Online analysis and diagnosis system for insulation of air separation power unit

Abstract

The invention relates to the technical field of air separation power unit insulation analysis, and discloses an air separation power unit insulation online analysis and diagnosis system. According to the system, partial discharge parameters, temperature and humidity data of the high-voltage motor and the temperature of a stator winding of the motor are acquired in real time through the data acquisition module, and the data transmitted by the modules are integrated and analyzed through the data processing module. The discharge intensity, the discharge energy, the temperature change rate, the humidity change rate, the high-voltage motor power factor and the winding temperature change rate are calculated, an insulation health index is calculated by integrating the numerical values and sent to the diagnosis and evaluation module, and the diagnosis and evaluation module diagnoses an insulation event based on the insulation health index and calculates the fault diagnosis accuracy rate. The diagnosis and evaluation module is used for analyzing and evaluating the insulation of the air separation power unit, generating an insulation online analysis and diagnosis report of the air separation power unit and sending the analysis and diagnosis report to the report module, and the report module monitors the equipment state in real time according to the output of the diagnosis and evaluation module and displays the insulation online analysis and diagnosis report of the air separation power unit on the central display end.

Description

Technical Field

[0001] The invention relates to the technical field of insulation analysis of air separation power groups, in particular to an online insulation analysis and diagnosis system for air separation power groups. Background Art

[0002] With the development of industry, high-voltage motors are increasingly used in various industries due to their wide application, remarkable results, simple operation and stable operation.

[0003] At present, most of the power equipment that drives large machinery basically uses high-voltage motors. Motor failure may be caused by various reasons, and the reasons are mainly divided into mechanical failure and electrical failure. Electrical failure will have a direct impact on the performance and service life of the motor. Common electrical failures include winding short circuit, phase loss operation, capacitor failure, etc. For example, winding short circuit may cause the motor to overheat or even burn out. Each failure during equipment operation may pose a great threat to the safe operation of the equipment. The stator winding insulation failure is one of the main failures. The motor stator winding coil is fixed in the stator core slot and connected to the motor terminal box through high-voltage lead wires. The proportion of motor failures caused by insulation structure damage is relatively high.

[0004] As there are more and more high-power high-voltage motors, the risk of high-voltage motor failure increases with the use time due to insulation aging, equipment wear, high temperature and humidity in the environment, etc. Traditional manual regular inspections cannot grasp equipment failure information in a timely manner, which can easily cause losses to the company's property and production. Summary of the invention

[0005] 1. Technical issues to be solved

[0006] In view of the shortcomings of the prior art, the present invention provides an online analysis and diagnosis system for insulation of an air-separated power group, which has the function of real-time acquisition of local discharge parameters, temperature, humidity data of high-voltage motors and the temperature of motor stator windings through a data acquisition module. The above-mentioned acquired data is transmitted to a data processing module through a network. The data processing module integrates and analyzes the data transmitted by the above-mentioned modules, calculates the discharge intensity Fdqd, discharge energy Fdnl, temperature change rate Wdbh, humidity change rate Sdbh, high-voltage motor power factor Ggyz and winding temperature change rate Rzwb, and calculates the insulation health index Jyzs ​​based on the above-mentioned numerical values. The system is sent to the diagnosis and evaluation module, which diagnoses the insulation event based on the insulation health index Jyzs, calculates the fault diagnosis accuracy Gzzq, and generates an online analysis and diagnosis report on the insulation of the air-separation power group and sends it to the reporting module. The reporting module monitors the equipment status in real time according to the output of the diagnosis and evaluation module, and displays the online analysis and diagnosis report on the insulation of the air-separation power group on the central display terminal. The online analysis and diagnosis system for the insulation of the air-separation power group composed of the above modules avoids the problem that the traditional manual periodic inspection cannot timely grasp the equipment fault information, which is easy to cause losses to the company's property and production, and solves the above problems.

