A large motor dynamic insulation monitoring and early warning device

Abstract

The utility model relates to a kind of large motor dynamic insulation monitoring analysis and early warning device, it is characterized by including: DC mutual inductor, installation in the rotor ground circuit of large motor, for real-time monitoring the leakage current of large motor;Signal processing module is electrically connected with the output end of DC mutual inductor, for receiving the output signal of DC mutual inductor, and the output signal is converted;Controller is electrically connected with signal processing module, the controller is configured as: the output result of signal processing module is compared with set threshold value, to obtain the insulation monitoring result of large motor.The device can carry out dynamic monitoring to the rotor insulation state of large motor, detect safety, efficient, high precision, effectively reduce motor failure, guarantee the normal operation of rolling mill set.

Description

Technical Field

[0001] This utility model relates to the field of large motor technology, and in particular to a dynamic insulation monitoring, analysis and early warning device for large motors. Background Technology

[0002] In today's industrial manufacturing sector, high-end stainless steel cold rolling mills use reversible rolling mills, which require large, high-precision motors. The main parameters of the large motor used in the 20-roll Sendzimir rolling mill are as follows: rated power 4000kW, speed 480RPM, rated voltage 3300V, rated current 713A, and power factor of 1.

[0003] The safe and reliable operation of large motors is crucial, thus placing extremely high demands on their insulation performance. Currently, large motors lack rotor insulation monitoring, analysis, and early warning devices. Over time, the insulation materials of large motors may degrade due to aging, humidity, contamination, or mechanical damage, leading to leakage current. In actual production processes, the lack of insulation monitoring devices has resulted in numerous accidents causing damage to large motors, and even gearbox bearings. Failures in large motors not only cause downtime in rolling mills, disrupting normal production, but also incur high equipment repair costs. Utility Model Content

[0004] The technical problem to be solved by this utility model is to provide a large motor dynamic insulation monitoring, analysis and early warning device that can monitor the insulation status of motors in real time and issue an alarm, in light of the above-mentioned prior art.

[0005] The technical solution adopted by this utility model to solve the above-mentioned technical problems is: a dynamic insulation monitoring, analysis and early warning device for large motors, characterized in that it includes:

[0006] DC current transformers are installed in the rotor grounding line of large motors to monitor the leakage current of large motors in real time.

[0007] The signal processing module is electrically connected to the output terminal of the DC transformer and is used to receive the output signal of the DC transformer and convert the output signal.

[0008] A controller, electrically connected to a signal processing module, is configured to compare the output of the signal processing module with a set threshold to obtain insulation monitoring results for a large motor.

[0009] To facilitate operators in quickly understanding the operating status of the large motor, an alarm system electrically connected to the controller is also included. The controller is configured to trigger an alarm when it detects that the leakage current of the large motor exceeds a preset threshold.

[0010] Preferably, the DC transformer is a Hall current sensor.

[0011] Preferably, the signal processing module includes an analog interface board that can convert analog signals into digital signals.

[0012] For ease of monitoring and diagnostics, the controller is also connected to a display module.

[0013] Preferably, the controller is a PLC controller.

[0014] To enable remote monitoring, the PLC controller is connected to a server, which is in turn connected to the Internet of Things (IoT).

[0015] Compared with existing technologies, the advantages of this invention are as follows: A DC current transformer is installed in the rotor grounding line of the large motor, and the leakage current of the large motor is monitored in real time through the DC current transformer, thereby dynamically monitoring the rotor insulation status of the large motor. This device has a reasonable structure, can dynamically monitor the rotor insulation status of the large motor, and is safe, efficient, and accurate in its detection, effectively reducing motor failures and ensuring the normal operation of the rolling mill. It can be extended to applications with similar large motors. Attached Figure Description

[0016] Figure 1 This is a control block diagram of the dynamic insulation monitoring, analysis and early warning device for large motors in this embodiment of the present invention. Detailed Implementation

[0017] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0018] like Figure 1 As shown, the large motor dynamic insulation monitoring, analysis, and early warning device in this embodiment includes a DC transformer, a signal processing module, and a controller. The DC transformer is installed in the rotor grounding line of the large motor to monitor the leakage current of the large motor in real time. The signal processing module is electrically connected to the output terminal of the DC transformer to receive the output signal of the DC transformer and convert the output signal. The controller is electrically connected to the signal processing module and is configured to compare the output result of the signal processing module with a set threshold to obtain the insulation monitoring result of the large motor.

[0019] The signal processing module includes an analog interface board that converts analog signals into digital signals. The controller is also connected to a display module, which in this embodiment is a display screen. The PLC controller is communicatively connected to a server, which in turn is connected to the Internet of Things (IoT).

[0020] The large motor dynamic insulation monitoring, analysis, and early warning device in this embodiment also includes an alarm system electrically connected to the controller. The controller is configured to trigger an alarm when it detects that the leakage current of the large motor exceeds a preset threshold. This alarm system can be either an audible alarm or a visual alarm.

