Roadway surrounding rock deformation self-powered monitoring system and method

Abstract

The invention belongs to the technical field of mine safety monitoring, and relates to a roadway surrounding rock deformation self-powered monitoring system and method. Aiming at the problems of dependence on external power supply, limited monitoring range, mismatching of sensing and supporting mechanical response, high operation and maintenance cost and the like in the existing roadway monitoring technology, a flexible piezoelectric film and a supporting anchor net are compounded into an integrated structure through a weaving embedding-hot pressing curing process; the tunnel supporting function and the surrounding rock vibration mechanical energy-electric energy conversion capability are achieved; the energy management unit is used for rectifying and storing the converted electric energy to realize self-energy supply of the system; the data processing unit analyzes the electric signal frequency (reflecting the vibration intensity) and the amplitude (associated deformation quantity), and combines a decision tree algorithm to construct a two-dimensional threshold linkage early warning model. The system can realize full-section continuous monitoring of the roadway without an external power supply, has a high-sensitivity response characteristic to tiny deformation of surrounding rocks, and provides reliable technical guarantee for safety monitoring of the deep roadway.

Description

Technical Field

[0001] This invention belongs to the interdisciplinary field of mine safety monitoring and new energy sensing technology, and specifically relates to a self-powered monitoring system and method for roadway surrounding rock deformation. It is applicable to real-time monitoring and early warning of deformation of surrounding rock in mine roadways, especially for the proactive prevention and control of disasters such as roof delamination and sidewall convergence in deep, high-stress roadways. Background Technology

[0002] Shallow resources in my country's main coal-producing areas are nearing depletion, and mining efforts are continuously extending to depths of over 1,000 meters. Deep geological conditions are characterized by "high stress, high water pressure, and high ground temperature," with the deformation rate of the surrounding rock in tunnels increasing by 3-5 times compared to shallower areas. Although traditional anchor bolt (cable) support systems are currently the mainstream choice, as underground concealed engineering projects, the development of internal fissures and the expansion of delamination are difficult to identify visually, creating an urgent need for real-time monitoring technology.

[0003] Current methods for monitoring deformation of surrounding rock in roadways have significant limitations. For example, roof delamination gauges, which are buried in the surrounding rock through boreholes, can only capture the amount of delamination at local points within the borehole, failing to reflect the overall deformation trend of the entire roadway cross-section, resulting in insufficient data representativeness. The cross-point method requires periodic manual statistical analysis of the displacement of the roof, floor, and sidewalls, which is not only cumbersome and time-consuming for each operation but also results in long data intervals, poor continuity, and significant human reading errors. Furthermore, while some automated monitoring equipment achieves automatic data acquisition, it relies on external power networks, leading to rapid power consumption in the high humidity and dusty underground environment, requiring monthly downtime for maintenance, increasing safety risks and operating costs. More critically, in existing technologies, the sensing elements and support structures are mostly designed separately, resulting in mechanical decoupling and response delays. When minor deformations occur in the surrounding rock, the sensing devices often trigger with a lag, leading to missed early hazards. Therefore, developing a monitoring solution that requires no external power supply, can cover the entire roadway cross-section, and can accurately capture minor deformations has become an important issue for ensuring the safety of deep roadway mining. Summary of the Invention

[0004] In view of the problems that existing methods for monitoring the deformation of surrounding rock in roadways have, such as large investment of manpower and material resources, serious interference from human factors, poor data accuracy, and inability to reflect the state of surrounding rock in real time, this invention provides a self-powered monitoring system and method for the deformation of surrounding rock in roadways, which aims to achieve efficient, accurate and automated monitoring of stress and deformation of surrounding rock in roadways.

[0005] The objective of this invention is mainly achieved through the following technical solutions:

[0006] One aspect of the present invention provides a method for monitoring the self-powered deformation of roadway surrounding rock, the specific steps of which are as follows:

[0007] Step 1. The piezoelectric-mesh composite support structure of claim 1, composed of a support anchor mesh substrate and a flexible piezoelectric material, is firmly installed on the surface of the surrounding rock of the roadway according to the roadway support design requirements. The support anchor mesh substrate can be made of metal or polymer material to provide basic mechanical support for the roadway; the flexible piezoelectric material is embedded or attached to the anchor mesh substrate in a mesh-like form to form a tightly integrated structure, realizing the integration of the piezoelectric sensing unit and the support anchor mesh substrate.

[0008] Step 2. Deploy the energy management unit and data processing unit at appropriate locations in the tunnel. The energy management unit is connected to the piezoelectric material via wiring to collect the electrical energy generated by the piezoelectric material; the data processing unit is connected to the energy management unit to receive and process relevant data, and data transmission lines are set up to ensure that the data can be accurately transmitted to the ground monitoring terminal.

[0009] Step 3. When the surrounding rock of the roadway deforms or vibrates, the support anchor mesh matrix deforms accordingly, causing the embedded or bonded flexible piezoelectric material to deform synchronously. Based on the piezoelectric effect, the piezoelectric material converts mechanical energy into unstable alternating current. This electrical signal serves as data for monitoring the surrounding rock condition and is also collected by the energy management unit.

