A control system for a high-voltage combined frequency converter used in mines

Abstract

The present invention discloses a control system for a mine high-voltage combined frequency converter. The present invention relates to the technical field of frequency converter control. By constructing a collaborative working mechanism of four core modules, namely a data acquisition module, an abnormal area determination module, a key ventilation fan determination module, and a frequency converter control module, the intelligent management of the mine ventilation system is realized; the system uses professional sensors to monitor key data in real time, combines mathematical models to accurately identify and evaluate abnormal positions, and establishes the corresponding relationship between the abnormal area and the ventilation fan through position association; based on the abnormal evaluation value and the position association relationship, the system can intelligently select the most suitable ventilation fan for adjustment, and through the multi-module collaborative control of the high-voltage combined frequency converter, realize the precise adjustment of the ventilation fan speed; this full-process intelligent control not only improves the operation efficiency of the mine ventilation system, but also provides a reliable technical guarantee for the safe production of the mine.

Description

Technical Field

[0001] The present invention relates to the technical field of frequency converter control, and particularly to a control system for a mine high-voltage combined frequency converter. Background Art

[0002] With the continuous development of coal mining technology and the continuous improvement of safety production requirements, the mine ventilation system, as an important infrastructure for ensuring the safety of miners' lives and the normal production of mines, urgently needs to improve its intelligent control level. The traditional mine ventilation system usually operates at a fixed speed or uses a simple frequency conversion adjustment method. This control method has many problems: on the one hand, due to the lack of real-time monitoring and comprehensive analysis capabilities of environmental parameters in each area of the mine, it is impossible to detect and respond to ventilation anomalies in local areas in a timely manner; on the other hand, the adjustment of the ventilator often relies on manual experience judgment, which not only cannot guarantee the accuracy of the adjustment but also is difficult to achieve coordinated control between multiple ventilators.

[0003] At present, although some mines have begun to use frequency converter control systems to adjust the operation of ventilators, there are generally problems such as insufficient utilization of monitoring data, inaccurate identification of abnormal areas, lack of scientific basis for ventilator selection, and unreasonable setting of adjustment parameters. Especially in a complex mine environment, how to accurately identify abnormal areas based on multi-source monitoring data, how to select the most suitable ventilator for adjustment, and how to determine the optimal adjustment parameters are all technical problems faced by the current mine frequency converter control system. Summary of the Invention

[0004] In view of the deficiencies of the prior art, the present invention provides a control system for a mine high-voltage combined frequency converter, which solves the problems in the background art.

[0005] To achieve the above object, the present invention is realized through the following technical solutions: A control system for a mine high-voltage combined frequency converter, comprising:

[0006] A mine data acquisition module, used to determine the positions of all ventilators in the mine and collect important position air flow demand data and environmental condition data in real time;

[0007] An abnormal area determination module, which obtains important position air flow demand data and environmental condition data, determines an abnormal evaluation value of the important position according to the air flow demand data and environmental condition data, and determines the abnormal position according to the abnormal evaluation value;

[0008] A key ventilator determination module, used to determine the key ventilator according to the specific position in the abnormal position, and at the same time associate the key ventilator with the abnormal position;

[0009] A frequency converter control module, used to perform frequency converter adjustment on the key ventilator.

[0010] As a further solution of the present invention: in the frequency converter control module, the frequency converter control module includes an adjustment coefficient value determination unit and a frequency converter control unit;

[0011] The adjustment coefficient value determination unit is used to determine the adjustment coefficient value of each key ventilator according to the total number of abnormal positions associated with each key ventilator and the abnormal evaluation value of the associated abnormal positions;

[0012] The frequency converter control unit is used to obtain the motor speed of the key ventilator and perform frequency converter adjustment on the key ventilator in combination with the adjustment coefficient value of the key ventilator.

[0013] As a further solution of the present invention: in the mine data acquisition module, the air flow demand data includes ventilation volume and wind speed;

[0014] The environmental condition data includes temperature, humidity, carbon monoxide concentration, oxygen concentration and pressure difference.

