Non-contact fault diagnosis device for hoisting mechanism of port automatic crane

Abstract

The invention relates to the technical field of crane fault diagnosis, in particular to a port automation crane hoisting mechanism non-contact fault diagnosis device which comprises a transverse component, an optical monitoring unit, an acoustic monitoring unit and an adjusting assembly. The adjusting assembly comprises an arc-shaped sliding rail, a supporting block, two telescopic units and a rotating unit; the transverse component is started to drive the optical monitoring unit and the acoustic monitoring unit to transversely move, a sensor can move along the lifting mechanism, the telescopic unit drives the sensor of the acoustic monitoring unit to independently stretch out and draw back, and the sensor is moved to a key component of the lifting mechanism to conduct acoustic monitoring by means of the characteristic that the sensor is small in size. Meanwhile, the rotating unit drives the optical monitoring unit to rotate to adjust the detection angle, so that multi-angle and multi-dimensional adjustment can be carried out on optical and acoustic sensors, the device is suitable for large-range monitoring of the hoisting mechanism, and then monitored signals are analyzed to obtain a fault diagnosis result.

Description

Technical Field

[0001] The invention relates to the technical field of crane fault diagnosis, and in particular to a non-contact fault diagnosis device for a hoisting mechanism of a port automated crane. Background Art

[0002] At present, in the automated cranes in ports, in order to ensure safety and reliability, it is necessary to diagnose the faults of the crane's hoisting mechanism. The non-contact fault diagnosis technology uses advanced sensors and data processing algorithms to monitor the working status of the crane's hoisting mechanism in real time. By setting sensors, it focuses on monitoring the status of the hoisting mechanism and its surrounding motors and winches. By designing an optically and acoustically coupled non-contact fault diagnosis device, it can identify, diagnose and locate problems such as abnormal vibration, abnormal temperature, deformation, loose bolts, abnormal noise, high friction caused by poor bearing coaxiality, etc.

[0003] In the prior art, the sensors of the non-contact fault diagnosis device are usually not directly installed on the lifting mechanism. The non-contact sensors measure the fault signals emitted by the target, thereby remotely detecting the fault. However, the lifting mechanism of the crane is usually large in size, and the non-contact sensors are only fixed in one area, and it is impossible to perform multi-dimensional fault diagnosis around the lifting mechanism, especially for the components on both sides of the lifting mechanism that are far apart. The sensors cannot remotely detect the fault signals, resulting in a limited detection range, which affects the accuracy of the diagnosis. Summary of the invention

[0004] The purpose of the present invention is to provide a non-contact fault diagnosis device for the lifting mechanism of a port automated crane, so as to solve the problem that the lifting mechanism of the crane in the prior art is usually large in size, the non-contact sensor is only fixed in one area, and it is impossible to perform multi-dimensional fault diagnosis around the lifting mechanism, especially for components on both sides of the lifting mechanism that are far apart, the sensor cannot remotely detect the fault signal, resulting in a limited detection range and affecting the accuracy of the diagnosis.

[0005] To achieve the above-mentioned object, the present invention provides a non-contact fault diagnosis device for a hoisting mechanism of an automated port crane, comprising a transverse component, an optical monitoring unit, an acoustic monitoring unit, an adjustment component and a diagnosis module, wherein the optical monitoring unit and the acoustic monitoring unit are both arranged above the transverse component, and the diagnosis module is used to perform fault diagnosis in combination with data collected by the optical monitoring unit and the acoustic monitoring unit;

[0006] The adjustment assembly includes an arc-shaped slide rail, a support block, two telescopic units and a rotating unit. The arc-shaped slide rail is arranged above the transverse component, the support block is arranged on one side of the arc-shaped slide rail, the two telescopic units are symmetrically arranged on both sides of the support block, the rotating unit is arranged at one end of the support block, the optical monitoring unit is arranged on the rotating unit, and the acoustic monitoring unit is arranged on the two telescopic units.

[0007] Wherein, the diagnosis module includes an artificial intelligence analysis submodule, a display screen, a duration setting submodule and an output viewing submodule, and the artificial intelligence analysis submodule, the display screen, the duration setting submodule and the output viewing submodule are connected in sequence;

[0008] The artificial intelligence analysis submodule is used to analyze and evaluate data by building a model using an artificial intelligence algorithm, thereby diagnosing faults;

[0009] The display screen is used to present relevant diagnostic results and issue an alarm for major faults through sound and light;

[0010] The duration setting submodule is used to divide the diagnosis duration into different duration scales such as real-time, hourly and monthly, and to predict and warn trends of different faults;

[0011] The output viewing submodule is used to display the time domain, frequency domain results and axis trajectory diagram of the diagnosis on the display screen.

