Intelligent monitoring device and evaluation system for long-term performance of a filling body in a downhole environment

Abstract

The present application belongs to the field of mine filling engineering and safety monitoring, and relates to an intelligent monitoring device and evaluation system for long-term performance of filling body in underground environment. The intelligent monitoring device comprises a packaging sheath, a sleeve, a sensor array, a signal conditioning circuit, a computing unit and a power supply module; the packaging sheath and the sleeve are made of titanium alloy material, the inner wall of the sleeve is coated with a silicon dioxide nano coating, which significantly improves the long-term service ability of the device; the sensor array comprises a solid-state ion selective electrode, an acoustic emission sensor array and an integrated wet temperature sensor; the device uses the signals obtained by the sensor array, and through a coupling algorithm of chemical corrosion rate and cumulative acoustic emission energy, the residual bearing capacity decay coefficient of the filling body is calculated in real time, and the result is transmitted to the monitoring server wirelessly for safety performance evaluation of the filling body; the evaluation result is more comprehensive, intuitive and timely, and provides a high-reliability and high-precision technical means for stability evaluation of filling body in green mining.

Description

Technical Field

[0001] This invention relates to the field of mine backfilling engineering and safety monitoring, specifically to an intelligent monitoring device and evaluation system for the long-term performance of backfill bodies in the underground environment. Background Technology

[0002] In mining engineering, especially in the field of "green mining," the backfilling method has become a key technology for treating underground goaf areas and controlling surface subsidence due to its ability to improve resource recovery rates. The main technical method involves injecting a backfill material formed by mixing cementing materials with solid waste such as slag into the underground space of the mine shaft to provide necessary support for the surrounding rock. With the increasing mining depth in modern mining engineering, the underground environment where the backfill material is located has become more complex. Its mechanical stability during long-term underground support is easily affected by the combined influence of underground stress distribution, groundwater infiltration, and erosion from various chemical components in the mine. The mechanical stability of the backfill material directly relates to the structural safety of the entire mining area, and consequently affects the safety of mining production.

[0003] Therefore, monitoring the long-term performance of backfill in the underground environment has become an essential part of modern mining engineering. By implementing necessary monitoring methods, relevant performance data of the backfill can be obtained, and then systematic model comparison or quantitative analysis can be carried out to evaluate the degree of damage to the backfill, determine whether it still has a safe bearing capacity, and thus prevent mine disaster risks caused by backfill instability.

[0004] Current technologies for monitoring and evaluating the performance of filling bodies mostly rely on core drilling or embedding traditional electronic strain gauges within the filling body. However, core drilling only monitors a localized portion of the filling body, resulting in incomplete data acquisition. Furthermore, the process inevitably disrupts the integrity of the filling body structure, making it unsuitable for long-term or frequent use. Additionally, laboratory testing of the cored samples is required to obtain evaluation conclusions, leading to significant time lag. Traditional electronic strain gauges, on the other hand, operate in complex chemical environments, where high concentrations of chloride ions or strong acidic chemicals can easily cause passivation of the electrodes or corrosion of the circuitry, resulting in severely distorted data and affecting evaluation results.

[0005] Furthermore, the existing technologies for monitoring the performance of backfill materials primarily focus on analyzing their physical and mechanical properties. They lack a mechanism to effectively correlate the erosion process of backfill materials with their mechanical properties in the complex chemical composition of the mining environment. This results in monitoring data that fails to comprehensively reflect the long-term performance evolution of backfill materials under the coupled effects of multiple factors, and thus cannot provide accurate scientific evidence for performance evaluation. Therefore, there is an urgent need in this field for a device and evaluation system capable of long-term performance monitoring of backfill materials in complex underground environments. This system would comprehensively address the problems of incomplete monitoring methods, easily distorted data, delayed evaluation results, and the inability to fully and effectively evaluate the performance of backfill materials in existing technologies. Summary of the Invention

[0006] To address the problem of monitoring and evaluating packing materials in the downhole environment in the prior art, this invention provides an intelligent monitoring device and evaluation system for the long-term performance of packing materials in the downhole environment.

[0007] Specifically, the intelligent monitoring device includes: The encapsulation sleeve, serving as the main mechanical load-bearing component of the monitoring device, is hollow inside, with micropores integrated into the outer wall to allow the pore fluid of the filling material to pass through, as well as a threaded anchoring structure for engaging with the filling slurry. The sleeve is fixed inside the encapsulation sleeve, sealed at both ends, and the inner wall is uniformly coated with a silicon dioxide nano-coating by plasma spraying process. The encapsulation sleeve and tubing are both made of titanium alloy, with a yield strength between 850 MPa and 920 MPa. The sensor array includes a solid-state ion-selective electrode unit disposed at the end of the sleeve, a piezoelectric ceramic acoustic emission sensor disposed inside the sleeve, and an integrated humidity and temperature sensor. The solid-state ion-selective electrode is used to acquire the chemical potential signal within the filler body. Its sensing end extends out of the end of the sleeve and is located in the cavity between the sleeve and the encapsulation sheath, and the extended part is sealed. The piezoelectric ceramic acoustic emission sensor is used to capture the stress wave signal generated by the development of microcracks inside the filler body. The integrated humidity and temperature sensor is used to sense temperature fluctuations within the filler body, thereby correcting the chemical potential signal output by the solid-state ion-selective electrode. The signal conditioning circuit, connected to the sensor array and disposed inside the sleeve, includes a high input impedance operational amplifier and a filter, used to perform impedance amplification and noise filtering on the weak electrical signal output by the sensor. The calculation unit, located inside the casing, is connected to the output of the signal conditioning circuit and is equipped with a coupling algorithm for real-time operation of the remaining bearing capacity of the filling material. This algorithm is used to calculate the attenuation coefficient of the remaining bearing capacity of the filling material based on the chemical and stress wave signals transmitted by the sensor array. The power supply module, located inside the bushing, is used to power the intelligent monitoring device.

