A method and system for detecting abnormal vibration of a high-speed rotating machinery blade

Abstract

The application discloses a kind of abnormal vibration detection method and system of high-speed rotating machinery blade, it is related to mechanical engineering field, it solves the problem that existing abnormal vibration detection method exists and detects the effect is not good, including steps S1: to each vibration detection point in the equipment vibration detection period is periodically abnormal vibration detection, according to the test result, rotating machinery equipment is divided into first type mechanical equipment and second type mechanical equipment, obtain rotating equipment type division data, step S2: according to rotating equipment type division data, second type mechanical equipment is carried out blade rotation error detection, according to the test result, obtain blade rotation error detection numerical value, step S3: according to rotating equipment type division data and blade rotation error detection numerical value, abnormal vibration early warning is carried out to high-speed rotating machinery blade, the accuracy and pertinence of abnormal vibration detection result of high-speed rotating machinery blade are guaranteed by the application.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of mechanical engineering, and relates to sensor technology, in particular to an abnormal vibration detection method and system for high-speed rotating mechanical blades. BACKGROUND

[0002] The existing abnormal vibration detection method has the following defects when detecting the vibration of high-speed rotating mechanical blades:

[0003] 1. The existing abnormal vibration detection method cannot perform periodic abnormal vibration detection on each vibration detection point in the device vibration detection cycle, cannot perform targeted vibration detection on the high-speed rotating mechanical blades according to the detection results, and cannot issue early warnings, so that the detection process lacks pertinence.

[0004] 2. The existing abnormal vibration detection method cannot create a space rectangular coordinate system according to the rotating equipment type division data to detect the blade rotation error of the high-speed rotating mechanical blades, so that the detection results lack accuracy.

[0005] Therefore, the application provides an abnormal vibration detection method and system for high-speed rotating mechanical blades. SUMMARY

[0006] In view of the deficiencies of the prior art, the application aims to provide an abnormal vibration detection method and system for high-speed rotating mechanical blades, and aims to improve the pertinence and accuracy of the abnormal vibration detection method for high-speed rotating mechanical blades.

[0007] In order to achieve the above-mentioned purpose, the application adopts the following technical scheme: an abnormal vibration detection method for high-speed rotating mechanical blades, comprising the following steps:

[0008] Step S1: A plurality of vibration detection points are arranged outside the rotating mechanical equipment, a device vibration detection cycle is created, periodic abnormal vibration detection is performed on each vibration detection point in the device vibration detection cycle, the rotating mechanical equipment is divided into a first type of mechanical equipment and a second type of mechanical equipment according to the detection results, and rotating equipment type division data is obtained.

[0009] Step S2: The blade rotation error of the second type of mechanical equipment is detected according to the rotating equipment type division data, and the blade rotation error detection value corresponding to the second type of mechanical equipment is obtained according to the detection results.

[0010] Step S3: The abnormal vibration of the high-speed rotating mechanical blades is warned according to the rotating equipment type division data and the blade rotation error detection value.

[0011] Further, the step S1 further comprises the following steps:

[0012] Step S11: setting a plurality of vibration detection points outside the rotating mechanical equipment, and selecting a characteristic vibration detection point from the plurality of vibration detection points;

[0013] Step S12: in the process of detecting the wind of the rotating mechanical equipment, taking the time point corresponding to the current time as the cycle end time point, and marking a device vibration detection cycle;

[0014] Step S13: detecting the vibration frequency of the characteristic vibration detection point in the device vibration detection cycle, and obtaining the cycle vibration frequency detection value corresponding to the characteristic vibration detection point according to the detection result;

[0015] Step S14: obtaining the cycle vibration frequency detection value corresponding to each vibration detection point respectively, and obtaining a plurality of cycle vibration frequency detection values;

[0016] Step S15: comparing the plurality of cycle vibration frequency detection values, and marking the cycle vibration frequency detection value with the largest value as the device vibration cycle detection value;

[0017] Step S16: obtaining a device vibration detection reference interval, if the device vibration cycle detection value is in the device vibration detection reference interval, the rotating mechanical equipment is divided into a first type of mechanical equipment, if the device vibration cycle detection value is not in the device vibration detection reference interval, the rotating mechanical equipment is divided into a second type of mechanical equipment, and the rotating equipment type division data is obtained.

[0018] Further, the step S13 further includes the following steps:

[0019] Step S131: dividing the device vibration detection cycle into a plurality of continuous detection time points, obtaining the device vibration frequency value corresponding to the characteristic vibration detection point at each detection time point respectively, and obtaining a plurality of device vibration frequency values;

[0020] Step S132: comparing the plurality of device vibration frequency values, marking the device vibration frequency value with the largest value as the peak vibration frequency value of the characteristic point, and marking the device vibration frequency value with the smallest value as the valley vibration frequency value of the characteristic point;

[0021] Step S133: obtaining the wind value range between the peak vibration frequency value of the characteristic point and the valley vibration frequency value of the characteristic point, obtaining the cycle wind peak valley interval, dividing the cycle wind peak valley interval into a plurality of vibration frequency subintervals, and marking the vibration frequency subintervals as F1 vibration frequency subinterval to Fa vibration frequency subinterval according to the interval wind value size.