[0012] Wherein, the artificial intelligence analysis submodule includes a data preprocessing unit, a key feature extraction unit and a model construction unit, and the data preprocessing unit, the key feature extraction unit and the model construction unit are connected in sequence;

[0013] The data preprocessing unit is used to preprocess the data collected by the optical monitoring unit and the acoustic monitoring unit to obtain preprocessed data;

[0014] The key feature extraction unit is used to extract the key feature parameters of the fault in the preprocessed data;

[0015] The model building unit is used to build a fault diagnosis model based on the extracted key feature parameters.

[0016] The duration setting submodule includes a time scale analysis unit, a space scale analysis unit, a multi-measurement point analysis unit, a single-side point analysis unit and a regional analysis unit, and the time scale analysis unit, the space scale analysis unit, the multi-measurement point analysis unit, the single-side point analysis unit and the regional analysis unit are connected in sequence;

[0017] The time scale analysis unit is used to analyze the detected data in combination with different time scales, and compare it with the constructed fault diagnosis model to identify the fault type;

[0018] The spatial scale analysis unit is used to more accurately locate the fault by using the spatial distribution feature method after identifying the specific location and range of the fault, and compare it with the constructed fault diagnosis model to identify the fault type;

[0019] The multi-measurement point analysis unit is used to measure the data of each key part in turn, comprehensively collect the operation data, conduct more accurate analysis by comparing the data of different measurement points, and compare with the constructed fault diagnosis model to identify the fault type;

[0020] The single-side point analysis unit is used to perform in-depth analysis on the data of a specific measuring point through a time series analysis method, and compare it with the constructed fault diagnosis model to identify the fault type;

[0021] The regional analysis unit is used to divide the crane hoisting mechanism into different areas, conduct an overall evaluation of each area, and compare it with the constructed fault diagnosis model to identify the fault type.

[0022] Among them, the adjustment assembly also includes two lifting components, a stabilizing plate, a driving unit, a supporting shell, a rotating inner shell, a telescopic component, a processor and a rotating unit, the two lifting components are sequentially arranged at the output ends of the transverse component, the output ends of the two lifting components are fixedly connected to the arc-shaped slide rail, a slide groove is arranged on one side of the transverse component, one end of the stabilizing plate is fixedly connected to the two lifting components, and the other end of the stabilizing plate is slidably connected to the slide groove, the driving unit is arranged on the arc-shaped slide rail, the supporting shell is arranged above the driving unit, the rotating inner shell is rotatably connected to the supporting shell and is located inside the supporting shell, the telescopic component is arranged inside the rotating inner shell, the processor is arranged on the inner wall of the rotating inner shell, and the rotating unit is arranged on the supporting shell and the rotating inner shell.

[0023] Wherein, the driving unit includes a slider, a first driving component and a roller, the slider is slidably connected to the arc-shaped slide rail, the first driving component is arranged inside the slider, the output end of the first driving component is fixedly connected to the roller, and the roller is in contact with the arc-shaped slide rail.

[0024] Wherein, the rotating unit comprises a rotating component and a plurality of limiting mechanisms, the rotating component is arranged on one side of the supporting shell, the output end of the rotating component passes through the supporting shell and is fixedly connected to the rotating inner shell, and the plurality of limiting mechanisms are sequentially arranged inside the supporting shell;

[0025] The limiting mechanism includes a limiting block, a limiting groove, two electromagnets, two telescopic rods and two springs. The limiting block is fixedly connected to the outer wall of the rotating inner shell, the limiting groove is arranged inside the supporting outer shell, the limiting block and the limiting groove are adapted to each other, the two electromagnets are respectively arranged at the limiting groove and the inner wall of the supporting shell, the two ends of the two telescopic rods are respectively fixedly connected to the limiting groove and the inner wall of the supporting shell, the two ends of the two springs are respectively movably connected to the limiting groove and the inner wall of the supporting shell, the spring is sleeved on the outside of the telescopic rod, and the two springs are distributed on both sides of the electromagnet.

[0026] Among them, the telescopic unit includes a mounting groove, a second driving component, a gear and a rack. The mounting groove is fixedly connected to the support block and is located on one side of the support block. The second driving component is arranged above the mounting groove. The rack is slidably connected to the mounting groove and is located inside the mounting groove. The output end of the second driving component passes through the mounting groove and is fixedly connected to the gear. The gear and the rack are meshed with each other.

