An axial flow fan surge warning system and method based on multi-source information fusion

Abstract

The present invention relates to an axial flow fan surge warning system and method based on multi-source information fusion, belonging to the field of fault monitoring of coal mine ventilation equipment. The warning system includes an on-line monitoring module for fan parameters, a data storage module, a surge evaluation module, a warning and alarm module, a man-machine interaction module, and a surge elimination processing module. The steps of the warning method are as follows: establishing an evaluation index system according to the operating state of the fan and the on-site environmental conditions; establishing an evaluation set for the surge state of the fan to determine the warning state of the fan; establishing a weight matrix; judging the membership relationship; performing a surge fuzzy evaluation, and evaluating the surge state of the fan according to the membership relationship between each evaluation index and the surge state; judging the current warning state of the fan; and taking corresponding measures according to the warning state of the fan. The present invention realizes the classified management of fan surge warning, improves the warning accuracy, is beneficial to improving the service life of the fan, reducing the maintenance cost, and ensuring the stable operation of the ventilation system.

Description

Technical Field

[0001] The present invention belongs to the field of coal mine ventilator equipment fault monitoring, relates to ventilator surge monitoring and early warning, and in particular to an axial flow fan surge early warning system and method based on multi-source information fusion. Background Art

[0002] As an indispensable and important equipment in coal mines, axial flow fans undertake important tasks such as providing fresh air flow for the mining face, exhausting toxic and harmful gases and dust, and improving the working environment. In particular, in some high-gas mines, if the ventilation system fails, the amount of gas outflow in the tunnel will gradually increase, forming a safety hazard of gas explosion and gas poisoning, seriously endangering the lives of underground workers. In order to ensure the normal operation of the underground ventilation system, the most important thing is to keep the fan running stably.

[0003] Axial flow fans have a simple structure, are stable and reliable, and are often used in engineering fields such as coal mining, chemical industry, and power generation. However, they are characterized by a certain surge phenomenon. When a fan surges, the air volume, air pressure, and current will fluctuate greatly, the vibration amplitude will increase, and the noise will increase, causing the fan to fail to work normally. If surge occurs for a long time, blades may break and mechanical parts may be fatigued, leading to paralysis of the ventilation system and even catastrophic consequences. Therefore, research on fan surge warning and timely withdrawal is particularly important.

[0004] Research has found that the current mainstream method for axial flow fan surge warning is to analyze parameters such as air volume and pressure, combined with the fan's performance curve, to determine whether it is in the surge alarm area. This method fails to subdivide the surge warning state, fails to reflect the impact of underground environmental parameters on surge, and fails to effectively classify and manage the severity of surge, which directly affects the accuracy of surge warning.

[0005] Therefore, achieving high-precision surge warning for axial flow fans, effectively classifying the severity of surge, and timely adjusting fan operating conditions are of great significance for preventing fan surge, effectively ensuring the stable operation of the ventilation system, and safe production management of coal mines. Summary of the invention

[0006] In view of this, the object of the present invention is to provide an axial flow fan surge warning system and method to achieve hierarchical management of surge warnings, reduce the damage rate and maintenance costs of the fan, and ensure stable operation of the ventilation system.

[0007] In order to achieve the above object, the present invention provides the following technical solution:

[0008] Solution 1: An axial flow fan surge warning system based on multi-source information fusion, the system includes a fan parameter online monitoring module, a data storage module, a surge evaluation module, a warning alarm module, a human-computer interaction module and a surge processing module.

[0009] The fan online monitoring module is used to collect the fan operating parameters, complete signal processing, and transmit data to the data storage module; the surge evaluation module is used to evaluate the current operating status of the fan; the early warning alarm module is used to prompt the current operating status of the fan; the de-surge processing module is used to prevent the fan from entering the surge area or to make the fan leave the surge area.

[0010] Solution 2: An axial flow fan surge warning method based on multi-source information fusion, the method comprising the following steps:

[0011] S1. Establish an evaluation index system based on the operating status of the fan and on-site environmental conditions;

[0012] S2. Establish an evaluation set V of the fan surge state, V = {V1, V2, V3, V4, V5}, where V1 to V5 represent the black warning state, the red warning state, the yellow warning state, the orange warning state and the green no warning state respectively;

[0013] S3. According to the historical data of the fan operation and the performance status of each indicator when the fan surges, the weight of each evaluation indicator is determined by expert scoring method and survey statistics method to establish a weight matrix;

[0014] S4, determining the affiliation: determining the threshold value of surge warning for each indicator in the evaluation indicator system, the threshold value being used to judge the surge warning state of the fan;

[0015] S5. Perform surge fuzzy evaluation, and evaluate the surge state of the fan according to the affiliation between various evaluation indicators and the surge state;

[0016] S6. According to the maximum membership principle, determine the corresponding relationship between the overall evaluation set and the evaluation set, and then judge the current warning state of the wind turbine;

[0017] S7. Take corresponding measures according to the wind turbine warning status.

