe points Ck, and substitute them into the calculation formula to calculate the displacement comprehensive inspection value P. The calculation formula is as follows:

[0091]

[0092] Where T is the number of offset risk points Bj; N is the number of offset safe points Ck; β t and β n are the weight factors corresponding to the offset risk point Bj and the offset safety point Ck, and β t >β n ; R is the error correction factor.

[0093] If the displacement comprehensive inspection value P exceeds the preset displacement comprehensive inspection threshold, a second abnormal signal of scanning monitoring is generated.

[0094] Step 3: Metal pipe deformation assessment.

[0095] Figure 3 is a workflow diagram for evaluating deformation of metal pipes according to the present invention, such as Figure 3 As shown, the process includes the following steps:

[0096] S301, obtaining spatial coordinate data of the outer surface of the metal pipe along the axial direction.

[0097] Along the axial direction of the measuring pipe section, at a fixed length interval of nm, a laser precision measuring instrument is used to obtain the spatial coordinate data of the outer surface of the metal pipe along the axial direction. The spatial coordinate data point set Q = (x1, y1, z1), (x2, y2, z2), (x3, y3, z3), ..., (x m ,y m ,z m );

[0098] S302, calculating characteristic parameters of the ellipse equation of the metal pipe cross section.

[0099] The elliptical shape characteristics of each measured section are determined by spatial coordinate data, and the adjacent section data points are projected onto the fitting section and substituted into the ellipse equation to obtain the characteristic parameters of the ellipse equation. The parameter characteristics include the major and minor axis radius parameters of the ellipse section and the coordinates of the ellipse center.

[0100] Specifically, the data point set Q is projected onto the same plane and an ellipse equation is fitted, which is as follows:

[0101]

[0102] Among them, (x0, y0) is the center coordinate of the elliptical cross section; a is the length of the semi-major axis of the elliptical cross section; b is the length of the semi-minor axis of the elliptical cross section.

[0103] S303, calculating the maximum bending deformation deflection, and determining the maximum bending deformation degree of the pipe.

[0104] According to the obtained coordinates of the center of the ellipse at different cross sections (x1, y1), (x2, y2), (x3, y3), ..., the starting position is (x0, y0), connect all the coordinates of the center of the ellipse, and draw the center curve L1 of the pipe ellipse;

[0105] Draw a straight line y=y0 that passes through the starting point (x0, y0) and is parallel to the original direction of the metal pipe, and mark the reference straight line y=y0 as the reference straight line L2;

[0106] Find the point (x m ,y m ), so that |y m -y0|maximum and mark it as h max ;h max It is the maximum vertical distance between the ellipse center curve L1 and the reference straight line L2, that is, the chord height at the maximum deformation.

[0107] The horizontal distance d from the starting point (x0, y0) to the maximum deformation is calculated by the formula as follows:

[0108] d = x m -x0;

[0109] The maximum bending deformation deflection F is calculated by the formula, and the calculation formula is as follows:

[0110] F=h max +d.

[0111] S304, obtaining the position coordinates of the maximum deviation of the metal pipe.

[0112] The major and minor axis radii of the cross section of the metal pipe at different positions are a i and b i , where i is the metal pipe position number.

[0113] Process the long and short axis radius parameter data of the measured pipe section to calculate the positions of different sections

[0114] The degree of flattening deformation is assigned as deviation; the position corresponding to the maximum deviation is marked as the position coordinate of the maximum deviation, that is, the place where the degree of flattening deformation of the metal pipe is the largest.

[0115] For each metal pipe with position number i, calculate its deviation E i ; The calculation formula is as follows:

[0116]

[0117] Compare the deviation E of all position numbers i , the deviation E i The cross-sectional position i corresponding to the maximum value max , position i max The coordinates of are taken as the coordinates of the maximum flattening deformation position and marked as the starting point coordinates of the metal pipe.

[0118] Through the above steps, determine the location where the metal pipe has the maximum flattening deformation max .

[0119] S305: Determine whether the metal pipe has undergone plastic deformation.

[0120] The difference between the arc length and the chord length of the tensile side curve divided by the chord length is the tensile strain caused by the bending of the metal pipe. The tensile stress of the pipe is calculated based on the elastic modulus data of the metal pipe. If the tensile stress exceeds the yield strength, it is considered that the metal pipe has undergone plastic deformation.