[0010] Step 4. The energy management unit processes the collected AC power, converts it into stable DC power through a rectifier and voltage regulator circuit, and stores it in internal energy storage components such as supercapacitors or rechargeable batteries to provide a continuous and stable power supply for the entire monitoring system, ensuring that the device can operate normally without relying on an external power source.

[0011] Step 5. The data processing unit performs in-depth processing of the acquired electrical signals based on preset analysis logic and algorithms. By analyzing characteristic parameters such as frequency and amplitude of the electrical signals, the vibration state of the surrounding rock is determined and compared with a preset frequency threshold. The amplitude is also compared with a preset safety threshold to comprehensively identify the degree and state of deformation of the surrounding rock.

[0012] Step 6. Once the surrounding rock vibration frequency exceeds the set threshold, the data processing unit immediately generates a warning signal of the corresponding level, such as yellow, blue, or red. The warning signal is transmitted to the ground monitoring terminal in real time via the wireless communication module. Based on the warning level, personnel take timely and appropriate safety measures, such as strengthening inspections, reinforcing support, or organizing personnel evacuation. Different levels of warning signals are displayed or transmitted using different methods.

[0013] Another aspect of the present invention provides a self-powered monitoring system for deformation of surrounding rock in roadways, characterized in that it comprises the following parts:

[0014] Piezoelectric-mesh composite support structure: As the core component of the entire device, it simultaneously undertakes the tasks of roadway mechanical support and surrounding rock deformation sensing. This structure uses a support anchor mesh matrix as its load-bearing skeleton, woven from low-alloy high-strength steel wire. The mesh size is dynamically adapted to the roadway span and surrounding rock characteristics. Flexible piezoelectric material is integrated with the anchor mesh matrix through a woven embedding-hot-press curing process. Mechanical coupling is achieved through a stress transfer layer at the metal wire intersections, ensuring effective stress transmission. This ensures that minute deformations of the surrounding rock drive the anchor mesh to stretch, simultaneously driving the piezoelectric material deformation, and achieving real-time conversion of mechanical energy to electrical energy based on the positive piezoelectric effect.

[0015] Energy Management Unit: Connected to multiple piezoelectric material monitoring units via waterproof and dustproof cables, forming a closed loop of "energy capture-conversion-storage". Its core is a full-bridge rectifier-low dropout voltage regulator integrated circuit, which can convert the alternating current output by the piezoelectricity into stable direct current; the energy storage stage adopts a supercapacitor or rechargeable battery architecture to provide a continuous and stable power supply for the operation of the entire device.

[0016] Data Processing Unit: Connected to the energy management unit via a signal interface, this unit is responsible for electrical signal analysis and early warning decision-making. It features a built-in low-power microcontroller and a decision tree algorithm trained on historical data. This allows for dual-channel analysis of the electrical signal's frequency (reflecting vibration intensity) and amplitude (corresponding to deformation). It generates tiered early warnings through preset multi-parameter linkage thresholds and continuously optimizes the tiered indicators by learning from and training on a large amount of historical data. This reduces system monitoring errors and establishes an accurate mapping relationship between vibration frequency f, actual rock deformation D, and the rock deformation state, improving the accuracy and timeliness of rock deformation state assessment. It also includes an anti-interference wireless communication module to transmit early warning information and related monitoring data to the ground terminal system.

[0017] Ground monitoring terminal: As the human-machine interaction hub, after receiving information transmitted by the data processing unit, it displays the stress and deformation status of the surrounding rock in the tunnel in real time in the form of intuitive images or charts. It has a built-in emergency response module to help staff keep abreast of the tunnel conditions and make timely decisions and take corresponding safety measures based on the early warning information.

[0018] Compared with the prior art, the present invention can achieve at least one of the following technical effects:

[0019] 1) The piezoelectric-mesh composite support structure provided by the present invention integrates sensing, power supply and support functions into one, so that the support structure and the sensing unit are closely combined. This can solve the problem of mechanical decoupling between the sensing unit and the support structure in traditional monitoring technology, and ensure that the deformation and vibration of the surrounding rock can be sensed in a timely and accurate manner, thereby improving the accuracy and reliability of monitoring.

[0020] 2) The piezoelectric-mesh composite support structure provided by the present invention utilizes the piezoelectric effect to achieve self-sufficiency of energy, eliminating the need for an external power source. It is adaptable to harsh environments such as dampness and dust in underground mines, reducing cable laying and power supply maintenance, and greatly reducing operation and maintenance costs and safety risks.

[0021] 3) The piezoelectric-mesh composite support structure provided by this invention can provide comprehensive monitoring coverage and reduce blind spots. With the mesh-distributed piezoelectric sensing structure, it can monitor the surrounding rock of the roadway in all directions without dead angles. Compared with the traditional single-point or local monitoring methods, it can effectively reduce monitoring blind spots, improve the monitoring ability of surrounding rock deformation, and promptly detect potential safety hazards.

[0022] 4) This invention employs intelligent analysis methods such as the decision tree algorithm built into the data processing unit, enabling automatic identification and graded early warning of surrounding rock deformation status with high accuracy. Workers can take timely measures based on the early warning information to effectively prevent serious production safety accidents such as roof collapses, thus ensuring coal mine production safety.