[0022] Further, the step S13 further comprises the following steps:

[0023] Step S134: obtaining the interval middle value corresponding to the F1 vibration frequency sub-interval to obtain the F1 vibration interval middle value, obtaining the interval middle value corresponding to the F2 vibration frequency sub-interval to obtain the F2 vibration interval middle value, and so on, obtaining the interval middle value corresponding to the Fa vibration frequency sub-interval to obtain the Fa vibration interval middle value;

[0024] Step S135: in the equipment vibration detection period, the detection time point of the equipment vibration frequency value in the F1 vibration frequency sub-interval is accumulated to obtain the F1 vibration frequency duration, the detection time point of the equipment vibration frequency value in the F2 vibration frequency sub-interval is accumulated to obtain the F2 vibration frequency duration, and so on, the detection time point of the equipment vibration frequency value in the Fa vibration frequency sub-interval is accumulated to obtain the Fa vibration frequency duration;

[0025] Step S136: obtaining the time length corresponding to the equipment vibration detection period to obtain the equipment vibration period length;

[0026] Step S137: calculating the equipment vibration period length, the F1 vibration interval middle value to the Fa vibration interval middle value, and the F1 vibration frequency duration to the Fa vibration frequency duration to obtain the periodic vibration frequency detection value corresponding to the characteristic vibration detection point;

[0027] The periodic vibration frequency detection value corresponding to the characteristic vibration detection point is calculated.

[0028] Further, the step S2 further comprises the following steps:

[0029] Step S21: obtaining rotating equipment type division data, and obtaining the first type mechanical equipment and the second type mechanical equipment according to the rotating equipment type division data;

[0030] Step S22: if the rotating mechanical equipment is the second type mechanical equipment, obtaining the rotating blades corresponding to the second type mechanical equipment to obtain a plurality of equipment rotating blades, marking any two pieces of the obtained plurality of equipment rotating blades as one rotating blade group to obtain a plurality of rotating blade groups, and selecting a sample rotating blade group from the obtained plurality of rotating blade groups;

[0031] Step S23: detecting the blade rotation error of the sample rotating blade group, and obtaining the blade installation deviation value corresponding to the sample rotating blade group according to the detection result;

[0032] Step S24: Obtain the blade installation deviation value corresponding to each rotating blade group respectively, obtain a plurality of blade installation deviation values, and compare the plurality of blade installation deviation values, and mark the largest blade installation deviation value as the blade rotation error detection value corresponding to the second type of mechanical equipment.

[0033] Further, the step S23 further includes the following steps:

[0034] Step S231: Obtain the equipment rotating blades in the sample rotating blade group, and mark the obtained equipment rotating blades as the first equipment rotating blade and the second equipment rotating blade respectively;

[0035] Step S232: Three-dimensional model the space region where the sample rotating blade group is located to obtain a sample region three-dimensional model, and create a three-dimensional coordinate system in the sample region three-dimensional model;

[0036] Step S233: Mark a feature point on the surface of the first equipment rotating blade to obtain a first blade feature point, and mark a feature point on the surface of the second equipment rotating blade to obtain a second blade feature point;

[0037] Step S234: Mark a feature rotation angle at the rotating crankshaft corresponding to the rotating mechanical equipment, obtain the coordinates of the first blade feature point in the sample region three-dimensional coordinate system when the first equipment rotating blade rotates to the feature rotation angle to obtain the first blade feature coordinates;

[0038] Step S235: Obtain the coordinates of the second blade feature point in the sample region three-dimensional coordinate system when the second equipment rotating blade rotates to the feature rotation angle to obtain the second blade feature coordinates;

[0039] Step S236: Calculate the first blade feature coordinates and the second blade feature coordinates to obtain the blade installation deviation value corresponding to the sample rotating blade group;

[0040] Calculate the blade installation deviation value corresponding to the sample rotating blade group.

[0041] Further, the step S23 further includes the following steps:

[0042] Mark the rotation axis corresponding to the sample rotating vane set as a first device coordinate point, draw a plane perpendicular to the ground through the first device coordinate point to obtain a first device coordinate plane, draw a straight line through the first device coordinate point in the first device coordinate plane to obtain a first device coordinate straight line, draw a straight line perpendicular to the first device coordinate straight line through the first device coordinate point to obtain a second device coordinate straight line, draw a plane perpendicular to the first device coordinate plane through the first device coordinate point to obtain a second device coordinate plane, and draw a straight line perpendicular to the first device coordinate plane through the first device coordinate point in the second device coordinate plane to obtain a third device coordinate straight line.

[0043] Mark the first coordinate point as a coordinate origin, mark the first device coordinate straight line as a coordinate x-axis, mark the second device coordinate straight line as a coordinate y-axis, and mark the third device coordinate straight line as a coordinate z-axis to obtain a sample area three-dimensional coordinate system.

[0044] Further, the step S3 further includes the following specific steps:

[0045] Step S31: Obtain rotating device type division data, and obtain a first type mechanical device and a second type mechanical device according to the rotating device type division data.

[0046] Step S32: If the rotating mechanical device is the first type mechanical device, no vane vibration abnormality early warning needs to be issued.

[0047] Step S33: If the rotating mechanical device is the second type mechanical device, issue a vane vibration abnormality early warning, and perform abnormality analysis on a vane rotation error.

[0048] Further, the step S33 further includes the following specific steps:

[0049] Obtain a vane rotation error detection value corresponding to the second type mechanical device.

[0050] Obtain a vane rotation error reference interval, if the vane rotation error detection value is in the vane rotation error reference interval, it is determined that the vane rotation angle is not abnormal, and if the vane rotation error detection value is not in the vane rotation error reference interval, it is determined that the vane rotation angle is abnormal, and an abnormality early warning is issued.

[0051] An abnormal vibration detection system for high-speed rotating mechanical vanes, comprising:

[0052] A vibration data module: a plurality of vibration monitoring points are arranged outside the rotating mechanical device, a device vibration monitoring period is created, periodic abnormal vibration monitoring is performed on each vibration monitoring point in the device vibration monitoring period, the rotating mechanical device is divided into a first type mechanical device and a second type mechanical device according to the detection result, and rotating device type division data is obtained.

