A method for online monitoring of tailings paste filling concentration

Abstract

The present invention relates to the field of monitoring, and in particular to an online monitoring method for tailings paste filling concentration. It includes: collecting acoustic wave signals and microseismic signals, using a frequency feature extraction algorithm to extract features from the collected acoustic wave signals and microseismic signals to obtain frequency features; calculating the comprehensive propagation velocity of the tailings paste by a comprehensive propagation velocity calculation algorithm; using a dynamic density calculation algorithm, combined with the physical properties of the paste particles, to calculate the dynamic density of the tailings paste; by obtaining the dynamic density, solid density and water density of the tailings paste, combined with a concentration correction factor, to calculate the dynamic mass concentration of the tailings paste; using a dynamic concentration fluctuation range monitoring algorithm to monitor the dynamic mass concentration changes of the tailings paste in real time. It solves the technical problem that in the process of tailings paste filling, the existing technology fails to fully consider the influence of various factors such as the particle size of the paste particles and the friction angle, resulting in low accuracy in dynamic density calculation.

Description

Technical Field

[0001] The invention relates to the field of monitoring, and in particular to an online monitoring method for tailings paste filling concentration. Background Art

[0002] Tailings paste filling is a technology that uses tailings (fine-grained waste generated during the mining process) mixed with cementitious materials (such as cement) and water to make a paste material to fill underground goafs. It aims to improve mine safety, reduce environmental pollution, and effectively utilize tailings resources. In the process of tailings paste filling, the concentration of the paste is a key parameter that determines the filling quality and stability. Too high a concentration will lead to poor fluidity, difficulty in pumping, and may even cause pipeline blockage; too low a concentration may lead to insufficient paste strength and inability to effectively support the goaf, thereby affecting the safety of the mine and the recovery rate of resources. Therefore, how to achieve precise control of the paste concentration is the core technical problem in the tailings paste filling system.

[0003] Traditional paste concentration monitoring relies on laboratory sampling and offline analysis. Although it can provide relatively accurate concentration data, its limitations are obvious. Offline monitoring cannot reflect changes in paste concentration in real time. It is necessary to wait until the sample analysis is completed before adjusting the process parameters, which may cause unnecessary fluctuations or quality problems in the tailings paste filling process. In addition, laboratory sampling requires downtime, which not only increases manpower and time costs, but may also affect the continuity and efficiency of production.

[0004] With the expansion of mining production scale and the increasing requirements for environmental protection and comprehensive resource utilization, tailings paste filling technology is gradually developing towards automation and intelligence. The introduction of online monitoring methods for tailings paste filling concentration has become an important way to promote the advancement of paste filling technology. Compared with traditional offline monitoring methods, online monitoring can achieve real-time and continuity of data, and significantly improve the stability and reliability of tailings paste filling.

[0005] However, the existing online monitoring methods for tailings paste filling concentration have the following technical problems: the existing tailings paste filling monitoring methods rely on fixed parameters or limited sensor types, and cannot reflect the dynamic physical state of the tailings paste in real time and comprehensively, resulting in large fluctuations in the concentration of the tailings paste during the filling process, and cannot be adjusted in time, which easily leads to uneven filling effects or abnormal physical properties; the calculation of the propagation velocity of the tailings paste is often based only on the single feature of the acoustic signal or the microseismic signal, ignoring the composite effect of the signal and the influence of the complex physical state, resulting in low accuracy and reliability in the propagation velocity calculation, making it difficult to accurately reflect the tailings paste concentration in the actual filling process. The propagation speed during the process; in the process of tailings paste filling, the existing technical means fail to fully consider the influence of various factors such as paste particle size and friction angle, resulting in low accuracy in dynamic density calculation. At the same time, the calculation of dynamic mass concentration also lacks a full description of the actual dynamic state, making it difficult to accurately evaluate the thickness and flow characteristics of the tailings paste; the existing monitoring methods mostly use simple concentration measurement, which cannot track the upper and lower limits of concentration fluctuations in real time and dynamically, especially under complex filling conditions. The amplitude and frequency of concentration fluctuations often have nonlinear and periodic changes, making concentration control inaccurate, which may lead to poor fluidity or uneven filling of the tailings paste. Summary of the invention

[0006] In order to solve the technical problems described in the background technology section, the present invention provides an online monitoring method for tailings paste filling concentration.