[0007] (II) Technical solution

[0008] To achieve the above object, the present invention provides the following technical solutions: an online analysis and diagnosis system for insulation of an air separation power unit, comprising a data acquisition module, a data processing module, a diagnosis and evaluation module and a reporting module;

[0009] The data acquisition module collects local discharge parameters, temperature, humidity data of the high-voltage motor and the temperature of the motor stator winding in real time, and the collected data is transmitted to the data processing module through the network;

[0010] The data processing module integrates and analyzes the data transmitted by the above modules, calculates the discharge intensity Fdqd, discharge energy Fdnl, temperature change rate Wdbh, humidity change rate Sdbh, high-voltage motor power factor Ggyz and winding temperature change rate Rzwb, and calculates the insulation health index Jyzs ​​based on the above values ​​and sends it to the diagnosis and evaluation module;

[0011] The diagnosis and evaluation module diagnoses insulation events based on the insulation health index Jyzs, calculates the fault diagnosis accuracy Gzzq, and generates an online analysis and diagnosis report of the insulation of the air separation power group and sends it to the reporting module;

[0012] The reporting module monitors the equipment status in real time according to the output of the diagnosis and evaluation module, and displays the online analysis and diagnosis report of the insulation of the air separation power unit on the central display terminal.

[0013] Preferably, the data processing module integrates and analyzes the data transmitted by the above modules to calculate the discharge intensity Fdqd. The calculation formula is as follows:

[0014]

[0015] In the formula, Fdqd represents the discharge intensity, Fdfz represents the discharge voltage amplitude, and Ljdz represents the discharge path resistance.

[0016] Preferably, the data processing module integrates and analyzes the data transmitted by the above modules to calculate the discharge energy Fdnl, and the calculation formula is as follows:

[0017]

[0018] In the formula, Fdnl represents the discharge energy, Yxdr represents the effective capacitance during the discharge process, and Dyfd represents the discharge voltage.

[0019] Preferably, the data processing module integrates and analyzes the data transmitted by the above modules, and calculates the temperature change rate Wdbh. The calculation formula is as follows:

[0020]

[0021] In the formula, Wdbh represents the temperature change rate, Tt2 represents the temperature at time point t2, Tt1 represents the temperature at time point t1, and t2-t1 represents the time interval.

[0022] Preferably, the data processing module integrates and analyzes the data transmitted by the above modules, and calculates the humidity change rate Sdbh. The calculation formula is as follows:

[0023]

[0024] In the formula, Sdbh represents the humidity change rate, Ht2 represents the humidity at time point t2, Ht1 represents the humidity at time point t1, and t2-t1 represents the time interval.

[0025] Preferably, the data processing module integrates and analyzes the data transmitted by the above modules, and calculates the power factor Ggyz of the high-voltage motor. The calculation formula is as follows:

[0026]

[0027] In the formula, Ggyz represents the power factor of the high-voltage motor, Plzj represents the actual power, and Wgzl represents the reactive power.

[0028] Preferably, the data processing module integrates and analyzes the data transmitted by the above modules, and calculates the winding temperature change rate Rzwb. The calculation formula is as follows:

[0029]

[0030] In the formula, Rzwb represents the winding temperature change rate, Rzwd a2 Indicates the winding temperature at time point a2, Rzwd a1 represents the winding temperature at time point a1, and a2-a1 represents the time interval.

[0031] Preferably, the data processing module comprehensively considers the discharge intensity Fdqd, the discharge energy Fdnl, the temperature change rate Wdbh, the humidity change rate Sdbh, the high-voltage motor power factor Ggyz and the winding temperature change rate Rzwb to calculate the insulation health index Jyzs, and the calculation formula is as follows:

[0032] Jyzs=0.2*Fdqd+0.3*Fdnl+Wdbh+Sdbh+0.4*Ggyz+0.1*Rzwb

[0033] In the formula, 0.1, 0.2, 0.3, and 0.4 represent the weight values ​​of the respective parameters.

