Bolt wear on-line detection alarm system and bolt wear on-line detection alarm method

Abstract

The invention discloses a bolt wear online detection alarm system and method, and relates to the technical field of bolt wear detection.The bolt wear online detection alarm system comprises an information acquisition unit, an information analysis unit and an alarm reminding unit, and the information acquisition unit comprises a bolt data acquisition module, an environment data acquisition module and an image information acquisition module; the information analysis unit is used for collecting bolt body information, environment data and bolt images, establishing a bolt working model in a normal state, calculating the standard temperature and the standard humidity of the surface of the bolt in the normal state, obtaining real-time environment data B, calculating a temperature influence coefficient and a humidity influence coefficient, and further calculating a comprehensive wear index and a deviation index of the bolt; and a bolt wear signal and a bolt loosening signal are judged and generated according to a preset threshold value, and an alarm is given. According to the invention, the wear condition of the bolt is comprehensively evaluated by comprehensively collecting the bolt body information and the surrounding environment data, the detection accuracy is improved, and unnecessary loss and risk are reduced through real-time monitoring and timely alarm reminding.

Description

Technical Field

[0001] This invention relates to the field of bolt wear technology, and in particular to an online bolt wear detection and alarm system and method. Background Technology

[0002] With social development and the progress of the times, bolts are widely used in production and processing. However, with the widespread use of bolts, bolt wear detection is also very necessary. If bolt wear and loosening are not detected in time, the bolt tension will decrease, which will further lead to a decrease in friction, causing the bolt connection to loosen. Loose bolts will reduce the performance of mechanical equipment, affect the working efficiency of the equipment, and may even increase the safety hazards of mechanical operation.

[0003] Traditional bolt wear detection methods typically rely on periodic manual or offline inspections. These methods often suffer from long inspection cycles, low accuracy, and inability to monitor in real time. Moreover, due to the lack of accurate data support, bolt wear problems are often discovered only after equipment failure or safety hazards have already occurred, increasing maintenance costs and risks.

[0004] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to propose an online bolt wear detection and alarm system and method. By comprehensively collecting bolt body information and surrounding environmental data, the wear condition of the bolt is comprehensively evaluated, which improves the accuracy of detection. Furthermore, by providing timely alarm reminders through real-time monitoring, unnecessary losses and risks are effectively reduced.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: including an information acquisition unit, an information analysis unit, and an alarm reminder unit;

[0007] The information acquisition unit includes a bolt data acquisition module, an environmental data acquisition module, and an image information acquisition module. The bolt data acquisition module includes information data A for acquiring the bolt body, environmental data B around the bolt, and image data of the bolt.

[0008] The information analysis unit includes a model building module, a data analysis module, an information judgment module, and an image analysis module. The model building module is used to receive the aforementioned data, generate bolt wear signals and bolt loosening signals through analysis and calculation, and send the signals to the alarm reminder unit.

[0009] The alarm reminder unit includes a wear alarm module and a loosening alarm module. The wear alarm module is used to receive bolt wear signals and issue a wear alarm sound through the wear alarm device to provide an alarm reminder.

[0010] The data analysis module is used to acquire real-time environmental data B, which includes real-time temperature Tb and relative humidity RHb around the bolt. The temperature influence coefficient Tx is calculated based on the real-time temperature Tb around the bolt and the standard temperature Tc of the bolt surface under normal conditions. The humidity influence coefficient RHx is calculated based on the relative humidity RHb around the bolt and the standard humidity RHc of the bolt surface under normal conditions.

[0011] The information judgment module is used to acquire information data A, which includes bolt surface temperature Ta and humidity RHa. Based on bolt surface temperature Ta and temperature influence coefficient Tx, bolt evaluation temperature Tk is calculated, and based on bolt surface humidity RHa and humidity influence coefficient RHx, bolt evaluation humidity RHk is calculated. Information data A also includes bolt surface axial stress σa. Based on bolt surface axial stress σa, bolt evaluation temperature Tk, and bolt evaluation humidity RHk, comprehensive wear index Mi is calculated. A preset comprehensive wear index threshold Mmax is set, and the bolt wear degree is judged according to the preset comprehensive wear index threshold Mmax. A bolt wear signal is generated and sent to the alarm reminder unit.

