A distributed edge sensing device, system and method for detecting derrick bearing capacity

Abstract

The present invention discloses a distributed edge sensing device, system, and method for detecting derrick bearing capacity, relating to the field of drilling derrick safety. The device comprises a base for mounting on a derrick and a housing connected to the base. A strain sensing device is provided on a surface of the base facing the derrick. A processing module, a power supply module, and a wireless transmission module are disposed within the base or housing. The input of the processing module is signal-connected to the strain sensing device, and the output of the processing module is signal-connected to the wireless transmission module. The present invention addresses the problem of the prior art in being unable to accurately and real-timely reflect the derrick bearing capacity, thereby achieving the goal of real-time and accurate safety detection of the derrick bearing capacity.

Description

Technical Field

[0001] The present invention relates to the field of drilling derrick safety, and in particular to a distributed edge sensing device, system and method for detecting the bearing capacity of a derrick. Background Art

[0002] With the continuous development of oil and gas resources, the safety and efficiency of drilling operations, as a key link in obtaining these resources, have attracted widespread attention. The safe and stable operation of the drilling derrick, a crucial structure in oil and gas extraction, is directly related to the safe production of the oil rig system and the personal safety of on-site operators. Therefore, the inspection and evaluation of the derrick's load-bearing capacity is particularly important. The inspection and evaluation of the derrick's load-bearing capacity of oil and gas drilling or workover rigs often involves complex working conditions, making it difficult to conduct on-site online evaluations using existing technologies.

[0003] Especially when facing micro-strain conditions, traditional testing methods typically involve building a derrick simulation model, inputting derrick operating parameters into the model for simulation, and obtaining test results. This traditional testing method suffers from low accuracy, a complex testing process, and tedious modeling. Furthermore, the accuracy of the results is highly dependent on the number of samples, making it impossible to accurately and instantly reflect the load-bearing status of the derrick. Summary of the Invention

[0004] The present invention provides a distributed edge sensing device, system and method for detecting derrick bearing capacity, so as to solve the problem in the prior art that the derrick bearing state cannot be accurately and in real time reflected, and achieve the purpose of real-time and accurate safety detection of the derrick bearing state.

[0005] The present invention is achieved through the following technical solutions:

[0006] A distributed edge sensing device for detecting the bearing capacity of a derrick comprises a base for installation on a derrick and a shell connected to the base; a strain sensing device is provided on a surface of the base facing the derrick; a processing module, a power supply module and a wireless transmission module are provided within the base or the shell; an input end of the processing module is signal-connected to the strain sensing device, and an output end of the processing module is signal-connected to the wireless transmission module.

[0007] To address the existing inability to accurately and immediately reflect the derrick's load-bearing status, the present invention proposes a distributed edge-sensing device for detecting derrick load capacity. This device is mounted on the outer wall of the derrick via a base, and a processing module, power supply module, and wireless transmission module are mounted on the base or housing. A strain sensing device is mounted on the base, facing the derrick, to monitor the derrick's strain in real time. The resulting strain signal is transmitted to the processing module, which performs local analysis and judgment, and can then be transmitted to a backend (such as a wellsite control room) via a wireless transmission module.

[0008] When this device is used, it is installed two by two at the test point of the derrick, and the strain of the two opposite side walls of the derrick is monitored in real time to analyze the load-bearing status of the derrick. Compared with the existing technology, this device can be installed on the derrick for a long time to work, and truly realizes the real-time monitoring of the derrick's bearing capacity; this application creatively adopts the idea of ​​distributed edge sensing technology to realize the detection of the derrick's bearing capacity, overcoming the problem of low detection accuracy caused by low modeling accuracy and insufficient sample number in the existing technology, and significantly improving the detection accuracy of the derrick's bearing capacity; because this application directly collects strain data on the surface of the derrick, it has a strong sensitivity to small strains, which is of great significance for ensuring the stable operation of the derrick and protecting the personal safety of on-site workers. In addition, this application not only improves the monitoring efficiency of the bearing capacity detection when the derrick is working, but also reduces the monitoring and maintenance costs of the derrick, providing strong support for the stable operation of oil and gas development equipment; the application of this application also helps to improve the overall efficiency of the oil extraction process, thereby improving economic benefits.