[0023] 5) The support anchor mesh matrix and related components provided by this invention are optimized in design, such as reasonable material selection and optimized structural shape, which can enhance the stability and bearing capacity of the overall structure. While effectively monitoring the deformation of the surrounding rock, it can better play the support role and maintain the stability of the surrounding rock of the roadway during service.

[0024] Other features and advantages of the present invention will be further set forth in the following description, and some of these will be learned through practice of the invention. The objectives and advantages of the present invention are realized and manifested through the structures described in the specification and claims. Attached Figure Description

[0025] The accompanying drawings are for illustrative purposes only and do not constitute a limitation of the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0026] Figure 1 This is a schematic diagram of the piezoelectric-mesh composite support structure in Example 1;

[0027] Figure 2 This is a schematic diagram of the composite structure of the piezoelectric sensing unit and the support anchor mesh substrate in Example 1;

[0028] Figure 3 This is a schematic diagram illustrating the working principle of the piezoelectric thin film in Example 1;

[0029] Figure 4 This is a schematic diagram of the energy management unit circuit in Example 2;

[0030] Figure 5 This is a schematic diagram of the data processing unit's workflow in Example 2;

[0031] Figure 6 This is a schematic diagram of the overall deployment of the self-powered monitoring system for roadway surrounding rock deformation in Example 3;

[0032] Figure 7 This is a schematic diagram of the self-powered monitoring method for roadway surrounding rock deformation in Example 3.

[0033] Reference numerals in the accompanying drawings: 1-Support anchor mesh substrate; 2-Piezoelectric sensing unit; 3-Energy management unit; 301-Rectifier and voltage regulator circuit; 302-Energy storage element; 4-Data processing unit; 5-Wireless communication module; 6-Ground monitoring terminal. The accompanying drawings are provided to further illustrate this disclosure and form part of the specification. They are used together with the following detailed description to explain this disclosure, but do not constitute a limitation thereof. Detailed Implementation

[0034] The following describes in further detail a self-powered monitoring system and method for roadway surrounding rock deformation according to the present invention, in conjunction with the accompanying drawings and specific embodiments. It should be understood that these embodiments are only for illustration and explanation of the present invention, and the scope of protection of the present invention is not limited thereto.

[0035] Example 1 (Integration of piezoelectric-mesh composite support structure and realization of piezoelectric sensing function)

[0036] like Figure 1-2 As shown, the piezoelectric-mesh composite support structure of this embodiment integrates support and sensing functions. Its core structure lies in the mechanical coupling and integrated composite of the support anchor mesh substrate 1 and the piezoelectric sensing unit 2. The support anchor mesh substrate 1 is woven from low-alloy high-strength steel wire to form a stable mechanical load-bearing frame. Its mesh size is designed according to the actual conditions of the roadway to ensure effective support for the surrounding rock. The piezoelectric sensing unit 2 uses a flexible polyvinylidene fluoride piezoelectric film as the sensing medium, ensuring it can meet the energy conversion requirements of small deformations, possesses good elongation to ensure no brittle fracture occurs when the anchor mesh deforms, and withstands the high humidity environment underground. The piezoelectric sensing unit 2 is embedded in the support anchor mesh substrate 1 in a mesh-like form, and the two are tightly combined through a special composite process. During the anchor mesh weaving process, the film is embedded at the intersection of the metal wires, and then a hot-pressing process is used to firmly bond the film and the metal wires, realizing the integrated structure of the piezoelectric sensing unit 2 and the support anchor mesh substrate 1. This structure enables the piezoelectric sensing unit 2 to generate mechanical deformation synchronously with the anchor mesh when the surrounding rock deforms and causes the anchor mesh to vibrate, and to efficiently convert mechanical energy into electrical signals based on the piezoelectric effect.

[0037] Based on the positive piezoelectric effect of piezoelectric materials, the linear piezoelectric equation D = d·T + ε is satisfied. T ·E, where D is the electric displacement, d is the piezoelectric constant matrix, T is the stress, and ε TLet be the dielectric constant under constant stress, and E be the external electric field strength. In this invention, the piezoelectric sensing unit is designed using a thin-film material, considering only the stress and electric field in the thickness direction (i.e., the three directions). Furthermore, since there is no external electric field in the application scenario of this invention, i.e., E³ = 0, it simplifies to a one-dimensional equation: D³ = d 33 •T3. When the surrounding rock deformation causes radial displacement of the anchor mesh (such as convergence of the roadway sides or roof subsidence), the deformation of the anchor mesh will generate a unidirectional pressure F transmitted to the surrounding rock along the thickness direction of the embedded piezoelectric film, resulting in synchronous mechanical deformation, satisfying d. 33 The working principle of a piezoelectric element, namely the longitudinal piezoelectric effect, is as follows: Figure 3 As shown in the figure, P represents the polarization direction. The stress it bears is T3 = F / A (F is the stress transmitted by the anchor mesh, and A is the contact area of ​​the membrane). Also, D3 = ε0·ε r ·E ' 3(ε0 is the vacuum permittivity, taken as 8.85 × 10⁻⁶) -12 F / m, ε r E is the relative permittivity of the piezoelectric element. ' 3 represents the electric field strength generated inside the thin film, and the output voltage U = E ' 3·t (where t is the thickness of the piezoelectric element). Combining the above equations, we can obtain the formula for the output voltage of the piezoelectric film under the compressive stress of the surrounding rock: Furthermore, the magnitude of the surrounding rock stress can be deduced from the output voltage value. (Where t = t0 + Δt, t0 is the initial thickness of the piezoelectric element, and Δt is the deformation in the thickness direction).