[0012] The image analysis module is used to receive and process the bolt image data. First, the bolt image data is preprocessed. Then, the preprocessed bolt image data is used to extract features to obtain a target contour map. Points are plotted along the contour edge of the target contour map to obtain edge contour points and determine the midpoint position of the bolt. A three-dimensional coordinate system is established to determine the midpoint coordinates of the bolt and the camera midpoint, resulting in a three-dimensional contour map of the bolt. A standard three-dimensional contour map of the bolt is preset. The three-dimensional contour map of the bolt is superimposed with the preset standard three-dimensional contour map to calculate the bolt offset index Fi. A bolt offset index threshold Fmax is preset. The degree of bolt offset is determined based on the preset bolt offset index threshold Fmax, and a bolt loosening signal is generated and sent to the alarm reminder unit.

[0013] The specific working process for calculating the standard temperature and standard humidity of the bolt surface under normal conditions is as follows:

[0014] S101. Based on normal information data A and normal environmental data B, the normal information data A includes the normal surface temperature Tap and normal humidity RHap of the bolt, and the normal environmental data B includes the normal ambient temperature Tbp and normal relative humidity RHbp around the bolt.

[0015] S102. Establish a bolt working model under normal conditions, whose objective function can be expressed as:

[0016] Where f(x) represents the objective function, Tap represents the normal surface temperature of the bolt under normal conditions, m = 1, 2, 3, ..., M, M represents the number of test simulations, and Tbp is the normal ambient temperature around the bolt under normal conditions.

[0017] S103. The ambient temperature around the bolt under normal conditions is obtained multiple times by the temperature sensor, and the standard temperature Tc of the bolt surface under normal conditions is obtained by substituting it into the objective function.

[0018] S104, By formula: Where RHc is the standard humidity of the bolt surface under normal conditions, and Q is a constant.

[0019] The specific process for calculating the temperature influence coefficient and humidity influence coefficient is as follows:

[0020] S201. Obtain the real-time temperature Tb and relative humidity RHb around the bolt;

[0021] S202, By formula: Where Tx is the temperature influence coefficient and W is a constant;

[0022] S203, via formula: Where RHx is the humidity influence coefficient and Y is a constant.

[0023] The specific process for calculating the comprehensive wear index is as follows:

[0024] S301. Obtain the bolt surface temperature Ta, bolt surface humidity RHa, and bolt surface axial stress σa;

[0025] S302, By formula: Where Tk is the bolt evaluation temperature;

[0026] S303, via formula: Where RHk represents the moisture content of the bolts;

[0027] S304, By formula: Where Mi is the comprehensive wear index and Z is a constant.

[0028] The specific process of processing bolt image data is as follows:

[0029] S401. Preprocessing: The acquired bolt image data is preprocessed through denoising, enhancement, and transformation.

[0030] S402, Feature Extraction: Perform feature extraction on the preprocessed bolt image data, and extract the edge contour based on the size and shape of the bolt in the image data to obtain the target contour map;

[0031] S403. Using a gradient-based projection statistical method, the target contour map is scanned in rows and columns to determine the starting row coordinates, height, column coordinates, and width of the target contour map, thereby locating the target contour map.

[0032] S404. Plot points along the outline edge of the target outline to obtain the edge outline points, and obtain the midpoint position through the edge outline points of the bolt.

[0033] The specific process for calculating the bolt offset index is as follows:

[0034] S501. Establish a three-dimensional coordinate system: Select the midpoint of the bolt as the origin, define the mutually perpendicular directions in the horizontal plane on the bolt as the X-axis and Y-axis directions, and define the Z-axis as perpendicular to the bolt surface and upward.

[0035] S502. Obtain the midpoint coordinates (X0, Y0, Z0) of the bolt, the midpoint coordinates (Xs, Ys, Zs) of the camera, and the simulated deflection angle θs between the midpoint of the bolt and the midpoint of the camera to determine the three-dimensional profile of the bolt.

[0036] S503. Based on the camera position, simulate the optimal position for bolt assembly, obtain the standard midpoint coordinates of the preset bolt as (Xy, Yy, Zy), and obtain the standard three-dimensional contour diagram of the preset bolt.

[0037] S504. Overlay the 3D contour map of the bolt with the preset standard 3D contour map of the bolt. Then, obtain the horizontal and vertical screenshots of the overlaid 3D contour map and the standard 3D contour map of the bolt, and compare them to generate the total overlapping area dlm and the total non-overlapping area elm. The total non-overlapping area elm is the bolt offset. Calculate the bolt offset index according to the following formula. Where b is a constant, Ψ is the offset factor, and Fi is the bolt offset index.