[0027] Wherein, the rotating unit includes a rotating block and a rotating component, the rotating block is rotatably connected to one end of the supporting block, the other end of the supporting block is fixedly connected to the output end of the telescopic component, and the rotating component is arranged at the connection between the rotating block and the supporting block.

[0028] Wherein, the optical monitoring unit comprises a laser vibrometer, an infrared thermal imager and a displacement sensor, and the laser rangefinder, the infrared thermal imager and the displacement sensor are sequentially arranged on the rotating block;

[0029] The acoustic monitoring unit comprises an acoustic coupler and an acoustic sensor, and the acoustic coupler and the acoustic sensor are respectively arranged at one end of the corresponding rack.

[0030] The present invention provides a non-contact fault diagnosis device for a hoisting mechanism of an automated port crane. The device is started by the transverse component, driving the optical monitoring unit and the acoustic monitoring unit to move transversely, so that the sensor can be moved along the hoisting mechanism and slide in an arc shape on the arc slide rail to move around the hoisting mechanism. The telescopic unit drives the sensor of the acoustic monitoring unit to telescope separately, and utilizes the small size of the sensor to move to the key component of the hoisting mechanism for acoustic monitoring. At the same time, the rotating unit drives the optical monitoring unit to rotate and adjust the detection angle, thereby enabling the optical and acoustic sensors to be adjusted at multiple angles and dimensions, with angle adjustment for optics and distance adjustment for acoustics. The device is suitable for large-scale monitoring of the hoisting mechanism, and the monitored signal is analyzed to obtain a fault diagnosis result, thereby improving the accuracy of the diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0032] Figure 1 It is a schematic diagram of the overall structure of the present invention.

[0033] Figure 2 It is a side view of the whole of the present invention.

[0034] Figure 3 The present invention Figure 2 AA line section view.

[0035] Figure 4 The present invention Figure 3 BB line cross-sectional view.

[0036] Figure 5 The present invention Figure 3 CC line section view.

[0037] Figure 6 The present invention Figure 1 Enlarged view of the local structure at D.

[0038] Figure 7 The present invention Figure 3 Enlarged view of the local structure at E.

[0039] Figure 8 It is a schematic structural diagram of the driving unit of the present invention.

[0040] Fig. 9 It is a schematic diagram of the diagnostic module of the present invention.

[0041] Fig.10 It is a schematic diagram of the artificial intelligence analysis submodule of the present invention.

[0042] Fig.11 It is a schematic diagram of the duration setting submodule of the present invention.

[0043] 1- horizontal component, 2- arc slide rail, 3- support block, 4- lifting component, 5- stable plate, 6- supporting shell, 7- rotating inner shell, 8- telescopic component, 9- processor, 10- slide groove, 11- slider, 12- first driving component, 13- roller, 14- rotating component, 15- limit block, 16- limit groove, 17- electromagnet, 18- telescopic rod, 19 spring, 20- installation groove, 21- second driving component, 22- gear, 23- rack, 24- rotating block, 25- rotating component, 26- laser vibrometer, 2 7-infrared thermal imager, 28-displacement sensor, 29-acoustic coupler, 30-acoustic sensor, 31-diagnosis module, 32-artificial intelligence analysis submodule, 321-data preprocessing unit, 322-key feature extraction unit, 323-model building unit, 33-display screen, 34-duration setting submodule, 341-time scale analysis unit, 342-spatial scale analysis unit, 343-multi-measurement point analysis unit, 344-single side point analysis unit, 345-regional analysis unit, 35-output viewing submodule. DETAILED DESCRIPTION

[0044] Embodiments of the present invention are described in detail below. Examples of the embodiments are shown in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, but should not be construed as limiting the present invention.

[0045] See also Figures 1 to 11 The present invention provides a non-contact fault diagnosis device for a lifting mechanism of an automated port crane, comprising a transverse component 1, an optical monitoring unit, an acoustic monitoring unit and an adjustment component, wherein the adjustment component comprises an arc-shaped slide rail 2, a support block 3, two telescopic units and a rotating unit, wherein the adjustment component further comprises two lifting components 4, a stabilizing plate 5, a driving unit, a supporting outer shell 6, a rotating inner shell 7, a telescopic component 8, a processor 9 and a rotating unit, wherein the driving unit comprises a slider 11, a first driving component 12 and a roller 13, wherein the rotating unit comprises a rotating component 14 and a plurality of limiting mechanisms, wherein the limiting mechanisms comprise a limiting block 15, a limiting groove 16, two electromagnets 17, two telescopic rods 18 and two springs 19, wherein the telescopic unit comprises an installation groove 20, a second driving component 21, a gear 22 and a rack 23, wherein the rotating unit comprises a rotating block 24 and a rotating component 25, wherein the optical monitoring unit comprises a laser vibrometer 26, an infrared thermal imager 27 and a displacement sensor 28, wherein the acoustic monitoring unit comprises an acoustic coupler 29 and an acoustic sensor 30.