[0038] Furthermore, according to d 33 The constitutive equation for a piezoelectric element, relating the stress (σ3) in the thickness direction to the output charge (Q), is: Q = F·d 33 =σ3·A·d 33 stress (Here, E is the elastic modulus of the piezoelectric film, ε3 is the strain along the thickness direction, Δt is the deformation along the thickness direction, and t0 is the initial thickness.) Combining these equations, we can obtain...

[0039] Treating the piezoelectric film as a capacitor element, its output charge (where t = t0 + Δt), combining these equations, we can obtain: The equation can be rearranged into a quadratic equation in terms of Δt: d 33 ·E·Δt 2 +d 33 ·E·t0·Δt-ε0·ε r ·t0·U=0, based on the quadratic formula, we can obtain Since the compression of the surrounding rock will reduce the film thickness, it is required that Δt < 0 and d33 Since the value is negative, the final result is the negative root.

[0040] Specifically, in the piezoelectric-mesh composite support structure proposed in this invention, the radial deformation of the surrounding rock is transmitted to the piezoelectric film through the mechanical transmission of the anchor mesh. However, the actual deformation (D) of the surrounding rock and the thickness deformation (Δt) of the piezoelectric film are not directly equivalent. Factors such as the elastic deformation of the anchor mesh and the bonding strength between the piezoelectric film and the anchor mesh result in a "transmission loss" with a fixed linear proportional relationship between the two. To accurately quantify this transmission relationship, a mechanical transmission coefficient k is introduced as a comparison index, defined as the ratio of the radial displacement deformation of the surrounding rock to the thickness deformation of the piezoelectric film, i.e., D = k·|Δt|. The value of k is determined by the physical characteristics of the composite structure, including the stiffness of the anchor mesh material, the composite process of the piezoelectric film and the anchor mesh, the mesh size, and the deformation rate of the surrounding rock. It needs to be calibrated through a mechanical simulation roadway surrounding rock loading experiment matched with the roadway support parameters. Specifically, the calibration method for the mechanical transmission coefficient k proposed in this invention will be described in detail in Example 2 below. After introducing parameter k, the actual deformation (D) of the surrounding rock can be obtained by inversely calculating the thickness deformation (Δt) of the piezoelectric film, providing a quantitative basis for subsequent algorithms related to the classification of surrounding rock deformation and early warning decision-making.

[0041] Furthermore, when the surrounding rock vibrates and displaces, causing the anchor mesh to vibrate, the piezoelectric film and the anchor mesh undergo synchronous mechanical deformation. Ignoring the minor errors caused by the elastic delay in the mechanical response between materials, the mechanical vibration frequency of the piezoelectric film is completely consistent with the vibration frequency of the anchor mesh, and thus also consistent with the vibration frequency of the surrounding rock, i.e., f0. 机械 =f 锚网 =f 围岩 f 机械 Let f be the mechanical vibration frequency of the piezoelectric film. Simultaneously, based on the physical characteristics of the piezoelectric effect, the periodic deformation of the mechanical vibration will be converted into a completely synchronous alternating electrical signal through the piezoelectric effect, i.e., f0. 机械 =f 电 The analog-to-digital conversion module of the data processing unit described in this invention directly acquires the frequency f of the alternating electrical signal output by the piezoelectric sensing unit. 电 That is, the vibration frequency of the surrounding rock, which can be used as a supplement to the monitoring of surrounding rock deformation to evaluate the degree of disturbance to the surrounding rock. Together with the actual deformation D of the surrounding rock calculated above, they can be used as the classification index of the monitoring and early warning system.

[0042] Example 2 (Experimental calibration method for the mechanical transmission coefficient k)

[0043] In particular, the calibration method for the mechanical transmission coefficient k proposed in this invention is as follows:

[0044] Step 1: Prepare an anchor mesh-piezoelectric film composite sample with the same structure as in the actual application scenario. The material specifications, mesh size and composite process of the anchor mesh and piezoelectric film are the same as those described in Example 1.

[0045] Step 2: Fix the composite sample on the hydraulic servo simulation loading test bench. The loading direction is perpendicular to the surface of the anchor mesh and consistent with the radial direction of the roadway to simulate the radial displacement of the surrounding rock. The loading range can cover 0-50mm or larger to match the actual deformation range of the roadway surrounding rock as closely as possible. The loading conditions can be divided into pre-loading and graded loading. During pre-loading, a 5mm pre-displacement is applied to the composite structure sample to simulate the stress state of the surrounding rock after the initial support of the roadway, eliminate the gap between the surrounding rock and the anchor mesh, and ensure the accuracy of subsequent measurements. During graded loading, a 1mm loading interval can be used, with radial displacement increasing stepwise from 5mm to 30mm to simulate the displacement range of the surrounding rock from slight to moderate to severe deformation.