[0009] Furthermore, this device uses a power supply module to power various electrical devices, a wireless transmission module to enable remote signal transmission, and a processing module to enable localized judgment during the detection process. This significantly improves response speed and flexibility compared to existing technologies. Of course, the processing module, power supply module, and wireless transmission module can all be implemented using existing hardware.

[0010] Furthermore, a magnet is provided on the base, which is used to attract the base to the derrick. This solution achieves a detachable connection between the distributed edge sensing device and the derrick through magnetic attraction. It is quick to install, easy to disassemble, and reusable. It also enables the application to flexibly and quickly adjust the position of the detection point on the derrick as needed. Compared with the existing technology that requires rewiring to adjust the detection point, it significantly improves the flexibility and adaptability of use.

[0011] Furthermore, an indicator device is provided on the housing, and the indicator device is signal-connected to the processing module and / or the wireless transmission module. The indicator device in this solution is used to reflect the real-time load-bearing safety status of the test point on the derrick, timely indicate the load-bearing capacity status of the derrick, and then perform early warning or alarm operations for abnormal conditions, thereby ensuring the real-time and response speed of the derrick load-bearing status monitoring. Depending on whether it is a local judgment or a background remote judgment, the control signal for the indicator device can be sent by the processing module or by the background via the wireless transmission module. In addition, the indicator device in this solution can adopt any indication method that can be implemented by those skilled in the art, such as sound, light, electricity, etc.

[0012] A distributed edge sensing system for detecting derrick bearing capacity includes several pairs of the aforementioned edge sensing devices; each pair of the edge sensing devices is symmetrically installed on the outer walls of the derrick on opposite sides, and the strain sensing device of each edge sensing device is in contact with the outer wall of the derrick.

[0013] In the distributed edge sensing system of the present application, the aforementioned edge sensing devices are used in pairs, and synchronous real-time monitoring of multiple points on the derrick can be achieved through one system.

[0014] A distributed edge sensing method for derrick bearing capacity detection is implemented based on the edge sensing device, comprising the following steps:

[0015] S1. symmetrically install the two edge sensing devices on the outer walls of the derrick at the point to be measured on both sides;

[0016] S2. Each strain sensing device monitors the strain signal in real time, converts it into a voltage signal, and transmits it to the processing module;

[0017] S3, the processing module performs adaptive filtering on the received voltage signal to obtain a self-enhanced signal;

[0018] S4. Determine the bearing capacity status of the current point to be measured based on the self-enhancement signals of the two relative edge sensing devices.

[0019] Furthermore, the method of adaptively filtering the received voltage signal to obtain the self-enhanced signal includes:

[0020] S301, establishing a filter through an affine projection algorithm;

[0021] S302, determining the expected response of the filter: inputting the voltage signal received in real time into the AR model, and using the output obtained by the AR model as the expected response E(t) of the filter;

[0022] S303, determine the error vector e of the filter t : U(t)=[u1,u2,……ut ], represents the received voltage signal vector; u t is the voltage signal at time t; T is the transposition operator; w t-1 is the filter coefficient at time t-1;

[0023] S304: Establish an input matrix I(t) based on the received voltage signal:

[0024]

[0025] Where: M represents the projection order; L represents the filter length;

[0026] S305 , inputting the input matrix I(t) into a filter, and using the output of the filter as a self-enhancement signal.

[0027] In this solution, the affine projection algorithm is a prior art, and it is not difficult for those skilled in the art to establish a filter based on the affine projection algorithm; similarly, the AR model is an autoregressive model, which is also a prior art, so it is not described here. After determining the expected response and error vector of the filter, this solution establishes an input matrix input to the filter using the received voltage signal to obtain a self-enhanced signal. It should be understood by those skilled in the art that the projection order M refers to the number of input signals selected at each moment t (including the signals of the current and previous (M-1) moments), and a reasonable selection of the value of M can improve the noise suppression effect and can repeatedly improve the utilization rate of historical information.

