CN111721969A - Tower drum health state monitoring method based on fixed detection and movable detection - Google Patents
Tower drum health state monitoring method based on fixed detection and movable detection Download PDFInfo
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- CN111721969A CN111721969A CN202010424780.8A CN202010424780A CN111721969A CN 111721969 A CN111721969 A CN 111721969A CN 202010424780 A CN202010424780 A CN 202010424780A CN 111721969 A CN111721969 A CN 111721969A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
- G01P15/00—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D17/00—Monitoring or testing of wind motors, e.g. diagnostics
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B7/00—Measuring arrangements characterised by the use of electric or magnetic techniques
- G01B7/02—Measuring arrangements characterised by the use of electric or magnetic techniques for measuring length, width or thickness
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
Abstract
The invention discloses a tower drum health state monitoring method based on fixed detection and movable detection, the top of the tower drum of the wind driven generator is fixedly provided with a fixed sensor for detecting the shaking of the top end of the tower drum, the invention installs a mobile sensor which can move up and down along the tower drum and is used for detecting the vibration of the tower drum, compares the monitoring results of the fixed sensors on different tower drums to determine a suspected fault tower drum, compares the monitoring results of the mobile sensors on different tower drums to determine a suspected fault point of the suspected fault tower drum, introduces the detection during the movement on the basis of the fixed detection, the problem of the overall fault of the tower drum can be checked, the possible position of the fault can be accurately determined, the accuracy of identifying the potential risk of the tower drum is improved, the equipment is adopted for fault pre-checking, the workload of wall climbing of inspectors can be avoided, and the requirement of high-altitude operation of the inspectors is reduced while the detection work efficiency is improved.
Description
Technical Field
The invention relates to the field of health state monitoring of wind power generation equipment, in particular to a tower drum health state monitoring method based on fixed detection and movable detection.
Background
The wind power generation is a power generation mode that a wind power generator is deployed in the offshore or mountain region and wind energy is converted into electric energy through the rotation of the wind power generator. The wind driven generator is generally deployed outdoors and greatly influenced by the surrounding environment, the wind driven generator and wind generate violent interaction for a long time, hidden faults of a tower drum structure can be caused, if the hidden faults are not eliminated in time, structural damage can be further generated to the tower drum, and even a tower drum can generate tower falling accidents under the dual functions of self gravity and wind power. In view of this, need carry out real-time supervision to tower section of thick bamboo health to can be fast accurate the stealthy trouble position of seeking, in time carry out the health maintenance to the tower section of thick bamboo and can guarantee aerogenerator continuous stable operation.
The tower is an important component of wind power generation equipment, and is mainly used for supporting a generator set and absorbing the vibration of fan blades and the generator set. The tower barrel is generally formed by connecting a plurality of hollow cylinders end to end in series, and all the hollow cylinders are fixedly connected through flanges. The pressure brought to the wind driven generator by the dead weight of the fan blades and the generator set and the gust wind is born, the structural damage of each column body possibly exists, and after the wind driven generator is used for a long time, the structure of the joint between the columns is aged, and the connection flange is loosened, so that the tower cylinder is not stably supported, the vibration of the wind driven generator is aggravated by the unstable tower cylinder support, the structural aging of the wind driven generator is further aggravated, and the health monitoring of the tower cylinder is particularly important.