[0046] Step 3: After each loading stage stabilizes, use a high-precision displacement sensor to monitor the displacement deformation D of the simulated surrounding rock, and use a laser thickness gauge to accurately measure and record the thickness deformation Δt of the piezoelectric film.

[0047] Step 4: Analyze the results of multiple sets of loaded data (≥30 sets) using statistical methods to obtain the final calibrated proportional coefficient k. The analysis method and specific steps are as follows.

[0048] Because experimental data may be affected by noise from measuring instruments (such as sensor accuracy errors) and interference from accidental factors (such as minor vibrations of the loading device), directly calculating k using the arithmetic mean would introduce errors. To make the calibration of the mechanical transmission coefficient k more scientific and reduce errors, this invention does not simply use the arithmetic mean of the data results as the final calibrated k value. Instead, it uses statistical methods to process the calibration experimental data. First, the data is preprocessed to check and remove outliers. Then, based on statistical principles and combined with regression analysis, a quantitative relationship between "tunnel surrounding rock deformation and piezoelectric film thickness change" is established. Finally, the optimal estimate and error range of the proportionality coefficient k are determined, thereby improving the reliability of k. The specific analysis steps are as follows:

[0049] 1) Data preprocessing: For the collected n sets of experimental data (D i ,|Δt i |), where D i Let |Δt| represent the simulated deformation of the i-th group of surrounding rock. i | represents the absolute value of the piezoelectric film thickness deformation for the corresponding group. Outliers are identified and removed using a box plot method. First, calculate k. i =D i / |Δt i|, (i = 1, 2, …, n), and arrange k i in ascending order to obtain an ordered array k (1) ≤ k (2) ≤ … ≤ k (n) ; then calculate the quartile positions, is the position of the lower quartile Q1, is the position of the upper quartile Q3 (if the position is non-integer, the quartile value is calculated using linear interpolation: if pos1 = a + b, a is the integer part, 0 < b < 1, then Q1 = k (a) + b·(k (a+1) - k (a) ), if pos3 = c + d, c is the integer part, 0 < d < 1), then Q3 = k (c) + d·(k (c+1) - k (c) )); secondly, set the outlier determination criterion: (k i < Q1 - 1.5(IQR)) or (k i > Q3 + 1.5(IQR)) (IQR = Q3 - Q1 is the interquartile range); finally, draw a box plot, and after removing all k i outliers that meet the above conditions, retain the remaining experimental data as the valid data set (it is recommended that the valid sample size n ≥ 30 to ensure the significance of the statistical results).

[0050] 2) Linear regression analysis: Perform least squares linear regression analysis on the valid data samples obtained in the first step to establish a linear regression model of D = k·|Δt| + ε (ε is the random error), and solve for the optimal k by minimizing the sum of squared residuals ∑(D i - k·|Δt i |) 2 : where is the optimal estimate of the regression coefficient k, which takes into account the overall trend of all data and can better reflect the true mechanical transfer relationship among the surrounding rock, anchor mesh, and piezoelectric film than the arithmetic mean.

[0051] 3) Error quantification: To clarify the reliability, calculate its 95% confidence interval: is the t-distribution quantile with degrees of freedom n - 2 (α = 0.05), and the error size is reflected by the interval width. The smaller the calculated interval, the smaller the error and the more reliable the result.

[0052] 4) Verification and correction: Use the coefficient of determination R 2 to verify the goodness of fit of the regression model: When R 2When the value is ≥0.95 (indicating that the model can explain more than 95% of the data variation), it is determined that... If the result is valid, supplement the experimental data or adjust the loading conditions, and repeat the above steps until the goodness-of-fit requirement is met.

[0053] The above statistical analysis method can be used to obtain a reasonable mechanical transmission coefficient calibration value k that takes into account both the overall trend of the data and the error characteristics. Finally, the actual deformation D of the surrounding rock at the anchor mesh where the corresponding piezoelectric film is located can be obtained by converting D=k·|Δt|.

[0054] Example 3 (Verification of the self-powered model of the energy management unit)

[0055] This embodiment focuses on the overall process and working principle of stable power supply and energy storage for the energy management unit. For example... Figure 5 As shown, the energy management unit 3 is connected to the piezoelectric sensing unit 2, and its internal components include a rectifier and voltage regulator circuit 301 and an energy storage element 302. The rectifier and voltage regulator circuit 301 uses a full-bridge rectifier chip and a low-dropout regulator, which can quickly and stably convert the unstable AC power generated by the piezoelectric sensing unit 2 into DC power. The energy storage element 302 can be a high-capacity supercapacitor to efficiently store the converted electrical energy, providing a continuous and stable power supply for the entire monitoring system. The core function of the energy management unit 3 is to efficiently convert the mechanical energy generated by the deformation and vibration of the surrounding rock into electrical energy, and then store and output it after rectification and voltage regulation. The energy utilization efficiency at each stage of this process and whether it can achieve a self-powered and stable power supply for the monitoring and early warning system should be verified and optimized through model calculations. Its energy transfer process and related analysis are as follows.