[0046] Wherein, the optical monitoring unit and the acoustic monitoring unit are both arranged above the transverse component 1, the arc-shaped slide rail 2 is arranged above the transverse component 1, the support block 3 is arranged on one side of the arc-shaped slide rail 2, the two telescopic units are symmetrically arranged on both sides of the support block 3, the rotating unit is arranged at one end of the support block 3, the optical monitoring unit is arranged on the rotating unit, and the acoustic monitoring unit is arranged on the two telescopic units. The transverse component 1 is started to drive the optical monitoring unit and the acoustic monitoring unit to move laterally, and the sensor can be moved along the lifting mechanism, and at the same time, it slides in an arc on the arc-shaped slide rail 2 and can move around the lifting mechanism. The telescopic unit drives the sensor of the acoustic monitoring unit to extend and retract separately, and uses the small size of the sensor to move to the key component of the lifting mechanism for acoustic monitoring. At the same time, the rotating unit drives the optical monitoring unit to rotate and adjust the detection angle; at the same time, the outer side of the transverse component 1 is also provided with a mounting hole, which is convenient for installation near the lifting mechanism.

[0047] Secondly, the two lifting components 4 are sequentially arranged at the output ends of the transverse component 1, and the output ends of the two lifting components 4 are fixedly connected to the arc-shaped slide rail 2. A slide groove 10 is arranged on one side of the transverse component 1, one end of the stabilizing plate 5 is fixedly connected to the two lifting components 4, and the other end of the stabilizing plate 5 is slidably connected to the slide groove 10. The driving unit is arranged on the arc-shaped slide rail 2, the supporting shell 6 is arranged above the driving unit, the rotating inner shell 7 is rotatably connected to the supporting shell 6 and is located inside the supporting shell 6, the telescopic component 8 is arranged inside the rotating inner shell 7, the processor 9 is arranged on the inner wall of the rotating inner shell 7, and the rotating unit is arranged on the supporting shell 6 and the rotating inner shell 7. The lifting component 4 is a cylinder, which can drive the arc-shaped slide rail 2 to be raised and lowered, the stabilizing plate 5 increases the stability of the lifting component 4, and the transverse component 1 is an electric slide rail; the driving unit can drive the support block 3 to move on the arc-shaped slide rail 2, the supporting outer shell 6 supports the rotating inner shell 7, and the telescopic component 8 is a cylinder, which can drive the support block 3 and multiple sensors to be telescopically adjusted; the processor 9 is electrically connected to each component, and instructions are sent remotely by the staff and controlled by the processor 9; the rotating unit can drive the rotating inner shell 7 to rotate, thereby adjusting the position of the support block 3 and multiple sensors.

[0048] At the same time, the slider 11 is slidably connected to the arc-shaped slide rail 2, the first driving component 12 is arranged inside the slider 11, and the output end of the first driving component 12 is fixedly connected to the roller 13, and the roller 13 is in contact with the arc-shaped slide rail 2. The first driving component 12 is a self-locking motor, and the first driving component 12 is started to drive the roller 13 to rotate and contact the arc-shaped slide rail 2, thereby driving the slider 11 to slide on the arc-shaped slide rail 2.

[0049] In addition, the rotating component 14 is arranged on one side of the supporting outer shell 6, the output end of the rotating component 14 passes through the supporting outer shell 6, and is fixedly connected to the rotating inner shell 7, and a plurality of the limiting mechanisms are sequentially arranged inside the supporting outer shell 6. The rotating component 14 is a motor, which drives the rotating inner shell 7 to rotate inside the supporting outer shell 6, and then is limited and locked by the limiting mechanism.

[0050] Then, the limit block 15 is fixedly connected to the outer wall of the rotating inner shell 7, the limit groove 16 is arranged inside the supporting outer shell 6, the limit block 15 and the limit groove 16 are adapted to each other, the two electromagnets 17 are respectively arranged on the limit groove 16 and the inner wall of the supporting outer shell 6, the two ends of the two telescopic rods 18 are respectively fixedly connected to the limit groove 16 and the inner wall of the supporting outer shell 6, the two ends of the two springs 19 are respectively movably connected to the limit groove 16 and the inner wall of the supporting outer shell 6, the spring 19 is sleeved on the outside of the telescopic rod 18, and the two springs 19 are distributed on both sides of the electromagnet 17. After the rotating inner shell 7 rotates 90 degrees, the limit block 15 can be adapted to the limit groove 16. At this time, the electromagnet 17 is powered off, and then the spring 19 rebounds, driving the limit groove 16 and the limit block 15 to adapt and limit; when the rotating inner shell 7 needs to be adjusted, the two electromagnets 17 are energized and attract each other, thereby making the limit groove 16 move away from the limit block 15 and canceling the limit.