[0038] A method for online detection and alarm of bolt wear includes the following steps:

[0039] Step 1: Obtain information data A of the bolt body, environmental data B of the surrounding environment, and image data of the bolt, and send information data A, environmental data B, and image data of the bolt to the information analysis unit;

[0040] Step 2: Establish and analyze the bolt working model under normal conditions. Based on the conditions of sunny and windless environment and no bolt wear, establish the bolt working model under normal conditions. By substituting the real-time temperature around the bolt into the objective function, calculate the standard temperature Tc and standard humidity RHc of the bolt surface under normal conditions.

[0041] Step 3: Obtain real-time environmental data B, which includes the real-time temperature Tb and relative humidity RHb around the bolt. Calculate the temperature influence coefficient Tx based on the real-time temperature Tb around the bolt and the standard surface temperature Tc of the bolt under normal conditions. Calculate the humidity influence coefficient RHx based on the relative humidity RHb around the bolt and the standard surface humidity RHc of the bolt under normal conditions.

[0042] Step 4: Obtain information data A, which includes bolt surface temperature Ta and humidity RHa. Based on bolt surface temperature Ta and temperature influence coefficient Tx, calculate bolt assessment temperature Tk. Based on bolt surface humidity RHa and humidity influence coefficient RHx, calculate bolt assessment humidity RHk. Information data A also includes bolt surface axial stress σa. Based on bolt surface axial stress σa, bolt assessment temperature Tk, and bolt assessment humidity RHk, calculate comprehensive wear index Mi. Set a preset comprehensive wear index threshold Mmax. Determine the wear degree of the bolt based on the preset comprehensive wear index threshold Mmax and generate a bolt wear signal. Send the bolt wear signal to the alarm reminder unit.

[0043] Step 5: The information analysis unit receives the bolt image data and processes it. First, the bolt image data is preprocessed. Then, the preprocessed bolt image data is used to extract features to obtain a target contour map. Points are plotted along the contour edge of the target contour map to obtain edge contour points and determine the midpoint position of the bolt. A three-dimensional coordinate system is established to determine the midpoint coordinates of the bolt and the camera midpoint, resulting in a three-dimensional contour map of the bolt. A standard three-dimensional contour map of the bolt is preset. The three-dimensional contour map of the bolt is superimposed with the preset standard three-dimensional contour map to calculate the bolt offset index Fi. A bolt offset index threshold Fmax is preset. The degree of bolt offset is judged based on the preset bolt offset index threshold Fmax, and a bolt loosening signal is generated and sent to the alarm reminder unit.

[0044] Step Six: Upon receiving a bolt wear signal, the wear alarm module emits a wear alarm sound to alert the user. Similarly, upon receiving a bolt loosening signal, the loosening alarm module emits a loosening alarm sound to alert the user.

[0045] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0046] This invention comprehensively assesses bolt wear by collecting bolt body information, surrounding environmental data, and image data, ensuring the integrity and accuracy of the detection data. Through real-time data processing, it quickly calculates the bolt's assessment temperature, assessment humidity, and comprehensive wear index, enabling real-time monitoring and early warning of bolt wear. Image processing and analysis determine the bolt's midpoint position and establish a three-dimensional coordinate system to accurately measure the bolt's offset position and offset index. Based on a preset threshold, the bolt's offset index is judged, thereby enabling monitoring of bolt loosening, timely alarm reminders, and reduced safety hazards. Attached Figure Description

[0047] Figure 1 A schematic flowchart of an online bolt wear detection and alarm system disclosed in this invention is shown.

[0048] Figure 2 This invention discloses a method flowchart of an online bolt wear detection and alarm system. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] Example 1:

[0051] like Figure 1 As shown, an online bolt wear detection and alarm system includes an information acquisition unit, an information analysis unit, and an alarm reminder unit;

[0052] The information acquisition unit includes a bolt data acquisition module, an environmental data acquisition module, and an image information acquisition module. The bolt data acquisition module is used to collect information data A of the bolt body and send information data A to the information analysis unit. The environmental data acquisition module is used to collect environmental data B around the bolt and send environmental data B to the information analysis unit. The image information acquisition module is used to acquire image data of the bolt through a camera and send the image data to the information analysis unit. Through the comprehensive acquisition of bolt body information data A, surrounding environmental data B, and bolt image data by the information acquisition unit, a comprehensive and accurate data foundation is provided for subsequent information analysis, thereby effectively improving the accuracy and reliability of information analysis.