[0056] 1) Full-process efficiency model of energy conversion and storage: The total energy transfer and utilization process of energy management unit 3 should cover three key links: piezoelectric conversion, rectification and voltage regulation, and energy storage. Therefore, the total energy utilization efficiency η 总 The calculation formula is: η 总 =η1·η2·η3·100%.

[0057] Where η1 is the piezoelectric conversion efficiency, which is the efficiency of the piezoelectric sensing unit in converting mechanical vibration energy into alternating current, defined as the ratio of output AC power to input mechanical power: (P ac,out To output AC power, i.e., the AC power generated by the vibration of the piezoelectric film, U ac and I ac These are the output AC voltage and AC current, respectively; P mech,in The input mechanical power, i.e., the mechanical power transmitted from the surrounding rock vibration deformation to the piezoelectric film through the anchor mesh, is given by F, where F is the normal force transmitted by the anchor mesh, v is the vibration velocity of the piezoelectric film, σ is the magnitude of the transmitted stress, A is the effective contact area, and f is the tensile strength. 机械 The vibration frequency is determined by the frequency f of the output alternating electrical signal.电 Value, A 振 (This refers to the vibration amplitude of the piezoelectric thin film).

[0058] η2 is the rectification and voltage regulation efficiency, i.e. Figure 4 The efficiency of the rectifier and voltage regulator integrated circuit 301 in converting alternating current (AC) into stable direct current (DC) is defined as the ratio of the stable output DC power to the input AC power. (P dc,reg U represents the DC power output after rectification and regulation, i.e., the operating power of the entire circuit. w I represents the operating voltage of each unit. dc To stabilize the DC current; P ac,in The input AC power of the rectifier and voltage regulator circuit is equal to the output AC power P of the piezoelectric converter. ac,out That is, P ac,in =P ac,out ).

[0059] η3 is the energy storage efficiency of the energy storage element, i.e. Figure 4 The energy utilization efficiency of the 302 supercapacitor during charging and discharging is defined as the ratio of the effective energy released during discharging to the energy received during charging. It is calculated by real-time integration of the power curve using the trapezoidal rule. (E dis To ensure the effective energy released during discharge, DC voltage and current sensors are deployed in the discharge circuit, and a high-precision timer is built into the circuit. At a set sampling time interval ΔT, such as 0.1s, n sets of voltage and current sample values ​​are recorded. dis,1 ,I dis,1 ), (U dis,2 ,I dis,2 ), (U dis,3 ,I dis,3 ), ..., (U dis,n ,I dis,n ), U dis,i I dis,i P represents the discharge voltage and discharge current obtained from the i-th sampling, respectively. dis,i E represents the discharge power of the i-th sample; ch The energy received for charging is also recorded in the charging circuit through DC voltage and current sensors, with m sets of voltage and current sample values ​​recorded at the same sampling time interval ΔT. (U ch,1 ,I ch,1 ), (U ch,2 ,I ch,2 ), (U ch,3 ,I ch,3 ), ..., (U ch,m ,I ch,m ), U ch,j I ch,iP represents the charging voltage and charging current obtained from the i-th sampling, respectively. ch,j (The charging power of the j-th sample).

[0060] Calculating the energy utilization efficiency of each stage is crucial for optimizing system component design, assessing the controllability of energy utilization and loss, and guiding hardware selection. For example, if the piezoelectric conversion efficiency η1 is too low, especially in scenarios with weak vibration in the surrounding rock of a mine, it is necessary to prioritize optimizing the piezoelectric material, such as replacing it with a piezoelectric ceramic with a higher piezoelectric coefficient, adjusting the composite process, or the installation structure. If the efficiency of other stages is also low, it is necessary to adjust and select a more efficient system deployment optimization scheme. This will not be elaborated on in detail here. Any system hardware changes or replacements made due to efficiency issues should fall within the scope of protection of this invention.

[0061] 2) Energy Matching Calculation Verification for Stable Power Supply: The key to whether Energy Management Unit 3 can achieve stable self-powered supply lies in two points: first, verifying the margin of real-time power supply; and second, verifying the fallback effect of energy storage discharge. To confirm whether the system input power, i.e., the direct power supplied by the piezoelectric converter, can cover the current load power at any given time, a power margin comparison is used here, because the operating voltage U of the rectified system... w Since the current margin is constant, the power margin is equivalent to the current margin, which is the piezoelectric direct supply current I at the rectifier output terminal, monitored in real time. dc and the system load current I at the load end load Verification: I dc ≥I load (If the load current fluctuates frequently, the maximum load current, i.e., the peak current, can be taken as I during the design phase.) load (To ensure coverage of extreme operating conditions), if the conditions are met, the energy is directly supplied via piezoelectric conversion, and the excess current is used to charge the energy storage element; if the conditions are not met, the second step of verification is performed to determine the real-time discharge voltage U of the energy storage element. stor Is it higher than the minimum operating voltage U? min If the conditions are met, the system can continue discharging as a safety net, the load will operate normally, and the system will be stable. Otherwise, a low-energy warning will be triggered, requiring manual adjustments, such as optimizing piezoelectric materials or circuit components to reduce system power consumption. To prevent the system from failing to meet the first-step startup condition, the energy storage components should be pre-charged with a basic charge at the factory or during maintenance to ensure basic discharge capacity during startup. Additionally, load components should be started in stages (core components first, then expansion components), and the microcontroller should support low-power operating modes to lower the startup power threshold and reduce energy consumption to achieve a closed-loop system.