[0015] As a further solution of the present invention: in the abnormal position determination module, the specific method for determining the abnormal evaluation value of the important position according to the air flow demand data and the environmental condition data and determining the abnormal position according to the abnormal evaluation value is as follows:

[0016] AS1: Mark the ventilation volume and wind speed in the air flow demand data and the temperature, humidity, carbon monoxide concentration, oxygen concentration and pressure difference in the environmental condition data as , ; Mark the ventilation volume, wind speed, temperature, humidity, carbon monoxide concentration, oxygen concentration and pressure difference as , , , , , , ;

[0017] AS2: Set the normal range interval for the ventilation volume and wind speed in the air flow demand data and the temperature, humidity, carbon monoxide concentration, oxygen concentration and pressure difference in the environmental condition data: ;

[0018] AS3: Calculate the deviation degree value for each important position through the following function:

[0019]

[0020] In the formula, represents the deviation degree value of a certain data in the air flow demand data and the environmental condition data, represents the ideal value of the data , and ; Expressed as allowing deviation from the range, and ;

[0021] AS4: Then, determine the anomaly evaluation value of each important position through the following formula:

[0022]

[0023] In the formula, represents the anomaly evaluation value, is the weight coefficient of one of the airflow demand data and the environmental condition data, and ;

[0024] AS5: Compare the anomaly evaluation value of each important position with the threshold value to determine the important positions where the anomaly evaluation value is greater than the threshold value , and mark them as anomaly positions.

[0025] As a further solution of the present invention: In the key ventilator determination module, the specific method for determining the key ventilator according to the specific position in the anomaly position is as follows:

[0026] BS1: Divide the important positions. The important positions include the positions of all ventilators in the mine and the positions in the mine where the airflow demand data and the environmental condition data need to be monitored in real time: Divide the positions of all ventilators in the mine into ventilator important positions, and divide the positions in the mine where the airflow demand data and the environmental condition data need to be monitored in real time into monitoring point important positions;

[0027] BS2: Obtain each anomaly position, and determine whether the anomaly position is located in the ventilator important positions; If the anomaly position is located in one of the ventilator important positions, then mark the ventilator at this position as the key ventilator, and at the same time associate the key ventilator with this anomaly position;

[0028] If the anomaly position is located in one of the monitoring point important positions, obtain the specific position information of this anomaly position, calculate the distances from this position to all ventilator important positions, determine the ventilator important position with the minimum distance among all ventilator important positions, and mark the ventilator at this ventilator important position as the key ventilator, and at the same time associate the key ventilator with this anomaly position.

[0029] As a further solution of the present invention: In the adjustment coefficient value determination unit, the specific method for determining the adjustment coefficient value of each key ventilator according to the total number of anomaly positions associated with each key ventilator and the anomaly evaluation values of the associated anomaly positions is as follows:

[0030] CS1: Obtain all key ventilators, determine the abnormal positions associated with each key ventilator, and determine the abnormal overflow value of each key ventilator through the following formula:

[0031]

[0032] In the formula, represents the abnormal overflow value of the th key ventilator, and , represents the total number of key ventilators, represents the th abnormal position associated with the th key ventilator, and , represents the total number of abnormal positions associated with the th key ventilator;

[0033] CS2: Then, determine the adjustment coefficient value of each key ventilator through the following formula based on the abnormal overflow value and the total number of associated abnormal positions:

[0034]

[0035] In the formula, represents the adjustment coefficient value of the th key ventilator, and are weight coefficients.

[0036] As a further solution of the present invention: In the frequency converter control unit, the specific method of obtaining the motor speed of the key ventilator and performing frequency converter adjustment on the key ventilator in combination with the adjustment coefficient value of the key ventilator is as follows:

[0037] DS1: Successively take each key ventilator as the target ventilator;

[0038] DS2: Obtain the current motor speed of the target ventilator and the adjustment coefficient value of the target ventilator; and determine the expected value of the current target ventilator motor speed through the following formula:

[0039]

[0040] In the formula, represents the expected value of the current target ventilator motor speed, represents the current motor speed of the target ventilator, is a weight coefficient;

[0041] The constraint of

[0042]

[0043] DS3: According to the expected value of the target ventilation fan motor speed , determine the frequency of the target ventilation fan motor frequency converter through the following formula:

[0044]

[0045] In the formula, represents the frequency of the target ventilation fan motor frequency converter, and P is the number of pole pairs of the motor.

[0046] Next, transmit the calculated to the target ventilation fan motor frequency converter to adjust the speed of the target ventilation fan motor.