[0053] The information analysis unit includes a model building module, a data analysis module, an information judgment module, and an image analysis module. The model building module is used to build and analyze the bolt working model under normal conditions. Based on the conditions of sunny and windless environment and no bolt wear, the bolt working model under normal conditions is built. By substituting the real-time temperature around the bolt into the objective function, the standard temperature Tc and standard humidity RHc of the bolt surface under normal conditions are calculated. By building the bolt working model under ideal conditions, and by comparing and analyzing the real-time environmental data with the ideal model, the standard temperature Tc and standard humidity RHc of the bolt surface can be calculated more accurately.

[0054] The specific working process for calculating the standard temperature and standard humidity of the bolt surface under normal conditions is as follows:

[0055] S101. Based on normal information data A and normal environmental data B, normal information data A includes normal bolt surface temperature Tap and normal humidity RHap, and normal environmental data B includes normal ambient temperature Tbp and normal relative humidity RHbp around the bolt.

[0056] S102. Establish a bolt working model under normal conditions, whose objective function can be expressed as:

[0057] Where f(x) represents the objective function, Tap represents the normal surface temperature of the bolt under normal conditions, m = 1, 2, 3, ..., M, M represents the number of test simulations, and Tbp is the normal ambient temperature around the bolt under normal conditions.

[0058] S103. The ambient temperature around the bolt under normal conditions is obtained multiple times by the temperature sensor, and the standard temperature Tc of the bolt surface under normal conditions is obtained by substituting it into the objective function.

[0059] S104, By formula: Where RHc is the standard humidity of the bolt surface under normal conditions, and Q is a constant;

[0060] The data analysis module is used to acquire real-time environmental data B, which includes the real-time temperature Tb and relative humidity RHb around the bolt. Based on the real-time temperature Tb around the bolt and the standard temperature Tc of the bolt surface under normal conditions, the temperature influence coefficient Tx is calculated, and based on the relative humidity RHb around the bolt and the standard humidity RHc of the bolt surface under normal conditions, the humidity influence coefficient RHx is calculated. By monitoring the environmental data B around the bolt in real time, the temperature influence coefficient Tx and humidity influence coefficient RHx are calculated, thereby enabling real-time adjustment of the bolt evaluation temperature Tk and evaluation humidity RHk. This allows for real-time monitoring of the bolt's working status and effective monitoring of bolt wear.

[0061] The specific process for calculating the temperature influence coefficient and humidity influence coefficient is as follows:

[0062] S201. Obtain the real-time temperature Tb and relative humidity RHb around the bolt;

[0063] S202, By formula: Where Tx is the temperature influence coefficient and W is a constant;

[0064] S203, via formula: Where RHx is the humidity influence coefficient, and Y is a constant;

[0065] The information judgment module is used to acquire information data A, which includes bolt surface temperature Ta and humidity RHa. Based on bolt surface temperature Ta and temperature influence coefficient Tx, bolt assessment temperature Tk is calculated. Based on bolt surface humidity RHa and humidity influence coefficient RHx, bolt assessment humidity RHk is calculated. Information data A also includes bolt surface axial stress σa. Based on bolt surface axial stress σa, bolt assessment temperature Tk, and bolt assessment humidity RHk, comprehensive wear index Mi is calculated. By calculating comprehensive wear index Mi and setting a comprehensive wear index threshold Mmax, the wear degree of the bolt can be effectively judged and wear signals can be issued in a timely manner, thereby avoiding equipment failures and safety accidents caused by excessive bolt wear.

[0066] The specific process for calculating the comprehensive wear index is as follows:

[0067] S301. Obtain the bolt surface temperature Ta, bolt surface humidity RHa, and bolt surface axial stress σa;

[0068] S302, By formula: Where Tk is the bolt evaluation temperature;

[0069] S303, via formula: Where RHk represents the moisture content of the bolts;

[0070] S304, By formula: Where Mi is the comprehensive wear index and Z is a constant;

[0071] The system presets a comprehensive wear index threshold Mmax, determines the degree of bolt wear based on the preset comprehensive wear index threshold Mmax, generates a bolt wear signal, and sends the bolt wear signal to the alarm reminder unit.