In order to monitor the health state of the wind driven generator in real time, the existing tower barrel health monitoring technology is mainly characterized in that angle sensors, displacement sensors and the like are installed at the top and the bottom of a tower barrel, the inclination angle of the tower barrel and the top offset of the tower barrel are respectively monitored, the whole deformation condition of the tower barrel cannot be obtained by the monitoring method, the displacement curve of the tower barrel under each frequency external force cannot be monitored, and therefore the health state of the tower barrel cannot be comprehensively and accurately monitored and evaluated. In order to overcome the problem, patent ZL201711008222.8 discloses a method for monitoring the health status of a tower drum, wherein a dual-axis acceleration sensor is fixedly arranged inside the tower drum to acquire vibration data of the tower drum, a dual-axis tilt sensor is adopted to acquire tilt angle data of a tower footing, whether the tower drum is healthy or not is determined by combining the vibration data and the tilt angle data, and an alarm is automatically given if the tower drum is abnormal. Obviously, whether a connection fault exists in the tower cylinder can be found in time through the health detection of the tower cylinder, the fault occurrence of the tower cylinder has randomness, and the fault occurrence point position cannot be determined in advance, so that the method can only be applied to checking the connection strength of the connection positions of the cylinders of the tower cylinder, and is not easy to be used for searching the structural damage to the cylinders of the tower cylinder caused by the self weight of wind power and a fan, and the problems that the health monitoring of the tower cylinder is not accurate enough or the burden of the tower cylinder is increased while a large amount of equipment is installed are caused. On the other hand, the gust acts on the wind driven generator to enable the tower barrel to swing, only the double-shaft acceleration sensor is adopted for monitoring, the monitoring is possibly different due to different acting wind power, the problems of false alarm or missing report are easily caused, and the like, and the monitoring method needs to be further improved.
Disclosure of Invention
The invention aims to solve the technical problem of providing a tower drum health state monitoring method based on fixed detection and detection during movement, which can accurately position the fault position of a tower drum.
In order to solve the technical problems, the technical solution of the invention is as follows:
a fixed sensor for detecting the top shaking of a tower cylinder is fixedly installed at the top of the tower cylinder of a wind driven generator, a mobile sensor for detecting the vibration of the tower cylinder and capable of moving up and down along the tower cylinder is installed on the tower cylinder, the monitoring results of the fixed sensors on different tower cylinders are compared, a suspected fault tower cylinder is determined, the monitoring results of the mobile sensors on different tower cylinders are compared, and a suspected fault point of the suspected fault tower cylinder is determined.
Preferably, the fixed sensor obtains top offset information of the top of the tower drum, performs fourier transform on the top offset information to obtain a first frequency domain signal, and compares the first frequency domain signals close to the tower drum of the wind driven generator to determine the suspected faulty tower drum.
Preferably, the mobile sensor obtains barrel wall offset information on the side wall of the tower barrel, Fourier transform is performed on the barrel wall offset information, a second frequency domain signal related to the height of the tower barrel is obtained, offset information functions of a plurality of detection points with different heights on the side wall of the tower barrel of each wind driven generator are obtained according to the second frequency domain signal, the rigidity with different heights is respectively obtained, and the suspected fault point is determined by comparing the rigidity with the same height of different wind driven generators.
Preferably, the fixed sensor or the mobile sensor is a GNSS and an acceleration sensor.
Preferably, when comparing the first frequency domain signals close to each other, a risk factor is defined for the tower of each wind driven generator, the difference between the first frequency domain signals of different wind driven generator towers is calculated in a traversing manner, if the difference between the first frequency domain signals meets a first threshold condition, the towers corresponding to the two wind driven generators respectively accumulate the respective risk factors, and when the risk factor is greater than a risk threshold, the tower of the wind driven generator is determined to be the suspected faulty tower.
Preferably, the stiffness is
Where M (x) is a bending moment function, and the offset information function F (x) can be fit to generate a functional relation by moving a large amount of data monitored by the monitoring points.
Preferably, when the suspected fault point is determined by comparing the rigidities of different wind driven generators at the same height, a suspected fault tower is determined, respective problem factors are defined for different heights on the suspected fault tower, the difference between the suspected fault tower and the rigidity of the compared tower at the same height is calculated in a traversing manner, if the detected rigidity difference meets a second threshold value condition, the problem factors of the height meeting the second threshold value condition are accumulated, and when the problem factor of one height is greater than the problem threshold value, the point at the height is determined as the suspected fault point.
Preferably, when the suspected fault point is determined by comparing the rigidities of different wind driven generators at the same height, the suspected fault tower drum and the comparison tower drums are determined, the difference between the suspected fault tower drum and the rigidity mean value of all the comparison tower drums at the same height is calculated, and if the detected rigidity difference meets a second threshold value condition, the point at the height is determined to be the suspected fault point.