[0028] Furthermore, step S4 specifically includes:

[0029] S401, calculating a phase difference sequence of self-enhancement signals relative to two edge sensing devices;

[0030] S402, calculating the energy difference and energy entropy difference of the sliding windows of the self-enhanced signals of the two edge sensing devices;

[0031] S403, calculating the decision parameter λ(t);

[0032] S404. Compare the decision parameter λ(t) with the decision threshold T(t):

[0033] If λ(t)>1.5T(t), the bearing capacity of the current test point is determined to be at the first level;

[0034] If T(t)<λ(t)≤1.5T(t), the bearing capacity of the current test point is determined to be at the secondary level;

[0035] If λ(t)≤T(t), the bearing capacity of the current test point is determined to be at level three;

[0036] Among them, the risks of the third level, second level and first level increase step by step.

[0037] The two relative edge sensing devices in this solution refer to two edge sensing devices symmetrically installed on the outer walls of the opposite sides of the derrick to be tested. This solution calculates the phase difference sequence, energy difference, and energy entropy difference respectively, and then calculates the decision parameters in the current state based on the above calculation results, compares the decision parameters with the decision threshold, and then determines the current load-bearing state of the test point. This solution divides the load-bearing state into three levels, among which the first level has the highest degree of danger (that is, the current load-bearing state of the test point is at the most dangerous level), and the third level has the lowest degree of danger (that is, the current load-bearing state of the test point is at a relatively safe level).

[0038] Furthermore, the phase difference sequence is calculated using the following formula: Where: is the phase difference sequence; is the instantaneous phase obtained by Hilbert transform of the self-enhanced signal of an edge sensing device; is the instantaneous phase obtained by Hilbert transform of the self-enhanced signal of another edge sensing device;

[0039] The energy difference is calculated by the following formula: ΔE(t)=|E X (t)-E Y (t)|; where: ΔE(t) is the energy difference; E X (t) represents the energy sequence of the self-enhanced signal of an edge sensing device; E Y (t) represents the energy sequence of the self-enhanced signal of another edge sensing device;

[0040] The energy entropy difference is calculated by the following formula: ΔH(t)=|H X (t)-H Y (t)|; ΔH(t) is the energy entropy difference; H X (t) represents the energy entropy of the self-enhanced signal of an edge sensing device; H Y (t) represents the energy entropy of the self-enhanced signal of another edge-sensing device.

[0041] It is easy to understand that in this scheme, the two edge sensing devices are represented by X and Y respectively, and the corresponding instantaneous phases are The corresponding energy sequences are E X (t), E Y (t); the corresponding energy entropy is H X (t), H Y (t).

[0042] In addition, the decision threshold T(t) in this scheme can be adaptively set according to the specific working conditions, such as using empirical methods, expert scoring, or dynamic adjustment based on specific working conditions.

[0043] Furthermore, the decision parameter λ(t) is calculated by the following formula:

[0044]

[0045] Where: ω PC (t) is the phase consistency weight; ω EE (t) is the energy entropy weight; E ref H is the energy reference value when the derrick is in the no-load state; ref is the energy entropy baseline value under the derrick no-load state; is the phase standard deviation; γ H is the entropy sensitivity coefficient; L0 is the sliding window length.

[0046] This solution creatively introduces the decision parameter λ(t) to identify the load-bearing state of the derrick, and provides a specific formula for calculating the decision parameter λ(t), which has excellent quantitative effect and fills the gap in the existing technology.

[0047] Furthermore, the decision threshold T(t) is calculated by the following formula:

[0048]

[0049] Where: μ base , σ base represent the mean and standard deviation of the decision parameter λ(t) under the no-load state of the derrick; k is the safety factor; L0 is the sliding window length.