[0072] The specific process for generating bolt wear signals is as follows:

[0073] S601. Obtain the comprehensive wear index Mi of the bolt;

[0074] S602. If Mi is greater than or equal to Mmax, a bolt wear signal is generated and sent to the alarm reminder unit.

[0075] If Mi is less than Mmax, no signal is generated;

[0076] The image analysis module receives and processes bolt image data. First, it preprocesses the bolt image data, then extracts features from the preprocessed bolt image data to obtain a target contour map. Points are plotted along the contour edge of the target contour map to obtain edge contour points and determine the midpoint position of the bolt. The image analysis module uses image data processing technology to obtain a three-dimensional contour map of the bolt and overlays it with a preset standard three-dimensional contour map to calculate the bolt offset index Fi. A preset bolt offset index threshold Fmax is set to effectively determine the degree of bolt offset and promptly issue a loosening signal to ensure the stability and safety of the bolt connection.

[0077] The specific process of processing bolt image data is as follows:

[0078] S401. Preprocessing: The acquired bolt image data is preprocessed through denoising, enhancement, and transformation.

[0079] S402, Feature Extraction: Perform feature extraction on the preprocessed bolt image data, and extract the edge contour based on the size and shape of the bolt in the image data to obtain the target contour map;

[0080] S403. Using a gradient-based projection statistical method, the target contour map is scanned in rows and columns to determine the starting row coordinates, height, column coordinates, and width of the target contour map, thereby locating the target contour map.

[0081] S404. Plot points along the outline edge of the target outline to obtain the edge outline points, and obtain the midpoint position through the edge outline points of the bolt;

[0082] Establish a three-dimensional coordinate system, determine the midpoint coordinates of the bolt and the camera, obtain the three-dimensional contour of the bolt, preset the standard three-dimensional contour of the bolt, overlay the three-dimensional contour of the bolt with the preset standard three-dimensional contour, and calculate the bolt offset index Fi.

[0083] The specific process for calculating the bolt offset index is as follows:

[0084] S501. Establish a three-dimensional coordinate system: Select the midpoint of the bolt as the origin, define the mutually perpendicular directions in the horizontal plane on the bolt as the X-axis and Y-axis directions, and define the Z-axis as perpendicular to the bolt surface and upward.

[0085] S502, Obtain the midpoint coordinates (X0, Y0, Z0) of the bolt and the midpoint coordinates (X... s Y s Z sThe simulated deflection angle θs between the bolt midpoint and the camera midpoint is used to determine the three-dimensional profile of the bolt.

[0086] S503. Based on the camera position, simulate the optimal position for bolt assembly and determine the standard midpoint coordinates of the preset bolt as (X... y Y y Z y This yields the standard three-dimensional profile of the preset bolt;

[0087] S504. Overlay the 3D contour map of the bolt with the preset standard 3D contour map of the bolt. Then, obtain the horizontal and vertical screenshots of the overlaid 3D contour map and the standard 3D contour map of the bolt, and compare them to generate the total overlapping area dlm and the total non-overlapping area elm. The total non-overlapping area elm is the bolt offset. Calculate the bolt offset index according to the following formula. Where b is a constant, Ψ is the offset factor, and Fi is the bolt offset exponent;

[0088] The preset bolt offset index threshold Fmax is used to determine the degree of bolt offset and generate a bolt loosening signal, which is then sent to the alarm reminder unit.

[0089] The specific process for generating a bolt loosening signal is as follows:

[0090] S701, Obtain the bolt offset index Fi;

[0091] S702. If Fi is greater than or equal to Fmax, a bolt loosening signal is generated and sent to the alarm reminder unit.

[0092] If Fi is less than Fmax, no signal is generated;

[0093] The alarm unit includes a wear alarm module and a loosening alarm module. The wear alarm module is used to receive bolt wear signals and issue a wear alarm sound through the wear alarm device to provide an alarm reminder.

[0094] The loosening alarm module is used to receive bolt loosening signals and issue a loosening alarm sound through the loosening alarm device to remind the operator. The wear alarm module and the loosening alarm module in the alarm reminder unit can issue alarm sounds in a timely manner to remind the operator to pay attention to the wear and loosening of the bolts, so as to take timely measures to avoid equipment failure and safety accidents.