[0053] The mechanical rotation module: according to the rotating equipment type division data, the second type of mechanical equipment is monitored for blade rotation error, and the second type of mechanical equipment is obtained according to the monitoring result The blade rotation error monitoring value corresponding to the error monitoring value of the blade rotation error of the second type of mechanical equipment is obtained;

[0054] The abnormal early warning module: according to the rotating equipment type division data and the blade rotation error monitoring value, the abnormal vibration of the high-speed rotating mechanical blade is early warned.

[0055] As described above, due to the adoption of the above technical scheme, the beneficial effects of the present application are:

[0056] 1. The present application carries out periodic abnormal vibration detection on each vibration detection point in the equipment vibration detection cycle, further detects the vibration of the high-speed rotating mechanical blade according to the detection result, and issues a warning, which can improve the lack of pertinence in the detection process.

[0057] 2. The present application creates a space rectangular coordinate system according to the rotating equipment type division data to detect the blade rotation error of the high-speed rotating mechanical blade, thereby improving the accuracy of the vibration detection result. BRIEF DESCRIPTION OF DRAWINGS

[0058] In order to facilitate the understanding of those skilled in the art, the present application will be further described below in conjunction with the drawings.

[0059] Figure 1 The embodiment steps of the present application are shown in the figure;

[0060] Figure 2 The overall system block diagram of the present application is shown in the figure. DETAILED DESCRIPTION

[0061] The technical scheme of the present application will be described below in conjunction with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0062] Embodiment one

[0063] Please refer to Figure 1 The present application provides a technical scheme: an abnormal vibration detection system for high-speed rotating mechanical blade, comprising the following steps in detail:

[0064] The step S1 further comprises the following steps in detail:

[0065] Step S11: setting a plurality of vibration detection points outside the rotating mechanical equipment, and selecting a characteristic vibration detection point from the plurality of vibration detection points.

[0066] Step S12: In the process of wind detection of the rotating mechanical equipment, the time point corresponding to the current time is marked as a cycle end time point, and a device vibration detection cycle is marked;

[0067] Step S13: Vibration frequency detection is performed on the characteristic vibration detection point in the device vibration detection cycle, and a cycle vibration frequency detection value corresponding to the characteristic vibration detection point is obtained according to the detection result;

[0068] In the step S13, the following steps are further included:

[0069] Step S131: The device vibration detection cycle is divided into a plurality of continuous detection time points, a device vibration frequency value corresponding to each detection time point of the characteristic vibration detection point is obtained respectively, and a plurality of device vibration frequency values are obtained;

[0070] Step S132: The plurality of device vibration frequency values are compared in value, the maximum device vibration frequency value is marked as a characteristic point peak vibration frequency value, and the minimum device vibration frequency value is marked as a characteristic point valley vibration frequency value;

[0071] Step S133: The wind value range between the characteristic point peak vibration frequency value and the characteristic point valley vibration frequency value is obtained, a cycle wind peak valley interval is obtained, the cycle wind peak valley interval is divided into a plurality of vibration frequency subintervals, and the divided vibration frequency subintervals are sequentially marked as F1 vibration frequency subinterval to Fa vibration frequency subinterval according to the interval wind value;

[0072] Step S134: The interval median value corresponding to the F1 vibration frequency subinterval is obtained, the F1 vibration interval median value is obtained, the interval median value corresponding to the F2 vibration frequency subinterval is obtained, the F2 vibration interval median value is obtained, and so on, the interval median value corresponding to the Fa vibration frequency subinterval is obtained, and the Fa vibration interval median value is obtained;

[0073] Step S135: In the device vibration detection cycle, the detection time points at which the device vibration frequency value is in the F1 vibration frequency subinterval are accumulated in length, the F1 vibration frequency duration is obtained, the detection time points at which the device vibration frequency value is in the F2 vibration frequency subinterval are accumulated in length, the F2 vibration frequency duration is obtained, and so on, the detection time points at which the device vibration frequency value is in the Fa vibration frequency subinterval are accumulated in length, and the Fa vibration frequency duration is obtained;

[0074] Step S136: The time length corresponding to the device vibration detection cycle is obtained, and a device vibration cycle duration is obtained;

[0075] Step S137: obtaining the periodic vibration frequency detection value corresponding to the feature vibration detection point by calculating the device vibration cycle time, the F1 vibration interval middle value to the Fa vibration interval middle value, and the F1 vibration frequency duration to the Fa vibration frequency duration;

[0076] The periodic vibration frequency detection value corresponding to the feature vibration detection point is calculated, and the specific formula is as follows:

[0077]

[0078] Wherein, Zzl is the periodic vibration frequency detection value corresponding to the feature vibration detection point, Zqzi is the Fi vibration interval middle value, Szci is the Fi vibration frequency duration, Zsc is the device vibration cycle time, and a is the number value corresponding to the vibration frequency sub-interval;

[0079] Step S14: obtaining the periodic vibration frequency detection value corresponding to each vibration detection point respectively, to obtain a plurality of periodic vibration frequency detection values;

[0080] Step S15: performing numerical comparison on the obtained plurality of periodic vibration frequency detection values, and marking the periodic vibration frequency detection value with the largest value as the device vibration cycle detection value;

[0081] Step S16: obtaining a device vibration detection reference interval, if the device vibration cycle detection value is in the device vibration detection reference interval, the rotating machinery equipment is divided into a first type of machinery equipment, if the device vibration cycle detection value is not in the device vibration detection reference interval, the rotating machinery equipment is divided into a second type of machinery equipment, to obtain rotating equipment type division data.