[0034] Preferably, the diagnostic evaluation module diagnoses insulation events based on the insulation health index Juzs, and the diagnostic method is as follows:

[0035] When the insulation health index Jyzs ​​is greater than 1, it indicates that the motor operation condition diagnosis is abnormal;

[0036] When the insulation health index Jyzs ​​is less than or equal to 1, it indicates that there is no abnormality in the motor operation diagnosis.

[0037] Preferably, the diagnosis and evaluation module diagnoses insulation events based on the data provided by the processing module and the insulation health index Jyzs, and calculates the fault diagnosis accuracy Gzzq, and the calculation formula is as follows:

[0038]

[0039] In the formula, Gzzq represents the fault diagnosis accuracy, Tp represents the actual number of faults correctly identified as faults, Tn represents the actual number of normals correctly identified as normal, Fp represents the actual number of normals incorrectly identified as faults, and Fn represents the actual number of faults incorrectly identified as normal.

[0040] Compared with the prior art, the present invention provides an online analysis and diagnosis system for insulation of an air separation power unit, which has the following beneficial effects:

[0041] The present invention collects local discharge parameters, temperature, humidity data of high-voltage motors and the temperature of motor stator windings in real time through a data acquisition module. The above-mentioned collected data are transmitted to a data processing module through a network. The data processing module integrates and analyzes the data transmitted by the above-mentioned modules, calculates the discharge intensity Fdqd, discharge energy Fdnl, temperature change rate Wdbh, humidity change rate Sdbh, high-voltage motor power factor Ggyz and winding temperature change rate Rzwb, and calculates the insulation health index Jyzs ​​based on the above-mentioned numerical values ​​and sends it to the diagnosis and evaluation module. The diagnosis and evaluation module diagnoses insulation events based on the insulation health index Jyzs, calculates the fault diagnosis accuracy Gzzq, and generates an online analysis and diagnosis report of the insulation of the air-separation power group and sends it to the reporting module. The reporting module monitors the equipment status in real time according to the output of the diagnosis and evaluation module, and displays the online analysis and diagnosis report of the insulation of the air-separation power group on the central display terminal. The online analysis and diagnosis system of the insulation of the air-separation power group composed of the above-mentioned modules avoids the problem that the traditional manual regular inspection cannot timely grasp the equipment fault information, which is easy to cause losses to the company's property and production. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments 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.

[0044] In view of the problem that the risk of high-voltage motor failure increases with the increase of service time, and the traditional manual regular inspection cannot timely grasp the equipment failure information, which is easy to cause losses to the company's property and production, an online analysis and diagnosis system for insulation of air separation power group is proposed. Figure 1 ,The system includes a data acquisition module, a data processing module, a diagnosis and evaluation module, and a reporting module;

[0045] The data acquisition module uses high-performance sensors and data acquisition systems to monitor multiple key parameters of high-voltage motors in real time, including partial discharge intensity, spectrum characteristics, temperature, humidity, etc. The partial discharge parameters are detected by high-frequency discharge sensors. These sensors can capture tiny current pulses and extract effective data through signal processing algorithms. The temperature and humidity data are collected in real time by precise temperature and humidity sensors. These sensors have high sensitivity and fast response capabilities. In addition, the temperature measurement of the motor stator winding uses infrared sensors or thermocouples to ensure that the temperature changes of the winding can be reflected in time. All collected data are uploaded to the central processing unit through a high-speed data acquisition system to form a real-time monitoring network. This network can support remote access and real-time analysis of data, providing a solid data foundation for subsequent status evaluation and fault diagnosis, and providing a scientific basis for preventive maintenance and decision support.

[0046] The data processing module integrates and analyzes the data transmitted by the above modules, calculates the discharge intensity Fdqd, discharge energy Fdnl, temperature change rate Wdbh, humidity change rate Sdbh, high-voltage motor power factor Ggyz and winding temperature change rate Rzwb, and calculates the insulation health index Jyzs ​​based on the above values, where:

[0047] The discharge intensity calculation formula is as follows:

[0048]

[0049] Monitoring the discharge intensity can detect insulation defects early and prevent potential electrical failures. In the formula, Fdqd represents the discharge intensity, Fdfz represents the discharge voltage amplitude, and Ljdz represents the discharge path resistance. By analyzing the change trend of the discharge intensity, the insulation health of the motor can be evaluated, which helps to formulate a maintenance plan.