[0062] Example 4 (Implementation of two-dimensional threshold linkage hierarchical early warning by data processing unit)

[0063] like Figure 6As shown, the data processing unit 4 is based on a low-power microcontroller and undertakes the intelligent judgment and early warning function of the surrounding rock deformation state. Its core logic is to achieve hierarchical early warning by linking the actual deformation of the surrounding rock D (associated electrical signal amplitude) and the vibration frequency f (associated electrical signal frequency) with a two-dimensional threshold, combined with a self-learning decision tree algorithm.

[0064] This unit digitizes the piezoelectric conversion load-side electrical signal through an analog-to-digital conversion module, extracting the alternating electrical signal frequency (corresponding to the surrounding rock vibration frequency f) and the electrical signal amplitude U (which is then used to infer the actual deformation of the surrounding rock, D). Based on the synergistic relationship between deformation reflecting cumulative deformation and vibration frequency reflecting the degree of disturbance, a two-dimensional hierarchical model is constructed using a decision tree algorithm to classify surrounding rock deformation into three levels: "mild deformation," "moderate deformation," and "severe deformation." The specific judgment logic is implemented through the following steps: ① Collect multiple sets of historical monitoring data from the roadway, including the actual deformation of the surrounding rock, D, vibration frequency f, and manually labeled deformation level (mild / moderate / severe); ② Using D and f as input features, construct a decision tree using the ID3 algorithm and calculate their information gain; ③ Based on the principle of maximizing information gain, recursively divide the nodes and determine the two-dimensional thresholds, such as f≤5Hz, D≤5mm → mild deformation, D>5mm → moderate deformation (this is only an example and not a reliable reference). Based on this, an error learning module can be added to achieve dynamic adjustment and correction based on environmental errors. For example, when considering the influence of temperature on the piezoelectric constant, the internally stored piezoelectric constant temperature calibration curve can be called to correct the D value.

[0065] Furthermore, the decision tree algorithm is embedded in the microcontroller using C language, employing an array to store node thresholds and decision rules, occupying ≤512KB of memory, and the time taken for a single decision process (including data acquisition, correction calculation, and rule matching) is ≤100ms. When the two-dimensional parameters match a certain level of deformation rule, the microcontroller immediately generates a warning signal of the corresponding level (e.g., mild → yellow, moderate → blue, severe → red), and sends it to the ground monitoring terminal 6 after encoding via the wireless communication module 5. A self-updating mechanism can also be added for practical application scenarios, such as automatically calling recent monitoring data (including manually reviewed deformation levels) weekly, recalculating information gain, and optimizing node partitioning to ensure long-term adaptation of the hierarchical model to actual working conditions.

[0066] This embodiment overcomes the limitations of single-parameter early warning by using a two-dimensional parameter linkage and self-correcting decision tree algorithm. At the same time, through an environmental error learning mechanism, the classification accuracy gradually improves over time, meeting the accuracy and reliability requirements of monitoring surrounding rock deformation in complex downhole environments.

[0067] Example 5 (Overall Application of the Self-Powered Monitoring System for Roadway Surrounding Rock Deformation)

[0068] like Figure 5-6As shown, this embodiment demonstrates the overall deployment and application of a self-powered monitoring system for roadway surrounding rock deformation in a roadway. During the roadway construction phase, the piezoelectric-mesh composite support structure described in Embodiment 1 is laid along the roadway axis according to the principle of "transversely covering the entire cross-section of the roadway and longitudinally overlapping without gaps." Each ring of support structure covers the roadway roof and both sides, with the mesh edges of adjacent piezoelectric sensing units 2 overlapping. The spacing between adjacent rings is determined according to the roadway span, ensuring comprehensive coverage monitoring of the roadway surrounding rock. Simultaneously, anchoring to the surrounding rock with anchor bolts ensures that the piezoelectric sensing units 2 are tightly attached to the surface of the surrounding rock, minimizing stress transmission loss. In addition, each ring of support structure is divided into four areas (roof area, left side area, and right side area) along the circumference of the roadway. The piezoelectric sensing units 2 in each area are interconnected internally through flexible conductive rubber strips. Along the roadway axis, each three rings of support structure are divided into one monitoring unit group. The rings in the group are connected by metal crimp terminals to form the total energy or signal output terminal of the unit group. An integrated interface is set up to collect the alternating signals (i.e., the amplitude D and frequency f of the electrical signal) in the area into a single composite signal output, and to collect the AC power generated in the area into the total energy output of the unit group through a diode array.

[0069] Furthermore, at regular intervals along the centerline of the tunnel roof, a combined module of the energy management unit 3 and data processing unit 4 as described in Embodiments 2 and 3 is installed. The module is encapsulated in an explosion-proof shell and fixed to a pre-fabricated groove in the roof using expansion bolts. The input end of the combined module is equipped with a multi-channel interface board, which connects to multiple monitoring unit groups via waterproof and dustproof lines such as double-sheathed shielded cables.