Preferably, the detected monitoring points are moved intensively near the suspected fault point to obtain a more accurate fault point position.
Preferably, the fixed sensor and the mobile sensor are the same set of sensor equipment, the sensor equipment moves up to the top end of the tower drum and is the fixed sensor when the sensor equipment is static at the top end, and the sensor equipment moves up and down and is the mobile sensor.
After the scheme is adopted, the moving detection is introduced on the basis of the fixed detection, so that the whole fault problem of the tower can be checked, the possible position of the fault can be accurately determined, the accuracy of identifying the potential risk of the tower is improved, the fault pre-checking by adopting equipment can avoid the workload of wall climbing of inspectors, the detection working efficiency is improved, and the requirement of high-altitude operation of the inspectors is reduced. A
Drawings
FIG. 1 is a schematic view of up and down movement control of a motion sensor directly using a rope;
fig. 2 is a schematic view showing up and down movement control of a movement sensor using a hoist;
fig. 3 is a schematic view of up-and-down movement control of a movement sensor using a driving motor;
FIG. 4 is a top view of the combination of the moving device and the cylindrical wall structure;
FIG. 5 is a schematic diagram of the steps involved in the method of the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and specific examples.
The invention discloses a tower drum health state monitoring method based on fixed detection and movable detection, which comprises the following preferred embodiments of the invention, as shown in fig. 1-5, the method comprises the following steps: the method comprises the steps of fixedly installing a fixed sensor 2 for detecting the top shake of a tower cylinder at the top of a tower cylinder 1 of the wind driven generator, installing a mobile sensor 3 for detecting the vibration of the tower cylinder, which can move up and down along the tower cylinder, on the tower cylinder, comparing the monitoring results of the fixed sensors 2 on different wind driven generator tower cylinders, determining a suspected fault tower cylinder, comparing the monitoring results of the mobile sensors 3 on different wind driven generator tower cylinders, particularly the monitoring results of the mobile sensors of the suspected fault tower cylinder and the tower cylinders around the suspected fault tower cylinder, and determining a suspected fault point of the suspected fault tower cylinder.
Specifically, a fixed sensor is installed on a tower cylinder of the wind driven generator, and top offset information of the top of the tower cylinder is obtained through the fixed sensor so as to judge whether each tower cylinder normally operates on the whole. Because the base of the tower is fixedly mounted to the ground, the top of the tower may be characterized more significantly when the tower is operating abnormally, and therefore the stationary sensor is preferably selected to be mounted at a high location, such as within the nacelle or on the surface of the nacelle at the top of the tower. The detection of the top offset information can be directly obtained through a Global Navigation Satellite System (GNSS) such as a Global Positioning System (GPS) and a Beidou, but the offset information obtained through the GNSS may have a certain deviation along with the change of the vibration frequency of the tower, so that an acceleration sensor is further installed while the GNSS is introduced, and the detection precision of the top offset information of the tower is improved after fusion reconstruction is carried out on the detection result obtained through the acceleration sensor and the GNSS detection result, and the specific fusion method can be seen in the research on a GPS and accelerometer fusion bridge deformation information extraction model on the third-phase 549 and 556 of the university report of China mining industry 44. The GNSS that is used for catching displacement information and the acceleration sensor that is used for catching shaking acceleration information are installed to this embodiment promptly simultaneously, choose all to pass through bolt, glue, strong magnet or other installation fixed mode fixed mounting at tower section of thick bamboo top with GNSS and acceleration sensor, and GNSS and acceleration sensor use is prior art, do not do specific description here to its specific circuit connection, for guaranteeing better signal transmission, can install the sensor in the outer bottom surface of cabin. The fixed sensor can be directly connected with the nacelle, so that a power supply can be led out from the nacelle to supply power, signal transmission can be directly led out from a communication line in the nacelle to transmit, or can be reported to a server through a wireless transmission module, such as a GPRS chip or a satellite communication module, and a power supply system and a signal transmission system including equipment such as a switch cabinet are generally arranged in the nacelle of the wind driven generator at present, the above systems can be directly utilized, and power consumption of the power supply system and the sensor terminal and signal transmission are the prior art, and details are not repeated herein.