[0082] Step S2: detecting the blade rotation error of the second type of machinery equipment according to the rotating equipment type division data, and obtaining the blade rotation error detection value corresponding to the second type of machinery equipment according to the detection result;

[0083] The step S2 further includes the following steps:

[0084] Step S21: obtaining rotating equipment type division data, and obtaining the first type of machinery equipment and the second type of machinery equipment according to the rotating equipment type division data;

[0085] Step S22: if the rotating machinery equipment is the second type of machinery equipment, the rotating blades corresponding to the second type of machinery equipment are obtained respectively, to obtain a plurality of device rotating blades, any two of the obtained plurality of device rotating blades are marked as a rotating blade group, a plurality of rotating blade groups are obtained, and a sample rotating blade group is selected from the obtained plurality of rotating blade groups; ​

[0086] Step S23: blade rotation error detection is performed on the sample rotating vane group, and a vane selection deviation value corresponding to the sample rotating vane group is obtained according to a detection result;

[0087] The step S23 further includes the following steps:

[0088] Step S231: a device rotating vane in the sample rotating vane group is obtained, and the obtained device selection vane is marked as a first device rotating vane and a second device rotating vane respectively;

[0089] Step S232: a space region where the sample rotating vane group is located is three-dimensionally modeled to obtain a sample region three-dimensional model, and a three-dimensional coordinate system is created in the sample region three-dimensional model;

[0090] The step S23 further includes the following steps:

[0091] A rotating axis corresponding to the sample rotating vane group is marked as a first device coordinate point, a plane perpendicular to the ground is made through the first device coordinate to obtain a first device coordinate plane, a straight line is made through the first device coordinate point in the first device coordinate plane to obtain a first device coordinate straight line, a straight line perpendicular to the first device coordinate straight line is made through the first device coordinate point to obtain a second device coordinate straight line, a plane perpendicular to the first device coordinate plane is made through the first device coordinate point to obtain a second device coordinate plane, and a straight line perpendicular to the first device coordinate plane is made through the first device coordinate point in the second device coordinate plane to obtain a third device coordinate straight line;

[0092] The first coordinate point is marked as a coordinate origin, the first device coordinate straight line is marked as a coordinate x-axis, the second device coordinate straight line is marked as a coordinate y-axis, and the third device coordinate straight line is marked as a coordinate z-axis to obtain a sample region three-dimensional coordinate system;

[0093] Step S233: a feature point is marked on a surface of the first device rotating vane to obtain a first vane feature point, and a feature point is marked on a surface of the second device rotating vane to obtain a second vane feature point;

[0094] Step S234: a feature rotating angle is marked at a rotating crank corresponding to the rotating mechanical device, when the first device rotating vane rotates to the feature rotating angle, a coordinate of the first vane feature point in the sample region three-dimensional coordinate system is obtained to obtain a first vane feature coordinate;

[0095] Step S235: when the second device rotating vane rotates to the feature rotating angle, a coordinate of the second vane feature point in the sample region three-dimensional coordinate system is obtained to obtain a second vane feature coordinate;

[0096] Step S236: obtaining the blade installation deviation value corresponding to the sample rotating blade group by calculating the first blade feature coordinates and the second blade feature coordinates;

[0097] The blade installation deviation value corresponding to the sample rotating blade group is calculated, and the specific formula is as follows:

[0098]

[0099] Wherein, Ypc is the blade installation deviation value corresponding to the sample rotating blade group, (x1, y1, z1) is the first blade feature coordinates, and (x2, y2, z2) is the first blade feature coordinates;

[0100] Step S24: obtaining the blade installation deviation value corresponding to each rotating blade group respectively, obtaining a plurality of blade installation deviation values, and comparing the plurality of blade installation deviation values, and marking the largest blade installation deviation value as the blade rotating error detection value corresponding to the second type mechanical equipment;

[0101] Step S3: performing abnormal vibration early warning on the high-speed rotating mechanical blade according to the rotating equipment type division data and the blade rotating error detection value;

[0102] The step S3 further includes the following steps:

[0103] Step S31: obtaining the rotating equipment type division data, and obtaining the first type mechanical equipment and the second type mechanical equipment according to the rotating equipment type division data;

[0104] Step S32: if the rotating mechanical equipment is the first type mechanical equipment, no blade vibration abnormal early warning is needed to be issued;

[0105] Step S33: if the rotating mechanical equipment is the second type mechanical equipment, the blade vibration abnormal early warning is issued, and the blade rotating error is analyzed abnormally;

[0106] The step S33 further includes the following steps:

[0107] Obtaining the blade rotating error detection value corresponding to the second type mechanical equipment;

[0108] Obtaining the blade rotating error reference interval, if the blade rotating error detection value is in the blade rotating error reference interval, it is judged that the blade rotating angle is not abnormal, if the blade rotating error detection value is not in the blade rotating error reference interval, it is judged that the blade rotating angle is abnormal, and the abnormal early warning is issued.

[0109] ​In the present application, if the corresponding calculation formula appears, the above calculation formula is to calculate the numerical value without dimension, and the weight coefficient, proportional coefficient and other coefficients existing in the formula are set to obtain a result value of quantizing each parameter. The size of the weight coefficient and the proportional coefficient can be determined as long as it does not affect the proportional relationship between the parameter and the result value.

[0110] Embodiment two

[0111] Please refer to Figure 2 , based on the same invention, the present application provides an abnormal vibration detection system for high-speed rotating machinery blades, which comprises a vibration data module, a mechanical rotation module, an abnormal early warning module and a server. The vibration data module, the mechanical rotation module and the abnormal early warning module are connected with the server respectively, and the server controls the vibration data module, the mechanical rotation module and the abnormal early warning module respectively.

[0112] The vibration data module is arranged outside the rotating machinery equipment, a plurality of vibration detection points are arranged outside the rotating machinery equipment, a device vibration detection period is created, periodic abnormal vibration detection is carried out on each vibration detection point in the device vibration detection period, the rotating machinery equipment is divided into a first type of machinery equipment and a second type of machinery equipment according to the detection result, and rotating equipment type division data is obtained.