[0051] Again, the mounting slot 20 is fixedly connected to the support block 3 and is located on one side of the support block 3. The second driving component 21 is arranged above the mounting slot 20. The rack 23 is slidably connected to the mounting slot 20 and is located inside the mounting slot 20. The output end of the second driving component 21 passes through the mounting slot 20 and is fixedly connected to the gear 22. The gear 22 and the rack 23 are meshed with each other. The entire telescopic unit of the mounting slot 20 is supported. The second driving component 21 is a self-locking motor, which drives the gear 22 to rotate. Through cooperation, it drives the rack 23 to telescopically move, and then drives the acoustic sensor 30 installed on the rack 23 to approach the lifting mechanism alone for acoustic detection. When acoustic detection is performed on important components of the lifting mechanism, the accuracy of acoustic detection is improved by approaching the component.

[0052] Furthermore, the rotating block 24 is rotatably connected to one end of the supporting block 3, and the other end of the supporting block 3 is fixedly connected to the output end of the telescopic component 8, and the rotating component 25 is disposed at the connection between the rotating block 24 and the supporting block 3. The rotating component 25 is a self-locking motor, which drives the rotating block 24 to rotate, thereby driving the installed multiple optical sensors to adjust the angle.

[0053] Finally, the laser rangefinder, the infrared thermal imager 27 and the displacement sensor 28 are sequentially arranged on the rotating block 24 ; the acoustic coupler 29 and the acoustic sensor 30 are respectively arranged at one end of the corresponding rack 23 . The laser rangefinder uses the principle of laser triangulation or interference method to measure the vibration information of the object in a non-contact manner, including amplitude, frequency and phase, and is suitable for monitoring abnormal vibration of rotating parts 14 such as bearings and gears 22; the infrared thermal imager 27 obtains its temperature distribution information in a non-contact manner by measuring the infrared radiation on the surface of the object, and is used to monitor the temperature anomaly of the equipment, such as overheating of components such as motors and transformers; the displacement sensor 28 uses optical principles (laser ranging) to measure the displacement change of the object in a non-contact manner, and is used to monitor the deformation of the equipment, such as structural displacement monitoring of bridges and buildings; the acoustic coupler 29 transmits sound waves such as ultrasonic waves from one medium to another, such as transmitting sound waves to the inside of the equipment through materials such as water or gel for detection, and is used in conjunction with the acoustic sensor 30 to monitor acoustic characteristics such as abnormal noise and friction noise inside the equipment; the acoustic sensor 30 collects sound signals during the operation of the equipment and converts them into electrical signals for subsequent processing, and is suitable for monitoring abnormal noise caused by bearing coaxiality difference and periodic sounds caused by gear 22 wear.

[0054] The artificial intelligence analysis submodule 32 is used to analyze and evaluate data by building a model using an artificial intelligence algorithm, thereby diagnosing faults;

[0055] Specifically include:

[0056] The data preprocessing unit 321 is used to preprocess the data collected by the optical monitoring unit and the acoustic monitoring unit to obtain preprocessed data;

[0057] High-precision sensors (optical sensors, acoustic sensors 30) are used to collect the operating data of the crane hoisting mechanism in real time, including vibration, temperature, and sound. The collected data is cleaned to remove noise, duplication, and outliers to obtain preprocessed data.

[0058] The key feature extraction unit 322 is used to extract the key feature parameters of the fault in the pre-processed data;

[0059] Extract key characteristic parameters from preprocessed data, including vibration frequency, amplitude, and temperature change trend, to simplify subsequent analysis.

[0060] The model building unit 323 is used to build a fault diagnosis model based on the extracted key feature parameters.

[0061] Use artificial intelligence algorithms (principal component analysis PCA) to extract and select features from preprocessed data; build a machine learning model (neural network) based on the extracted feature parameters; use historical fault data and normal operation data to train the model so that it can accurately identify fault characteristics; optimize model parameters and evaluate performance to ensure its stability and accuracy in practical applications, thereby completing model establishment and training; apply the trained model to the real-time monitoring system to perform real-time analysis on the operating data of the crane's hoisting mechanism. When abnormal data is detected, the early warning mechanism is immediately triggered to remind the operator to take corresponding measures.