[0070] When the system is running, if the surrounding rock of the roadway deforms or vibrates, the piezoelectric sensing unit 2 in the piezoelectric-mesh composite support structure deforms synchronously with the anchor mesh, converting mechanical energy into electrical energy based on the piezoelectric effect. The energy management unit 3 collects the electrical energy, rectifies and stabilizes it before storing it to power the system. The data processing unit 4 analyzes the electrical signals, and if the frequency and amplitude exceed the preset two-dimensional thresholds, it generates a warning signal of the corresponding level (e.g., yellow warning indicates slight deformation, blue warning indicates moderate deformation, and red warning indicates severe deformation), and transmits the warning signal to the ground monitoring terminal 6 through the wireless communication module 5. The ground monitoring terminal 6 displays the status of the surrounding rock of the roadway in an intuitive graphical interface. Based on the warning signal level, staff can take timely safety measures such as strengthening inspections, reinforcing supports, and evacuating personnel, realizing real-time monitoring and proactive control of roadway surrounding rock deformation.

[0071] This system, through the integrated support and monitoring design of piezoelectric materials and anchor mesh substrate, combined with self-powered technology and intelligent analysis algorithms, effectively solves the problems of power supply and monitoring blind spots of traditional monitoring methods, improves the reliability and timeliness of safety monitoring in deep roadways, and realizes the function of preliminary early warning of surrounding rock deformation.

[0072] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A self-powered monitoring system for deformation of surrounding rock in roadways, characterized in that, include: The piezoelectric-mesh composite support structure includes a support anchor mesh matrix (for roadway support) and a piezoelectric sensing unit (embedded or integrated in the support anchor mesh matrix in a mesh pattern, capable of converting anchor mesh vibration into electrical signals); An energy management unit, connected to the piezoelectric sensing unit, is used to collect and store the electrical energy generated by the piezoelectric sensing unit; The data processing unit, connected to the energy management unit, is used to analyze the frequency and amplitude of the electrical signal and generate an early warning signal based on the analysis results.

2. The tunnel surrounding rock self-powered deformation monitoring system according to claim 1, characterized in that, In the piezoelectric-mesh composite support structure, the piezoelectric sensing unit and the support anchor mesh matrix form an integrated structure. When the surrounding rock deforms and causes the anchor mesh to vibrate, the piezoelectric sensing unit and the anchor mesh synchronously generate mechanical deformation, thereby converting mechanical energy into electrical signals.

3. The tunnel surrounding rock self-powered deformation monitoring system according to claim 1, characterized in that, The energy management unit includes a rectifier and voltage regulator circuit and an energy storage element. The rectifier and voltage regulator circuit converts the AC power generated by the piezoelectric sensing unit into DC power, and the energy storage element stores the converted DC power to power the data processing unit.

4. The tunnel surrounding rock self-powered deformation monitoring system according to claim 1, characterized in that, The data processing unit has a built-in low-power microcontroller that can analyze the frequency and amplitude of electrical signals and generate graded early warning signals based on a preset frequency-deformation (calculated and converted from electrical signal amplitude) two-dimensional threshold linkage logic.

5. A method for monitoring self-powered deformation of surrounding rock in roadways, characterized in that, Includes the following steps: Installation steps: Lay the piezoelectric-mesh composite support structure along the entire cross section of the roadway, with the edges of adjacent structural meshes overlapping. Anchor bolts are used to ensure that the piezoelectric sensing unit is tightly attached to the surrounding rock. Energy management units and data processing units are installed at certain intervals on the roadway roof. Signal acquisition steps: When the deformation of the surrounding rock causes the anchor mesh to deform, the piezoelectric sensing unit synchronously generates an alternating electrical signal. The signal frequency is consistent with the vibration frequency of the surrounding rock, and the signal amplitude is used to inversely calculate the deformation of the surrounding rock using the piezoelectric effect formula. Energy harvesting steps: The energy management unit collects the energy of the electrical signal, and the AC power generated by the piezoelectric conversion is rectified and regulated to be converted into DC power for real-time power supply. Excess energy is stored in the supercapacitor energy storage element. Data analysis steps: The data processing unit analyzes the frequency and amplitude of the electrical signal and calls the decision tree algorithm to compare the analysis results with a preset two-dimensional threshold. Warning procedure: When the frequency of the electrical signal exceeds a preset two-dimensional threshold, the data processing unit generates a corresponding warning signal and sends it to an external terminal through a wireless communication module.

6. The method for monitoring self-powered deformation of roadway surrounding rock according to claim 5, characterized in that, The data analysis step also includes environmental correction, which involves calibrating the piezoelectric constant based on temperature sensor data and combining the calculated value of deformation to correct for energy storage efficiency fluctuations, in order to reduce monitoring errors.

7. The method for monitoring self-powered deformation of roadway surrounding rock according to claim 5, characterized in that, In the data analysis step, the decision tree algorithm updates itself weekly using monitoring data, re-optimizes the threshold division, and adapts to the dynamic changes in the deformation characteristics of the surrounding rock.

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