Application of ship propulsion motor bearing state monitoring big data analysis system

Abstract

The application relates to a big data analysis system applied to a ship propulsion motor bearing state monitoring system, which comprises a central control unit, a ship propulsion motor bearing detection module, a fault detection module, a data processing module, a motor real-time alarm module, a motor state control module and an information storage module; the fault detection module, a heat dissipation module, the motor state control module and the information storage module are connected with the central control unit respectively; the data processing module is connected with the fault detection module; the motor fault detection module is used for real-time detection of the rotating speed and noise of the motor, so that the motor fault can be timely sent out; the motor real-time alarm module is used for receiving and processing the instructions sent out by the central processing module, and corresponding alarm information is sent out according to the processing result of the instructions; the system can detect abnormal conditions, and can estimate the operation result, so that the operation is accurate and fine.

Description

Technical Field

[0001] This invention relates to the field of marine propulsion motor bearing testing technology, specifically to a big data analysis system for monitoring the condition of marine propulsion motor bearings. Background Technology

[0002] Marine propulsion motors are widely used in marine equipment. During operation, these motors generate a significant amount of heat. If this heat exceeds a certain range, it can affect the motor's normal operation and, in severe cases, cause it to burn out. Current technologies mostly involve adding temperature sensors inside the motor to detect the temperature. When a set temperature is reached, a cooling fan is used to dissipate heat. However, this detection method has very low accuracy. Furthermore, it only detects the motor's temperature and cannot transmit relevant information to the outside world. It also cannot record the motor's operating status, making it difficult for staff to accurately collect relevant data. Additionally, the condition of the motor bearings needs to be monitored in real time to ensure its normal operation. Summary of the Invention

[0003] The purpose of this invention is to provide a big data analysis system for monitoring the condition of ship propulsion motor bearings, in order to solve the technical problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: This system, applied to a big data analysis system for monitoring the condition of marine propulsion motor bearings, includes a central control unit, a marine propulsion motor bearing detection module, a fault detection module, a data processing module, a real-time motor alarm module, a motor status control module, and an information storage module. The fault detection module, heat dissipation module, motor status control module, and information storage module are all connected to the central control unit, and the data processing module is connected to the fault detection module. The motor fault detection module performs real-time monitoring of the motor's speed and noise to facilitate timely detection of motor faults. The real-time motor alarm module receives and processes instructions from the central processing module and issues corresponding alarm information based on the processing results. The marine propulsion motor bearing detection module monitors the motor's temperature, load, and power supply status in real time. The motor status control module controls the normal operation of various motor components. The information storage module stores various data processing information, fault detection information, heat dissipation information, and motor status information.

[0005] As a further aspect of the present invention: the central control unit is connected to a remote control terminal via a wireless signal, and the remote control terminal is used to remotely operate and control the central processing module.

[0006] As a further embodiment of the present invention: the heat dissipation module includes a first data processing unit, which is electrically connected to a first signal transceiver unit, a motor load detection unit, a motor temperature detection unit, a motor power supply detection unit, a motor temperature storage unit, and a motor temperature comparison unit.

[0007] As a further aspect of the present invention: the motor load detection unit is used to detect the load status of the motor in real time and send the detection data to the first data processing unit for processing and comparison; the motor temperature detection unit uses German to detect the temperature of the motor in real time and sends the temperature detection results to the first data processing unit for processing and analysis; the motor power supply detection unit is used to detect the power supply status of the motor in real time, including the current and voltage stability during power supply.

[0008] As a further embodiment of the present invention: the fault detection module includes a data comparison unit, an anomaly detection unit and an alarm unit, and the data comparison unit, the anomaly detection unit and the alarm unit are connected in sequence.

[0009] As a further aspect of the present invention, the central control unit is controlled by a programmable PLC controller.

[0010] As a further embodiment of the present invention: the heat dissipation module includes a fault indicator light, which corresponds one-to-one with the variable frequency cooling fan and is disposed next to the variable frequency cooling fan; the fault indicator light is electrically connected to the controller and is used to emit light when the notification signal is received.

[0011] As a further aspect of the present invention: the PLC controller included in the central control unit is used to send a control signal to the intermediate relays of the two heat dissipation components closest to the faulty variable frequency cooling fan when a fault signal is received; the intermediate relays are electrically connected to the controller and are used to operate at high speed when the control signal is received.