[0050] This solution creatively adopts a method of dynamically adjusting the specific value of the decision threshold T(t), realizing adaptive adjustment of the decision threshold. The logic of this dynamic adjustment combines the historical data of the collected signals with the real-time fluctuations, significantly improving the monitoring accuracy of the derrick load-bearing status.

[0051] Compared with the prior art, the present invention has at least the following advantages and beneficial effects:

[0052] 1. The present invention provides a distributed edge sensing device, system, and method for detecting derrick bearing capacity. The device adopts the technical concept of distributed edge sensing to realize the detection of derrick bearing capacity, overcoming the problem of low detection accuracy caused by low modeling accuracy and insufficient sample quantity in the existing technology, and significantly improving the detection accuracy of derrick bearing capacity.

[0053] 2. The distributed edge sensing device, system and method for detecting the bearing capacity of a derrick of the present invention have strong sensitivity to small strains, which is of great significance for ensuring the stable operation of the derrick and protecting the personal safety of on-site workers.

[0054] 3. The distributed edge sensing device, system and method for derrick bearing capacity detection of the present invention not only improves the monitoring efficiency of bearing capacity detection when the derrick is working, but also reduces the monitoring and maintenance costs of the derrick, providing strong support for the stable operation of oil and gas development equipment; the application of this application also helps to improve the overall efficiency of the oil extraction process, thereby improving economic benefits.

[0055] 4. The present invention provides a distributed edge sensing device, system, and method for detecting derrick bearing capacity, which realizes adaptive adjustment of the decision threshold and significantly improves the monitoring accuracy of the derrick bearing status. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0057] Figure 1 is a front view of an edge sensing device in a specific embodiment of the present invention;

[0058] Figure 2 A side view of an edge sensing device in a specific embodiment of the present invention;

[0059] Figure 3 It is a back view of the edge sensing device in a specific embodiment of the present invention;

[0060] Figure 4 This is a schematic diagram of the installation of an edge sensing system in a specific embodiment of the present invention;

[0061] Figure 5 Schematic diagram of a half-bridge differential circuit in a specific embodiment of the present invention;

[0062] Markings and corresponding parts names in the accompanying drawings:

[0063] 1-base, 2-housing, 3-strain sensing device, 4-magnet, 5-indicating device, 6-antenna, 7-solar panel. DETAILED DESCRIPTION

[0064] In order to make the objects, technical solutions and advantages of the present invention more clear, the present invention is further described in detail below in conjunction with the examples and drawings. The schematic embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention. In the description of this application, it should be understood that the orientations or positional relationships indicated by terms such as "front", "back", "left", "right", "up", "down", "vertical", "horizontal", "high", "low", "inside", "outside", etc. are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the scope of protection of this application.

[0065] Example 1:

[0066] like Figures 1 to 3 The distributed edge sensing device for detecting the bearing capacity of a derrick shown includes a base 1 for installation on a derrick, a housing 2 detachably connected to the base 1, a strain sensing device 3 provided on the surface of the base 1 facing the derrick, and a processing module, a power supply module, and a wireless transmission module provided within the base 1 and / or the housing 2; the input end of the processing module is signal-connected to the strain sensing device 3, and the output end of the processing module is signal-connected to the wireless transmission module. The processing module, power supply module, and wireless transmission module can be adaptively selected and installed within the base 1 and / or the housing 2 according to specific size and shape requirements. There are no specific requirements for their specific installation locations; it is sufficient to ensure that they can each function normally.

[0067] In this embodiment, the strain sensing device 3 is a strain sensor; the processing module can be implemented using a PLC or the like; and the wireless transmission module can be implemented using wireless technologies such as Bluetooth, Wi-Fi, 4G / 5G, and GPRS. Preferably, the wireless transmission module can include an antenna 6 to enhance signal transmission stability.