[0050] The discharge energy calculation formula is as follows:

[0051]

[0052] The magnitude of the discharge energy reflects the degree of insulation degradation. A higher energy value may mean more serious insulation damage. In the formula, Fdnl represents the discharge energy, Yxdr represents the effective capacitance during the discharge process, and Dyfd represents the discharge voltage. By quantifying the discharge energy, equipment managers can take corresponding maintenance measures for different energy levels to reduce maintenance costs.

[0053] The temperature change rate calculation formula is as follows:

[0054]

[0055] Monitoring the temperature change rate helps to detect insufficient heat dissipation or overheating, maintain the normal operating temperature of the motor, and avoid insulation aging caused by overheating. In the formula, Wdbh represents the temperature change rate, T t2 represents the temperature at time t2, T t1 It indicates the temperature at time point t1, and t2-t1 indicates the time interval. Rapid temperature changes may indicate equipment failure. Trend analysis can be used to intervene in advance and reduce downtime.

[0056] The humidity change rate calculation formula is as follows:

[0057]

[0058] High humidity environment will accelerate the aging of insulation materials. Monitoring the humidity change rate can help identify moisture problems and adjust environmental control measures in time. In the formula, Sdbh represents the humidity change rate, H t2 Represents the humidity at time point t2, H t1 represents the humidity at time point t1, t2-t1 represents the time interval, and controlling the humidity change rate helps maintain the performance of the motor insulation system and reduce the risk of short circuit and failure;

[0059] The formula for calculating the power factor of a high-voltage motor is as follows:

[0060]

[0061] Power factor monitoring can reflect the working efficiency of the motor and optimize energy consumption. In the formula, Ggyz represents the power factor of the high-voltage motor, Plzj represents the actual power, and Wgzl represents the reactive power. Abnormal power factor may indicate internal problems of the equipment, such as winding short circuit or load imbalance, helping technicians to conduct troubleshooting in time;

[0062] The calculation formula of winding temperature change rate is as follows:

[0063]

[0064] Monitoring the winding temperature change rate can detect overload in time and avoid damage to the insulation layer caused by high temperature. In the formula, Rzwb represents the winding temperature change rate, Rzwd a2 Indicates the winding temperature at time point a2, Rzwd a1 Indicates the winding temperature at time point a1, a2-a1 indicates the time interval. Long-term tracking of winding temperature changes helps predict the remaining life of the insulation material in the motor and supports maintenance decisions;

[0065] The insulation health index calculation formula is as follows:

[0066] Jyzs=0.2*Fdqd+0.3*Fsnl+Wdbh+Sdbh+0.4*Ggyz+0.1*Rzwb

[0067] The insulation health index integrates multiple key indicators to provide a comprehensive and intuitive insulation status assessment, which is convenient for equipment management. In the formula, 0.1, 0.2, 0.3 and 0.4 represent the weight values ​​of their respective parameters. By monitoring the insulation health index, managers can make maintenance and investment decisions based on data-driven methods, optimize utilization benefits, and reduce failure rates and maintenance costs.