[0008] Furthermore, the outer shape of the encapsulation sleeve is designed as a spindle shape with sharp ends and a rounded middle, the threaded anchoring structure is set in the middle of the encapsulation sleeve, and the micropores are set at both ends of the encapsulation sleeve.

[0009] Furthermore, the solid-state ion-selective electrode unit includes a sulfate ion-selective electrode and a pH measuring electrode. The sensing end of the sulfate ion-selective electrode uses a lanthanum fluoride single-crystal film as a sensing layer to obtain information on the sulfate ion concentration in the filling material. The sensing end of the pH measuring electrode uses an iridium oxide thin film as a sensing layer to obtain information on the acidity or alkalinity in the filling material and to screen the effectiveness of sulfate ion concentration in corrosion detection. The sensing layer of the solid-state ion-selective electrode unit is located in the cavity between the sleeve and the encapsulation sheath, and a fluororubber sealing ring is provided at the end of the sensing end of the solid-state ion-selective electrode unit that extends out of the sleeve.

[0010] Furthermore, the input impedance of the operational amplifier in the signal conditioning circuit is greater than 10Ω. 12 The filter is a third-order Butterworth low-pass filter composed of precision resistors and capacitors, with a cutoff frequency set to 1kHz. The signal conditioning circuit also has a built-in automatic gain control module, which is used to dynamically adjust the signal amplification factor according to the real-time output amplitude of the piezoelectric ceramic acoustic emission sensor.

[0011] Furthermore, the coupling algorithm built into the computing unit includes: Chemical signal extraction stage; A sulfate ion selective electrode collects the sulfate ion potential signal in the pore water of the filling material, and a temperature sensor senses the real-time temperature inside the filling material at the same sampling frequency. Both signals are processed by a signal conditioning circuit and then transmitted to the computing unit. The computing unit pre-stores the Nernst equation, corrects the potential signal for temperature, and converts it into the average molar concentration of sulfate ions [SO4] within the sampling interval ΔT. 2- Next, the erosion effectiveness is screened by combining the pH value measured by the pH measuring electrode. If the pH is between 8 and 12, then [SO4] 2- [This represents the effective sulfate ion concentration, used for subsequent chemical erosion rate calculations; otherwise, the data is simply recorded.] Stress wave signal extraction stage; The vibration of the ceramic sheet caused by the elastic stress wave in the microcracks inside the filling body is sensed by the piezoelectric ceramic acoustic emission sensor and converted into a continuous voltage fluctuation signal. After being processed by the signal conditioning circuit, the effective voltage fluctuation signal above 1kHz is retained and transmitted to the computing unit. The stages of calculating chemical erosion rates and defining acoustic emission energy; Calculate the chemical erosion rate Where N is the sliding window length, representing the data acquired by the same intelligent monitoring device at different sampling intervals within a preset time window length, [SO4] 2- ] i This represents the effective molar concentration of sulfate ions at a given sampling interval, [SO4]. 2- ] i-1 This indicates the effective molar concentration of sulfate ions in the previous sampling interval; For voltage fluctuation signals, the computing unit has a built-in db4 wavelet packet decomposition program to decompose the preprocessed voltage fluctuation signals into narrow sub-bands with multiple frequency band characteristics. The reconstructed time-domain voltage signal sequence in the frequency band range of 100kHz to 500kHz is extracted and converted into instantaneous energy through electrical energy relationship. Then, according to the calculation period synchronized with the chemical erosion rate, all effective instantaneous energies are summed to obtain the cumulative acoustic emission energy E. The calculation stage of the attenuation coefficient of the remaining bearing capacity of the filling body; The R and E values ​​are normalized and converted into deterioration ratio values ​​R1 and E1 ranging from 0 to 1: R1 = min(R / R0, 1), E1 = min(E / E0, 1), where R0 and E0 are the limit chemical erosion rate and limit stress damage energy that the backfill can withstand to maintain safe and stable performance, respectively, which are calibrated by design calculations before the backfill is constructed. Then, the residual bearing capacity attenuation coefficient η of the backfill is calculated according to η = 1 - (α·R1 + β·E1), where α and β are material constants calibrated in advance according to the backfill material ratio, used to balance the contribution rate of chemical erosion and mechanical load on the strength attenuation of the backfill. The value rules are: α + β ≈ 1. When the backfill has low cohesion and the cement-sand ratio is small, such as below 1:2, the influence of chemical erosion is small, and β is taken as 0.5 to 0.6, α as 0.4 to 0.5; when the cement-sand ratio is greater than 1:2, α is taken as 0.5 to 0.6, β as 0.4 to 0.5.

[0012] Furthermore, the space between the piezoelectric ceramic acoustic emission sensor and the inner wall of the sleeve is filled with acoustic coupling adhesive, which has acoustic impedance characteristics that match the titanium alloy material and the piezoelectric ceramic.

[0013] Furthermore, the power supply module of the intelligent monitoring device uses a lithium thionyl chloride battery, and the computing unit has a built-in multi-level deep sleep mechanism.

[0014] Furthermore, after obtaining the bearing capacity attenuation coefficient η, in order to achieve remote data transmission and performance evaluation of the filling body, this invention also constructs a performance evaluation system, including multiple intelligent monitoring devices deployed inside the underground filling body, wireless relay nodes deployed in the underground roadways, and a monitoring server located on the surface. The intelligent monitoring devices and the monitoring server integrate wireless transmission modules that can communicate with the wireless relay nodes, for transmitting or receiving data packets and system instructions containing the attenuation coefficient η, raw sensor data, and intelligent monitoring device identification codes; the monitoring server runs visualization evaluation software with a three-dimensional view of the filling stope.