[0018] Further, in step S1, the evaluation index includes primary evaluation index and secondary evaluation index. The primary evaluation index includes wind pressure, flow, speed, vibration, voltage and current, wind tube length and tunnel area; the secondary evaluation index includes fan operation characteristics, fan state characteristics and working environment characteristics.

[0019] Further, step S4 is specifically as follows: Set the thresholds of each evaluation index when the fan surges, then compare the actual detected values of each evaluation index with the thresholds, and obtain the membership matrix of each evaluation index according to the comparison results.

[0020] Further, the surge fuzzy evaluation is specifically as follows:

[0021] According to the surge evaluation set V and each evaluation index, the membership relationship between the fan surge state and each evaluation index is represented by the membership matrix R, as shown in the following formula:

[0022]

[0023] In the formula, r ij represents the attribution of the i-th evaluation index to the j-th warning state;

[0024] Introduce the evaluation index weight set matrix W:

[0025] W = [w1 w2…w m

[0026] In the formula, w i represents the correlation degree between the i-th evaluation index and the fan surge state; According to the membership degree matrix R and the evaluation index weight set matrix W, the overall evaluation set B is obtained:

[0027] B = W × R.

[0028] The beneficial effects of the present invention are as follows: The present invention applies fuzzy comprehensive evaluation to the surge warning system of mine local ventilators, solves the problem of difficult surge warning caused by complex and changeable working conditions and strong coupling of various influencing factors, represents the current operating conditions of the fan with a multi-state set, realizes the classification management of surge warning, is beneficial to improving the service life of the fan, reducing the damage rate and maintenance cost of the fan, and ensuring the stable operation of the ventilation system.

[0029] Other advantages, objectives and features of the present invention will be described to some extent in the subsequent specification, and to some extent, will be obvious to those skilled in the art based on the study of the following text, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be described in detail preferably with reference to the accompanying drawings, wherein:

[0031] Figure 1 is a schematic diagram of the surge warning system;

[0032] Figure 2 ​It is a schematic diagram of the evaluation index system;

[0033] Figure 3 It is a schematic diagram of the surge warning method process. Specific implementation manners

[0034] The following uses specific specific examples to illustrate the implementation manners of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation manners. The details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0035] Among them, the attached drawings are only for illustrative purposes, showing only schematic diagrams, not physical diagrams, and cannot be understood as a limitation to the present invention; in order to better illustrate the embodiments of the present invention, some components in the attached drawings will be omitted, enlarged or reduced, which does not represent the size of the actual product; for those skilled in the art, it is understandable that some well-known structures and their descriptions in the attached drawings may be omitted.

[0036] In the attached drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components; in the description of the present invention, it should be understood that if there are terms such as "upper", "lower", "left", "right", "front", "rear", etc. indicating the orientation or positional relationship, they are based on the orientation or positional relationship shown in the attached drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, the terms describing the positional relationship in the attached drawings are only for illustrative purposes and cannot be understood as a limitation to the present invention. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific circumstances.

[0037] As Figure 1 shown is an axial flow fan surge warning system, which includes an online monitoring module for fan parameters, a data storage module, a surge evaluation module, a warning and alarm module, a human-machine interaction module, and a surge elimination processing module.

[0038] Among them, the online monitoring module for fan parameters is used to collect various parameters during the operation of the fan, complete signal processing, and transmit data to the data storage module. Among the various parameters of the fan, there are fan air pressure, air duct flow, vibration amplitude, rotational speed, voltage, current, length of the flexible air duct, and roadway area.

[0039] The data storage module is used to store the data of the fan, and the data storage module includes a dynamic storage area and a static storage area. The static storage area is used to store the fan model, rated speed, rated power, rated working voltage and current, and the changes in various parameters when the fan surges; the dynamic storage area is used to store the real-time parameters of the fan such as wind pressure, flow, vibration, etc. when the fan is running in a certain period of time.