[0062] The display screen 33 is used to present relevant diagnostic results and issue an alarm for major faults through sound and light;

[0063] The display screen 33 can display different diagnostic results for the staff to view, and send out an alarm for major faults through sound and light. At the same time, it also displays different display results output by the output viewing submodule 35.

[0064] The duration setting submodule 34 is used to divide the diagnosis duration into different duration scales such as real-time, hourly and monthly, and to predict and warn trends of different faults;

[0065] Specifically include:

[0066] The time scale analysis unit 341 is used to analyze the detected data in combination with different time scales, and compare it with the constructed fault diagnosis model to identify the fault type;

[0067] Combined with data at different time scales (such as real-time, hourly, monthly, etc.), analysis is performed to identify the development trend and periodicity of faults. The identified time scale data is compared with the constructed fault diagnosis model to determine whether there is a difference. If there is a difference, it means that a fault exists. In addition, time series analysis algorithms are used to predict and warn of faults.

[0068] The spatial scale analysis unit 342 is used to more accurately locate the fault by using the spatial distribution feature method after identifying the specific location and range of the fault, and compare it with the constructed fault diagnosis model to identify the fault type;

[0069] The identified spatial scale data is compared with the constructed fault diagnosis model to determine whether there is a difference. If there is a difference, it means that a fault exists. Different parts and areas of the crane hoisting mechanism are monitored and analyzed to identify the specific location and scope of the fault. Spatial distribution characteristics, clustering algorithms and other methods are used to more accurately locate and evaluate the fault.

[0070] The multi-measurement point analysis unit 343 is used to measure the data of each key part in turn, comprehensively collect the operation data, compare the data of different measurement points for more accurate analysis, and compare with the constructed fault diagnosis model to identify the fault type;

[0071] Through multi-dimensional and multi-angle adjustment, the sensor is continuously moved between the key parts of the crane hoisting mechanism, but it remains stable during each detection until the result is detected and then moves again. The operation is repeated to perform multiple measurement points to achieve the effect of comprehensive collection of operation data; by comparing the data of different measurement points, the specific location and range of the fault are identified, and combined with the spatial distribution characteristics, the fault is more accurately located and analyzed; then the identified multi-measurement point data is compared with the constructed fault diagnosis model to determine whether there is a difference. If there is a difference, it means that a fault exists.

[0072] The single-side point analysis unit 344 is used to perform in-depth analysis on the data of a specific measuring point through a time series analysis method, and compare it with the constructed fault diagnosis model to identify the fault type;

[0073] Conduct in-depth analysis on the data of specific measuring points (key parameters of vibration acceleration and temperature), extract fault feature information through time series analysis, spectrum analysis and other methods, and judge the type and severity of the fault based on the analysis results; in specific operations: compare the identified single measuring point data with the constructed fault diagnosis model to determine whether there is a difference. If there is a difference, it means there is a fault.

[0074] The regional analysis unit 345 is used to divide the crane hoisting mechanism into different regions, perform an overall evaluation on each region, and compare it with the constructed fault diagnosis model to identify the fault type.

[0075] The crane hoisting mechanism is divided into different areas (motor area and drum area), and each area is evaluated as a whole to identify the area with possible failure risk. This area is then monitored in detail, and the monitored data is compared with the constructed fault diagnosis model to obtain the fault type.

[0076] The output viewing submodule 35 is used to display the diagnosis results in the time domain and frequency domain and the axis trajectory diagram on the display screen 33.

[0077] Time domain results: Through the time domain analysis method, the time domain characteristic parameters of vibration, temperature and other data are extracted, and the time domain waveform is drawn to show the dynamic change process of the data. According to the time domain characteristic parameters and waveform, the type and severity of the fault are judged;

[0078] Frequency domain results: Use signal processing techniques such as Fourier transform to convert time domain data into frequency domain data, draw a spectrum diagram, and display the frequency distribution characteristics of the data. According to the frequency components and peak sizes in the spectrum diagram, the specific location and type of the fault can be determined;

[0079] Axis trajectory diagram: For the rotating component 14 (bearings, motors), an axis trajectory diagram is drawn to show its motion trajectory. By analyzing the shape, size, stability and other characteristics of the axis trajectory diagram, it is determined whether there is any abnormality in the rotating component 14. Combined with other diagnostic results, the fault of the rotating component 14 is more accurately located and analyzed, and the time domain, frequency domain results and the axis trajectory diagram are output to the display screen 33 for display.

