Bearing capacity monitoring system for fan hoisting operation platform of large crawler crane

Abstract

The utility model belongs to the technical field of fan hoisting construction, and particularly relates to a large crawler crane fan hoisting operation platform bearing capacity monitoring system which comprises soil pressure sensors, embedded steel plates, a vibrating wire collector, an Internet of Things gateway, a storage battery and a structure early warning analysis cloud platform. The soil pressure sensor and the embedded steel plate are embedded underground, the soil pressure sensor is located below the center of a roadbed steel plate on the ground, and the soil pressure sensor abuts against the upper end of the embedded steel plate and abuts against the lower end of the soil pressure sensor. The conditions of non-uniform stress and inaccurate detection caused by too small contact surface area of the soil pressure sensor and non-uniform sand settlement are avoided, the soil pressure sensor is used for measuring the contact pressure of a platform compaction soil interface, the stress surface is uniformly transmitted through the force transmission shaft, and the soil pressure change in a measured structure can be known.

Description

TECHNICAL FIELD

[0001] The utility model belongs to fan hoisting construction technical field especially relates to a large -scale caterpillar crane wind turbine hoisting operation platform bearing capacity monitoring system. BACKGROUND

[0002] The terrain and topography of the Middle East and Africa region are flat, and the coastal desert environment provides abundant wind resources, but for the construction process of the wind power generation project, too much wind often becomes a great construction obstacle, especially in the field of fan hoisting, the capture of hoisting effective period is particularly important. Although the desert environment provides flat terrain and topography, the bearing capacity of the sandstone ground is affected by the liquidity of sand, the size of the stress point, and the ground is prone to uneven settlement, and the compaction degree index of the hoisting area ground is not easy to achieve. Due to the influence of wind direction and hoisting weight, the maximum stress point of the caterpillar crane is prone to overturning during hoisting, which has great safety hazards.

[0003] The utility model designs a large -scale caterpillar crane wind turbine hoisting operation platform bearing capacity monitoring system to solve the above problems. CONTENT OF THE UTILITY MODEL

[0004] In order to achieve the above purpose, the utility model adopts the following technical scheme:

[0005] A large -scale caterpillar crane wind turbine hoisting operation platform bearing capacity monitoring system, it includes a plurality of earth pressure sensor, a plurality of embedded steel plate, vibration string collection appearance, thing internet gateway, battery, structure early warning analysis cloud platform, earth pressure sensor and embedded steel plate quantity is same, and earth pressure sensor and embedded steel plate are embedded in the ground, and earth pressure sensor is located below the center of the roadbed steel plate on the ground, and earth pressure sensor is located on the upper end of the embedded steel plate, and is in contact with the lower end of the earth pressure sensor, and earth pressure sensor is connected with vibration string collection appearance through data line, and vibration string collection appearance is connected with thing internet gateway through data line, and vibration string collection appearance and thing internet gateway are electrically connected with battery.

[0006] As a preferred scheme, the thing internet gateway can wirelessly transmit data to the structure early warning analysis cloud platform.

[0007] As a preferred scheme, the embedded depth of the earth pressure sensor is greater than 20cm.

[0008] As a preferred scheme, the embedded steel plate is embedded at 30cm below the roadbed steel plate.

[0009] Compared with the prior art, the utility model has the advantages of:

[0010] 1. The pre-embedded steel plate increases the stress area when the soil pressure sensor is pre-embedded, avoids uneven stress and inaccurate detection caused by the small area of the contact surface of the soil pressure sensor and uneven settlement of sand, and the soil pressure sensor is used for measuring the contact pressure of the platform compacted soil interface, the stress surface is uniformly transmitted through the force transmission shaft, and the soil pressure change inside the measured structure can be understood.

[0011] 2. The utility model discloses a soil pressure sensor and pre-embedded steel plate are used to monitor the soil pressure of the area below the roadbed steel plate of the crawler crane station, understand the ground bearing capacity of each hoisting force point in the actual hoisting process, and avoid the overturning risk of the crawler crane caused by uneven stress and ground settlement in the hoisting process. ACCURACY

[0012] Figure 1 It is the schematic diagram of the utility model.

[0013] Figure 2 It is the schematic diagram of the pre-embedding of the soil pressure sensor and the pre-embedded steel plate of the utility model.

[0014] Figure 3 It is the working process schematic diagram of the utility model in hoisting monitoring.

[0015] The figure mark name: 1, soil pressure sensor, 2, pre-embedded steel plate, 3, vibration string acquisition instrument, 4, thing internet gateway, 5, battery, 6, structure early warning analysis cloud platform. DETAILED DESCRIPTION

[0016] The specific embodiments of the utility model are described in further detail below in combination with the drawings and examples. The following examples or drawings are used to illustrate the utility model, but not to limit the scope of the utility model.

[0017] A large crawler crane wind machine hoisting operation platform bearing capacity monitoring system, as shown in Figure 1 And Figure 2 It includes a plurality of soil pressure sensors 1, a plurality of pre-embedded steel plates 2, a vibration string acquisition instrument 3, a thing internet gateway 4, a battery 5, a structure early warning analysis cloud platform 6, the soil pressure sensor 1 and the pre-embedded steel plate 2 are the same number, the soil pressure sensor 1 and the pre-embedded steel plate 2 are six, and the soil pressure sensor 1 and the pre-embedded steel plate 2 are pre-embedded underground, the soil pressure sensor 1 is located below the center of the roadbed steel plate on the ground, the soil pressure sensor 1 is abutted on the upper end of the pre-embedded steel plate 2, and the soil pressure sensor 1 is abutted on the lower end of the soil pressure sensor 1, the soil pressure sensor 1 is connected with the vibration string acquisition instrument 3 through the data line, the vibration string acquisition instrument 3 is connected with the thing internet gateway 4 through the data line, the vibration string acquisition instrument 3 and the thing internet gateway 4 are electrically connected with the battery 5, and the thing internet gateway 4 can wirelessly transmit data to the structure early warning analysis cloud platform 6.