In order to realize accurate positioning of the fault position, a movement sensor is further installed on the tower, specifically, a movement device may be installed on the outer wall of the tower, for example, as shown in fig. 1-4, a guide rail 4 is fixedly welded on the outer surface of the tower, the guide rail 4 may be two steel rails vertically arranged in parallel along the outer wall of the tower, the cross section of each steel rail is in an i shape, the movement device is a sliding trolley 5 matched with the guide rail 4, one side of the sliding trolley 5 close to the outer wall of the tower is provided with a positioning roller 51 embedded into the i shape groove from the side of the steel rail, the sliding trolley 5 can be pulled by a rope 7 to move, or the sliding trolley 5 can be driven by an automatic control device, for example, a roller 6 may be fixedly installed on the top surface of the tower, a rope 7 bypasses the roller 6 and one end of the rope is fixedly bound on, meanwhile, the base of the tower barrel is provided with a winch 8, the other end of the rope is tied to an output shaft of the winch 8, and the sliding trolley 5 is located at different heights outside the tower barrel by controlling the winch 8. Of course, the power device for driving the sliding trolley 5 to move can also be directly and fixedly installed on the sliding trolley 5, specifically, the sliding trolley 5 is fixedly installed with the driving motor 9, the rope 7 is wound on the output shaft of the driving motor 9, the other end of the rope 7 is fixedly bound to the bottom surface of the cabin on the top of the tower 1, the driving motor 9 is used for controlling the sliding trolley 5 to lift, the storage battery is carried on the sliding trolley 5 for providing power for the driving motor 9 so that the driving motor can drive the sliding trolley 5 to drive the mobile sensor to move up and down along the tower barrel, when the storage battery is carried, the mobile device can adopt a vehicle-mounted photovoltaic panel charging or wireless charging mode for supplying power, if a wireless charging mode is adopted, a wireless charging receiving end is arranged on one side, close to the tower drum, of the sliding trolley 5, a wireless charging transmitting end is arranged on the surface of the tower drum, and the wireless charging transmitting end is connected into a wind driven generator system to obtain electricity. An automatic ladder climbing elevator can also be used as a transportation moving sensor of the carrying sliding trolley 5, and the specific structure of the automatic ladder climbing device is the prior art and is not described in detail herein. The sliding trolley 5 can also be controlled in a magnetic suspension mode, a track capable of generating a magnetic field is arranged on the surface of the tower barrel, the moving device is limited and mounted on the track, an induction coil capable of generating an alternating electromagnetic field is arranged on the sliding trolley 5, and the sliding trolley 5 is driven to move up and down by adjusting the induction coil and utilizing the relation between the electromagnetic field and the magnetic field of the track.
The sliding trolley 5 is provided with a mobile sensor 3, which is similar to a fixed sensor and also comprises a GNSS for capturing displacement information and an acceleration sensor for capturing shaking acceleration information, the mobile sensor captures data and then sends the data to a server in real time in a wireless transmission mode for signal reporting, and the sliding trolley 5 can also be provided with a data storage module 52 for collecting the data and then reporting the data to the server. The data acquisition of the mobile sensor can be powered by the storage battery 53 on the mobile device, the specific setting of the power supply circuit is omitted in the prior art, and the power supply of the storage battery is realized by adopting a vehicle-mounted photovoltaic panel charging or wireless charging mode, which is omitted in detail. Furthermore, in order to ensure that the mobile sensor can obtain accurate offset information of the wall of the tower drum, the mobile sensor can be tightly attached to the outside of the wall of the tower drum to detect the wall of the tower drum after the mobile device reaches a specified position. Specifically, as shown in fig. 4, a resettable mobile sensor support plate 54 may be designed on one side of the mobile device close to the tower, the mobile sensor 3 is fixedly mounted on the mobile sensor support plate 54, an electromagnet 55 is fixed on one side of the mobile sensor support plate 54 close to the tower 1, and the other side of the mobile sensor support plate is connected with the mobile device through a spring 56.