[0080] When using the non-contact fault diagnosis device for the lifting mechanism of a port automated crane of the present embodiment, the lateral component 1 is started to drive the optical sensor and the acoustic sensor 30 to move laterally, and then move along the lifting mechanism, so that the two ends of the lifting mechanism that are far away can be monitored over a large range to avoid inaccurate monitoring due to excessive distance. At the same time, the arc-shaped slide rail 2 slides in an arc shape and can move around the lifting mechanism. The second driving component 21 drives the gear 22 to rotate, and through cooperation, drives the rack 23 to move telescopically, thereby driving the acoustic sensor 30 installed on the rack 23 to approach the lifting mechanism alone for acoustic detection, thereby When acoustic detection is performed on important components of the lifting mechanism, the accuracy of acoustic detection is improved by approaching the component. By utilizing the small size of the sensor, it is moved to the key components of the lifting mechanism for acoustic monitoring. At the same time, the rotating component 25 drives the rotating block 24 to rotate, thereby driving the installed multiple optical sensors to adjust their angles. Through the above-mentioned structural setting, the optical and acoustic sensors can be adjusted at multiple angles and dimensions, the angle can be adjusted for optics, and the distance can be adjusted for acoustics. Therefore, it can be suitable for large-scale monitoring of the lifting mechanism, and the monitored signal can be analyzed to obtain fault diagnosis results, thereby improving the accuracy of diagnosis.

[0081] What is disclosed above is only one or more preferred embodiments of the present application, and cannot be used to limit the scope of rights of the present application. Ordinary technicians in this field can understand that all or part of the processes of implementing the above embodiments and equivalent changes made according to the claims of the present application are still within the scope covered by the present application.

Claims

1. A non-contact fault diagnosis device for a hoisting mechanism of an automated port crane, comprising a transverse component, an optical monitoring unit, an acoustic monitoring unit and a diagnostic module, wherein the optical monitoring unit and the acoustic monitoring unit are both arranged above the transverse component, and the diagnostic module is used to perform fault diagnosis in combination with data collected by the optical monitoring unit and the acoustic monitoring unit, and is characterized in that: Also included are adjustment components; The adjustment assembly includes an arc-shaped slide rail, a support block, two telescopic units and a rotating unit. The arc-shaped slide rail is arranged above the transverse component, the support block is arranged on one side of the arc-shaped slide rail, the two telescopic units are symmetrically arranged on both sides of the support block, the rotating unit is arranged at one end of the support block, the optical monitoring unit is arranged on the rotating unit, and the acoustic monitoring unit is arranged on the two telescopic units.

2. The non-contact fault diagnosis device for the hoisting mechanism of the port automated crane according to claim 1, characterized in that: The diagnosis module includes an artificial intelligence analysis submodule, a display screen, a duration setting submodule and an output viewing submodule, wherein the artificial intelligence analysis submodule, the display screen, the duration setting submodule and the output viewing submodule are connected in sequence; The artificial intelligence analysis submodule is used to analyze and evaluate data by building a model using an artificial intelligence algorithm, thereby diagnosing faults; The display screen is used to present relevant diagnostic results and issue an alarm for major faults through sound and light; The duration setting submodule is used to divide the diagnosis duration into different duration scales such as real-time, hourly and monthly, and to predict and warn trends of different faults; The output viewing submodule is used to display the time domain, frequency domain results and axis trajectory diagram of the diagnosis on the display screen.

3. The non-contact fault diagnosis device for the hoisting mechanism of the port automated crane according to claim 2, characterized in that: The artificial intelligence analysis submodule includes a data preprocessing unit, a key feature extraction unit and a model building unit, and the data preprocessing unit, the key feature extraction unit and the model building unit are connected in sequence; The data preprocessing unit is used to preprocess the data collected by the optical monitoring unit and the acoustic monitoring unit to obtain preprocessed data; The key feature extraction unit is used to extract the key feature parameters of the fault in the preprocessed data; The model building unit is used to build a fault diagnosis model based on the extracted key feature parameters.

