Intelligent portal crane safety detection and early warning system and method

Abstract

The invention relates to the technical field of safety monitoring of hoisting equipment, and discloses a safety detection and early warning system and method for an intelligent portal crane, and the system comprises a front-end sensing module which is used for collecting the operation data and operation pictures of the portal crane in real time, and carrying out the fusion; the voiceprint recognition module is used for assisting in judging whether internal parts make abnormal sounds or not; the data processing module is used for monitoring operation data of the portal crane through a machine learning algorithm, identifying abnormity and evaluating a health state; and the terminal display module is used for displaying the operation state and the operation data of the portal crane and displaying the monitoring result and the alarm information to a manager. According to various operation data, the integrated machine learning algorithm is utilized, abnormal modes are accurately recognized, and whether the equipment has potential safety hazards or not is rapidly judged, so that early potential faults of the equipment are found in time, the accuracy of fault early warning is improved, and the accidental shutdown time and the maintenance cost are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of safety monitoring of lifting equipment, and in particular to an intelligent gantry crane safety detection and early warning system and method. Background Art

[0002] With the improvement of industrial automation, gantry cranes, as a type of lifting machinery among special equipment, play an indispensable role in construction and municipal engineering. However, due to the complex working environment and frequent workload, gantry cranes are prone to various faults, such as metal fatigue, mechanical wear, failure of safety devices, illegal operations, etc., which are not only safety hazards, but may also cause safety accidents.

[0003] However, in the current technology, the traditional gantry crane detection method mainly relies on manual inspection and simple sensor detection, which has limited detection accuracy and cannot meet the accuracy of equipment detection, thereby reducing the efficiency of detection and alarm. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an intelligent gantry crane safety monitoring and early warning system and method to solve the problem of limited detection accuracy, inability to meet the accuracy of equipment detection, and reduced detection and alarm efficiency.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent gantry crane safety detection and early warning system, comprising: Front-end perception module: used to collect and integrate the operation data and operation pictures of the gantry crane in real time; Voiceprint recognition module: used to assist in determining whether the internal parts make abnormal noises; Data processing module: used to monitor the operating data of the gantry crane through machine learning algorithms, identify anomalies and evaluate health status; Terminal display module: used to display the operating status and operating data of the gantry crane, and show the monitoring results and alarm information to the management personnel.

[0006] Preferably, the front-end perception module includes a sensor group unit, an image acquisition unit and a wireless communication unit; The sensor group unit includes a temperature sensor and a vibration sensor, which are installed at vulnerable parts of the gantry crane to collect real-time information on changes in the surrounding environment; The image acquisition unit is installed in an area with a wide field of view and is used to capture the entire work area and map the data collected by the sensor group unit onto the work area. The wireless communication unit is used to transmit the collected data to the data processing module through the industrial Internet of Things technology.

[0007] Preferably, the vibration sensor adopts a high-sensitivity MEMS accelerometer for measuring vibration, and the image acquisition unit adopts an industrial-grade high-definition camera for providing clear images under low-light conditions.

[0008] Preferably, sensors of different specifications or types can be replaced in the sensor group unit according to actual needs, and the image acquisition unit supports upgrading to a camera model with a higher resolution.

[0009] Preferably, the voiceprint recognition module includes a voiceprint recognition unit and a drone patrol unit; The voiceprint recognition unit is used to collect the internal voiceprint data of the gantry crane through the audio sensor; The drone patrol unit is used to push the voiceprint recognition unit to a high point to monitor the gantry crane.

[0010] Preferably, the data processing module includes a data preprocessing unit, a machine learning model unit, an alarm and report generation unit, and a data storage and management unit; The data preprocessing unit is used to filter the collected data to remove noise interference; The machine learning model unit is used to train the neural network model based on a large amount of historical operation data and fault cases of gantry cranes, and then analyze the collected operation data and voiceprint data for equipment operation, fault prediction and health assessment; The alarm and report generating unit is used to identify abnormal signals of the operation data and voiceprint data of the device and output the device operation report; The data storage and management unit is used to store operating data, voiceprint data, training data and parameters of machine learning models, and abnormal reports through a large-capacity solid-state hard drive to establish a data index library.

[0011] Preferably, the terminal display module includes a data display unit, an interactive control unit and an alarm prompt unit; The data display unit is used to present the operating status and operating data of the gantry crane; The interactive control unit is used to manage interactive operations between the management personnel and the system; The alarm prompt unit is used to display and directly output alarm information through the judgment data of the alarm and report generating unit.