[0015] Furthermore, the wireless relay node conducts wireless communication through sub-gigahertz spread spectrum communication technology, and the wireless transmission module adopts a daisy-chain networking protocol or a star topology, with a transmission power of not less than 20dBm and an effective transmission distance of not less than 500m in the underground roadway environment.

[0016] Furthermore, the process of evaluating the safety performance of the filling material includes: Data transmission stage: After completing the calculation of the attenuation coefficient η of the remaining bearing capacity of the filling body, the calculation unit automatically transmits the data packet containing η and the original sensor data, as well as the identification code of the corresponding intelligent monitoring device, through the wireless transmission module after encryption, and finally transmits it to the monitoring server via the wireless relay node; Data identification stage: After the monitoring server receives the data packet, the visualization evaluation software runs automatically and marks the received η value according to the identification code of the intelligent monitoring device in the three-dimensional view to mark the corresponding intelligent monitoring device position. Performance evaluation phase: When η > 1.2G / F, the system determines that the performance of the filling body is in a safe state, and the corresponding position is marked in green in the 3D view; when G / F < η ≤ 1.2G / F, the system determines that the performance of the filling body has significantly decreased and is in a state of insufficient safety, and the corresponding position is marked in yellow in the 3D view, and an early warning command is issued to control the intelligent monitoring device to shorten the sampling interval and closely monitor the filling body; when η ≤ G / F, the system determines that the filling body has a risk of sudden change in bearing capacity and is in a dangerous state, and the corresponding position is marked in red in the 3D view, and an audible and visual alarm is issued, and an evacuation command is issued to the underground workers; where F is the design bearing capacity of the filling body; G is the ground stress load, which is calculated and calibrated before the construction of the filling body, and represents the total stress exerted by the underground rock mass on the filling body.

[0017] Compared with the prior art, the beneficial effects of this invention are as follows: 1. This invention provides physical protection for the device through an alkali-resistant titanium alloy encapsulation sleeve and casing, combined with a silica nano-coating applied to the casing to resist chemical corrosion from the filling material. This significantly improves the survivability of the monitoring device in the extreme underground environment of mining areas. Under experimental conditions, the intelligent monitoring device of this invention can operate stably in simulated mine water environments rich in strong acid or alkali ions, with an effective service life of no less than 3 years. This solves the technical problem of traditional electronic sensors failing due to corrosion in the early stages of service, providing an effective solution for long-term performance monitoring of filling materials in underground environments.

[0018] 2. Unlike traditional monitoring methods that rely on single-dimensional strain or humidity monitoring, this invention uses a coupled algorithm based on the chemical erosion rate R and cumulative acoustic emission energy E to quantify the combined impact of chemical dissolution and physical damage accumulation on the bearing capacity of the backfill. By fusing data from both chemical and physical dimensions, the attenuation coefficient η is calculated in real time within the computational unit of the intelligent monitoring device. This directly transforms complex stress wave and chemical potential signals into safety indicators with clear engineering significance, enabling real-time safety status evaluation of the backfill. Compared to traditional single-monitoring methods or core drilling, this invention provides a more comprehensive, intuitive, and timely demonstration of the backfill's safety performance. It offers a highly reliable and precise technical means for assessing the stability of backfill in green mining operations in deep mines, possessing significant engineering value and social benefits for improving mine safety production levels. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention.

[0020] Figure 1 This is a cross-sectional view of an intelligent monitoring device for the long-term performance of filling materials in a downhole environment according to the present invention. Figure 2 This is a schematic diagram of the encapsulation sheath of an intelligent monitoring device for the long-term performance of filling material in a downhole environment according to the present invention; Figure 3 This is a flowchart of a coupling algorithm in an intelligent monitoring device for the long-term performance of filling material in a downhole environment according to the present invention. Figure 4 This is a schematic diagram of the overall architecture of a long-term performance evaluation system for a filling body in a downhole environment according to the present invention.

[0021] In the attached diagram: 1. Encapsulation sleeve; 11. Micropore; 12. Threaded anchoring structure; 2. Sleeve; 3. Piezoelectric ceramic acoustic emission sensor; 4. Integrated humidity and temperature sensor; 5. Sulfate ion selective electrode; 6. pH measuring electrode; 7. Signal conditioning circuit; 8. Calculation unit; 9. Power supply module. Detailed Implementation

[0022] The technical solution of the present invention will now be described with reference to the accompanying drawings. However, the described embodiments are only some embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0023] It should be noted that in the description of this invention, the terms "upper," "lower," "inner," "outer," etc., indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings; this is merely for ease of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention.

[0024] The accompanying drawings show schematic diagrams of structures according to embodiments disclosed in this invention. These drawings are not to scale, and some details may be enlarged or omitted for illustrative purposes.

[0025] like Figure 1-4 In one specific embodiment of the present invention shown, it is necessary to monitor the stability of the backfill material in the goaf of a deep mine. A smart monitoring device and evaluation system for the long-term performance of the backfill material in the underground environment is used. The device and system intelligently coordinate several steps, including sensing and processing the relevant physical and chemical parameters of the backfill material underground, transmitting the data to the evaluation system for safety status evaluation and early warning of the backfill material, so as to realize the full-cycle performance monitoring and evaluation of the backfill material from the time the backfill material enters the mining area until its service end.

[0026] Specifically, such as Figure 1 As shown, the intelligent monitoring device includes an encapsulation sleeve 1, a tube 2 fixed inside the encapsulation sleeve 1, and a sensor array, a signal conditioning circuit 7, a computing unit 8, and a power supply module 9 arranged sequentially on the tube 2.

[0027] The encapsulation sleeve 1 serves as the main mechanical load-bearing component of the monitoring device. It is hollow internally, and its outer wall is integrally machined with micropores 2 and threaded anchoring structures 12. The sleeve 2 is sealed at both ends, and its inner wall is uniformly coated with a silicon dioxide nano-coating with a thickness of approximately 500 nm using a plasma spraying process. Considering the requirements for durability, both the encapsulation sleeve 1 and the sleeve 2 are made of high-strength and highly corrosion-resistant titanium alloys (such as TC4 titanium alloy) modified through a precision heat treatment process. The yield strength of the finished titanium alloy can reach between 850 MPa and 920 MPa.