[0047] The present invention provides a control system for a mine-used high-voltage combined frequency converter. Compared with the prior art, it has the following beneficial effects:

[0048] By constructing a cooperative working mechanism of four core modules, namely a data acquisition module, an abnormal area determination module, a key ventilation fan determination module, and a frequency converter control module, the present invention realizes the intelligent management of the mine ventilation system. The system uses professional sensors to monitor key data in real time, combines mathematical models to accurately identify and evaluate abnormal positions, and establishes the corresponding relationship between the abnormal area and the ventilation fan through position association.

[0049] Based on the abnormal evaluation value and the position association relationship, the system can intelligently select the most suitable ventilation fan for adjustment, and through the multi-module cooperative control of the high-voltage combined frequency converter, realize the precise adjustment of the ventilation fan speed. This full-process intelligent control not only improves the operation efficiency of the mine ventilation system, but also provides a reliable technical guarantee for the safe production of the mine. Brief Description of the Drawings

[0050] The following further describes the present invention with reference to the accompanying drawings.

[0051] Figure 1 is the structural framework diagram of a control system for a mine-used high-voltage combined frequency converter according to the present invention. Detailed Embodiments

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0053] Embodiment 1

[0054] Please refer toFigure 1 , the present invention provides a control system for a mine high-voltage combined frequency converter, including;

[0055] A mine data acquisition module, which is used to determine the positions of all ventilators in the mine and collect real-time air flow demand data and environmental condition data at important positions;

[0056] The important positions include the positions of all ventilators in the mine and the positions in the mine where real-time monitoring of air flow demand data and environmental condition data is required;

[0057] It should be noted that the positions where real-time monitoring of air flow demand data and environmental condition data is required are specifically determined by relevant mine workers. Usually, there are certain risks at these positions where real-time monitoring of air flow demand data and environmental condition data is required. For example, there may be situations such as low oxygen concentration or poor gas circulation;

[0058] The air flow demand data includes ventilation volume and wind speed;

[0059] The environmental condition data includes temperature, humidity, carbon monoxide concentration, oxygen concentration and pressure difference;

[0060] It should be noted that both the air flow demand data and the environmental condition data are obtained by installing corresponding sensors at important positions. For example, the data collection of ventilation volume is measured by using an air flow meter to measure the ventilation volume in the mine, the data collection of wind speed is measured by using an anemometer to measure the air flow speed in the mine, the data collection of temperature is measured by using a temperature sensor to measure the temperature in the mine, the data collection of humidity is measured by using a humidity sensor to measure the relative humidity in the mine, the data collection of carbon monoxide concentration is measured by using a carbon monoxide gas detector to measure the carbon monoxide concentration in the mine, the data collection of oxygen concentration is measured by using an oxygen sensor to measure the oxygen concentration in the mine, and the data collection of pressure difference is measured by using a differential pressure sensor to measure the air pressure difference between different areas of the mine;

[0061] The mine data acquisition module realizes the real-time collection and monitoring of key data such as ventilation volume, wind speed, temperature, humidity, carbon monoxide concentration, oxygen concentration and pressure difference by deploying professional sensor devices at important positions in the mine; especially in risk areas with low oxygen concentration or poor gas circulation, through the configuration of professional devices such as air flow meters, anemometers, temperature sensors, humidity sensors, carbon monoxide gas detectors, oxygen sensors and differential pressure sensors, the accuracy, real-time and comprehensiveness of data collection are ensured, providing reliable basic data support for subsequent abnormal judgment and control adjustment of the system;

[0062] An abnormal position determination module, which obtains the air flow demand data and environmental condition data of important positions, determines the abnormal evaluation value of important positions according to the air flow demand data and environmental condition data, and determines the abnormal positions according to the abnormal evaluation value;

[0063] The specific method for determining the abnormal evaluation value of important positions according to the air flow demand data and environmental condition data, and determining the abnormal positions according to the abnormal evaluation value is as follows:

[0064] AS1: Mark the ventilation volume, wind speed in the air flow demand data, and temperature, humidity, carbon monoxide concentration, oxygen concentration, and pressure difference in the environmental condition data as , ;

[0065] Specifically, mark the ventilation volume, wind speed, temperature, humidity, carbon monoxide concentration, oxygen concentration, and pressure difference as , , , , , , ;

[0066] AS2: Set the normal range intervals for the ventilation volume, wind speed in the air flow demand data, and temperature, humidity, carbon monoxide concentration, oxygen concentration, and pressure difference in the environmental condition data: ;

[0067] AS3: Calculate the deviation degree value for each important position through the following function:

[0068]

[0069] In the formula, represents the deviation degree value of a certain data in the air flow demand data and environmental condition data, represents the ideal value of the data , and ; represents the allowable deviation range, and ;