[0012] A method for safety detection and early warning of an intelligent gantry crane, the method comprising the following steps: S1. Data collection: The operation data is collected through the front-end perception module, and the operation data of the gantry crane is integrated into the picture of the operation area. The internal voiceprint data of the gantry crane is collected through the voiceprint recognition module; S2, data transmission and preprocessing: the collected data is transmitted to the data processing module through the wireless communication unit, and then the collected data is filtered to remove noise interference; S3, model analysis and report generation: The neural network model is trained through the machine learning model unit, and the pre-processed data is input into the model to analyze and monitor the equipment operation, predict faults and assess health, and identify abnormal operation behaviors; S4, Information display and interaction: Display the analysis results and various data of equipment operation through the terminal, and issue an alarm for abnormal behavior; S5. Equipment inspection and maintenance: According to actual needs, replace sensors of different specifications or types in the sensor group unit, and upgrade the camera model of the image acquisition unit.

[0013] The present invention provides an intelligent gantry crane safety detection and early warning system and method. It has the following beneficial effects: 1. The present invention uses integrated machine learning algorithms to accurately identify abnormal patterns and quickly determine whether there are safety hazards in the equipment through various types of operating data, thereby timely discovering early potential failures of the equipment, improving the accuracy of fault warnings, and reducing unexpected downtime and maintenance costs.

[0014] 2. The present invention continuously collects operating data from multiple aspects through sensors in the front-end perception module, and integrates the operating data with the operation screen, providing more comprehensive and three-dimensional information for subsequent data processing and analysis, and complementing the data and the screen, which helps to more accurately judge the equipment operation status. At the same time, the integrated information facilitates the observation of subsequent managers and improves the scientificity and accuracy of decision-making.

[0015] 3. The present invention improves the flexibility and adaptability of detection by replacing sensors of different specifications or types according to actual needs. At the same time, the image acquisition unit supports upgrading to higher-resolution camera models, which helps to obtain clearer and more detailed working area images, providing better visual data for data mapping and equipment status analysis, and enhancing the practicality and durability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a framework diagram of an intelligent gantry crane safety detection and early warning system of the present invention; Figure 2 This is a framework diagram of a front-end perception module of an intelligent gantry crane safety detection and early warning system of the present invention; Figure 3 This is a framework diagram of a voiceprint recognition module and data processing module of an intelligent gantry crane safety detection and early warning system of the present invention; Figure 4This is a data processing module framework diagram of an intelligent gantry crane safety detection and early warning system of the present invention; Figure 5 This is a terminal display module framework diagram of an intelligent gantry crane safety detection and early warning system of the present invention; Figure 6 The present invention is a flow chart of an intelligent gantry crane safety detection and early warning method. DETAILED DESCRIPTION

[0017] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings 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.

[0018] Please see attached Figure 1 -Attached Figure 5 The embodiment of the present invention provides an intelligent gantry crane safety detection and early warning system, including: Front-end perception module: used to collect and integrate the operation data and operation pictures of the gantry crane in real time; Voiceprint recognition module: used to assist in determining whether the internal parts make abnormal noises; Data processing module: used to monitor the operating data of the gantry crane through machine learning algorithms, identify anomalies and evaluate health status; Terminal display module: used to display the operating status and operating data of the gantry crane, and show the monitoring results and alarm information to the management personnel.

[0019] Specifically, the front-end perception module is used to continuously collect operation data and integrate the operation data with the operation screen, providing more comprehensive and three-dimensional information for subsequent data processing and analysis. The data and the screen complement each other, which helps to more accurately judge the operation status of the equipment. At the same time, the integrated information is convenient for subsequent management personnel to observe and improve the scientificity and accuracy of decision-making. The voiceprint recognition module can reflect the operating status of the crane's internal parts through sound features. The sounds emitted during normal operation and during a fault are different. The voiceprint recognition module collects the sounds of the gantry crane's internal parts during operation, analyzes these sounds, extracts key features, and compares them with the pre-set normal voiceprint model to determine whether there are abnormal noises. The data processing module uses integrated machine learning algorithms to accurately identify abnormal patterns and quickly determine whether the equipment has safety hazards based on various operating data received from the front-end sensing unit. It can not only detect early potential equipment failures, such as slight wear and looseness of components, but also generate detailed reports to provide decision-making basis for managers, improve the accuracy of fault warning, and reduce unexpected downtime and maintenance costs. Through the terminal display module, the operating status, operating data and monitoring results of the gantry crane analyzed by the data processing center are presented in an intuitive and easy-to-understand form, and the changing trends of key parameters are displayed in charts, thereby improving the efficiency of information transmission, helping managers to fully understand the equipment status and make decisions quickly, effectively ensuring the safe and stable operation of the gantry crane and reducing the probability of accidents.