[0012] As a further aspect of the present invention, it also includes a cooling module, which is bidirectionally connected to the central control unit and can effectively cool the motor.

[0013] Compared with the prior art, the advantages of this invention are: The system involved in this invention can detect abnormal conditions and predict the operation results, making the operation precise and accurate. By adding a central control unit, a ship propulsion motor bearing detection module, a fault detection module, a data processing module, a real-time motor alarm module, a motor status control module, and an information storage module, the central control unit determines whether the motor is in a high-temperature or low-temperature state based on the heat dissipation module. When the motor is in a high-temperature state, the central control unit activates the cooling module through the motor temperature control module. The cooling module can cool the motor, thereby ensuring its operation and reducing losses under high-temperature conditions. In addition, the design of several variable frequency cooling fans can effectively dissipate heat from the motor and can individually detect whether each variable frequency cooling fan is damaged, quickly locating the faulty variable frequency cooling fan, facilitating timely troubleshooting by maintenance personnel, and effectively preventing damage to the electrical components of the injection molding machine due to excessive temperature. Attached Figure Description

[0014] Figure 1 This is a flowchart illustrating the overall structure of the big data analysis system for monitoring the condition of ship propulsion motor bearings, as described in this invention. Figure 2 This is a flowchart of the heat dissipation module applied to the big data analysis system for monitoring the condition of marine propulsion motor bearings according to the present invention; Figure 3 This is a flowchart of the fault detection module applied to the big data analysis system for monitoring the condition of marine propulsion motor bearings, as described in this invention. In the diagram: 1. Central control unit; 2. Heat dissipation module; 3. Fault detection module; 4. Data processing module; 5. Real-time motor alarm module; 6. Motor status control module; 7. Information storage module; 8. First data processing unit; 9. First signal transceiver unit; 10. Motor load detection unit; 11. Motor temperature detection unit; 12. Motor power supply detection unit; 13. Motor temperature storage unit; 14. Motor temperature comparison unit; 15. Data comparison unit; 16. Anomaly detection unit; 17. Alarm unit. Detailed Implementation

[0015] 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. Example

[0016] Please refer to Figures 1 to 3 In the embodiments of the present invention: The system includes a central control unit 1, a heat dissipation module 2, a fault detection module 3, a data processing module 4, a real-time motor alarm module 5, a motor status control module 6, and an information storage module 7. The fault detection module 3, heat dissipation module 2, motor status control module 6, and information storage module 7 are all connected to the central control unit 1. The data processing module 4 is connected to the fault detection module 3. The fault detection module 3 is used to detect the motor's speed and noise in real time, facilitating timely detection of motor faults. The real-time motor alarm module receives and processes instructions from the central control unit and issues corresponding alarm information based on the processing results. The heat dissipation module 2 is used to detect the motor's temperature, load, and power supply status in real time. The motor status control module 6 controls the normal operation of various motor components. The information storage module stores various data processing information, fault detection information, heat dissipation information, and motor status information.

[0017] The central control unit 1, heat dissipation module 2, fault detection module 3, data processing module 4, motor real-time alarm module 5, motor status control module 6, and information storage module 7 are installed inside the motor housing and perform their respective functions during operation. The central control unit 1 controls the operation of the entire system. The fault detection module 3 can effectively detect the operation of the motor. Once a problem occurs, it can be detected and dealt with in a timely manner. In addition, the heat dissipation module 2 is designed to detect the relevant heat dissipation of the motor in real time. Example

[0018] Based on Embodiment 1, the central control unit 1 is connected to a remote control terminal via a wireless signal. The remote control terminal is used to remotely operate and control the central control unit 1. The heat dissipation module 2 includes a first data processing unit 8, which is electrically connected to a first signal transceiver unit 9, a motor load detection unit 10, a motor temperature detection unit 11, a motor power supply detection unit 12, a motor temperature storage unit 13, and a motor temperature comparison unit 14. The motor load detection unit 10 is used to detect the load status of the motor in real time and send the detection data to the first data processing unit 8 for processing and comparison. The motor temperature detection unit 11 detects the temperature of the motor in real time and sends the temperature detection results to the first data processing unit 8 for processing and analysis. The motor power supply detection unit 12 is used to detect the power supply status of the motor in real time, including the current and voltage stability during power supply. Example