Further, the fixed sensor and the mobile sensor may employ the same set of sensor equipment, and the same set of sensor equipment serves as the fixed sensor and the mobile sensor in different use situations, respectively. When the sensor equipment moves up to the top end of the tower drum and is static at the top end, the sensor equipment is the fixed sensor, when the sensor equipment moves up and down, the sensor equipment is the mobile sensor, when the sensor equipment is applied, the sensor equipment is used as the fixed sensor for a long time to carry out fixed detection on the health state of each wind driven generator tower drum, once a suspected fault tower drum is found, the sensor equipment starts to slide up and down to obtain mobile detection data, each wind driven generator can carry out synchronous operation in a mode of remotely controlling a motor or a winch, and then the position of the suspected fault point is finally determined.
And the server side obtains the data and then determines a suspected fault tower and a suspected fault point through processing and comparison. Firstly, a suspected fault tower barrel is determined through data obtained through fixed detection, a GNSS and an acceleration sensor can be used for directly obtaining a large number of instantaneous values of vibration displacement and acceleration of the top of the tower barrel, series of top offset information is obtained through data fusion or top offset information is directly obtained through the GNSS, the top offset information can be time domain signals or frequency domain signals, the time domain signals represent offsets of the top of the tower barrel at different time points, the frequency domain signals represent offsets of the top of the tower barrel at different vibration frequencies, in order to better compare different wind driven generators, the frequency domain signals containing the offsets are adopted for analysis in the embodiment, therefore, during operation, the system performs Fourier transformation on the obtained top offset information to obtain corresponding first frequency domain signals SiWherein i is the serial number of aerogenerator in the wind farm, i 1, 2iThe suspected fault tower r, r ∈ { i | i ═ 1, 2.. n } is determined, the embodiment has universality, and the first frequency domain signals S of all the wind turbine towers are selected and comparediN, determining a judgment standard for mutual approaching according to actual conditions in actual operation, for example, setting a distance threshold between the two, determining that the two are not close to each other when the distance threshold is larger than the distance threshold, determining that the two are close to each other when the distance threshold is smaller than or equal to the distance threshold, comparing the first frequency domain signals of the peripheral specified number of wind driven generator towers of the research target wind driven generator, and if only part of the wind driven generators are adopted for comparison, allowing each wind driven generator to obtain a first frequency domain signal of the peripheral specified number of wind driven generator towers according to actual application conditionsAnd the corresponding selection method is not the focus of attention in the scheme and is not repeated herein. Comparing the first frequency domain signal SiIn particular, each tower of each wind turbine is defined with a respective risk factoriAfter the tower drum numerical values detected by all the fixed sensors are reported, the difference between the first frequency domain signals of different wind driven generator tower drums is calculated in a traversing way: sn-Sn-1，Sn-Sn-2，......，Sn-S1，Sn-1-Sn-2，Sn-1-Sn-3，......，S2-S1The difference between the first frequency domain signals may determine a specific comparison scheme according to actual service needs, for example, a representative frequency may be selected, the offset of each wind turbine generator at the representative frequency may be checked and compared, the offsets may also be sequentially compared for different frequencies, and then the difference between the offsets is accumulated, and the like, and the specific comparison scheme is not a key point of the present disclosure, and is not further described herein, if the detected difference between the first frequency domain signals satisfies a first threshold condition α, the towers corresponding to the two wind turbine generators respectively accumulate their respective risk factors, for example, if S is detectedi-S1∈α is a first threshold condition, theni＝i+1，1＝1+1 risk factor of tower of wind power generatoriGreater than a risk threshold ω1And then, determining that the tower of the wind driven generator is a suspected fault tower r.