[0028] The sensor array is used to acquire and monitor the physical and chemical parameters inside the filling material. Specifically, the sensor array includes a solid-state ion-selective electrode unit disposed at the end of the sleeve 2, a piezoelectric ceramic acoustic emission sensor 3 disposed inside the sleeve 2, and an integrated humidity and temperature sensor 4. The solid-state ion-selective electrode unit is the core of chemical parameter monitoring, including a sulfate ion-selective electrode 5 and a pH measuring electrode 6. The sensing end of the sulfate ion-selective electrode 5 uses a lanthanum fluoride single crystal film as the sensing layer, and the sensing end of the pH measuring electrode 6 uses an iridium oxide thin film as the sensing layer. The sensing end of the solid-state ion-selective electrode unit extends out of the end of the sleeve 2 and is located in the cavity between the sleeve 2 and the encapsulation sheath 1, so that the sensing layer can contact the pore liquid of the filling material passing through the micropores 2 on the encapsulation sheath 1. The protruding position of the solid-state ion-selective electrode unit at the end of the sleeve 2 is sealed. In this embodiment, a fluororubber sealing ring is used to tightly adhere to the protruding part to prevent the pore liquid from seeping into the inside of the sleeve 2 and damaging the circuit components. The piezoelectric ceramic acoustic emission sensor 3 is used to capture weak acoustic emission signals generated by cracking of cement hydration products inside the filling body or slippage of the aggregate interface of the filling body; the integrated humidity and temperature sensor 4 is used to sense temperature fluctuations inside the filling body. Since the output potential of the solid ion selective electrode is significantly affected by temperature fluctuations, the influence of temperature fluctuations can be corrected by the temperature value fed back in real time by the integrated humidity and temperature sensor 4, thereby ensuring the absolute accuracy of ion concentration measurement.

[0029] In terms of circuit and data processing, the signal conditioning circuit 7 includes a high input impedance operational amplifier and a filter for preprocessing the weak electrical signal output by the sensor, including impedance amplification and noise filtering. The output of the signal conditioning circuit 7 is connected to the computing unit 8. The core hardware of the computing unit 8 is a high-performance microprocessor based on a 32-bit RISC architecture with a main frequency of up to 400MHz. It is equipped with a coupled evaluation algorithm for the remaining bearing capacity of the infill body running in real time. After receiving the signal preprocessed by the signal conditioning circuit 7, it can calculate the attenuation coefficient η of the remaining bearing capacity of the infill body according to the coupling relationship between the chemical erosion rate and the accumulated acoustic emission energy.

[0030] To improve the data sensing accuracy of intelligent monitoring devices in filling bodies, such as Figure 2As shown, the outer shape of the encapsulation sleeve 1 is designed as a spindle shape with sharp ends and a rounded middle, conforming to hydrodynamic characteristics. The threaded anchoring structure 12 is located in the middle of the encapsulation sleeve 1, and the micropores 2 are located at both ends of the encapsulation sleeve 1. During the filling slurry injection stage, its high-speed flow state can easily generate a large area of ​​turbulence around the intelligent monitoring device. The spindle-shaped design of the encapsulation sleeve 1 helps to ensure that the device is tightly surrounded by the filling body. Compared with other shapes, it can avoid the generation of local voids around the device, thereby ensuring that the stress state of the filling body is truly transmitted to the intelligent monitoring device. The position of the micropores also further improves the contact between the sensing layer of the solid-state ion selective electrode and the pore liquid of the filling body.

[0031] In the specific implementation process, when the filling slurry is injected into the mining area and gradually solidifies and undergoes volume shrinkage, the titanium alloy encapsulation sleeve 1 and casing 2 can effectively resist the complex stress generated by the slurry's own weight and pumping pressure during the initial stage of filling in deep mines. The spiral anchoring structure on the encapsulation sleeve 1 can form a mechanical interlocking engagement with the filling body, thereby stably fixing itself within the filling body without displacement, ensuring that the minute strain, displacement, and vibration energy inside the filling body are transmitted to the sensor array on the casing 2 without damage; specifically in this embodiment, the thread tooth depth of the threaded anchoring structure 12 of the encapsulation sleeve 1 is not less than 2mm to ensure that the thread has sufficient contact surface with the filling slurry and provides sufficient physical anchoring engagement.

[0032] Regarding chemical protection of the device, the silica nano-coating on the casing 2 in this embodiment has an amorphous, non-crystalline structure with a porosity of less than 0.5%, presenting as a continuous and dense ion diffusion barrier layer. Since highly corrosive hydroxide ions, sulfate ions, and chloride ions in the downhole water environment can penetrate into the pores of the packing material during long-term service, the silica nano-coating can isolate these highly corrosive ions in the pore liquid at the molecular scale, preventing them from penetrating into the casing 2, thereby protecting the internal sensing array or other electronic components. It should be noted that the solid-state ion-selective electrode unit is located at the end of the casing 2. The sensing layer of the electrode unit is in contact with the cavity between the casing 2 and the encapsulation sleeve 1, ensuring that the sensing layer is in contact with the pore liquid entering the device through the micropores 2 on the encapsulation sleeve 1, thus achieving the purpose of chemical parameter sensing.

[0033] With the physical protection of the titanium alloy and the chemical protection of the silica nano-coating, this device can be used for long-term monitoring of filling bodies in complex underground mining environments.