[0095] Example 2:

[0096] like Figure 2 As shown, an online detection and alarm method for bolt wear includes the following steps:

[0097] Step 1: Obtain information data A of the bolt body, environmental data B of the surrounding environment, and image data of the bolt, and send information data A, environmental data B, and image data of the bolt to the information analysis unit;

[0098] Step 2: Establish and analyze the bolt working model under normal conditions. Based on the conditions of sunny and windless environment and no bolt wear, establish the bolt working model under normal conditions. By substituting the real-time temperature around the bolt into the objective function, calculate the standard temperature Tc and standard humidity RHc of the bolt surface under normal conditions.

[0099] Step 3: Obtain real-time environmental data B. Real-time environmental data B includes the real-time temperature Tb and relative humidity RHb around the bolt. Calculate the temperature influence coefficient Tx based on the real-time temperature Tb around the bolt and the standard temperature Tc of the bolt surface under normal conditions. Calculate the humidity influence coefficient RHx based on the relative humidity RHb around the bolt and the standard humidity RHc of the bolt surface under normal conditions.

[0100] Step 4: Obtain information data A, which includes bolt surface temperature Ta and humidity RHa. Based on bolt surface temperature Ta and temperature influence coefficient Tx, calculate bolt assessment temperature Tk. Based on bolt surface humidity RHa and humidity influence coefficient RHx, calculate bolt assessment humidity RHk. Information data A also includes bolt surface axial stress σa. Based on bolt surface axial stress σa, bolt assessment temperature Tk, and bolt assessment humidity RHk, calculate comprehensive wear index Mi. Set a preset comprehensive wear index threshold Mmax. Determine the wear degree of the bolt based on the preset comprehensive wear index threshold Mmax and generate a bolt wear signal. Send the bolt wear signal to the alarm reminder unit.

[0101] Step 5: The information analysis unit receives the bolt image data and processes it. First, the bolt image data is preprocessed. Then, the preprocessed bolt image data is used to extract features to obtain a target contour map. Points are plotted along the contour edge of the target contour map to obtain edge contour points and determine the midpoint position of the bolt. A three-dimensional coordinate system is established to determine the midpoint coordinates of the bolt and the camera midpoint, resulting in a three-dimensional contour map of the bolt. A standard three-dimensional contour map of the bolt is preset. The three-dimensional contour map of the bolt is superimposed with the preset standard three-dimensional contour map to calculate the bolt offset index Fi. A bolt offset index threshold Fmax is preset. The degree of bolt offset is judged based on the preset bolt offset index threshold Fmax, and a bolt loosening signal is generated and sent to the alarm reminder unit.

[0102] Step 6: When the wear alarm module receives the bolt wear signal, it will issue a wear alarm sound through the wear alarm device to remind the user. When the loosening alarm module receives the bolt loosening signal, it will issue a loosening alarm sound through the loosening alarm device to remind the user.

[0103] In summary, this invention comprehensively collects bolt body information, surrounding environmental data, and image data to comprehensively assess bolt wear, ensuring the integrity and accuracy of the detection data. By processing the collected data in real time, it quickly calculates the bolt's assessment temperature, assessment humidity, and comprehensive wear index, thereby achieving real-time monitoring and early warning of bolt wear status. Through image processing and analysis, it determines the bolt's midpoint position and establishes a three-dimensional coordinate system to accurately measure the bolt's offset position and offset index. Based on a preset threshold, it judges the bolt's offset index, thereby achieving monitoring of bolt loosening, timely alarm reminders, and reducing safety hazards.

[0104] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each group of sample data; as long as it does not affect the ratio between the parameter and the quantized value, it is acceptable.

[0105] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by means of a device or a combination of computer software and electronic hardware; whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0106] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. An online detection and alarm system for bolt wear, characterized in that, It includes an information acquisition unit, an information analysis unit, and an alarm notification unit; The information acquisition unit includes a bolt data acquisition module, an environmental data acquisition module, and an image information acquisition module. The bolt data acquisition module includes information data A for acquiring the bolt body, environmental data B around the bolt, and image data of the bolt. The information analysis unit includes a model building module, a data analysis module, an information judgment module, and an image analysis module. The model building module is used to receive the aforementioned data, generate bolt wear signals and bolt loosening signals through analysis and calculation, and send the signals to the alarm reminder unit. The alarm reminder unit includes a wear alarm module and a loosening alarm module. The wear alarm module is used to receive bolt wear signals and issue a wear alarm sound through the wear alarm device to provide an alarm reminder.