[0020] The front-end perception module includes a sensor group unit, an image acquisition unit and a wireless communication unit; The sensor group unit includes a temperature sensor and a vibration sensor, which are installed at vulnerable parts of the gantry crane to collect real-time information on changes in the surrounding environment; The image acquisition unit is installed in an area with a wide field of view, and is used to capture the entire work area and map the data collected by the sensor group unit onto the work area. The wireless communication unit is used to transmit the collected data to the data processing module through the industrial Internet of Things technology.

[0021] Specifically, the sensor group unit is installed on the vulnerable parts of the gantry crane to monitor the equipment operation status in real time. At the same time, the temperature sensor can keenly capture the temperature changes of the vulnerable parts. Through temperature anomalies, it can be judged whether the equipment has problems such as overload and poor heat dissipation. The vibration sensor focuses on monitoring vibration conditions. Once abnormal vibration occurs, it can provide early warning signals for potential faults such as loose and worn equipment parts. Its operating data is the basic information for evaluating the health status of the equipment, providing a key basis for subsequent data analysis, effectively reducing the possibility of sudden equipment failures, and ensuring the continuous and stable operation of the gantry crane. The image acquisition unit captures the entire work area to ensure that the entire work area can be captured clearly, providing intuitive visual information. The data collected by the sensor group unit is mapped to the work area screen, allowing managers to directly observe the real-time situation of the work area. At the same time, the status data of key parts of the equipment can be obtained synchronously, which improves the readability and comprehensibility of the information. When an abnormality occurs in the equipment, the manager can quickly locate the abnormal point, realize efficient troubleshooting and accurate decision-making, and improve the overall management efficiency. The wireless communication unit is responsible for transmitting the temperature and vibration data collected by the sensor group unit and the working area image data taken by the image acquisition unit to the data processing module stably and quickly. This ensures that the data collected by the front end can be delivered to the subsequent processing link in time, realizing real-time data sharing and analysis, so as to timely discover safety hazards and trigger alarms, providing strong support for the efficient operation of the entire intelligent gantry crane safety detection and early warning system; The vibration sensor uses a highly sensitive MEMS accelerometer to measure vibration, and the image acquisition unit uses an industrial-grade high-definition camera to provide clear images under low-light conditions.

[0022] Specifically, the highly sensitive MEMS accelerometer, used as a vibration sensor, can accurately capture extremely subtle vibration changes in vulnerable parts of the gantry crane during operation, providing key vibration data basis for the evaluation of the equipment's operating status. The industrial-grade high-definition camera, used as an image acquisition unit, can ensure that no important details are missed due to ambient light problems, thereby improving the front-end perception module's monitoring accuracy of the equipment's operating status.

[0023] The sensor group unit can be replaced with sensors of different specifications or types according to actual needs, and the image acquisition unit supports upgrading to camera models with higher resolution.

[0024] Specifically, the sensor group unit can replace sensors of different specifications or types according to actual needs to improve the flexibility and adaptability of detection. When the detection environment changes or the monitoring accuracy requirements for specific parameters increase, it can be adjusted quickly. At the same time, the image acquisition unit supports upgrading to higher-resolution camera models, which helps to obtain clearer and more detailed images of the work area, provide better-quality visual data for data mapping and equipment status analysis, and enhance the practicality and durability of the system.

[0025] The voiceprint recognition module includes a voiceprint recognition unit and a drone patrol unit; The voiceprint recognition unit is used to collect the internal voiceprint data of the gantry crane through the audio sensor; The drone patrol unit is used to push the voiceprint recognition unit to a high point to monitor the gantry crane.

[0026] Specifically, the voiceprint recognition unit uses audio sensors to collect the internal operating sounds of the gantry crane, analyzes the sound characteristics, identifies abnormal signals, and discovers potential faults in advance, providing intelligent monitoring means for equipment safety detection, improving the system's ability to perceive abnormal conditions, and reducing the risk of sudden equipment failures; The drone patrol unit can send the voiceprint recognition unit to the high point of the gantry crane, breaking through the limitations of ground monitoring, collecting voiceprint data from multiple angles, and avoiding monitoring blind spots. It has strong maneuverability and can adjust the monitoring position in real time, expanding the voiceprint monitoring range, improving the comprehensiveness and accuracy of data collection, and enhancing the reliability of the security monitoring system.