[0034] Regarding sensor data acquisition and transmission, the input impedance of the operational amplifier in the signal conditioning circuit 7 is designed to be greater than 10Ω. 12The impedance is set to Ω to match the extremely high output impedance of the solid-state ion-selective electrode unit, preventing measurement errors. The sensor output signal, after impedance amplification, passes through a third-order Butterworth low-pass filter. This filter consists of high-precision, low-temperature drift resistors and capacitors, with a cutoff frequency set to 1kHz, used to filter out high-frequency power frequency interference and spatial radio frequency noise induced by the complex electromagnetic environment downhole. Furthermore, the signal conditioning circuit 7 includes an automatic gain control (AGC) module. This module monitors the output amplitude of the piezoelectric ceramic acoustic emission sensor 3 in real time. When the filling material enters the accelerated damage stage and generates a high-energy acoustic emission signal, the AGC module can quickly reduce the gain to prevent signal saturation distortion; while in the initial stage of microcrack initiation in the filling material, it automatically increases the gain to capture subtle signals.

[0035] Furthermore, to ensure the continuity of sound wave transmission, a sound-conducting coupling adhesive is filled between the piezoelectric ceramic acoustic emission sensor 3 and the inner wall of the sleeve 2. This sound-conducting coupling adhesive has acoustic impedance characteristics that match those of the titanium alloy and the piezoelectric ceramic. In this embodiment, the sound-conducting coupling adhesive is a modified epoxy resin sound-conducting adhesive. In addition to fixing the position of the piezoelectric ceramic acoustic emission sensor 3, it can also maintain the same sound-conducting characteristics as the titanium alloy and the piezoelectric ceramic, and maintain extremely high capture sensitivity for weak acoustic emission signals generated by cracking of cement hydration products or slippage of aggregate interfaces inside the filling body.

[0036] Specifically, the coupled evaluation algorithm for the attenuation coefficient η of the remaining bearing capacity of the fill material built into the calculation unit 8 includes the following: Chemical signal extraction stage; A solid-state ion-selective electrode acquires the sulfate ion potential signal in the pore fluid of the filling body at a sampling frequency of 10 Hz. Simultaneously, a temperature sensor detects the real-time temperature inside the filling body at the same sampling frequency. Both signals are processed by the signal conditioning circuit 7 and transmitted to the computing unit 8. The computing unit 8 calibrates the chemical parameters according to the relationship between the potential signal and ion concentration using the pre-stored Nernst equation, and dynamically corrects the slope term in the Nernst equation based on the temperature data, converting the potential signal into the molar concentration of sulfate ions [SO4] within the sampling interval ΔT. 2- In this embodiment, ΔT is taken as 1 hour, which means that all potential signals sampled by the sensor within 1 hour are integrated into an average molar concentration of sulfate ions for that period of time; then, the pH value measured by pH measuring electrode 6 is used for effective screening of corrosion. If pH = 8 to 12, then [SO4 2-The effective sulfate ion concentration is used for subsequent chemical erosion rate calculations. This is because within this pH range, the hydroxide ion concentration in the pore fluid of the filling material is relatively high, which, together with sulfate ions, will have a synergistic erosive effect on cement hydration products in the filling material, such as calcium hydroxide and calcium silicate hydrate. If the pH value is outside this range, the current chemical erosion conditions are considered weak, and the effective erosion rate is not included in the calculation. Otherwise, only the data is recorded. Stress wave signal extraction stage; When the microcracks inside the filling material crack or slip, elastic stress waves are released. Since the intelligent monitoring device of the present invention is firmly attached to the filling material, the stress waves are transmitted through the encapsulation sleeve and tube to the piezoelectric ceramic acoustic emission sensor 3, which causes mechanical vibration of the ceramic sheet. Due to the piezoelectric effect, the vibration is converted into a continuous voltage fluctuation signal and transmitted to the signal conditioning circuit 7. After being processed by the signal conditioning circuit 7, an effective voltage fluctuation signal of more than 1 kHz is retained and transmitted to the computing unit 8. The stages of calculating chemical erosion rates and defining acoustic emission energy; Using the obtained molar concentration of sulfate ions [SO4] 2- Calculate the chemical erosion rate Where N is the sliding window length, representing continuous data acquired by the same intelligent monitoring device at different sampling intervals within a certain pre-set time window length. In this embodiment, N=10, indicating that the chemical erosion rate is calculated using the sulfate ion molar concentration data at each sampling interval within a continuous 10-hour period. [SO4] 2- ] i This represents the measured effective molar concentration of sulfate ions at a given sampling interval, [SO4]. 2- ] i-1 This indicates the effective molar concentration of sulfate ions in the previous sampling interval; For voltage fluctuation signals, the 24-bit high-precision analog-to-digital converter (ADC) built into the computing unit 8 samples the preprocessed voltage fluctuation signals at a sampling rate of not less than 1MHz, first converting them into discrete digital voltage sequences; then, the db4 wavelet packet decomposition program is executed to decompose the digital voltage sequence into narrow sub-bands with multiple frequency band characteristics, and the sequence in the frequency band range of 100kHz to 500kHz is extracted to obtain the reconstructed time-domain voltage signal sequence v. This frequency band is the core frequency band for acoustic emission signals generated by the cracking of cement hydration products in the filling body and the slippage of the aggregate interface; since the essence of acoustic emission energy is the energy accumulation of the voltage signal in the time dimension, the computing unit 8 then converts the reconstructed time-domain voltage signal sequence v into the instantaneous energy e of each sampled data based on the electrical energy formula, e=v² / R·t, where R is the equivalent load resistance of the signal conditioning circuit 7, which is preset by the hardware design before the equipment leaves the factory, and t is the sampling period, which is 1 / 1MHz in this example. Finally, according to the calculation period synchronized with the chemical erosion rate, i.e. 1 hour in this embodiment, the instantaneous energy of all effective samples within this time period is summed to obtain the cumulative acoustic emission energy E. This parameter characterizes the elastic energy release intensity caused by the accumulation of microscopic damage inside the filling body within the corresponding sampling interval, i.e. the degree of mechanical damage accumulation of the filling body. The calculation stage of the attenuation coefficient of the remaining bearing capacity of the filling body; The larger the values ​​of R and E, the greater the chemical corrosion and stress damage. The obtained R and E values ​​are normalized, and the ratios of the chemical corrosion limit rate R0 and the stress damage limit energy E0 are converted into degradation ratio values ​​R1 and E1 ranging from 0 to 1. Specifically: R1 = min(R / R0, 1), E1 = min(E / E0, 1). The chemical corrosion limit rate R0 and the stress damage limit energy E0 are determined by the design life and failure threshold of the infill material during the design phase before infill construction, and represent the limits that the infill material can withstand to maintain safe and stable performance. The chemical erosion rate or ultimate stress damage energy is then calculated; subsequently, the residual bearing capacity attenuation coefficient η = 1 - (α·R1 + β·E1) is calculated, where α and β are material constants pre-calibrated based on the backfill material ratio, such as the cement-sand ratio and aggregate particle size distribution, used to balance the contribution rate of chemical erosion and mechanical load on the strength attenuation of the backfill. α + β ≈ 1, and their values ​​follow the following rules: when the backfill has poor cohesion and the cement-sand ratio is small, such as below 1:2, the influence of chemical erosion is small, and β = 0.5 to 0.6 and α = 0.4 to 0.5 are taken; when the cement-sand ratio is greater than 1:2, α = 0.5 to 0.6 and β = 0.4 to 0.5 are taken. In one test scenario of this implementation case, destructive tests were conducted on standard test blocks of filling bodies with different cement-sand ratios. Combined with the synchronously collected R and E values, the least squares method was used to fit and determine α and β. For example, for ordinary Portland cement filling material with a cement-sand ratio of 1:4, the value of α was determined to be 0.45 and the value of β was determined to be 0.55.