After the suspected fault tower cylinder r is determined, a suspected fault point needs to be further accurately determined, and the suspected fault point is determined through the wall offset information on the side wall of the tower cylinder, which is obtained through the mobile sensor. Similarly, the detection of the wall offset information can be directly obtained through a Global Navigation Satellite System (GNSS) such as a Global Positioning System (GPS) and a Beidou, an acceleration sensor can be installed while the GNSS is introduced, and the detection result obtained through the acceleration sensor and the GNSS detection result are fused and reconstructed to obtain the offset information with different heights and higher accuracy of the tower barrel, so that in the embodiment, the mobile sensor also selects the GNSS and the acceleration sensor. The mobile sensor obtains the wall offset information of the tower cylinder and then sends the wall offset information to the server, the server calculates the rigidity of the tower cylinder with different heights to obtain the rigidity of the tower cylinder with different heights, and the rigidity of the tower cylinder with the same height around the suspected fault tower cylinder is compared with the rigidity of the tower cylinder with the same height around the suspected fault tower cylinder to determine the fault position.
Theoretically, under the action of wind with a certain frequency, the wall offset information of a certain height of the tower drum at a certain moment is taken as a research object, and the following functional relation can be obtained:
in the functional relationship, M (x) is a bending moment function only related to the height x, the bending moment function can be determined according to the shape and the size of the tower when the tower is constructed, K (x) represents the rigidity of the tower at different heights x, and C, D is a constant. And performing secondary derivation on the functional relation to obtain:
then
The above equation is a functional relationship composed of the second derivative of the offset information function, the bending moment function and the stiffness function. The bending moment function M (x) can be obtained by external force and tower drum structure by using basic knowledge of structural mechanics, and a functional relation between the bending moment function and the height value can be established for obtaining different bending moment results and height values, so that bending moment information of any height can be obtained. The offset information function F (x) can be used for generating a functional relation through fitting of a large amount of data monitored by the mobile monitoring points, during specific operation, the server side obtains the cylindrical wall offset information of different heights on the tower from the mobile sensor, and the system also performs Fourier transform on the obtained cylindrical wall offset information to obtainObtaining a corresponding second frequency domain signal S'ijThe wind power generation system comprises a wind power generation field, a wind power generation system and a wind power generation system, wherein i is the serial number of a wind power generator in the wind power field, i is 1, 2. The second frequency domain signal S 'is for the wind turbine i due to differences in vibration amplitude at different heights'ijObtaining a deviation information function of a plurality of detection points with different heights on the side wall of each wind driven generator tower cylinder through fitting according to data related to the height x:
S’ij＝Fij(xj)。
f can be obtained by carrying out secondary derivation on the offset information function of each height on each wind driven generator "ij(xj)。
In summary, when a certain height x of a certain wind power generator i is determined as xjThen, the second derivative value F of the bending moment function and the offset information function of the corresponding height can be determinedij”(xj)、M(xj) Substituting the above function relation on the rigidity, any wind driven generator i with a certain height x ═ x can be obtainedjRigidity K of upper towerijComprises the following steps:
similarly, after the suspected fault tower is determined, the same height x of different wind driven generator towers is compared with the same height x of different wind driven generator towersjRigidity K ofij(xj) And i is 1, 2 and 3 … … n, the position of the tower drum rigidity mutation, namely a suspected fault point, can be preliminarily determined, and then an operator is dispatched to arrive at the site to further inspect and maintain the suspected fault point. During specific comparison, a plurality of wind driven generator tower drums located around the suspected fault tower drum can be designated as comparison tower drums, the embodiment has universality, all the same wind driven generator tower drums are selected to be compared, and respective problem factors are defined for different heights of the suspected fault tower drums rjAnd traversing and calculating each height x ═ xjJ 1, 2, 3 … … m, the difference in stiffness between the suspected faulty tower r and the comparable tower at the same height as the tower,
Δ(xj)＝Krj(xj)-Kij(xj)，
i＝1、2.....n，j＝1、2……m，r∈{i|i＝1、2.....n}。
if the detected difference in rigidity satisfies a second threshold condition, the corresponding pair of heights x ═ xjIs accumulated, e.g., Δ (x)j) ∈β is a second threshold condition, thenj＝j+1, problem factor when a certain heightjGreater than a problem threshold ω2And then, determining the height point as a suspected fault point, further, intensively moving the detected monitoring point near the suspected fault point to obtain a more accurate fault point position, and sending the fault point position to related operation and maintenance personnel to remind the operation and maintenance personnel to carry out troubleshooting and maintenance on the fault point, so as to avoid major risks.