2. The bolt wear online detection and alarm system according to claim 1, characterized in that, The data analysis module is used to acquire real-time environmental data B, which includes real-time temperature Tb and relative humidity RHb around the bolt. The temperature influence coefficient Tx is calculated based on the real-time temperature Tb around the bolt and the standard temperature Tc of the bolt surface under normal conditions. The humidity influence coefficient RHx is calculated based on the relative humidity RHb around the bolt and the standard humidity RHc of the bolt surface under normal conditions. The information judgment module is used to acquire information data A, which includes bolt surface temperature Ta and humidity RHa. Based on bolt surface temperature Ta and temperature influence coefficient Tx, bolt evaluation temperature Tk is calculated, and based on bolt surface humidity RHa and humidity influence coefficient RHx, bolt evaluation humidity RHk is calculated. Information data A also includes bolt surface axial stress σa. Based on bolt surface axial stress σa, bolt evaluation temperature Tk, and bolt evaluation humidity RHk, comprehensive wear index Mi is calculated. A preset comprehensive wear index threshold Mmax is set, and the bolt wear degree is judged according to the preset comprehensive wear index threshold Mmax. A bolt wear signal is generated and sent to the alarm reminder unit.

3. The bolt wear online detection and alarm system according to claim 2, characterized in that, The image analysis module is used to receive and process the bolt image data. First, the bolt image data is preprocessed. Then, the preprocessed bolt image data is used to extract features to obtain a target contour map. Points are plotted along the contour edge of the target contour map to obtain edge contour points and determine the midpoint position of the bolt. A three-dimensional coordinate system is established to determine the midpoint coordinates of the bolt and the camera midpoint, resulting in a three-dimensional contour map of the bolt. A standard three-dimensional contour map of the bolt is preset. The three-dimensional contour map of the bolt is superimposed with the preset standard three-dimensional contour map to calculate the bolt offset index Fi. A bolt offset index threshold Fmax is preset. The degree of bolt offset is determined based on the preset bolt offset index threshold Fmax, and a bolt loosening signal is generated and sent to the alarm reminder unit.

4. The bolt wear online detection and alarm system according to claim 3, characterized in that, The specific working process for calculating the standard temperature and standard humidity of the bolt surface under normal conditions is as follows: S101. Based on normal information data A and normal environmental data B, the normal information data A includes the normal surface temperature Tap and normal humidity RHap of the bolt, and the normal environmental data B includes the normal ambient temperature Tbp and normal relative humidity RHbp around the bolt. S102. Establish a bolt working model under normal conditions, whose objective function can be expressed as: Where f(x) represents the objective function, Tap represents the normal surface temperature of the bolt under normal conditions, m = 1, 2, 3, ..., M, M represents the number of test simulations, and Tbp is the normal ambient temperature around the bolt under normal conditions. S103. The ambient temperature around the bolt under normal conditions is obtained multiple times by the temperature sensor, and the standard temperature Tc of the bolt surface under normal conditions is obtained by substituting it into the objective function. S104, By formula: Where RHc is the standard humidity of the bolt surface under normal conditions, and Q is a constant.

5. The bolt wear online detection and alarm system according to claim 1, characterized in that, The specific process for calculating the temperature influence coefficient and humidity influence coefficient is as follows: S201. Obtain the real-time temperature Tb and relative humidity RHb around the bolt; S202, By formula: Where Tx is the temperature influence coefficient and W is a constant; S203, via formula: Where RHx is the humidity influence coefficient and Y is a constant.

6. The bolt wear online detection and alarm system according to claim 3, characterized in that, The specific process for calculating the comprehensive wear index is as follows: S301. Obtain the bolt surface temperature Ta, bolt surface humidity RHa, and bolt surface axial stress σa; S302, By formula: Where Tk is the bolt evaluation temperature; S303, via formula: Where RHk represents the moisture content of the bolts; S304, By formula: Where Mi is the comprehensive wear index and Z is a constant.

7. The bolt wear online detection and alarm system according to claim 1, characterized in that, The specific process of processing bolt image data is as follows: S401. Preprocessing: The acquired bolt image data is preprocessed through denoising, enhancement, and transformation. S402, Feature Extraction: Perform feature extraction on the preprocessed bolt image data, and extract the edge contour based on the size and shape of the bolt in the image data to obtain the target contour map; S403. Using a gradient-based projection statistical method, the target contour map is scanned in rows and columns to determine the starting row coordinates, height, column coordinates, and width of the target contour map, thereby locating the target contour map. S404. Plot points along the outline edge of the target outline to obtain the edge outline points, and obtain the midpoint position through the edge outline points of the bolt.