[0113] Specifically as follows:

[0114] A plurality of vibration detection points are arranged outside the rotating machinery equipment, and a characteristic vibration detection point is selected from the plurality of vibration detection points.

[0115] It should be noted that:

[0116] In the present application, the rotating machinery equipment outside includes but is not limited to the rotating machinery equipment shell, the support and the rotating blade.

[0117] In the process of wind power detection of the rotating machinery equipment, the time point corresponding to the current time is taken as the cycle end time point, and a device vibration detection period is marked.

[0118] It should be noted that:

[0119] Since the time point corresponding to the current time is dynamically updated, the cycle end time point is also dynamically updated, and the device vibration detection period is fixed in length, so that the device vibration detection period is dynamically updated.

[0120] The vibration frequency of the characteristic vibration detection point in the device vibration detection period is detected, and the cycle vibration frequency detection value corresponding to the characteristic vibration detection point is obtained according to the detection result.

[0121] Specifically as follows:

[0122] The device vibration detection period is divided into a plurality of continuous detection time points, and the device vibration frequency value corresponding to each detection time point at the feature vibration detection point is obtained to obtain a plurality of device vibration frequency values;

[0123] The obtained plurality of device vibration frequency values are compared in value size, the device vibration frequency value with the largest value is marked as the feature point peak vibration frequency value, and the device vibration frequency value with the smallest value is marked as the feature point valley vibration frequency value;

[0124] The wind power value range between the feature point peak vibration frequency value and the feature point valley vibration frequency value is obtained to obtain a periodic wind power peak valley interval, the periodic wind power peak valley interval is divided into a plurality of vibration frequency subintervals, and the divided vibration frequency subintervals are sequentially marked as F1 vibration frequency subinterval to Fa vibration frequency subinterval according to the interval wind power value size;

[0125] It should be noted here that:

[0126] In this application, F here refers to the symbol corresponding to the vibration frequency subinterval, and a refers to the number value corresponding to the vibration frequency subinterval;

[0127] The interval median value corresponding to the F1 vibration frequency subinterval is obtained to obtain the F1 vibration interval median value, the interval median value corresponding to the F2 vibration frequency subinterval is obtained to obtain the F2 vibration interval median value, and so on. The interval median value corresponding to the Fa vibration frequency subinterval is obtained to obtain the Fa vibration interval median value;

[0128] In the device vibration detection period, the detection time points of the device vibration frequency value in the F1 vibration frequency subinterval are accumulated in length to obtain the F1 vibration frequency duration, the detection time points of the device vibration frequency value in the F2 vibration frequency subinterval are accumulated in length to obtain the F2 vibration frequency duration, and so on. The detection time points of the device vibration frequency value in the Fa vibration frequency subinterval are accumulated in length to obtain the Fa vibration frequency duration;

[0129] The time length corresponding to the device vibration detection period is obtained to obtain the device vibration period length;

[0130] The device vibration period length, the F1 vibration interval median value to the Fa vibration interval median value, and the F1 vibration frequency duration to the Fa vibration frequency duration are calculated to obtain the periodic vibration frequency detection value corresponding to the feature vibration detection point;

[0131] The periodic vibration frequency detection value corresponding to the feature vibration detection point is calculated, and the specific formula is as follows:

[0132] ;

[0133] Wherein, Zzl is the characteristic vibration detection point corresponding to the periodic vibration frequency detection value, Zqzi is the Fi vibration interval value, Szci is the Fi vibration frequency duration, Zsc is the device vibration cycle length, and a is the number value corresponding to the vibration frequency sub-interval.

[0134] It should be noted here that:

[0135] In specific implementation, the following test data exists:

[0136] If the F1 vibration interval value is 0.5 kHz, the F2 vibration interval value is 0.8 kHz, the F3 vibration interval value is 1.1 kHz, the F1 vibration frequency duration is 0.5 h, the F2 vibration frequency duration is 1.5 h, the F3 vibration frequency duration is 1.2 h, and the device vibration cycle length is 3.2, then the characteristic vibration detection point corresponding to the periodic vibration frequency detection value can be calculated as 0.8655.

[0137] The process of obtaining the periodic vibration frequency detection value corresponding to the characteristic vibration detection point is repeated to obtain the periodic vibration frequency detection value corresponding to each vibration detection point, and a plurality of periodic vibration frequency detection values are obtained.

[0138] The process of obtaining the periodic vibration frequency detection value corresponding to the characteristic vibration detection point is repeated to obtain the periodic vibration frequency detection value corresponding to each vibration detection point, and a plurality of periodic vibration frequency detection values are obtained, and the obtained plurality of periodic vibration frequency detection values are compared in value, and the periodic vibration frequency detection value with the largest value is marked as the device vibration cycle detection value.

[0139] Obtain the device vibration detection reference interval, if the device vibration cycle detection value is in the device vibration detection reference interval, the rotating machinery equipment is divided into the first type machinery equipment, if the device vibration cycle detection value is not in the device vibration detection reference interval, the rotating machinery equipment is divided into the second type machinery equipment, and the rotating equipment type division data is obtained.

[0140] It should be noted here that:

[0141] The device vibration detection reference interval is obtained, specifically as follows:

[0142] The first type machinery equipment referred to herein includes the case where the device vibration cycle detection value is in the device vibration detection reference interval.

[0143] The historical vibration record corresponding to the rotating mechanical equipment is acquired, the equipment vibration period detection value corresponding to a plurality of historical normal vibration periods is acquired according to the historical vibration record, a plurality of equipment vibration period detection values are obtained, and the maximum equipment vibration period detection value in the plurality of equipment vibration period detection values is marked as the upper limit of the equipment vibration detection reference interval, and the minimum equipment vibration period detection value in the plurality of equipment vibration period detection values is marked as the lower limit of the equipment vibration detection reference interval.