[0037] The bearing capacity attenuation coefficient η in the engineering of backfill is the ratio of the remaining bearing capacity of the backfill to its design bearing capacity. The greater the chemical erosion rate R or the cumulative acoustic emission energy E, the more serious the damage to the performance of the backfill. This is reflected in the smaller η, which indicates that the bearing capacity of the backfill is attenuated compared to the design value, and the more dangerous the performance of the backfill.

[0038] After obtaining the bearing capacity attenuation coefficient η, in order to achieve remote data transmission and performance evaluation of the filling body, this invention also constructs a performance evaluation system, including multiple intelligent monitoring devices deployed inside the underground filling body, wireless relay nodes deployed in the underground roadways, and a monitoring server located on the surface. The intelligent monitoring devices and the monitoring server integrate wireless transmission modules capable of communicating with the wireless relay nodes, used to transmit or receive data packets containing the attenuation coefficient η, raw sensor data, and intelligent monitoring device identification codes; the monitoring server runs visualization evaluation software with a three-dimensional view of the filling stope. The specific working process of the safety performance evaluation system is as follows: Data transmission phase: The wireless relay node conducts wireless communication through sub-GHz spread spectrum communication technology. The wireless transmission module adopts a daisy-chain networking protocol or a star topology, with a transmission power of not less than 20dBm and an effective transmission distance of not less than 500m in the underground roadway environment. After calculating the attenuation coefficient η of the remaining bearing capacity of the filling body, the calculation unit 8 automatically transmits the data packet containing η and the original sensor data, as well as the identification code of the corresponding intelligent monitoring device, after encryption through the wireless transmission module. The data packet is then transmitted to the monitoring server via the wireless relay node. Data identification stage: After the monitoring server receives the data packet, the visualization evaluation software runs automatically and marks the received η value in the three-dimensional view according to the identification code of the intelligent monitoring device, indicating the location of each intelligent monitoring device. Performance evaluation phase: When designing the bearing capacity of backfill, a safety redundancy is usually considered, and the design bearing capacity F is taken as 1.2 to 1.5 times the actual ground stress load G. The ground stress load G represents the total stress exerted by the underground rock mass on the backfill. The design survey and calculation are performed before the backfill is constructed. During this stage, the visualization evaluation software evaluates the safety status of the filling body based on the η value: when η > 1.2G / F, it indicates that the remaining bearing capacity of the filling body still meets the design bearing capacity level, and the system determines that the performance of the filling body is in a safe state, marked in green in the 3D view; when G / F < η ≤ 1.2G / F, the system determines that the performance of the filling body has significantly decreased and is in a state of insufficient safety, but the remaining bearing capacity can still withstand the total stress of the underground rock mass, marked in yellow in the 3D view, and issues an early warning command to control the intelligent monitoring device to shorten the sampling interval and closely monitor the filling body; when η ≤ G / F, the system determines that the remaining bearing capacity of the filling body cannot withstand the total stress of the underground rock mass, and there is a risk of sudden instability, in a dangerous state, marked in red in the 3D view, and issues an audible and visual alarm, issuing an evacuation command to the underground workers.

[0039] The specific implementation process of this invention is as follows: Before pouring the backfill in the mining area, construction personnel select stress-sensitive areas within the backfill and determine their three-dimensional coordinates based on the mining area's geometry and geological stress distribution characteristics. The intelligent monitoring device is then positioned according to these three-dimensional coordinates, fixed to the stress-sensitive area using a support frame, and activated. Next, backfill grout is poured in. The grout coats the spiral anchoring structure on the outer surface of the monitoring device, forming a tight physical coating during the setting process. The intelligent monitoring device is then fixed in its current position to begin monitoring. During the backfill grout setting stage, initial curing period, strength development period, and long-term service, the intelligent monitoring device can continuously and in real-time capture the physical and chemical field parameters inside the backfill. The coupled evaluation algorithm, performed by the aforementioned calculation unit 8, calculates the remaining bearing capacity attenuation coefficient of the backfill in real-time and wirelessly transmits it to a ground-based monitoring server. The monitoring server runs a safety performance evaluation program to assess the safety of the remaining bearing capacity attenuation coefficient of the backfill and issues corresponding instructions promptly.