[0019] Based on Embodiment 2, the fault detection module 3 includes a data comparison unit 15, an anomaly detection unit 16, and an alarm unit 17, which are connected sequentially. The central control unit 1 is controlled by a programmable PLC controller. The heat dissipation module includes a fault indicator light, which corresponds one-to-one with the variable frequency cooling fan and is located next to the variable frequency cooling fan. The fault indicator light is electrically connected to the controller and is used to emit light upon receiving the notification signal. The PLC controller included in the central control unit is used to send a control signal to the intermediate relays of the two heat dissipation components closest to the faulty variable frequency cooling fan when a fault signal is received. The intermediate relays are electrically connected to the controller and are used to operate at high speed upon receiving the control signal. The module also includes a cooling module, which is bidirectionally connected to the central control unit and can effectively cool the motor.

[0020] In all the solutions mentioned above, for connections between two components, welding, bolt and nut connection, bolt or screw connection, or other known connection methods can be selected according to the actual situation. These will not be elaborated here. For all fixed connections mentioned above, welding is preferred. 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. A big data analysis system for monitoring the condition of marine propulsion motor bearings, characterized in that: The system includes a central control unit, a marine propulsion motor bearing detection module, a fault detection module, a data processing module, a real-time motor alarm module, a motor status control module, and an information storage module. The fault detection module, heat dissipation module, motor status control module, and information storage module are connected to the central control unit, and the data processing module is connected to the fault detection module. The motor fault detection module is used to detect the motor's speed and noise in real time, facilitating timely detection of motor faults. The real-time motor alarm module receives and processes instructions from the central control module and issues corresponding alarm information based on the processing results. The marine propulsion motor bearing detection module is used to detect the motor's temperature, load, and power supply status in real time. The motor status control module controls the normal operation of various components of the motor. The information storage module is used to store various data processing information, fault detection information, heat dissipation information, and motor status information.

2. The big data analysis system for monitoring the condition of ship propulsion motor bearings according to claim 1, characterized in that: The central control unit is connected to a remote control terminal via a wireless signal. The remote control terminal is used to remotely operate and control the central processing module.

3. The big data analysis system for monitoring the condition of ship propulsion motor bearings according to claim 2, characterized in that: The heat dissipation module includes a first data processing unit, which is electrically connected to a first signal transceiver unit, a motor load detection unit, a motor temperature detection unit, a motor power supply detection unit, a motor temperature storage unit, and a motor temperature comparison unit.

4. The big data analysis system for monitoring the condition of ship propulsion motor bearings according to claim 1, characterized in that: The motor load detection unit is used to detect the load status of the motor in real time and send the detection data to the first data processing unit for processing and comparison. The motor temperature detection unit uses German to detect the temperature of the motor in real time and sends the temperature detection results to the first data processing unit for processing and analysis. The motor power supply detection unit is used to detect the power supply status of the motor in real time, including the current and voltage stability during power supply.

5. The big data analysis system for monitoring the condition of ship propulsion motor bearings according to claim 4, characterized in that: The fault detection module includes a data comparison unit, an anomaly detection unit, and an alarm unit, which are connected in sequence.

6. The big data analysis system for monitoring the condition of ship propulsion motor bearings according to claim 1, characterized in that: The central control unit is controlled by a programmable PLC controller.

7. The big data analysis system for monitoring the condition of ship propulsion motor bearings according to claim 1, characterized in that: The heat dissipation module includes a fault indicator light, which corresponds one-to-one with the variable frequency cooling fan and is located next to the variable frequency cooling fan; the fault indicator light is electrically connected to the controller and is used to emit light when the notification signal is received.

8. The big data analysis system for monitoring the condition of ship propulsion motor bearings according to claim 7, characterized in that: The PLC controller included in the central control unit is used to send a control signal to the intermediate relays of the two heat dissipation components closest to the faulty variable frequency cooling fan when a fault signal is received; the intermediate relays are electrically connected to the controller and are used to operate at high speed when the control signal is received.

9. The big data analysis system for monitoring the condition of ship propulsion motor bearings according to claim 8, characterized in that: It also includes a cooling module, which is bidirectionally connected to the central control unit and can effectively cool the motor.

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