[0144] In the present application, the first type of mechanical equipment referred to here is a normal vibration mechanical equipment, and the second type of mechanical equipment referred to here is an abnormal vibration mechanical equipment.

[0145] The vibration data module acquires the rotating equipment type classification data and transmits it to the mechanical rotating module and the abnormal early warning module.

[0146] The mechanical rotating module detects the blade rotation error of the second type of mechanical equipment according to the rotating equipment type classification data, and acquires the blade rotation error detection value corresponding to the second type of mechanical equipment according to the detection result.

[0147] Specifically as follows:

[0148] The rotating equipment type classification data is acquired, and the first type of mechanical equipment and the second type of mechanical equipment are respectively acquired according to the rotating equipment type classification data.

[0149] If the rotating mechanical equipment is the second type of mechanical equipment, the rotating blades corresponding to the second type of mechanical equipment are respectively acquired, a plurality of equipment rotating blades are obtained, any two of the plurality of equipment rotating blades are marked as a rotating blade group, a plurality of rotating blade groups are obtained, and a sample rotating blade group is selected from the plurality of rotating blade groups.

[0150] The sample rotating blade group is detected for blade rotation error, and the blade installation deviation value corresponding to the sample rotating blade group is acquired according to the detection result.

[0151] Specifically as follows:

[0152] The equipment rotating blades in the sample rotating blade group are acquired, and the acquired equipment rotating blades are respectively marked as a first equipment rotating blade and a second equipment rotating blade.

[0153] The space region where the sample rotating blade group is located is modeled in three dimensions to obtain a sample region three-dimensional model, and a three-dimensional coordinate system is created in the sample region three-dimensional model.

[0154] Specifically as follows:

[0155] Mark the rotation axis corresponding to the sample rotating vane set as a first device coordinate point, draw a plane perpendicular to the ground through the first device coordinate point to obtain a first device coordinate plane, draw a straight line through the first device coordinate point in the first device coordinate plane to obtain a first device coordinate straight line, draw a straight line perpendicular to the first device coordinate straight line through the first device coordinate point to obtain a second device coordinate straight line, draw a plane perpendicular to the first device coordinate plane through the first device coordinate point to obtain a second device coordinate plane, and draw a straight line perpendicular to the first device coordinate plane through the first device coordinate point in the second device coordinate plane to obtain a third device coordinate straight line;

[0156] Mark the first coordinate point as a coordinate origin, mark the first device coordinate straight line as a coordinate x-axis, mark the second device coordinate straight line as a coordinate y-axis, and mark the third device coordinate straight line as a coordinate z-axis to obtain a sample region three-dimensional coordinate system;

[0157] Mark a feature point on the surface of the first device rotating vane to obtain a first vane feature point, and mark a feature point on the surface of the second device rotating vane to obtain a second vane feature point;

[0158] It should be noted here that:

[0159] Here, the position of the first vane feature point on the surface of the first device rotating vane is the same as the position of the second vane feature point on the surface of the second device rotating vane.

[0160] Mark a feature rotation angle at the rotating crankshaft corresponding to the rotating mechanical device, acquire the coordinates of the first vane feature point in the sample region three-dimensional coordinate system when the first device rotating vane rotates to the feature rotation angle to obtain first vane feature coordinates;

[0161] Acquire the coordinates of the second vane feature point in the sample region three-dimensional coordinate system when the second device rotating vane rotates to the feature rotation angle to obtain second vane feature coordinates;

[0162] Calculate the vane installation deviation value corresponding to the sample rotating vane set from the first vane feature coordinates and the second vane feature coordinates;

[0163] Calculate the vane installation deviation value corresponding to the sample rotating vane set, and the specific formula is as follows:

[0164] ;

[0165] Wherein, Ypc is the vane installation deviation value corresponding to the sample rotating vane set, (x1, y1, z1) is the first vane feature coordinates, and (x2, y2, z2) is the first vane feature coordinates;

[0166] The acquisition process of the blade selection deviation value corresponding to the sample rotating blade group is repeated, and the blade selection deviation value corresponding to each rotating blade group is acquired respectively to obtain a plurality of blade selection deviation values, and the obtained plurality of blade selection deviation values are compared in value, and the blade selection deviation value with the largest value is marked as the blade rotation error detection value corresponding to the second type of mechanical equipment;

[0167] The mechanical rotating module acquires the blade rotation error detection value and transmits it to the abnormal early warning module;

[0168] The abnormal early warning module performs abnormal vibration early warning on the high-speed rotating mechanical blade according to the rotating equipment type division data and the blade rotation error detection value;

[0169] Specifically as follows:

[0170] Obtain rotating equipment type division data, and obtain first type mechanical equipment and second type mechanical equipment according to rotating equipment type division data;

[0171] If the rotating mechanical equipment is the first type of mechanical equipment, no blade vibration abnormality early warning needs to be issued;

[0172] If the rotating mechanical equipment is the second type of mechanical equipment, blade vibration abnormality early warning is issued, and abnormal analysis is performed on the blade rotation error;

[0173] Specifically as follows:

[0174] Obtain the blade rotation error detection value corresponding to the second type of mechanical equipment;

[0175] Obtain the blade rotation error reference interval, if the blade rotation error detection value is in the blade rotation error reference interval, it is judged that the blade rotation angle is not abnormal, if the blade rotation error detection value is not in the blade rotation error reference interval, it is judged that the blade rotation angle is abnormal, and an abnormal early warning is issued.