[0040] Furthermore, the power supply module 9 of the intelligent monitoring device uses a high-energy-density lithium thionyl chloride (Li-SOCl2) battery, which has a higher rated battery capacity for the same volume. The computing unit 8 has a built-in multi-level deep sleep mechanism. The cooperation between the power supply module 9 and the sleep mechanism ensures that the power consumption of the device is controlled below 10μA during non-collection periods. Based on the sampling interval of 1 hour in this embodiment and the frequency of performing 24 complete data acquisition and fusion operations per day, the theoretical battery life of the device can exceed 36 months. This ensures long-term monitoring of the filling body during its long-term service in the mining area.

[0041] The above constitutes the intelligent monitoring device and evaluation system for the long-term performance of the filling material in the underground environment according to the present invention. Throughout the monitoring cycle, the intelligent monitoring device continuously works in collaboration with the evaluation system, forming a complete closed loop from data acquisition, processing and analysis to safety early warning. The alkali-resistant titanium alloy encapsulation sleeve 1 of the intelligent monitoring device, combined with the design of a nano-coating, solves the problem of sensor survival in extreme environments; its calculation based on the coupling of chemical and physical stress indicators solves the problem of the disconnect between monitoring data and the chemical erosion effects of the complex underground environment; and through the collaboration of the monitoring device and the evaluation system, a comprehensive understanding of the full life-cycle performance of the filling material can be achieved, enabling the early detection of potential instability risks, buying valuable time for the prevention and control of mine disasters, realizing real-time and intelligent management of mine safety, ensuring that the present invention provides accurate safety decision support for the green mining field of deep mines, and effectively guaranteeing the safety and continuity of mining production.

[0042] It should be noted that the above-disclosed embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Those skilled in the art can understand that implementing all or part of the above-described embodiments and making equivalent changes in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A smart monitoring device for the long-term performance of filling materials in a downhole environment, characterized in that, include: The encapsulation sleeve, which serves as the main mechanical load-bearing component of the monitoring device, is hollow inside and has micropores on the outer wall that allow the pore fluid of the filling material to pass through, as well as a threaded anchoring structure for engaging with the filling material slurry. The sleeve is fixed inside the encapsulation sleeve, sealed at both ends, and the inner wall is uniformly coated with a silicon dioxide nano-coating by plasma spraying process. The encapsulation sleeve and tubing are both made of titanium alloy, with a yield strength between 850 MPa and 920 MPa. The sensor array includes a solid-state ion-selective electrode unit disposed at the end of the sleeve, a piezoelectric ceramic acoustic emission sensor disposed inside the sleeve, and an integrated humidity and temperature sensor. The solid-state ion-selective electrode is used to acquire the chemical potential signal within the filler body. Its sensing end extends out of the end of the sleeve and is located in the cavity between the sleeve and the encapsulation sheath, and the extended part is sealed. The piezoelectric ceramic acoustic emission sensor is used to capture the stress wave signal generated by the development of microcracks inside the filler body. The integrated humidity and temperature sensor is used to sense temperature fluctuations within the filler body, thereby correcting the chemical potential signal output by the solid-state ion-selective electrode. The signal conditioning circuit, connected to the sensor array and disposed inside the sleeve, includes a high input impedance operational amplifier and a filter, used to perform impedance amplification and noise filtering on the weak electrical signal output by the sensor. The calculation unit, located inside the casing, is connected to the output of the signal conditioning circuit and is equipped with a coupling algorithm for real-time operation of the remaining bearing capacity of the filling material. This algorithm is used to calculate the attenuation coefficient of the remaining bearing capacity of the filling material based on the chemical and stress wave signals transmitted by the sensor array. The power supply module, located inside the bushing, is used to power the intelligent monitoring device.

2. The intelligent monitoring device for long-term performance of filling material in downhole environment according to claim 1, characterized in that, The outer shape of the encapsulation sleeve is designed as a spindle shape with sharp ends and a rounded middle. The threaded anchoring structure is set in the middle of the encapsulation sleeve, and the micropores are set at both ends of the encapsulation sleeve.

3. The intelligent monitoring device for long-term performance of filling material in downhole environment according to claim 2, characterized in that, The solid-state ion-selective electrode unit includes a sulfate ion-selective electrode and a pH measuring electrode. The sensing end of the sulfate ion-selective electrode uses a lanthanum fluoride single-crystal film as the sensing layer to obtain information on the sulfate ion concentration in the filling material. The sensing end of the pH measuring electrode uses an iridium oxide thin film as the sensing layer to obtain information on the acidity and alkalinity in the filling material and to screen the effectiveness of sulfate ion concentration in corrosion detection. A fluororubber sealing ring is provided at the end of the sleeve protruding from the sensing end of the solid-state ion-selective electrode unit.

4. The intelligent monitoring device for long-term performance of filling material in downhole environment according to claim 1, characterized in that, The input impedance of the operational amplifier in the signal conditioning circuit is greater than 10. 12 The filter is a third-order Butterworth low-pass filter composed of precision resistors and capacitors, with a cutoff frequency set to 1kHz. The signal conditioning circuit also has a built-in automatic gain control module, which is used to dynamically adjust the signal amplification factor according to the real-time output amplitude of the piezoelectric ceramic acoustic emission sensor.