[0027] The data processing module includes a data preprocessing unit, a machine learning model unit, an alarm and report generation unit, and a data storage and management unit; The data preprocessing unit is used to filter the collected data and remove noise interference; The machine learning model unit is used to train the neural network model based on a large amount of historical operation data and fault cases of gantry cranes, and then analyze the collected operation data and voiceprint data for equipment operation, fault prediction and health assessment; The alarm and report generation unit is used to identify abnormal signals in the operation data and voiceprint data of the equipment and output the equipment operation report; The data storage and management unit is used to store operating data, voiceprint data, training data and parameters of machine learning models, and abnormal reports through a large-capacity solid-state hard drive, and to establish a data index library.

[0028] Specifically, the data preprocessing unit is responsible for cleaning the collected raw data and removing the noise interference, ensuring that the data entering the subsequent analysis link is authentic and reliable, laying a solid foundation for accurate analysis of the equipment operation status, effectively improving data availability, and allowing subsequent modules to work based on non-interference data; Through the machine learning model unit, a large amount of historical operation data and fault cases of gantry cranes are used to train the neural network model. Then, the trained model is used to analyze the newly collected operation data and voiceprint data to quickly determine whether there are safety hazards in the current state, realize equipment operation status analysis, fault prediction and health status assessment, and provide intelligent analysis support for the safe and stable operation of equipment; The alarm and report generation unit monitors the operation data and voiceprint data in real time. Once an abnormal signal is identified, an alarm is triggered immediately and an equipment operation report is generated, covering the time, location, possible causes and other key contents of the abnormality. This allows managers to grasp the abnormality of the equipment in a timely manner, providing a detailed basis for troubleshooting and handling, and ensuring the stability of the entire intelligent gantry crane operation. The data storage and management unit facilitates efficient retrieval and call of data. Users can review historical operation data to analyze the long-term operation trend of equipment, and retrieve relevant data of specific fault cases for fault diagnosis, ensuring the long-term safe storage and convenient use of data, and providing solid data support for the continuous optimization and upgrade of the system.

[0029] The terminal display module includes a data display unit, an interactive control unit and an alarm prompt unit; The data display unit is used to present the operating status and operating data of the gantry crane; The interactive control unit is used to manage the interaction between the manager and the system; The alarm prompt unit is used to display and directly output alarm information through the judgment data of the alarm and report generation unit.

[0030] Specifically, the data display unit can directly display the operating status and data of the equipment to the operator, so that the user can quickly understand the operating status of the equipment, whether it is the smooth operation during normal operation or the potential risks when the operating data fluctuates. It provides convenience for managers to grasp the equipment status in real time and improves the efficiency and accuracy of equipment management. Through the interactive control unit, the equipment operation history data within a specific time period can be queried to analyze the long-term operation trend of the equipment. The system parameters can also be adjusted to optimize the monitoring and early warning settings according to different operating scenarios and equipment status, thus achieving efficient communication and collaboration between humans and machines, making the entire safety detection and early warning system more flexible and intelligent.

[0031] The alarm prompt unit detects abnormal conditions based on the output data of the data processing module, and uses intuitive alarm methods such as red warning lights or alarm sounds to ensure that managers can detect equipment abnormalities at the first time and take countermeasures quickly to effectively avoid accidents or reduce accident losses, providing key guarantees for the safe and stable operation of gantry cranes.

[0032] Please see attached Figure 6 , an intelligent gantry crane safety detection and early warning method, the method comprises the following steps: S1. Data collection: The operation data is collected through the front-end perception module, and the operation data of the gantry crane is integrated into the picture of the operation area. The internal voiceprint data of the gantry crane is collected through the voiceprint recognition module; S2, data transmission and preprocessing: the collected data is transmitted to the data processing module through the wireless communication unit, and then the collected data is filtered to remove noise interference; S3, model analysis and report generation: The neural network model is trained through the machine learning model unit, and the pre-processed data is input into the model to analyze and monitor the equipment operation, predict faults and assess health, and identify abnormal operation behaviors; S4, Information display and interaction: Display the analysis results and various data of equipment operation through the terminal, and issue an alarm for abnormal behavior; S5. Equipment inspection and maintenance: According to actual needs, replace sensors of different specifications or types in the sensor group unit, and upgrade the camera model of the image acquisition unit.