[0068] The diagnosis and evaluation module diagnoses insulation events based on the insulation health index Jyzs, calculates the fault diagnosis accuracy Gzzq, and generates an online analysis and diagnosis report on the insulation of the air separation power unit. The diagnosis method is as follows:

[0069] When the insulation health index Jyzs ​​is greater than 1, it indicates that the motor operation condition diagnosis is abnormal;

[0070] When the insulation health index Jyzs ​​is less than or equal to 1, it means that there is no abnormality in the motor operation diagnosis;

[0071] The fault diagnosis accuracy calculation formula is as follows:

[0072]

[0073] By calculating the accuracy, managers can evaluate the performance of the fault diagnosis model, thereby ensuring that fault diagnosis can minimize the occurrence of false positives and false negatives and improve the reliability of diagnosis. In the formula, Gzzq represents the fault diagnosis accuracy, Tp represents the actual number of faults correctly identified as faults, Tn represents the actual number of normals correctly identified as normal, Fp represents the actual number of normals incorrectly identified as faults, and Fn represents the actual number of faults incorrectly identified as normal. When the accuracy is clear, the operation and maintenance team can make decisions more effectively based on data, arrange maintenance or replacement plans, and avoid waste of resources due to premature or late intervention.

[0074] The reporting module monitors the equipment status of the air separation power group in real time based on the output of the diagnosis and evaluation module. It uses advanced data acquisition and processing technology to conduct a comprehensive analysis of key data such as motor temperature, humidity, insulation health index and fault diagnosis results. The module tracks the operating status of the equipment in real time, identifies potential fault risks, and generates detailed online analysis and diagnosis reports. Through visualization technology, these reports are intuitively displayed on the central display terminal, allowing operators to quickly understand the operating status and health level of the equipment. In addition, the reporting module also has a real-time early warning function. Once an abnormal situation is detected, the system will automatically issue an alarm to ensure that the technical team can intervene and take measures in time, thereby maximizing the safety and reliability of the equipment and reducing downtime;

[0075] The system is designed to be composed of: PDM host, coupling capacitor, temperature and humidity, load sensor, RTD sensor terminal block, signal transmission cable, etc.

[0076] The preliminary hardware design of the online analysis and diagnosis system for insulation of air separation power group is as follows:

[0077] (1) Add three coupling capacitors in the motor junction box, complete the signal line and primary jumper cable connection, and lead out three sensor signal lines;

[0078] (2) Install temperature, humidity and load sensors in the motor junction box. The above components can be fixed with cable ties, and three sensor signal wires are led out at the same time;

[0079] (3) Use the RTD sensor terminal block in the motor stator winding RTD junction box and complete the wiring, and lead out 6 sensor signal wires;

[0080] (4) Set up a PDM main box near the motor. The sensor signal line should be within 20 meters, and AC220V power supply should be sent to the PDM main box. According to the remote communication requirements, add RS485 signal line;

[0081] (5) All sensor signal lines in the junction boxes, a total of 12 lines in two junction boxes, are led to the PDM main box and wired. The collected data is analyzed and processed in a unified manner to achieve online analysis and diagnosis of the equipment status.

[0082] The online analysis and diagnosis system for insulation of air separation power units composed of the above modules avoids the problem that traditional manual regular inspections cannot timely obtain equipment failure information, which is likely to cause losses to the company's property and production.

[0083] 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 online analysis and diagnosis system for insulation of air separation power group, characterized by: It includes data acquisition module, data processing module, diagnosis and evaluation module and reporting module; The data acquisition module collects local discharge parameters, temperature, humidity data of the high-voltage motor and the temperature of the motor stator winding in real time, and the collected data is transmitted to the data processing module through the network; The data processing module integrates and analyzes the data transmitted by the above modules, calculates the discharge intensity Fdqd, discharge energy Fdnl, temperature change rate Wdbh, humidity change rate Sdbh, high-voltage motor power factor Ggyz and winding temperature change rate Rzwb, and calculates the insulation health index Jyzs ​​based on the above values ​​and sends it to the diagnosis and evaluation module; The diagnosis and evaluation module diagnoses insulation events based on the insulation health index Jyzs, calculates the fault diagnosis accuracy Gzzq, and generates an online analysis and diagnosis report of the insulation of the air separation power group and sends it to the reporting module; The reporting module monitors the equipment status in real time according to the output of the diagnosis and evaluation module, and displays the online analysis and diagnosis report of the insulation of the air separation power unit on the central display terminal.