[0070] AS4: Then determine the abnormal evaluation value of each important position through the following formula:

[0071]

[0072] In the formula, represents the abnormal evaluation value, is the weight coefficient of a certain data in the air flow demand data and environmental condition data, and ;

[0073] AS5: The abnormal evaluation value at each important position is compared with the threshold value to determine the important positions where the abnormal evaluation value is greater than the threshold value , and mark them as abnormal positions;

[0074] The abnormal area determination module first standardizes seven types of key data and sets the normal range interval, then evaluates the abnormality degree of each parameter through a deviation degree value calculation function, and then calculates the comprehensive abnormal evaluation value in combination with the weight coefficient; by comparing the abnormal evaluation value with the preset threshold value, the abnormal positions that need to be focused on can be accurately identified; this evaluation method based on a mathematical model not only realizes the precise quantification of abnormal situations, but also realizes the differential treatment of the importance of different parameters through weight configuration, improving the scientificity and reliability of the determination of abnormal areas;

[0075] The key ventilator determination module is used to determine the key ventilator according to the specific position in the abnormal positions, and at the same time associate the key ventilator with the abnormal position;

[0076] The specific method for determining the key ventilator according to the specific position in the abnormal positions is as follows:

[0077] BS1: Divide the important positions, where the important positions include the positions of all ventilators in the mine and the positions in the mine where the air flow demand data and environmental condition data need to be monitored in real time:

[0078] Divide the positions of all ventilators in the mine into ventilator important positions, and divide the positions in the mine where the air flow demand data and environmental condition data need to be monitored in real time into monitoring point important positions;

[0079] BS2: Obtain each abnormal position and judge whether the abnormal position is located in the ventilator important positions; if the abnormal position is located in one of the ventilator important positions, mark the ventilator at this position as the key ventilator, and at the same time associate the key ventilator with the abnormal position;

[0080] If the abnormal position is located in one of the monitoring point important positions, obtain the specific position information of the abnormal position, calculate the distances from this position to all ventilator important positions, determine the ventilator important position with the minimum distance from this position to all ventilator important positions, and mark the ventilator at this ventilator important position as the key ventilator, and at the same time associate the key ventilator with the abnormal position;

[0081] The key ventilator determination module divides important positions into two categories: important positions of ventilators and important positions of monitoring points, and establishes an intelligent ventilator selection mechanism; for anomalies located at ventilator positions, the corresponding ventilator is directly determined as the key ventilator; for anomalies located at monitoring points, by calculating the distances to each ventilator, the nearest ventilator is selected as the key ventilator; this intelligent selection mechanism based on location association ensures that the system can select the most suitable ventilator for adjustment for anomalies at different positions, establishing an accurate correspondence between the anomaly positions and ventilators, providing a clear control target for subsequent frequency conversion adjustment;

[0082] The frequency converter control module is used to perform frequency converter adjustment on the key ventilators; the frequency converter control module includes an adjustment coefficient value determination unit and a frequency converter control unit;

[0083] The adjustment coefficient value determination unit is used to determine the adjustment coefficient value of each key ventilator according to the total number of anomaly positions associated with each key ventilator and the anomaly evaluation values of the associated anomaly positions;

[0084] The specific method for determining the adjustment coefficient value of each key ventilator according to the total number of anomaly positions associated with each key ventilator and the anomaly evaluation values of the associated anomaly positions is as follows:

[0085] CS1: Obtain all key ventilators, and determine the anomaly positions associated with each key ventilator. Determine the anomaly overflow value of each key ventilator through the following formula:

[0086]

[0087] In the formula, represents the anomaly overflow value of the th key ventilator, and , represents the total number of key ventilators, represents the th anomaly position associated with the th key ventilator, and , represents the total number of anomaly positions associated with the th key ventilator. For different key ventilators, the value of the total number of associated anomaly positions takes different values;

[0088] CS2: Then, determine the adjustment coefficient value of each key ventilator through the following formula according to the anomaly overflow value and the total number of associated anomaly positions:

[0089]

[0090] In the formula, represents the The adjustment coefficient value of each key fan, and is the weight coefficient;

[0091] A frequency converter control unit is used to obtain the motor speed of the key ventilator and perform frequency converter regulation on the key ventilator in combination with the regulation coefficient value of the key ventilator;

[0092] The inverter control module achieves precise adjustment of key fans through the coordinated work of the adjustment coefficient value determination unit and the inverter control unit.