[0176] It should be noted here that:

[0177] In this application, the blade rotation angle not abnormal herein includes the case that the blade rotation error detection value is at the boundary of the blade rotation error reference interval;

[0178] The blade rotation error reference interval is acquired, specifically as follows:

[0179] The lower limit of the blade rotation error reference interval herein is 0, that is, there is no blade rotation error;

[0180] A plurality of historical working records of a plurality of rotating machinery devices in a blade rotation abnormal state are acquired, a blade rotation error detection value corresponding to each historical working record is acquired, and a blade rotation error detection value with a minimum value is marked as an upper limit of a blade rotation error reference interval.

[0181] The preferred embodiments of the application disclosed above are only used to help explain the application. The preferred embodiments do not describe all the details and limit the application to the specific embodiments. Obviously, many modifications and variations can be made according to the content of the specification. The specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the application, so that those skilled in the art can well understand and utilize the application. The application is limited only by the claims and their full scope and equivalents.

Claims

1. A method for detecting abnormal vibration of high-speed rotating mechanical blades, characterized in that, include: Step S1: Set up several vibration detection points on the outside of the rotating machinery and perform periodic abnormal vibration detection on each vibration detection point during the equipment vibration detection cycle. Based on the detection results, classify the rotating machinery into first-type machinery and second-type machinery and obtain rotating machinery type classification data. Step S2: Based on the data categorized by rotating equipment type, perform blade rotation error detection on the second type of mechanical equipment and obtain the blade rotation error detection value; Step S3: Based on the data classification of rotating equipment type and the blade rotation error detection values, perform abnormal vibration early warning for high-speed rotating machinery blades; Step S1 further includes the following specific steps: Step S11: Set up several vibration detection points on the outside of the rotating machinery, and arbitrarily select one characteristic vibration detection point from the set vibration detection points; Step S12: During the wind force detection of rotating machinery, the current time point is taken as the end time point of the cycle, and a vibration detection cycle of the equipment is marked. Step S13: Perform vibration frequency detection on the characteristic vibration detection points in the equipment vibration detection cycle, and obtain the periodic vibration frequency detection value corresponding to the characteristic vibration detection points based on the detection results. Step S14: Obtain the periodic vibration frequency detection value corresponding to each vibration detection point to obtain multiple periodic vibration frequency detection values; Step S15: Compare the obtained multiple periodic vibration frequency detection values ​​and mark the periodic vibration frequency detection value with the largest value as the equipment vibration period detection value. Step S16: Obtain the equipment vibration detection reference range. If the equipment vibration period detection value is within the equipment vibration detection reference range, the rotating machinery is classified as the first type of machinery. If the equipment vibration period detection value is not within the equipment vibration detection reference range, the rotating machinery is classified as the second type of machinery, thus obtaining the rotating equipment type classification data.

2. The method for detecting abnormal vibration of a high-speed rotating mechanical blade according to claim 1, characterized in that, Step S13 further includes the following specific steps: Step S131: Divide the equipment vibration detection cycle into several consecutive detection time points, and obtain the equipment vibration frequency value corresponding to the characteristic vibration detection point at each detection time point to obtain multiple equipment vibration frequency values. Step S132: Compare the obtained vibration frequency values ​​of multiple devices, mark the device vibration frequency value with the largest value as the peak vibration frequency value of the feature point, and mark the device vibration frequency value with the smallest value as the valley vibration frequency value of the feature point. Step S133: Obtain the range of wind force values ​​between the peak vibration frequency value and the valley vibration frequency value of the feature point to obtain the periodic wind force peak and valley interval. Divide the periodic wind force peak and valley interval into several vibration frequency sub-intervals and label the divided vibration frequency sub-intervals sequentially according to the size of the interval wind force value as F1 vibration frequency sub-interval to Fa vibration frequency sub-interval.

3. The method for detecting abnormal vibration of a high-speed rotating mechanical blade according to claim 2, characterized in that, Step S13 further includes the following specific steps: Step S134: Obtain the midpoint value of the interval corresponding to the vibration frequency sub-interval to get the midpoint value of the vibration interval from F1 to Fa; Step S135: During the equipment vibration detection cycle, the duration of the detection time points where the equipment vibration frequency value is in the F1 vibration frequency sub-interval is accumulated to obtain the duration of the F1 vibration frequency, and the duration of the detection time points where the equipment vibration frequency value is in the Fa vibration frequency sub-interval is accumulated to obtain the duration of the Fa vibration frequency. Step S136: Obtain the time length corresponding to the equipment vibration detection cycle to get the equipment vibration cycle duration; Step S137: Calculate the periodic vibration frequency detection value corresponding to the characteristic vibration detection point by taking the equipment vibration cycle duration, the midpoint of the F1 vibration interval to the midpoint of the Fa vibration interval, and the duration of the F1 vibration frequency to the duration of the Fa vibration frequency. The periodic vibration frequency detection value corresponding to the characteristic vibration detection point is calculated.

4. The method for detecting abnormal vibration of a high-speed rotating mechanical blade according to claim 1, characterized in that, Step S2 further includes the following specific steps: Step S21: Obtain rotating equipment type classification data, and obtain the first type of mechanical equipment and the second type of mechanical equipment according to the rotating equipment type classification data; Step S22: If the rotating machinery is of type II, the rotating blades corresponding to type II machinery are acquired to obtain multiple rotating blades. Any two optional blades among the acquired multiple optional blades are marked as a rotating blade group to obtain multiple rotating blade groups. Then, a sample rotating blade group is selected from the acquired multiple rotating blade groups. Step S23: Perform blade rotation error detection on the sample rotating blade group, and obtain the blade selection deviation value corresponding to the sample rotating blade group based on the detection results; Step S24: Obtain the blade selection deviation value corresponding to each rotating blade group, obtain multiple blade selection deviation values, compare the obtained multiple blade selection deviation values, and mark the blade selection deviation value with the largest value as the blade rotation error detection value corresponding to the second type of mechanical equipment.