5. The intelligent monitoring device for long-term performance of filling material in downhole environment according to claim 3, characterized in that, The coupling algorithm built into the computing unit includes: Chemical signal extraction stage; A sulfate ion selective electrode collects the sulfate ion potential signal in the pore water of the filling material, and a temperature sensor senses the real-time temperature inside the filling material at the same sampling frequency. Both signals are processed by a signal conditioning circuit and then transmitted to the computing unit. The computing unit pre-stores the Nernst equation, corrects the potential signal for temperature, and converts it into the average molar concentration of sulfate ions [SO4] within the sampling interval ΔT. 2- Next, the erosion effectiveness is screened by combining the pH value measured by the pH measuring electrode. If the pH is between 8 and 12, then [SO4] 2- [This represents the effective sulfate ion concentration, used for subsequent chemical erosion rate calculations; otherwise, the data is simply recorded.] Stress wave signal extraction stage; The vibration of the ceramic sheet caused by the elastic stress wave in the microcracks inside the filling body is sensed by the piezoelectric ceramic acoustic emission sensor and converted into a continuous voltage fluctuation signal. After being processed by the signal conditioning circuit, the effective voltage fluctuation signal above 1kHz is retained and transmitted to the computing unit. The stages of calculating chemical erosion rates and defining acoustic emission energy; Calculate the chemical erosion rate Where N is the sliding window length, representing the data acquired by the same intelligent monitoring device at different sampling intervals within a preset time window length, [SO4] 2- ] i This represents the effective molar concentration of sulfate ions at a given sampling interval, [SO4] 2- ] i-1 This indicates the effective molar concentration of sulfate ions in the previous sampling interval; For voltage fluctuation signals, the computing unit has a built-in db4 wavelet packet decomposition program to decompose the preprocessed voltage fluctuation signals into narrow sub-bands with multiple frequency band characteristics. The reconstructed time-domain voltage signal sequence in the frequency band range of 100kHz to 500kHz is extracted and converted into instantaneous energy through electrical energy relationship. Then, according to the calculation period synchronized with the chemical erosion rate, all effective instantaneous energies are summed to obtain the cumulative acoustic emission energy E. The calculation stage of the attenuation coefficient of the remaining bearing capacity of the filling body; The R and E values ​​are normalized and converted into deterioration ratio values ​​R1 and E1 ranging from 0 to 1: R1 = min(R / R0, 1), E1 = min(E / E0, 1), where R0 and E0 are the limit chemical erosion rate and limit stress damage energy that the backfill can withstand to maintain safe and stable performance, respectively, which are calibrated by design calculations before the backfill is constructed. Then, the residual bearing capacity attenuation coefficient η of the backfill is calculated according to η = 1 - (α·R1 + β·E1), where α and β are material constants calibrated in advance according to the backfill material ratio, used to balance the contribution rate of chemical erosion and mechanical load on the strength attenuation of the backfill. The value rules are: α + β ≈ 1. When the backfill has low cohesion and the cement-sand ratio is small, such as below 1:2, the influence of chemical erosion is small, and β is taken as 0.5 to 0.6, α as 0.4 to 0.5; when the cement-sand ratio is greater than 1:2, α is taken as 0.5 to 0.6, β as 0.4 to 0.

5.

6. The intelligent monitoring device for long-term performance of filling material in downhole environment according to claim 1, characterized in that, The space between the piezoelectric ceramic acoustic emission sensor and the inner wall of the sleeve is filled with acoustic coupling adhesive, which has acoustic impedance characteristics that match the titanium alloy material and the piezoelectric ceramic.

7. The intelligent monitoring device for long-term performance of filling material in downhole environment according to claim 1, characterized in that, The power supply module of the intelligent monitoring device uses a lithium thionyl chloride battery, and the computing unit has a built-in multi-level deep sleep mechanism.

8. A long-term performance evaluation system for the downhole environment of a filling body, constructed based on the intelligent monitoring device described in any one of claims 1-7, wherein the intelligent monitoring device is deployed inside the downhole filling body, characterized in that, It also includes wireless relay nodes deployed in underground roadways and a monitoring server located on the ground. The intelligent monitoring device and the monitoring server integrate a wireless transmission module that can communicate with the wireless relay nodes, and are used to transmit or receive data packets and system instructions containing attenuation coefficient η, raw sensor data and intelligent monitoring device identification code; the monitoring server runs visualization evaluation software with a three-dimensional view of the filling mining area.

9. A long-term performance evaluation system for downhole environments of filling bodies according to claim 8, characterized in that, The wireless relay node conducts wireless communication through sub-gigahertz spread spectrum communication technology. The wireless transmission module adopts a daisy-chain networking protocol or a star topology, with a transmission power of not less than 20dBm and an effective transmission distance of not less than 500m in the underground roadway environment.

10. A long-term performance evaluation system for downhole environments of filling bodies according to claim 9, characterized in that, The process of evaluating the safety performance of filling materials includes: Data transmission stage: After the calculation of the attenuation coefficient η of the remaining bearing capacity of the filling body is completed, the calculation unit automatically transmits the data packet containing η and the original sensor data, as well as the identification code of the corresponding intelligent monitoring device, through the wireless transmission module after encryption, and finally transmits it to the monitoring server via the wireless relay node; Data identification stage: After the monitoring server receives the data packet, the visualization evaluation software runs automatically and marks the received η value according to the identification code of the intelligent monitoring device in the three-dimensional view to mark the corresponding intelligent monitoring device position. Performance evaluation phase: When η > 1.2G / F, the system determines that the performance of the filling body is in a safe state, and the corresponding position is marked in green in the 3D view; when G / F < η ≤ 1.2G / F, the system determines that the performance of the filling body has significantly decreased and is in a state of insufficient safety, and the corresponding position is marked in yellow in the 3D view, and an early warning command is issued to control the intelligent monitoring device to shorten the sampling interval and closely monitor the filling body; when η ≤ G / F, the system determines that the filling body has a risk of sudden change in bearing capacity and is in a dangerous state, and the corresponding position is marked in red in the 3D view, and an audible and visual alarm is issued, and an evacuation command is issued to the underground workers; where F is the design bearing capacity of the filling body; G is the ground stress load, which is calculated and calibrated before the construction of the filling body, and represents the total stress exerted by the underground rock mass on the filling body.

Images