[0093] Embodiment 2

[0094] In the specific implementation process, this embodiment is based on the first embodiment and is different from the first embodiment in that this embodiment further describes the inverter adjustment process in the inverter control unit;

[0095] In the inverter control unit, the specific method of obtaining the motor speed of the key ventilator and adjusting the inverter of the key ventilator in combination with the adjustment coefficient value of the key ventilator is:

[0096] DS1: Each key ventilator is used as the target ventilator in turn;

[0097] DS2: Obtain the current motor speed of the target ventilator and the adjustment coefficient value of the target ventilator; and determine the expected value of the current motor speed of the target ventilator by the following formula:

[0098]

[0099] In the formula, Indicates the expected value of the current target fan motor speed, Indicates the current motor speed of the target ventilator, is the weight coefficient;

[0100] To ensure that the target fan motor speed does not exceed its maximum allowable value , introduce the following constraints:

[0101]

[0102] DS3: The inverter adjusts the operating frequency of the target fan motor To control the speed of the target ventilator motor, and the relationship between the operating frequency of the target ventilator motor and the speed of the target ventilator motor is: , where P is the number of pole pairs of the motor, which is usually a fixed value; according to the expected value of the target fan motor speed , determine the target fan motor inverter frequency by the following formula:

[0103]

[0104] In the formula, is expressed as the frequency of the target ventilator motor frequency converter;

[0105] Next, the calculated is transmitted to the target ventilator motor frequency converter to adjust the speed of the target ventilator motor;

[0106] It should be noted that in the high-voltage combined frequency converter, the working mode of the high-voltage combined frequency converter is that multiple frequency converters control multiple motors: the high-voltage combined frequency converter usually includes multiple frequency converter modules, and each module is used to control the operation of an independent motor; for example, an industrial production line may require multiple high-power motors. At this time, each motor needs an independent frequency converter to adjust the speed to meet different load requirements. In this embodiment, each frequency converter in the high-voltage combined frequency converter corresponds to the adjustment of the motor speed of a ventilator;

[0107] The frequency converter control module first calculates the abnormal overflow value and the adjustment coefficient value based on the number and degree of abnormal positions associated with each key ventilator, and then combines the current motor speed to calculate the optimal motor speed expectation value and the frequency converter frequency through a scientific mathematical model; it can increase the speed of the key ventilator to accelerate the air circulation in the mine, thereby effectively improving the airflow demand data and environmental condition data at the abnormal position and quickly bringing them to a reasonable numerical range; during this process, the system also considers the maximum motor speed limit to ensure the safety of the adjustment process; this adjustment mechanism based on multi-parameter comprehensive calculation not only realizes the precise control of the ventilator, but also ensures the coordinated operation of the entire ventilation system through the collaborative work of multiple modules of the high-voltage combined frequency converter, effectively improving the intelligent level and operation efficiency of the mine ventilation system.

[0108] Embodiment III

[0109] In the specific implementation process of this embodiment, it includes all the implementation processes of the above two groups of embodiments.

[0110] Some of the data in the above formula are numerically calculated after removing their dimensions, and the content not described in detail in this specification belongs to the prior art well-known to those skilled in the art.