[0018] The role of the embedded steel plate 2 is to increase the force area when embedding the soil pressure sensor, to avoid the uneven force and inaccurate detection caused by the small contact area of the soil pressure sensor 1 and the uneven settlement of the sand. The soil pressure sensor 1 is used to measure the contact pressure of the platform compacted soil interface, and the force surface is uniformly transmitted through the force shaft, which can understand the soil pressure change inside the measured structure.

[0019] The Internet of Things gateway 4 can transmit data wirelessly to the structure early warning analysis cloud platform 6 through the inserted 4G Internet of Things card when there is a network environment, and can use a notebook computer to directly connect to perform local data observation and collection when there is no network environment, and then import the local data into the structure early warning analysis cloud platform 6 for data statistics and analysis.

[0020] The structure early warning analysis cloud platform 6 has data receiving capability and can provide data change line graph drawing according to time period for the data provided by each soil pressure sensor 1, and mark the threshold time point.

[0021] Through the soil pressure sensor 1 and the embedded steel plate 2, the soil pressure of the area below the roadbed steel plate of the crawler crane station is monitored, and the ground bearing capacity of each hoisting force point in the actual hoisting process is understood, and the risk of overturning of the crawler crane caused by uneven force and ground settlement in the hoisting process is avoided.

[0022] The embedded depth of the soil pressure sensor 1 is greater than 20 cm, and the embedded steel plate 2 is embedded at a depth of 30 cm below the roadbed steel plate, so that the soil pressure transmitted by the upper equipment during hoisting will not cause inaccurate data monitoring due to uneven force and uneven settlement.

[0023] Work flow:

[0024] When hoisting the desert wind machine, a 500-800t large crawler crane is used for hoisting, the crawler crane station area is sprayed and compacted by a roller, which belongs to a compacted backfilling sand foundation. Before hoisting, the hoisting station roadbed steel plate needs to be laid, three roadbed steel plates with equal size are laid to ensure that the total length of the spliced roadbed steel plates is sufficient for the station adjustment during the operation of the crawler crane.

[0025] Six measuring points are designed, after the actual site survey and layout, the soil pressure sensor 1 and the embedded steel plate 2 are positioned and embedded, and the soil pressure sensor is marked with measuring points from right upper, right middle, left middle, right middle, left lower, and right lower. After embedding, the six soil pressure sensors 1 are connected to the vibrating string acquisition instrument 3 in sequence according to the marked detection points of the data acquisition line, and the data line is buried in the soil.

[0026] Through the Internet gateway 4, the vibrating string collector 3 transmits data to the structure early warning analysis cloud platform 6, before the structure early warning analysis cloud platform 6 receives the data, a structure stress analysis calculation model should be built on the structure early warning analysis cloud platform 6, the vibration frequency of the vibrating string of the soil pressure sensor 1 transmitted by the Internet gateway 4 is carried out data calculation processing, the vibration frequency is converted into stress through the background conversion formula;

[0027] The converted stress data is analyzed according to the change trend curve of time, the maximum stress time of each monitoring point in the hoisting process and the hoisting scene at the moment are found, the maximum bearing capacity moment of each monitoring point is confirmed, that is, the safety control risk point and the quality acceptance standard, and meanwhile, the maximum bearing capacity of each monitoring point is compared, the maximum stress of each force point in the whole hoisting process is found, the point is the maximum safety hidden danger, and the highest standard value of quality acceptance, which will be used as the acceptance standard of the subsequent hoisting operation platform.

[0028] The above is only a preferred embodiment of the present application, and does not limit the present application in any form, any simple modification or equivalent change made according to the technical essence of the present application to the above embodiment falls within the protection scope of the present application.

Claims

1. A large crawler crane wind turbine hoisting platform load bearing capacity monitoring system characterized by: The application relates to a soil pressure sensor (1), a number of embedded steel plates (2), a vibrating string acquisition instrument (3), an Internet of Things gateway (4), a storage battery (5) and a structure early warning analysis cloud platform (6), wherein the soil pressure sensor (1) and the embedded steel plate (2) are equal in number, the soil pressure sensor (1) and the embedded steel plate (2) are embedded underground, the soil pressure sensor (1) is located below the center of a roadbed steel plate on the ground, the soil pressure sensor (1) is in abutment with the upper end of the embedded steel plate (2) and is in abutment with the lower end of the soil pressure sensor (1), the soil pressure sensor (1) is connected with the vibrating string acquisition instrument (3) through a data line, the vibrating string acquisition instrument (3) is connected with the Internet of Things gateway (4) through a data line, and the vibrating string acquisition instrument (3) and the Internet of Things gateway (4) are electrically connected with the storage battery (5).

2. The carrying capacity monitoring system for a large crawler crane wind turbine hoisting platform according to claim 1, characterized in that: The Internet of Things gateway (4) can wirelessly transmit data to the structure early warning analysis cloud platform (6).

3. The carrying capacity monitoring system for a large crawler crane wind turbine hoisting platform according to claim 1, characterized in that: The embedding depth of the soil pressure sensor (1) is greater than 20 cm.

4. The carrying capacity monitoring system for a large crawler crane wind turbine hoisting platform according to claim 3, characterized in that: The embedded steel plate (2) is embedded at a position 30 cm underground of a roadbed steel plate.

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