2. The online analysis and diagnosis system for insulation of an air separation power unit according to claim 1 is characterized in that: The data processing module integrates and analyzes the data transmitted by the above modules and calculates the discharge intensity Fdqd. The calculation formula is as follows: In the formula, Fdqd represents the discharge intensity, Fdfz represents the discharge voltage amplitude, and Ljdz represents the discharge path resistance.

3. The online analysis and diagnosis system for insulation of an air separation power unit according to claim 2 is characterized in that: The data processing module integrates and analyzes the data transmitted by the above modules and calculates the discharge energy Fdnl. The calculation formula is as follows: In the formula, Fdnl represents the discharge energy, Yxdr represents the effective capacitance during the discharge process, and Dyfd represents the discharge voltage.

4. The online analysis and diagnosis system for insulation of air separation power group according to claim 3 is characterized by: The data processing module integrates and analyzes the data transmitted by the above modules and calculates the temperature change rate Wdbh. The calculation formula is as follows: In the formula, Wdbh represents the temperature change rate, T t2 represents the temperature at time t2, T t1 represents the temperature at time point t1, and t2-t1 represents the time interval.

5. The online analysis and diagnosis system for insulation of air separation power group according to claim 4 is characterized in that: The data processing module integrates and analyzes the data transmitted by the above modules and calculates the humidity change rate Sdbh. The calculation formula is as follows: In the formula, Sdbh represents the humidity change rate, H t2 Represents the humidity at time point t2, H t1 represents the humidity at time point t1, and t2-t1 represents the time interval.

6. The online analysis and diagnosis system for insulation of air separation power group according to claim 5 is characterized by: The data processing module integrates and analyzes the data transmitted by the above modules, and calculates the high-voltage motor power factor Ggyz. The calculation formula is as follows: In the formula, Ggyz represents the power factor of the high-voltage motor, Plzj represents the actual power, and Wgzl represents the reactive power.

7. The online analysis and diagnosis system for insulation of air separation power unit according to claim 6 is characterized by: The data processing module integrates and analyzes the data transmitted by the above modules, and calculates the winding temperature change rate Rzwb. The calculation formula is as follows: In the formula, Rzwb represents the winding temperature change rate, Rzwd a2 Indicates the winding temperature at time point a2, Rzwd a1 represents the winding temperature at time point a1, and a2-a1 represents the time interval.

8. The online analysis and diagnosis system for insulation of air separation power unit according to claim 7 is characterized in that: The data processing module comprehensively calculates the insulation health index Jyzs ​​by combining the discharge intensity Fdqd, the discharge energy Fdnl, the temperature change rate Wdbh, the humidity change rate Sdbh, the high-voltage motor power factor Ggyz and the winding temperature change rate Rzwb. The calculation formula is as follows: Jyzs=0.2*Fdqd+0.3*Fdnl+Wdbh+Sdbh+0.4*Ggyz+0.1*Rzwb In the formula, 0.1, 0.2, 0.3, and 0.4 represent the weight values ​​of the respective parameters.

9. The online analysis and diagnosis system for insulation of air separation power unit according to claim 8 is characterized in that: The diagnostic evaluation module diagnoses insulation events based on the insulation health index Jyzs, and the diagnostic method is as follows: When the insulation health index Jyzs ​​is greater than 1, it indicates that the motor operation condition diagnosis is abnormal; When the insulation health index Jyzs ​​is less than or equal to 1, it indicates that there is no abnormality in the motor operation diagnosis.

10. The online analysis and diagnosis system for insulation of air separation power unit according to claim 9, characterized in that: The diagnosis and evaluation module diagnoses insulation events based on the insulation health index Jyzs ​​and calculates the fault diagnosis accuracy Gzzq. The calculation formula is as follows: In the formula, Gzzq represents the fault diagnosis accuracy, Tp represents the actual number of faults correctly identified as faults, Tn represents the actual number of normals correctly identified as normal, Fp represents the actual number of normals incorrectly identified as faults, and Fn represents the actual number of faults incorrectly identified as normal.

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