[0121] Among them, tensile strain ε is used to indicate the degree of elongation or shortening of metal steel due to stress, and the calculation formula is as follows:

[0122]

[0123] Among them, L arc is the arc length of the bent part of the metal pipe; L0 is the chord length.

[0124] Arc length refers to the length of the curve of the bent part of the metal pipe.

[0125] The chord length refers to the straight-line distance between the two end points of the curved section of a metal pipe.

[0126] Tensile stress refers to the tensile force per unit area of ​​a metal pipe. The tensile stress is calculated by the formula as follows:

[0127] σ=E·ε;

[0128] Where E is the elastic modulus of the metal pipe.

[0129] σ y is the yield strength of the metal pipe, when σ>σ y When , it is considered that the metal pipe with position number i has undergone plastic deformation, it is marked as a defective metal pipe, and the first abnormal signal of measurement and monitoring is generated.

[0130] Step 4: When the first abnormal signal of measurement and monitoring and its corresponding metal pipe number position are received, the vibration data in the car at the current moment is analyzed to determine whether it exceeds the preset vibration data threshold: if the vibration data exceeds the preset vibration data threshold, it is determined that the car is in a vibration-damaging state at this time, and the total duration of the vibration period in the car being in the vibration-damaging state and the maximum duration of a single time are calculated, and the car vibration detection value is obtained. If the car vibration detection value exceeds the preset car vibration detection threshold, a third abnormal signal of scanning monitoring is generated.

[0131] Step 5: When the system receives any abnormal signal among the scanning monitoring first abnormal signal, the scanning monitoring second abnormal signal, the scanning monitoring third abnormal signal, and the measuring monitoring first abnormal signal, an alarm is generated and sent to the user interface module.

[0132] The beneficial effects of this embodiment are as follows: through real-time monitoring and precise evaluation, potential safety hazards of metal pipes during transportation can be discovered in time, reducing losses caused by unexpected situations during transportation; early warning and timely intervention can avoid the repair and replacement costs caused by damage to metal pipes, while also reducing downtime and economic losses caused by accidents; the multi-module integrated system can automatically complete most of the monitoring and analysis work, reducing the workload of operators and improving management efficiency.

[0133] The weight factors of the present invention are used to measure the degree of influence of different factors or variables on a certain result or decision. The definition of weight coefficient refers to the value assigned to each factor when comparing and evaluating multiple factors to reflect its importance or priority. These weight coefficients can be determined according to specific circumstances and needs, and are usually jointly formulated and confirmed by professionals or relevant stakeholders. By reasonably setting the weight coefficients, it can help the program or system make decisions or predictions more accurately.

[0134] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

[0135] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A metal pipe transportation safety monitoring system based on big data, characterized in that: The system includes a data acquisition module, an image processing module, a position offset monitoring module, a vibration monitoring module, a metal pipe deformation assessment module, an abnormal signal generation and alarm module, and a user interface module; Data acquisition module: used to collect the initial image of the interior of the carriage after loading is completed, and to collect real-time images of the interior of the carriage regularly during transportation, and to collect relevant data of metal pipes; Image processing module: used to compare the real-time image of the carriage with the initial image, and identify the position change of the metal pipes; Position offset monitoring module: used to compare the offset with the preset threshold, and classify the monitoring points into safe points, risk points and dangerous points; calculate the displacement comprehensive inspection value to determine whether it exceeds the preset threshold; Vibration monitoring module: used to analyze real-time vibration data, determine whether it exceeds the preset threshold, calculate the total duration and the maximum duration of a single vibration, and evaluate whether the car is in a state of vibration damage; Metal pipe deformation assessment module: collects spatial coordinate data of the outer surface of the metal pipe, fits the ellipse equation according to the coordinate data, and calculates the ellipse characteristic parameters; Draw the center curve of the ellipse, calculate the maximum bending deformation deflection, determine the position coordinates of the maximum deviation, and judge whether plastic deformation occurs; Abnormal signal generation and alarm module: generate abnormal signals according to monitoring results, and send abnormal signals to the user interface module; User interface module: receive and display abnormal alarm information.