In order to implement the method, a tower drum health state monitoring system based on fixed detection and mobile detection needs to be matched, the system comprises a server side adopting wireless communication and a detection end installed on a tower drum, the detection end comprises a fixed sensor and a mobile sensor, the mobile sensor is installed on a mobile device, the mobile device moves up and down along the tower drum, the mobile device can be powered in a wireless charging mode, and the mobile sensor and the fixed sensor both comprise a GNSS and an acceleration sensor.
The above-mentioned embodiments are only preferred embodiments of the present invention, and do not limit the technical scope of the present invention, so that the changes and modifications made by the claims and the specification of the present invention should fall within the scope of the present invention.
Claims (10)
1. A tower drum health state monitoring method based on fixed detection and mobile detection is characterized in that: the method comprises the steps of fixedly installing a fixed sensor for detecting the top shaking of the tower cylinder at the top of the tower cylinder of the wind driven generator, installing a mobile sensor for detecting the vibration of the tower cylinder, which can move up and down along the tower cylinder, on the tower cylinder, comparing the monitoring results of the fixed sensor on different tower cylinders, determining a suspected fault tower cylinder, comparing the monitoring results of the mobile sensor on different tower cylinders, and determining a suspected fault point of the suspected fault tower cylinder.
2. The tower health monitoring method based on stationary detection and mobile detection as claimed in claim 1, wherein: the method comprises the steps that the fixed sensor obtains top offset information of the top of a tower drum, Fourier transform is conducted on the top offset information to obtain a first frequency domain signal, and the first frequency domain signal close to the tower drum of the wind driven generator is compared to determine the suspected fault tower drum.
3. The tower health monitoring method based on stationary detection and mobile detection as claimed in claim 1, wherein: the mobile sensor obtains the barrel wall offset information on the side wall of the tower barrel, Fourier transform is carried out on the barrel wall offset information, a second frequency domain signal related to the height of the tower barrel is obtained, the offset information function of a plurality of detection points with different heights on the side wall of the tower barrel of each wind driven generator is obtained according to the second frequency domain signal, the rigidity with different heights is respectively obtained, and the suspected fault point is determined by comparing the rigidity with the same height of different wind driven generators.
4. The tower health monitoring method based on stationary detection and mobile detection as claimed in claim 2 or 3, wherein: the fixed sensor or the mobile sensor is a GNSS and an acceleration sensor.
5. The tower health monitoring method based on stationary detection and mobile detection as claimed in claim 2, wherein: comparing first frequency domain signals close to the tower drums of the wind driven generators, defining risk factors for the tower drum of each wind driven generator, traversing and calculating the difference between the first frequency domain signals of different tower drums of the wind driven generators, if the difference between the first frequency domain signals meets a first threshold condition, accumulating the respective risk factors of the tower drums of the two corresponding wind driven generators respectively, and determining the tower drum of the wind driven generator as the suspected fault tower drum when the risk factors are greater than a risk threshold.
6. The tower health monitoring method based on stationary detection and mobile detection as claimed in claim 3, wherein: the rigidity is
Where M (x) is a bending moment function, and the offset information function F (x) can be fit to generate a functional relation by moving a large amount of data monitored by the monitoring points.
7. The tower health monitoring method based on stationary detection and mobile detection as claimed in claim 3, wherein: when the suspected fault point is determined by comparing the rigidities of different wind driven generators at the same height, a suspected fault tower cylinder is determined, problem factors of different heights on the suspected fault tower cylinder are defined, the difference between the suspected fault tower cylinder and the rigidity of the same height of the compared tower cylinder at each height is calculated in a traversing mode, if the detected rigidity difference meets a second threshold value condition, the problem factors of the height meeting the second threshold value condition are accumulated, and when the problem factor of one height is larger than the problem threshold value, the point of the height is determined to be the suspected fault point.