[0033] Specifically, in the data collection stage, the front-end perception module and the voiceprint recognition module work together to integrate the operation data with the work area screen, collect internal voiceprint data, and provide rich and comprehensive information for subsequent analysis. The wireless communication unit is then used to ensure fast and stable data transmission. The data processing module filters noise and improves data quality. During model analysis and report generation, the machine learning model is trained to accurately analyze equipment operation, predict faults, and generate detailed reports. The analysis results are intuitively presented through the terminal through information display and interaction, and abnormal alarms are issued in a timely manner to help managers make quick decisions. At the same time, before detection, sensors can be flexibly replaced and cameras upgraded according to actual needs based on equipment inspections and maintenance to ensure that the system always maintains the best monitoring performance.

[0034] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent gantry crane safety detection and early warning system, characterized in that: include: Front-end perception module: used to collect and integrate the operation data and operation pictures of the gantry crane in real time; Voiceprint recognition module: used to assist in determining whether the internal parts make abnormal noises; Data processing module: used to monitor the operating data of the gantry crane through machine learning algorithms, identify anomalies and evaluate health status; Terminal display module: used to display the operating status and operating data of the gantry crane, and show the monitoring results and alarm information to the management personnel.

2. According to claim 1, the intelligent gantry crane safety detection and early warning system is characterized in that: The front-end perception module includes a sensor group unit, an image acquisition unit and a wireless communication unit; The sensor group unit includes a temperature sensor and a vibration sensor, which are installed at vulnerable parts of the gantry crane to collect real-time information on changes in the surrounding environment; The image acquisition unit is installed in an area with a wide field of view and is used to capture the entire work area and map the data collected by the sensor group unit onto the work area. The wireless communication unit is used to transmit the collected data to the data processing module through the industrial Internet of Things technology.

3. The intelligent gantry crane safety detection and early warning system according to claim 2 is characterized in that: The vibration sensor adopts a high-sensitivity MEMS accelerometer to measure vibration, and the image acquisition unit adopts an industrial-grade high-definition camera to provide clear images under low-light conditions.

4. The intelligent gantry crane safety detection and early warning system according to claim 3 is characterized in that: The sensor group unit can be replaced with sensors of different specifications or types according to actual needs, and the image acquisition unit supports upgrading to a camera model with a higher resolution.

5. The intelligent gantry crane safety detection and early warning system according to claim 1 is characterized in that: The voiceprint recognition module includes a voiceprint recognition unit and a drone patrol unit; The voiceprint recognition unit is used to collect the internal voiceprint data of the gantry crane through the audio sensor; The drone patrol unit is used to push the voiceprint recognition unit to a high point to monitor the gantry crane.

6. The intelligent gantry crane safety detection and early warning system according to claim 1 is characterized in that: The data processing module includes a data preprocessing unit, a machine learning model unit, an alarm and report generation unit, and a data storage and management unit; The data preprocessing unit is used to filter the collected data to remove noise interference; The machine learning model unit is used to train the neural network model based on a large amount of historical operation data and fault cases of gantry cranes, and then analyze the collected operation data and voiceprint data for equipment operation, fault prediction and health assessment; The alarm and report generating unit is used to identify abnormal signals of the operation data and voiceprint data of the device and output the device operation report; The data storage and management unit is used to store operating data, voiceprint data, training data and parameters of machine learning models, and abnormal reports through a large-capacity solid-state hard drive to establish a data index library.

7. The intelligent gantry crane safety detection and early warning system according to claim 1 is characterized in that: The terminal display module includes a data display unit, an interactive control unit and an alarm prompt unit; The data display unit is used to present the operating status and operating data of the gantry crane; The interactive control unit is used to manage interactive operations between the management personnel and the system; The alarm prompt unit is used to display and directly output alarm information through the judgment data of the alarm and report generating unit.

8. An intelligent gantry crane safety detection and early warning method, characterized in that: An intelligent gantry crane safety detection and early warning system according to any one of claims 1 to 7, the method comprising the following steps: S1. Data collection: The operation data is collected through the front-end perception module, and the operation data of the gantry crane is integrated into the picture of the operation area. The internal voiceprint data of the gantry crane is collected through the voiceprint recognition module; S2, data transmission and preprocessing: the collected data is transmitted to the data processing module through the wireless communication unit, and then the collected data is filtered to remove noise interference; S3, model analysis and report generation: The neural network model is trained through the machine learning model unit, and the pre-processed data is input into the model to analyze and monitor the equipment operation, predict faults and assess health, and identify abnormal operation behaviors; S4, Information display and interaction: Display the analysis results and various data of equipment operation through the terminal, and issue an alarm for abnormal behavior; S5. Equipment inspection and maintenance: According to actual needs, replace sensors of different specifications or types in the sensor group unit, and upgrade the camera model of the image acquisition unit.

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