2. According to the big data-based metal pipe transportation safety monitoring system of claim 1, it is characterized in that: The system workflow is as follows: Step 1: Obtain the initial image of the carriage, the real-time image of the carriage and the metal pipe data; Step 2: Compare the real-time image of the carriage with the initial image of the carriage to obtain the position offset of the m monitoring points with respect to the metal pipe; if there is an offset danger point Ai in the carriage of the transport vehicle at the corresponding moment, generate a first abnormal signal for scanning monitoring; if there is no offset danger point Ai, calculate the displacement comprehensive inspection value P, and if the displacement comprehensive inspection value P exceeds the threshold, generate a second abnormal signal for scanning monitoring; Step 3: metal pipe deformation assessment, determining whether the metal pipe has plastic deformation, and if so, generating a first abnormal signal for measurement and monitoring; Step 4: when the first abnormal signal of the measurement monitoring and its corresponding metal pipe number position are received, it is determined whether it exceeds the preset vibration data threshold, and the cabin vibration detection value is calculated. If the cabin vibration detection value exceeds the preset threshold, a third abnormal signal of the scanning monitoring is generated; Step 5: When any abnormal signal among the scanning monitoring first abnormal signal, the scanning monitoring second abnormal signal, the scanning monitoring third abnormal signal, and the measuring monitoring first abnormal signal is received, an alarm is generated and sent to the user interface module.

3. According to the big data-based metal pipe transportation safety monitoring system of claim 2, it is characterized in that: In the step 1, the initial image of the carriage, the real-time image of the carriage and the metal pipe data are obtained as follows: When the loading of the metal pipes is completed, m monitoring points are set on the outer contour of the loaded goods inside the carriage, and the monitoring points include an image scanner and a laser precision measuring instrument; Scan the interior of the carriage of the transport vehicle with an image scanner to obtain the image of the carriage loading; scan the metal pipes inside the carriage with a laser precision measuring instrument to obtain the metal pipe data; When the loading of the metal pipes is completed, the interior of the carriage of the transport vehicle is scanned by an image scanner to obtain an initial image of the carriage; during the transportation process of the transport vehicle, the interior of the carriage of the transport vehicle is scanned by an image scanner to obtain a real-time image of the carriage.

4. According to the big data-based metal pipe transportation safety monitoring system of claim 2, it is characterized in that: The specific process of step 2 is as follows: When the position offset does not exceed the minimum value of the preset position offset threshold range, the corresponding monitoring point Ck is marked as an offset safety point Ck; wherein k=1, 2, 3, ..., m; When the position offset is within the preset position offset threshold range, the corresponding monitoring point Bj is marked as an offset risk point Bj; wherein j = 1, 2, 3, ..., m; When the position offset exceeds the maximum value of the preset position offset threshold range, the corresponding monitoring point Ai is marked as an offset danger point Ai; wherein i = 1, 2, 3, ..., m; Among them, i≠j≠k; If there is an offset danger point Ai in the carriage of the transport vehicle at the corresponding moment, a first abnormal signal of scanning monitoring is generated; If there is no offset dangerous point Ai, further analysis is performed as follows: obtain the number of offset dangerous points Bj and the number of offset safe points Ck, and substitute them into the calculation formula to calculate the displacement comprehensive inspection value P. The calculation formula is as follows: Where T is the number of offset risk points Bj; N is the number of offset safe points Ck; β t and β n are the weight factors corresponding to the offset risk point Bj and the offset safety point Ck, and β t >β n ; R is the error correction factor; If the displacement comprehensive inspection value P exceeds the preset displacement comprehensive inspection threshold, a second abnormal signal of scanning monitoring is generated.