[0068] The base 1 is provided with a magnet 4 for adsorbing the base 1 on the derrick. In this embodiment, the magnet 4 comprises two NdFeB sub-magnets, which are respectively embedded on both sides of the strain sensing device 3 .

[0069] The housing 2 is provided with an indicator device 5, which is signal-connected to the processing module and / or the wireless transmission module. In this embodiment, the indicator device 5 includes three indicator lights of different colors, corresponding to three different load status levels; the three indicator lights are preferably green, yellow, and red.

[0070] The power supply module in this embodiment is a battery, which can be a rechargeable battery for added power. In a more preferred embodiment, the charging module may further include a solar panel 7, which is disposed on the housing 2, opposite the strain sensing device 3, and is used to replenish the battery or provide backup power. Furthermore, the solar panel 7 may employ a multi-busbar design to improve energy conversion efficiency.

[0071] It can be seen that this embodiment uses two magnets to establish a positioning connection with the derrick at the point to be measured. It is quick to install, easy to disassemble, reusable, and highly adaptable. A high-sensitivity resistance strain sensor is used to accurately detect the strain data of the measured point. A solar panel with a multi-busbar design is used to improve energy utilization and extend the continuous working time of the device. Wireless transmission technology is used to transmit processed data in real time, which can promptly reflect the bearing capacity status of the derrick and provide early warning or alarm processing for abnormal conditions, thereby ensuring real-time performance and response speed.

[0072] Example 2:

[0073] A distributed edge sensing system for derrick bearing capacity detection, using the following Figure 1-3 The edge sensing device shown in FIG; two edge sensing devices are a pair, such as Figure 4 As shown, each pair of edge sensing devices are symmetrically mounted on opposite outer walls of the derrick, and the strain sensing device 3 of each edge sensing device is tightly attached to the outer wall of the derrick.

[0074] Preferably, the distributed edge perception system of this embodiment further includes a main control room, and each wireless transmission module communicates wirelessly with the main control room.

[0075] In a more preferred embodiment, the two wireless transmission modules in each pair of edge sensing devices communicate with each other.

[0076] Example 3:

[0077] A distributed edge sensing method for detecting derrick bearing capacity, characterized in that it is based on the edge sensing device described in any one of claims 1 to 3, and includes the following steps:

[0078] Step 1: symmetrically install the two edge sensing devices on the outer walls of the derrick at opposite sides of the point to be measured.

[0079] Step 2: Each strain sensing device monitors the strain signal in real time, converts it into a voltage signal, and transmits it to the processing module.

[0080] Step 3: The processing module performs adaptive filtering on the received voltage signal to obtain a self-enhanced signal; specifically, the process includes:

[0081] Build the filter through the affine projection algorithm;

[0082] Determine the expected response of the filter: Input the real-time received voltage signal into the AR model, and use the output of the AR model as the expected response E(t) of the filter;

[0083] Determine the filter error vector e t : U(t)=[u1,u2,……u t ], represents the received voltage signal vector; u t is the voltage signal at time t; T is the transposition operator; w t-1 is the filter coefficient at time t-1;

[0084] The input matrix I(t) is established based on the received voltage signal:

[0085]

[0086] Where: M represents the projection order; L represents the filter length;

[0087] The input matrix I(t) is input to the filter, and the output of the filter is used as the self-enhancement signal.

[0088] Step 4: Determine the bearing capacity of the current point to be measured based on the self-enhancement signals of the two relative edge sensing devices; specifically, include:

[0089] (1) Calculate the phase difference sequence of the self-enhanced signals relative to the two edge sensing devices:

[0090]

[0091] Where: is the phase difference sequence; is the instantaneous phase obtained by Hilbert transform of the self-enhanced signal of an edge sensing device; is the instantaneous phase obtained by Hilbert transform of the self-enhanced signal of another edge sensing device.