[0111] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A control system for a high-voltage combined frequency converter for mining, characterized in that, Including: A mine data acquisition module, which is used to determine the positions of all ventilators in the mine and collect the air flow demand data and environmental condition data at important positions in real time; An abnormal area determination module, which obtains the air flow demand data and environmental condition data at important positions, determines the abnormal evaluation value of important positions according to the air flow demand data and environmental condition data, and determines the abnormal positions according to the abnormal evaluation value; A key ventilator determination module, which is used to determine the key ventilator according to the specific position in the abnormal positions, and at the same time associate the key ventilator with the abnormal position; A frequency converter control module, which is used to adjust the frequency converter of the key ventilator; In the frequency converter control module, the frequency converter control module includes an adjustment coefficient value determination unit and a frequency converter control unit; The adjustment coefficient value determination unit is used to determine the adjustment coefficient value of each key ventilator according to the total number of abnormal positions associated with each key ventilator and the abnormal evaluation value of the associated abnormal positions; The frequency converter control unit is used to obtain the motor speed of the key ventilator and adjust the frequency converter of the key ventilator in combination with the adjustment coefficient value of the key ventilator; In the mine data acquisition module, the air flow demand data includes the ventilation volume and the wind speed; The environmental condition data includes temperature, humidity, carbon monoxide concentration, oxygen concentration and pressure difference; In the abnormal position determination module, the specific method for determining the abnormal evaluation value of important positions according to the air flow demand data and environmental condition data and determining the abnormal positions according to the abnormal evaluation value is as follows: AS1: Mark the ventilation volume in the air flow demand data, and the temperature, humidity, carbon monoxide concentration, oxygen concentration, and pressure difference in the environmental condition data as , ; Mark the ventilation volume, wind speed, temperature, humidity, carbon monoxide concentration, oxygen concentration, and pressure difference as , , , , , , ; AS2: Set the normal range intervals for the ventilation volume in the air flow demand data, the wind speed, and the temperature, humidity, carbon monoxide concentration, oxygen concentration, and pressure difference in the environmental condition data: ; AS3: Calculate the deviation degree value for each important position through the following function: ； In the formula, represents the deviation degree value of either the air flow demand data or the environmental condition data, represents the data of the ideal value, and ; represents the allowable deviation range, and ; AS4: Then determine the abnormal evaluation value of each important position through the following formula: ； In the formula, is expressed as an anomaly evaluation value, is the weight coefficient of either the air flow demand data or the environmental condition data, and ; AS5: Evaluate the anomaly value at each important position and compare it with the threshold value to determine the important positions where the anomaly evaluation value is greater than the threshold value and mark them as anomaly positions; In the key ventilator determination module, the specific method for determining the key ventilator according to the specific position in the abnormal positions is as follows: BS1: Divide the important positions. The important positions include the positions of all ventilators in the mine and the positions in the mine where the air flow demand data and environmental condition data need to be monitored in real time: Divide the positions of all ventilators in the mine into ventilator important positions, and divide the positions in the mine where the air flow demand data and environmental condition data need to be monitored in real time into monitoring point important positions; BS2: Obtain each abnormal position and judge whether the abnormal position is located in the ventilator important positions; If the abnormal position is located in one of the ventilator important positions, mark the ventilator at this position as the key ventilator, and at the same time associate the key ventilator with the abnormal position; If the abnormal position is located in one of the monitoring point important positions, obtain the specific position information of the abnormal position, calculate the distances from this position to all ventilator important positions, determine the ventilator important position with the minimum distance from this position to all ventilator important positions, and mark the ventilator at this ventilator important position as the key ventilator, and at the same time associate the key ventilator with the abnormal position.

2. The control system of a mine-used high-voltage combined frequency converter according to claim 1, characterized in that, In the adjustment coefficient value determination unit, the specific method for determining the adjustment coefficient value of each key ventilator according to the total number of abnormal positions associated with each key ventilator and the abnormal evaluation value of the associated abnormal positions is as follows: CS1: Obtain all key ventilators, determine the abnormal positions associated with each key ventilator, and determine the abnormal overflow value of each key ventilator through the following formula: ； In the formula, represents the abnormal overflow value of the th key ventilator, and , represents the total number of key ventilators, represents the th abnormal position associated with the th key ventilator, and , represents the total number of abnormal positions associated with the th key ventilator; CS2: Then, determine the adjustment coefficient value of each key ventilator according to the abnormal overflow value and the total number of associated abnormal positions through the following formula: ； In the formula, represents the adjustment coefficient value of the th key ventilator, and are weight coefficients.

3. The control system of a mine-used high-voltage combined frequency converter according to claim 2, characterized in that, In the frequency converter control unit, the specific method of obtaining the motor speed of the key ventilator and performing frequency converter adjustment on the key ventilator in combination with the adjustment coefficient value of the key ventilator is as follows: DS1: Successively take each key ventilator as the target ventilator; DS2: Obtain the current motor speed of the target ventilator and the adjustment coefficient value of the target ventilator; And determine the expected value of the current target ventilator motor speed through the following formula: ； In the formula, represents the expected value of the current target ventilation fan motor speed, represents the current motor speed of the target ventilation fan, is the weight coefficient; The constraint is determined by the following formula: ； DS3: According to the expected value of the target ventilator motor speed , determine the frequency of the target ventilator motor frequency converter through the following formula: ； In the formula, represents the frequency of the motor frequency converter of the target ventilator, and P is the number of pole pairs of the motor; Next, the calculated is transmitted to the target ventilator motor frequency converter to adjust the rotational speed of the target ventilator motor.

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