5. The metal pipe transportation safety monitoring system based on big data according to claim 2 is characterized in that: The process of step three is as follows: S301, obtaining spatial coordinate data of the outer surface of the metal pipe along the axial direction; Along the axial direction of the measuring pipe section, at a fixed length interval of nm, a laser precision measuring instrument is used to obtain the spatial coordinate data of the outer surface of the metal pipe along the axial direction; the spatial coordinate data point set Q = (x1, y1, z1), (x2, y2, z2), (x3, y3, z3), ..., (x m ,y m ,z m ); S302, calculating characteristic parameters of the ellipse equation of the metal pipe cross section; The elliptical shape characteristics of each measured section are determined by spatial coordinate data, and the obtained adjacent section data points are projected onto the fitting section and brought into the ellipse equation to obtain characteristic parameters of the ellipse equation. The parameter characteristics include the radius parameters of the major and minor axes of the ellipse section and the coordinates of the center of the ellipse. Specifically, the data point set Q is projected onto the same plane and an ellipse equation is fitted, which is as follows: Among them, (x0, y0) are the center coordinates of the elliptical cross section; a is the length of the semi-major axis of the elliptical cross section; b is the length of the semi-minor axis of the elliptical cross section; S303, calculating the maximum bending deformation deflection, and determining the maximum bending deformation degree of the pipe; S304, obtaining the position coordinates of the maximum deviation of the metal pipe; S305, determining whether the metal pipe has undergone plastic deformation, and if so, generating a first abnormal measurement and monitoring signal.

6. The metal pipe transportation safety monitoring system based on big data according to claim 2 is characterized in that: The specific process of step 4 is as follows: When the first abnormal measurement and monitoring signal and its corresponding metal pipe number position are received, the vibration data in the car at the current moment is analyzed to determine whether it exceeds the preset vibration data threshold: if the vibration data exceeds the preset vibration data threshold, it is determined that the car is in a vibration-damaging state at this time, and the total duration of the car in the vibration-damaging state during the vibration period and the maximum duration of a single time are calculated, and the car vibration detection value is obtained; if the car vibration detection value exceeds the preset car vibration detection threshold, a third abnormal scanning monitoring signal is generated.

7. The metal pipe transportation safety monitoring system based on big data according to claim 2 is characterized in that: In S303, the maximum bending deformation deflection is calculated to determine the maximum bending deformation degree of the pipe. The specific process is as follows: According to the obtained coordinates of the center of the ellipse at different cross sections (x1, y1), (x2, y2), (x3, y3), ..., the starting position is (x0, y0), connect all the coordinates of the center of the ellipse, and draw the center curve L1 of the pipe ellipse; Draw a straight line y=y0 that passes through the starting point (x0, y0) and is parallel to the original direction of the metal pipe, and mark the reference straight line y=y0 as the reference straight line L2; Find the point (x m ,y m ), so that |y m -y0|maximum and mark it as h max ;h max is the maximum vertical distance between the ellipse center curve L1 and the reference straight line L2, that is, the chord height at the maximum deformation; The horizontal distance d from the starting point (x0, y0) to the maximum deformation is calculated by the formula as follows: d=x m -x0; The maximum bending deformation deflection F is calculated by the formula, and the calculation formula is as follows: F=h max +d。 8. The metal pipe transportation safety monitoring system based on big data according to claim 2 is characterized in that: In S304, the position coordinates of the maximum deviation of the metal pipe are obtained, and the specific process is as follows: The major and minor axis radii of the cross section of the metal pipe at different positions are a i and b i , where i is the metal pipe position number; For each metal pipe with position number i, calculate its deviation E i ; The calculation formula is as follows: Compare the deviation E of all position numbers i , the deviation E i The cross-sectional position i corresponding to the maximum value max , position i max The coordinates of are taken as the coordinates of the maximum flattening deformation position and marked as the starting point coordinates of the metal pipe; Through the above steps, determine the location where the metal pipe has the maximum flattening deformation max .

9. The metal pipe transportation safety monitoring system based on big data according to claim 2 is characterized in that: The specific process of S305 is as follows: Tensile strain ε is used to indicate the degree of elongation or shortening of metal steel due to stress. The calculation formula is as follows: Among them, L arc is the arc length of the bent part of the metal pipe; L0 is the chord length; the arc length refers to the curve length of the bent part of the metal pipe; the chord length refers to the straight-line distance between the two end points of the bent part of the metal pipe; Tensile stress refers to the tensile force per unit area of ​​a metal pipe. The tensile stress is calculated by the formula as follows: σ=E·ε; Where, E is the elastic modulus of the metal pipe; σ y is the yield strength of the metal pipe, when σ>σ y When , it is considered that the metal pipe with position number i has undergone plastic deformation, it is marked as a defective metal pipe, and the first abnormal signal of measurement and monitoring is generated.

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