[0040] The surge evaluation module is used to evaluate the current operating status of the fan. According to whether surge occurs or there is a trend of surge, the operating status of the fan is divided into black alarm, red alarm, yellow alarm, orange alarm and green normal, which respectively indicate the operating status of severe surge, moderate surge, slight surge, impending surge and no surge.

[0041] The early warning and alarm module is used to indicate the current operating status of the fan, and uses indicator lights, buzzers, and interface displays to express surge evaluation with observable and easily discovered results. The human-computer interaction module is used for communication between operators and the system, such as modifying parameters, extracting or importing data, and displaying the operating status of the fan.

[0042] The de-surge processing module is used to change external conditions to prevent the fan from entering the surge area, or to make the fan leave the surge area to maintain the fan in a stable and normal working state. Specific de-surge control measures include but are not limited to:

[0043] (1) Reduce the speed to adjust the negative pressure on the fan side and reduce the fan vibration caused by wind pressure fluctuations;

[0044] (2) Adjust the opening of the air damper to reduce the equivalent wind resistance on one side of the fan, increase the air volume, and keep the fan away from the surge area;

[0045] (3) Use adjustment plates to reduce mine ventilation resistance;

[0046] (4) If the fan's operating status is still in the surge danger zone or there is no obvious improvement after taking corresponding measures, emergency measures should be taken to prevent the fan from operating in the surge zone for too long and causing sudden shutdown.

[0047] like Figure 3 The following is a fan surge warning method, which is as follows:

[0048] S1. Establish an evaluation index system. Analyze the influencing factors leading to the surge of axial flow fans to establish an evaluation index system. The secondary evaluation indexes are the operating characteristics of the fan, the state characteristics of the fan, and the working environment characteristics. The primary evaluation indexes can specifically include air pressure, flow rate, rotational speed, vibration, voltage and current, duct length, and roadway area. Among them, the operating characteristics of the fan include air pressure and flow rate, the state characteristics of the fan include rotational speed, vibration, voltage and current, and the working environment characteristics include duct length and roadway area, as Figure 2 shown.

[0049] S2. Establish an evaluation set for the surge state. According to the range of surge early warning and combined with the goal of surge evaluation, the evaluation set can be divided into V = {V1, V2, V3, V4, V5}, where V1 to V5 represent the black warning state, red warning state, yellow warning state, orange warning state, and green non-warning state of the fan surge in sequence.

[0050] S3. Establish a weight matrix. The determination of weights mainly includes the expert scoring method and the survey and statistics method, such as the 1-9 scale method. When considering the weights of various indexes, the historical data of the fan operation can be used as a reference to statistically analyze the performance status of each index when the fan surges, so as to determine the weights of each evaluation index. For example, air pressure and flow rate have a greater impact on the fan surge, and larger weight factors should be set when considering the weights.

[0051] S4. Determine the membership relationship. Set the threshold values of each evaluation index when the fan surges, then compare the actual measured values of each evaluation index with the threshold values, and obtain the membership matrix of each evaluation index according to the comparison results.

[0052] Taking air pressure as an example, through data statistical analysis and experience, determine the critical value P max when the fan surges, and then compare the air pressure P obtained by the online monitoring module with the critical value. If the air pressure P exceeds the critical value P max , the membership matrix of this evaluation index is [1, 0, 0, 0, 0], and it can be judged as the black warning state. Correspondingly, if the air pressure is at the lower limit of the warning value, the membership matrix of this evaluation index is [0, 0, 0, 0, 1], and it can be judged as the green non-warning state. Especially, if the air pressure is in the interval [0.95P max , P max , the membership matrix of this evaluation index is [0, 1, 0, 0, 0], and it can be judged as the red warning state.

[0053] S5. Surge fuzzy evaluation. Based on the analytic hierarchy process, fuzzy evaluation can be divided into primary fuzzy evaluation and secondary fuzzy evaluation.