5. The method for detecting abnormal vibration of a high-speed rotating mechanical blade according to claim 4, characterized in that, Step S23 further includes the following specific steps: Step S231: Obtain the equipment rotating blades in the sample rotating blade group, and mark the obtained equipment optional blades as the first equipment rotating blade and the second equipment rotating blade respectively; Step S232: Perform three-dimensional modeling of the spatial region where the sample rotating blade group is located to obtain a three-dimensional model of the sample region, and create a three-dimensional coordinate system in the three-dimensional model of the sample region; Step S233: Mark a feature point on the surface of the rotating blade of the first device to obtain the first blade feature point; mark a feature point on the surface of the rotating blade of the second device to obtain the second blade feature point. Step S234: Mark a characteristic rotation angle at the crankshaft corresponding to the rotating machinery. When the first rotating blade rotates to the characteristic rotation angle, obtain the coordinates of the first blade feature point in the three-dimensional coordinate system of the sample area to obtain the first blade feature coordinates. Step S235: When the second device rotates the blade to the characteristic rotation angle, the coordinates of the second blade feature points in the three-dimensional coordinate system of the sample area are obtained to obtain the feature coordinates of the second blade. Step S236: Calculate the blade selection deviation value corresponding to the sample rotating blade group by using the feature coordinates of the first blade and the feature coordinates of the second blade; The blade selection deviation values ​​corresponding to the sample rotating blade group are calculated.

6. The method for detecting abnormal vibration of a high-speed rotating mechanical blade according to claim 5, characterized in that, Step S23 further includes the following specific steps: Mark the rotation axis center corresponding to the sample rotating blade group as the first equipment coordinate point. Draw a plane perpendicular to the ground through the first equipment coordinate point to obtain the first equipment coordinate plane. In the first equipment coordinate plane, draw any straight line through the first equipment coordinate point to obtain the first equipment coordinate line. Draw a straight line perpendicular to the first equipment coordinate line through the first equipment coordinate point to obtain the second equipment coordinate line. Draw a plane perpendicular to the first equipment coordinate plane through the first equipment coordinate point to obtain the second equipment coordinate plane. In the second equipment coordinate plane, draw a straight line perpendicular to the first equipment coordinate plane through the first equipment coordinate point to obtain the third equipment coordinate line. Mark the first coordinate point as the origin, the first device coordinate line as the x-axis, the second device coordinate line as the y-axis, and the third device coordinate line as the z-axis to obtain the three-dimensional coordinate system of the sample area.

7. The method for detecting abnormal vibration of a high-speed rotating mechanical blade according to claim 1, characterized in that, Step S3 further includes the following specific steps: Step S31: Obtain rotating equipment type classification data, and obtain the first type of mechanical equipment and the second type of mechanical equipment according to the rotating equipment type classification data; Step S32: If the rotating machinery is a type 1 machinery, then there is no need to issue an abnormal blade vibration warning; Step S33: If the rotating machinery is of type II, issue an early warning of abnormal blade vibration and perform anomaly analysis on the blade rotation error.

8. The method for detecting abnormal vibration of a high-speed rotating mechanical blade according to claim 7, characterized in that, Step S33 further includes the following specific steps: Obtain the blade rotation error detection value corresponding to the second type of mechanical equipment; Obtain the blade rotation error baseline range. If the blade rotation error detection value is within the blade rotation error baseline range, it is determined that the blade rotation angle is not abnormal. If the blade rotation error detection value is not within the blade rotation error baseline range, it is determined that the blade rotation angle is abnormal, and an abnormality warning is issued.

9. An abnormal vibration detection system for high-speed rotating mechanical blades, applicable to the abnormal vibration detection method for high-speed rotating mechanical blades as described in any one of claims 1-8, characterized in that, The abnormal vibration detection system includes: Vibration data module: Several vibration monitoring points are set on the outside of the rotating machinery, a vibration monitoring cycle is created, and periodic abnormal vibration monitoring is performed on each vibration monitoring point in the vibration monitoring cycle. Based on the detection results, the rotating machinery is divided into first type machinery and second type machinery, and rotating machinery type classification data is obtained. Mechanical rotation module: Based on the data classification of rotating equipment type, the blade rotation error of the second type of mechanical equipment is monitored, and the blade rotation error monitoring value corresponding to the second type of mechanical equipment is obtained based on the monitoring results; Anomaly warning module: Based on the type of rotating equipment and the monitoring values ​​of blade rotation error, it provides early warning of abnormal vibration of high-speed rotating machinery blades; The vibration data module is also used to set up several vibration detection points on the outside of rotating machinery and to arbitrarily select a characteristic vibration detection point from among the set vibration detection points. During the wind force detection of rotating machinery, the current time point is taken as the end time point of the cycle, marking a vibration detection cycle of the equipment. Vibration frequency is detected at characteristic vibration detection points during the equipment vibration detection cycle, and the periodic vibration frequency detection value corresponding to the characteristic vibration detection point is obtained based on the detection results. The periodic vibration frequency detection value corresponding to each vibration detection point is obtained separately, resulting in multiple periodic vibration frequency detection values; The obtained multiple periodic vibration frequency detection values ​​are compared numerically, and the periodic vibration frequency detection value with the largest value is marked as the equipment vibration period detection value. Obtain the equipment vibration detection reference range. If the equipment vibration period detection value is within the equipment vibration detection reference range, the rotating machinery is classified as the first type of machinery. If the equipment vibration period detection value is not within the equipment vibration detection reference range, the rotating machinery is classified as the second type of machinery, thus obtaining the rotating equipment type classification data.

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