[0092] (2) Calculate the energy difference and energy entropy difference of the sliding window of the self-enhanced signal of the two edge sensing devices:

[0093] ΔE(t)=|E X (t)-E Y (t)|;

[0094] ΔH(t)=|H X (t)-H Y (t)|;

[0095] Where: ΔE(t) is the energy difference; E X(t) represents the energy sequence of the self-enhanced signal of an edge sensing device; E Y (t) represents the energy sequence of the self-enhancement signal of another edge sensing device; ΔH(t) is the energy entropy difference; H X (t) represents the energy entropy of the self-enhanced signal of an edge sensing device; H Y (t) represents the energy entropy of the self-enhanced signal of another edge-sensing device.

[0096] (3) Calculate the decision parameter λ(t):

[0097]

[0098] Where: ω PC (t) is the phase consistency weight; ω EE (t) is the energy entropy weight; E ref H is the energy reference value when the derrick is in the no-load state; ref is the energy entropy baseline value under the derrick no-load state; is the phase standard deviation; γ H is the entropy sensitivity coefficient; L0 is the sliding window length.

[0099] (4) Compare the decision parameter λ(t) and the decision threshold T(t):

[0100] If λ(t)>1.5T(t), the bearing capacity of the current test point is determined to be at the first level; at this time, the bearing state of the current position is at a dangerous level, and the red indicator light is turned on;

[0101] If T(t)<λ(t)≤1.5T(t), the bearing capacity of the current test point is determined to be at the secondary level; at this time, the bearing state of the current position is at the warning level, and the yellow indicator light is turned on;

[0102] If λ(t)≤T(t), it is determined that the bearing capacity of the current test point is at level three; at this time, the bearing state of the current position is at a safe level, and the green indicator light is turned on.

[0103] Preferably, this embodiment dynamically adjusts the decision threshold T(t), and the adjustment formula is as follows:

[0104]

[0105] Where: μ base , σ base They represent the mean and standard deviation of the decision parameter λ(t) under the no-load state of the derrick respectively; k is the safety factor, and in this embodiment, k=2; L0 is the sliding window length; max() represents the maximum value.

[0106] In a more preferred embodiment, the strain signal is converted into a voltage signal through a half-bridge differential circuit; the half-bridge differential circuit used in this embodiment is as follows Figure 5 As shown, given voltage U0, the output voltage ΔU is:

[0107]

[0108] In a more preferred embodiment, two opposing edge sensing devices are defined as a primary sensing device and a secondary sensing device, respectively, and their wireless transmission modules are configured to communicate with each other. The processing module of the secondary sensing device transmits its processed self-enhanced signal to the processing module of the primary sensing device, which then completes the calculation and judgment process in step 4.

[0109] Example 4:

[0110] A distributed edge sensing method for derrick bearing capacity detection, based on Example 3:

[0111] Calculated by the following formula:

[0112]

[0113] Where: X(t) and Y(t) represent the self-enhancement signals of the two edge sensing devices respectively; stands for Hilbert transform.

[0114] Preferably, the energy sequence E X The calculation method of (t) is:

[0115] For the signal X(t), define the sliding window length L0=100, and each time the window moves 5 sampling points, the energy sequence is:

[0116] Energy entropy H X The calculation formula for (t) is:

[0117]

[0118] Where: p i represents the normalized energy probability.

[0119] E Y (t), H Y The calculation method of (t) is similar and will not be described here.

[0120] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0121] It should be noted that, in this document, terms such as "include," "comprises," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In addition, the term "connected" as used herein, unless otherwise specified, may refer to direct connection or indirect connection via other components.