[0054] Among them, the first-level fuzzy evaluation is specifically as follows: Analyze and calculate the first-level evaluation index factor set. Specifically, according to the membership relationship between a certain evaluation index and the evaluation set, combined with the weight information, a first-level fuzzy comprehensive surge evaluation system can be obtained, and its expression is:

[0055] B i =W i ·R i

[0056] In the formula, B i represents the evaluation result of the first-level evaluation index, W i represents the weight set matrix of the first-level evaluation index, and R i represents the membership matrix of the first-level evaluation index. Among them, the weight set matrix W i of the first-level evaluation index has the following expression:

[0057] W i =[w i1 ,w i2 ,…,w ij ,…]

[0058] In the formula, w ij represents the membership of the jth evaluation index in the ith secondary evaluation index to the surge state, and there is:

[0059] W i T ×[1 1…1]=1

[0060] The second-level fuzzy evaluation is specifically as follows: On the basis of the first-level fuzzy evaluation, analyze and calculate the secondary evaluation index, and the calculation formula is:

[0061] B = W ΙΙ ·R ΙΙ

[0062] In the formula, B represents the overall evaluation set, W ΙΙ represents the weight set matrix of the secondary evaluation index, and R ΙΙ represents the membership matrix of the secondary evaluation index. Among them, the expression of the weight set matrix W ΙΙ of the secondary evaluation index is:

[0063] W ΙΙ =[w1,w2,w3]

[0064] In the formula, w i represents the degree of association between the ith secondary evaluation index and the surge state, and w1 + w2 + w3 = 1.

[0065] The expression of the membership matrix R ΙΙ of the secondary evaluation index is:

[0066]

[0067] In the formula, B i represents the evaluation set of the i-th secondary evaluation index, and r ij represents the belonging situation of the i-th secondary evaluation index to the j-th warning state.

[0068] S6. Evaluation of the fan operation state. According to the principle of maximum membership degree, determine the corresponding relationship between the overall evaluation set B and the evaluation set V, and then judge what state the current fan is in. For example, among the elements in the overall evaluation set B, the evaluation set element corresponding to the maximum value is the surge state of the fan.

[0069] S7. Take corresponding anti-surge measures according to the surge warning state.

[0070] As can be seen from the above, the embodiment of the present invention can give an early warning of the surge state of the fan and take corresponding measures, effectively reducing the probability of the fan entering the surge state. At the same time, it also adds a protection barrier to the ventilator and the underground ventilation network, which is beneficial to improving the safety and working efficiency of underground operations.

[0071] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. 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 solutions of the present invention can be modified or equivalently replaced without departing from the purpose and scope of the present technical solution, and they should all be covered by the scope of the claims of the present invention.

Claims

1. An axial flow fan surge warning method based on multi-source information fusion, characterized in that: The method comprises the following steps: S1. Establish an evaluation index system according to the operating state of the fan and the on-site environmental conditions; S2. Establish an evaluation set V for the surge state of the fan, V = {V1, V2, V3, V4, V5}, where V1 to V5 represent the black warning state, red warning state, yellow warning state, orange warning state and green non-warning state in sequence; S3. Determine the weights of each evaluation index by the expert scoring method and the survey and statistics method according to the historical data of the fan operation and the performance status of each index when the fan surges, so as to establish a weight matrix; S4. Judge the membership relationship and determine the threshold value for surge warning of each index in the evaluation index system, and this threshold value is used to judge the surge warning state of the fan; S5. Surge fuzzy evaluation. Evaluate the surge state of the fan according to the membership relationship between each evaluation index and the surge state. Specifically: According to the surge evaluation set V and each evaluation index, represent the membership relationship between the surge state of the fan and each evaluation index through the membership matrix R, as shown in the following formula: where r ij represents the belonging of the i-th evaluation index to the j-th evaluation state, where i = 1, 2, …, m and j = 1, 2, …, n; Introduce the evaluation index weight set matrix W: W = [w1 w2…w m ​ where w i represents the degree of association between the i-th evaluation index and the surge state of the fan; the overall evaluation set B is obtained from the membership matrix R and the evaluation index weight set matrix W: B = W × R; S6. According to the maximum membership degree principle, determine the corresponding relationship between the overall evaluation set and the evaluation set, and then judge the warning state where the fan is currently located; S7. Take corresponding measures according to the warning state of the fan.

2. The surge warning method for an axial flow fan according to claim 1, wherein: In step S1, the evaluation indexes include primary evaluation indexes and secondary evaluation indexes; The primary evaluation indexes include wind pressure, flow rate, rotational speed, vibration, voltage and current, air duct length and roadway area; the secondary evaluation indexes include fan operation characteristics, fan state characteristics and working environment characteristics.

3. The surge warning method for an axial flow fan according to claim 1, characterized in that: Step S4 is specifically: set the threshold values of each evaluation index when the fan surges, then compare the actual measured values of each evaluation index with the threshold values, and obtain the membership matrix of each evaluation index according to the comparison results.

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