8. The bolt wear online detection and alarm system according to claim 1, characterized in that, The specific process for calculating the bolt offset index is as follows: S501. Establish a three-dimensional coordinate system: Select the midpoint of the bolt as the origin, define the mutually perpendicular directions in the horizontal plane on the bolt as the X-axis and Y-axis directions, and define the Z-axis as perpendicular to the bolt surface and upward. S502, Obtain the midpoint coordinates (X0, Y0, Z0) of the bolt and the midpoint coordinates (X... s Y s Z s The simulated deflection angle θs between the bolt midpoint and the camera midpoint is used to determine the three-dimensional profile of the bolt. S503. Based on the camera position, simulate the optimal position for bolt assembly and determine the standard midpoint coordinates of the preset bolt as (X... y Y y Z y This yields the standard three-dimensional profile of the preset bolt; S504. Overlay the 3D contour map of the bolt with the preset standard 3D contour map of the bolt. Then, obtain the horizontal and vertical screenshots of the overlaid 3D contour map and the standard 3D contour map of the bolt, and compare them to generate the total overlapping area dlm and the total non-overlapping area elm. The total non-overlapping area elm is the bolt offset. Calculate the bolt offset index according to the following formula. Where b is a constant, Ψ is the offset factor, and Fi is the bolt offset index.

9. A method for online detection and alarm of bolt wear, applied to the online detection and alarm system for bolt wear as described in any one of claims 1-8, characterized in that, Includes the following steps: Step 1: Obtain information data A of the bolt body, environmental data B of the surrounding environment, and image data of the bolt, and send information data A, environmental data B, and image data of the bolt to the information analysis unit; Step 2: Establish and analyze the bolt working model under normal conditions. Based on the conditions of sunny and windless environment and no bolt wear, establish the bolt working model under normal conditions. By substituting the real-time temperature around the bolt into the objective function, calculate the standard temperature Tc and standard humidity RHc of the bolt surface under normal conditions. Step 3: Obtain real-time environmental data B, which includes the real-time temperature Tb and relative humidity RHb around the bolt. Calculate the temperature influence coefficient Tx based on the real-time temperature Tb around the bolt and the standard surface temperature Tc of the bolt under normal conditions. Calculate the humidity influence coefficient RHx based on the relative humidity RHb around the bolt and the standard surface humidity RHc of the bolt under normal conditions. Step 4: Obtain information data A, which includes bolt surface temperature Ta and humidity RHa. Based on bolt surface temperature Ta and temperature influence coefficient Tx, calculate bolt assessment temperature Tk. Based on bolt surface humidity RHa and humidity influence coefficient RHx, calculate bolt assessment humidity RHk. Information data A also includes bolt surface axial stress σa. Based on bolt surface axial stress σa, bolt assessment temperature Tk, and bolt assessment humidity RHk, calculate comprehensive wear index Mi. Set a preset comprehensive wear index threshold Mmax. Determine the wear degree of the bolt based on the preset comprehensive wear index threshold Mmax and generate a bolt wear signal. Send the bolt wear signal to the alarm reminder unit. Step 5: The information analysis unit receives the bolt image data and processes it. First, the bolt image data is preprocessed. Then, the preprocessed bolt image data is used to extract features to obtain a target contour map. Points are plotted along the contour edge of the target contour map to obtain edge contour points and determine the midpoint position of the bolt. A three-dimensional coordinate system is established to determine the midpoint coordinates of the bolt and the camera midpoint, resulting in a three-dimensional contour map of the bolt. A standard three-dimensional contour map of the bolt is preset. The three-dimensional contour map of the bolt is superimposed with the preset standard three-dimensional contour map to calculate the bolt offset index Fi. A bolt offset index threshold Fmax is preset. The degree of bolt offset is judged based on the preset bolt offset index threshold Fmax, and a bolt loosening signal is generated and sent to the alarm reminder unit. Step 6: When the wear alarm module receives the bolt wear signal, it will issue a wear alarm sound through the wear alarm device to remind the user. When the loosening alarm module receives the bolt loosening signal, it will issue a loosening alarm sound through the loosening alarm device to remind the user.

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