Claims

1. A distributed edge sensing method for derrick bearing capacity detection, characterized in that: The edge sensing device is implemented based on an edge sensing device, comprising a base (1) for mounting on a derrick, and a housing (2) connected to the base (1); a strain sensing device (3) is provided on a surface of the base (1) facing the derrick; a processing module, a power supply module, and a wireless transmission module are provided in the base (1) or the housing (2); an input end of the processing module is signal-connected to the strain sensing device (3), and an output end of the processing module is signal-connected to the wireless transmission module; The distributed edge sensing method for detecting derrick bearing capacity comprises the following steps: S1. symmetrically install the two edge sensing devices on the outer walls of the derrick at the point to be measured on both sides; S2. Each strain sensing device monitors the strain signal in real time, converts it into a voltage signal, and transmits it to the processing module; S3, the processing module performs adaptive filtering on the received voltage signal to obtain a self-enhanced signal; S4, judging the bearing capacity status of the current point to be measured based on the self-enhancement signals of the two relative edge sensing devices; Step S4 specifically includes: S401, calculating a phase difference sequence of self-enhancement signals relative to two edge sensing devices; S402, calculating the energy difference and energy entropy difference of the sliding windows of the self-enhanced signals of the two edge sensing devices; S403, calculating the decision parameter λ(t); S404. Compare the decision parameter λ(t) with the decision threshold T(t): If λ(t)>1.5T(t), the bearing capacity of the current test point is determined to be at the first level; If T(t)<λ(t)≤1.5T(t), the bearing capacity of the current test point is determined to be at the secondary level; If λ(t)≤T(t), the bearing capacity of the current test point is determined to be at level three; The risks of the third level, second level and first level increase step by step; The decision parameter λ(t) is calculated by the following formula: Where: ω PC (t) is the phase consistency weight; ω EE (t) is the energy entropy weight; E ref H is the energy reference value when the derrick is in the no-load state; ref is the energy entropy baseline value under the derrick no-load state; is the phase standard deviation; γ H is the entropy sensitivity coefficient; L0 is the sliding window length; The decision threshold T(t) is calculated by the following formula: Where: μ base , σ base represent the mean and standard deviation of the decision parameter λ(t) under the no-load state of the derrick; k is the safety factor; L0 is the sliding window length.

2. A distributed edge sensing method for derrick bearing capacity detection according to claim 1, characterized in that: The method for adaptively filtering the received voltage signal to obtain a self-enhanced signal includes: S301, establishing a filter through an affine projection algorithm; S302, determining the expected response of the filter: inputting the voltage signal received in real time into the AR model, and using the output obtained by the AR model as the expected response E(t) of the filter; S303, determine the error vector e of the filter t : U(t)=[u1,u2,……u t ], represents the received voltage signal vector; u t is the voltage signal at time t; T is the transposition operator; w t-1 is the filter coefficient at time t-1; S304: Establish an input matrix I(t) based on the received voltage signal: Where: M represents the projection order; L represents the filter length; S305 , inputting the input matrix I(t) into a filter, and using the output of the filter as a self-enhancement signal.

3. The distributed edge sensing method for derrick bearing capacity detection according to claim 1, characterized in that: The phase difference sequence is calculated by the following formula: Where: is the phase difference sequence; is the instantaneous phase obtained by Hilbert transform of the self-enhanced signal of an edge sensing device; is the instantaneous phase obtained by Hilbert transform of the self-enhanced signal of another edge sensing device; The energy difference is calculated by the following formula: ΔE(t)=|E X (t)-E Y (t)|; where: ΔE(t) is the energy difference; E X (t) represents the energy sequence of the self-enhanced signal of an edge sensing device; E Y (t) represents the energy sequence of the self-enhanced signal of another edge sensing device; The energy entropy difference is calculated by the following formula: ΔH(t)=|H X (t)-H Y (t)|; ΔH(t) is the energy entropy difference; H X (t) represents the energy entropy of the self-enhanced signal of an edge sensing device; H Y (t) represents the energy entropy of the self-enhanced signal of another edge-sensing device.

4. The distributed edge sensing method for derrick bearing capacity detection according to claim 1, characterized in that: A magnet (4) is provided on the base (1), and the magnet (4) is used to adsorb the base (1) on the derrick.

5. The distributed edge sensing method for derrick bearing capacity detection according to claim 1, characterized in that: An indicating device (5) is provided on the housing (2), and the indicating device (5) is signal-connected to the processing module and / or the wireless transmission module.

Images