[0021] In this embodiment, the controller is a PLC controller; the DC transformer is a Hall current sensor. The Hall current sensor in this embodiment has the following specifications: power supply voltage (POWER): 24VDC; input range (IN): DC 0~30A; output (OUT): DC 0~5V / 0~10V or 4-20mA; and the Hall current sensor is a 12mm through-hole type.

[0022] Hall effect current sensors utilize the Hall effect principle to measure the magnetic field strength generated by a current, thereby determining the current magnitude. This method is not limited by the type of current (AC or DC) and has the following significant advantages:

[0023] Hall effect current sensors can monitor the leakage current of a motor rotor in real time, which is crucial for the timely detection of insulation problems. In contrast, traditional insulation monitoring devices may require periodic testing or only provide readings under specific conditions.

[0024] 1. Accuracy: Hall current sensors provide high-precision measurement results because they rely on the Hall effect principle, a highly accurate method for current detection. Traditional insulation monitoring devices, due to technological limitations, may not be as accurate as Hall current sensors.

[0025] 2. Continuity: Hall current sensors can continuously monitor the insulation status of the motor rotor, rather than intermittently; this helps to more accurately track the health status of the motor and prevent potential failures.

[0026] 3. Safety: Because Hall current sensors can operate without direct contact with high-voltage circuits, they offer a safer detection method. Traditional insulation monitoring, on the other hand, may require personnel to come into contact with electrical equipment, posing certain safety risks.

[0027] 4. Integration: Hall current sensors can be easily integrated into existing monitoring systems, providing automated data acquisition and analysis. This reduces the need for manual intervention and improves monitoring efficiency.

[0028] 5. Fault diagnosis: The data collected by the Hall current sensor can not only determine the insulation condition of the circuit, but also calculate the insulation resistance, which is very helpful for fault diagnosis.

[0029] In summary, Hall current sensors offer a more advanced, safe, and efficient solution for monitoring motor rotor insulation. While traditional insulation-to-ground testers can also effectively monitor insulation performance, Hall current sensors offer significant advantages in terms of real-time performance, accuracy, continuity, and safety.

[0030] In this embodiment, the working process of the dynamic insulation monitoring, analysis and early warning device for large motors is as follows: the leakage current of the large motor is monitored by a Hall current sensor, and its current signal is converted into a standard DC 0-5V / 0-10V or 4-20mA signal output, which is then sent to the analog interface board and then transmitted to the PLC controller. If the controller detects that the leakage current of the large motor exceeds the preset threshold, the controller will alarm and notify the operator to take further inspection and maintenance measures.

[0031] A dedicated Iba data acquisition board (model VME-5565) is integrated on the VEM framework. Data is acquired to the industrial control computer via fiber optic cable. The data acquisition and forwarding program is then installed on the local server. The data is then transferred to the remote intelligent operation and maintenance platform through the local server. The remote intelligent operation and maintenance platform completes the data storage and query functions, and also has the ability to perform multi-data comparison and analysis.

[0032] Specifically, it includes:

[0033] Data acquisition architecture: Unlike systems that can only measure data from a single motor, this system deploys Hall current sensors in different units. These sensors are connected to the PLC controller of each unit via Iba data acquisition boards (using the VEM framework bus communication protocol for data acquisition). Data from the three units is transmitted to a server via fiber optic cable. The server is configured with three data acquisition cards (VMIC5565) and the same domain address. The data is then aggregated on an industrial computer and transmitted to the Internet of Things (IoT) for remote monitoring. Alarm values ​​can also be set.

[0034] The above description is only a preferred embodiment of the present utility model. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present utility model, and these improvements and modifications should also be considered within the protection scope of the present utility model.

Claims

1. A dynamic insulation monitoring, analysis, and early warning device for large-scale motors, characterized in that... include: DC current transformers are installed in the rotor grounding line of large motors to monitor the leakage current of large motors in real time. The signal processing module is electrically connected to the output terminal of the DC transformer and is used to receive the output signal of the DC transformer and convert the output signal. A controller, electrically connected to a signal processing module, is configured to compare the output of the signal processing module with a set threshold to obtain insulation monitoring results for a large motor.

2. The large-scale motor dynamic insulation monitoring, analysis, and early warning device according to claim 1, characterized in that: It also includes an alarm system electrically connected to the controller, which is configured to trigger an alarm when the controller detects that the leakage current of the large motor exceeds a preset threshold.

3. The large-scale motor dynamic insulation monitoring, analysis, and early warning device according to claim 1, characterized in that: The DC transformer is a Hall current sensor.

4. The large-scale motor dynamic insulation monitoring, analysis, and early warning device according to claim 1, characterized in that: The signal processing module includes an analog interface board, which can convert analog signals into digital signals.

5. The large-scale motor dynamic insulation monitoring, analysis, and early warning device according to any one of claims 1 to 4, characterized in that: The controller is also connected to a display module.

6. The large-scale motor dynamic insulation monitoring, analysis, and early warning device according to claim 5, characterized in that: The controller is a PLC controller.

7. The large-scale motor dynamic insulation monitoring, analysis, and early warning device according to claim 6, characterized in that: The PLC controller is connected to a server, and the server is connected to the Internet of Things (IoT).

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