8. The tower health monitoring method based on stationary detection and mobile detection as claimed in claim 3, wherein: and when the rigidity of different wind driven generators at the same height is compared to determine a suspected fault point, determining a suspected fault tower drum and a comparison tower drum, calculating the difference between the suspected fault tower drum and the rigidity mean value of all the comparison tower drums at the same height, and if the detected rigidity difference meets a second threshold condition, determining the point at the height as the suspected fault point.
9. The tower health monitoring method based on stationary detection and mobile detection as claimed in claim 7 or 8, wherein: the detected monitoring points are moved intensively near the suspected fault point to obtain a more accurate fault point position.
10. The tower health monitoring method based on stationary detection and mobile detection as claimed in claim 1, wherein: the fixed sensor and the mobile sensor adopt the same set of sensor equipment, the sensor equipment moves up to the top end of the tower cylinder and is fixed when the sensor equipment is static on the top end, and the sensor equipment moves up and down and is the mobile sensor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010424780.8A CN111721969A (en) | 2020-05-19 | 2020-05-19 | Tower drum health state monitoring method based on fixed detection and movable detection |
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| CN202010424780.8A CN111721969A (en) | 2020-05-19 | 2020-05-19 | Tower drum health state monitoring method based on fixed detection and movable detection |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113063400A (en) * | 2021-03-15 | 2021-07-02 | 北京云庐科技有限公司 | Real-time monitoring method and system for single-pipe tower |
| CN113419260A (en) * | 2021-06-17 | 2021-09-21 | 阳光新能源开发有限公司 | Photovoltaic module shaking detection method and device and photovoltaic power station system |
| CN113653606A (en) * | 2021-07-20 | 2021-11-16 | 中国海洋大学 | Health state monitoring equipment and method for offshore wind turbine blade |
| CN114323398A (en) * | 2021-12-29 | 2022-04-12 | 广西建工集团智慧制造有限公司 | Real-time detection method and device for pre-tightening force of main limb bolt of tower crane tower body |
| CN114577333A (en) * | 2022-01-12 | 2022-06-03 | 中国海洋大学 | Fan tower drum vibration monitoring system based on mobile sensing and modal parameter extraction method |
| CN115307543A (en) * | 2022-07-13 | 2022-11-08 | 哈尔滨工业大学 | Device and method for measuring geometric dimension of inner cavity of large-sized high-speed rotating equipment |
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2020
- 2020-05-19 CN CN202010424780.8A patent/CN111721969A/en active Pending
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113063400A (en) * | 2021-03-15 | 2021-07-02 | 北京云庐科技有限公司 | Real-time monitoring method and system for single-pipe tower |
| CN113419260A (en) * | 2021-06-17 | 2021-09-21 | 阳光新能源开发有限公司 | Photovoltaic module shaking detection method and device and photovoltaic power station system |
| CN113653606A (en) * | 2021-07-20 | 2021-11-16 | 中国海洋大学 | Health state monitoring equipment and method for offshore wind turbine blade |
| CN113653606B (en) * | 2021-07-20 | 2022-11-08 | 中国海洋大学 | Health state monitoring equipment and method for offshore wind turbine blade |
| CN114323398A (en) * | 2021-12-29 | 2022-04-12 | 广西建工集团智慧制造有限公司 | Real-time detection method and device for pre-tightening force of main limb bolt of tower crane tower body |
| CN114577333A (en) * | 2022-01-12 | 2022-06-03 | 中国海洋大学 | Fan tower drum vibration monitoring system based on mobile sensing and modal parameter extraction method |
| CN115307543A (en) * | 2022-07-13 | 2022-11-08 | 哈尔滨工业大学 | Device and method for measuring geometric dimension of inner cavity of large-sized high-speed rotating equipment |
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