4. The non-contact fault diagnosis device for the hoisting mechanism of the port automated crane according to claim 3, characterized in that: The duration setting submodule comprises a time scale analysis unit, a space scale analysis unit, a multi-measurement point analysis unit, a single-side point analysis unit and a regional analysis unit, wherein the time scale analysis unit, the space scale analysis unit, the multi-measurement point analysis unit, the single-side point analysis unit and the regional analysis unit are connected in sequence; The time scale analysis unit is used to analyze the detected data in combination with different time scales, and compare it with the constructed fault diagnosis model to identify the fault type; The spatial scale analysis unit is used to more accurately locate the fault by using the spatial distribution feature method after identifying the specific location and range of the fault, and compare it with the constructed fault diagnosis model to identify the fault type; The multi-measurement point analysis unit is used to measure the data of each key part in turn, comprehensively collect the operation data, conduct more accurate analysis by comparing the data of different measurement points, and compare with the constructed fault diagnosis model to identify the fault type; The single-side point analysis unit is used to perform in-depth analysis on the data of a specific measuring point through a time series analysis method, and compare it with the constructed fault diagnosis model to identify the fault type; The regional analysis unit is used to divide the crane hoisting mechanism into different areas, conduct an overall evaluation of each area, and compare it with the constructed fault diagnosis model to identify the fault type.

5. The non-contact fault diagnosis device for the hoisting mechanism of the port automated crane according to claim 4, characterized in that: The adjustment assembly also includes two lifting components, a stabilizing plate, a driving unit, a supporting shell, a rotating inner shell, a telescopic component, a processor and a rotating unit. The two lifting components are sequentially arranged at the output ends of the transverse component, and the output ends of the two lifting components are fixedly connected to the arc-shaped slide rail. A slide groove is arranged on one side of the transverse component, one end of the stabilizing plate is fixedly connected to the two lifting components, and the other end of the stabilizing plate is slidably connected to the slide groove. The driving unit is arranged on the arc-shaped slide rail, the supporting shell is arranged above the driving unit, the rotating inner shell is rotatably connected to the supporting shell and is located inside the supporting shell, the telescopic component is arranged inside the rotating inner shell, the processor is arranged on the inner wall of the rotating inner shell, and the rotating unit is arranged on the supporting shell and the rotating inner shell.

6. The non-contact fault diagnosis device for the hoisting mechanism of the port automated crane according to claim 5, characterized in that: The driving unit includes a slider, a first driving component and a roller. The slider is slidably connected to the arc-shaped slide rail. The first driving component is arranged inside the slider. The output end of the first driving component is fixedly connected to the roller. The roller is fitted with the arc-shaped slide rail.

7. The non-contact fault diagnosis device for the hoisting mechanism of a port automated crane according to claim 6, characterized in that: The rotating unit comprises a rotating component and a plurality of limiting mechanisms, wherein the rotating component is arranged at one side of the supporting shell, the output end of the rotating component passes through the supporting shell and is fixedly connected to the rotating inner shell, and the plurality of limiting mechanisms are sequentially arranged inside the supporting shell; The limiting mechanism includes a limiting block, a limiting groove, two electromagnets, two telescopic rods and two springs. The limiting block is fixedly connected to the outer wall of the rotating inner shell, the limiting groove is arranged inside the supporting outer shell, the limiting block and the limiting groove are adapted to each other, the two electromagnets are respectively arranged at the limiting groove and the inner wall of the supporting shell, the two ends of the two telescopic rods are respectively fixedly connected to the limiting groove and the inner wall of the supporting shell, the two ends of the two springs are respectively movably connected to the limiting groove and the inner wall of the supporting shell, the spring is sleeved on the outside of the telescopic rod, and the two springs are distributed on both sides of the electromagnet.

8. The non-contact fault diagnosis device for the hoisting mechanism of a port automated crane according to claim 7, characterized in that: The telescopic unit includes a mounting groove, a second driving component, a gear and a rack. The mounting groove is fixedly connected to the support block and is located on one side of the support block. The second driving component is arranged above the mounting groove. The rack is slidably connected to the mounting groove and is located inside the mounting groove. The output end of the second driving component passes through the mounting groove and is fixedly connected to the gear. The gear and the rack are meshed with each other.

9. The non-contact fault diagnosis device for the hoisting mechanism of the port automated crane according to claim 8, characterized in that: The rotating unit includes a rotating block and a rotating component. The rotating block is rotatably connected to one end of the supporting block. The other end of the supporting block is fixedly connected to the output end of the telescopic component. The rotating component is arranged at the connection between the rotating block and the supporting block.

10. The non-contact fault diagnosis device for the hoisting mechanism of a port automated crane according to claim 9, characterized in that: The optical monitoring unit includes a laser vibrometer, an infrared thermal imager and a displacement sensor, and the laser rangefinder, the infrared thermal imager and the displacement sensor are sequentially arranged on the rotating block; The acoustic monitoring unit comprises an acoustic coupler and an acoustic sensor, and the acoustic coupler and the acoustic sensor are respectively arranged at one end of the corresponding rack.

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