[0007] The present invention provides an online monitoring method for tailings paste filling concentration, which specifically includes the following technical solutions:

[0008] A method for online monitoring of tailings paste filling concentration comprises the following steps:

[0009] S1: Real-time acquisition of acoustic wave signals and microseismic signals, and the use of frequency feature extraction algorithms to extract features from the acquired acoustic wave signals and microseismic signals to obtain frequency features; based on the frequency features, the comprehensive propagation velocity of the tailings paste is calculated using a comprehensive propagation velocity calculation algorithm;

[0010] S2: According to the comprehensive propagation speed of the tailings paste, the dynamic density calculation algorithm is used, combined with the physical properties of the paste particles, to calculate the dynamic density of the tailings paste; by obtaining the dynamic density, solid density and water density of the tailings paste, combined with the concentration correction factor, the dynamic mass concentration of the tailings paste is calculated;

[0011] S3: Use the dynamic concentration fluctuation range monitoring algorithm to monitor the dynamic mass concentration changes of the tailings paste in real time and provide the fluctuation range of the tailings paste concentration.

[0012] Preferably, the S1 specifically includes:

[0013] The frequency feature extraction algorithm squares the collected acoustic wave signals and microseismic signals and then sums them, and extracts the frequency features inside the tailings paste through Fourier transform. The Fourier transform uses a sine basis function to decompose the acoustic wave signals and microseismic signals and calculates the contribution of each frequency component.

[0014] Preferably, the S1 specifically includes:

[0015] The frequency feature extraction formula is:

[0016]

[0017] in, Indicates frequency characteristics; Indicates time from arrive Perform integration; Indicates The acoustic wave sensor The sound wave signals collected at all times; Indicates Microseismic sensors in Microseismic signals collected at all times; and represent the square of acoustic wave signal and microseismic signal respectively; It means to sum the squares of the acoustic wave signals collected by all acoustic wave sensors. represents the number of acoustic wave sensors in the acoustic wave sensor array; It means to sum the squares of the microseismic signals collected by all microseismic sensors. represents the number of microseismic sensors in the microseismic sensor array; represents the sine basis function used for Fourier transform; Indicates that in the cycle The phase of the inner sine wave; Indicates the time period of signal acquisition.

[0018] Preferably, the S1 specifically includes:

[0019] The comprehensive propagation velocity calculation algorithm calculates the comprehensive propagation velocity of the tailings paste by combining the frequency characteristics with the total energy of the acoustic signal and the microseismic signal, and uses the coupling correction coefficient to adjust the mapping relationship between the frequency characteristics and the comprehensive propagation velocity of the tailings paste.

[0020] Preferably, the S1 specifically includes:

[0021] The calculation formula for the comprehensive propagation velocity of tailings paste is:

[0022]

[0023] in, It indicates the comprehensive propagation velocity of tailings paste; Indicates frequency characteristics; It means summing the squares of all frequency features; Represents the number of frequency features; represents the coupling correction factor; Represents the total energy of the sound wave signal; Represents the total energy of microseismic signals.

[0024] Preferably, the S2 specifically includes:

[0025] The dynamic density calculation algorithm introduces the cubic and exponential attenuation factors of the comprehensive propagation velocity of the tailings paste, and combines the particle size distribution factor and the friction angle correction term to calculate the dynamic density of the tailings paste. The specific formula is:

[0026]

[0027] in, Indicates the dynamic density of tailings paste; represents the dynamic factor of particle distribution; It indicates the comprehensive propagation velocity of tailings paste; It represents the cube of the comprehensive propagation velocity of tailings paste; represents the exponential decay factor; It is the physical property parameter of tailings paste; represents the particle size distribution factor; represents the friction angle correction term; represents the tangent function; represents a constant term; Indicates the dynamic and static friction angle of paste particles.

[0028] Preferably, the S2 specifically includes:

[0029] The calculation formula for the dynamic mass concentration of tailings paste is:

[0030]

[0031] in, Indicates the dynamic mass concentration of tailings paste; Indicates the dynamic density of tailings paste; Indicates the density of water; Indicates the solid density of tailings paste; represents the concentration correction factor; represents the cosine adjustment term; Indicates the comprehensive propagation velocity of tailings paste.

[0032] Preferably, the S3 specifically includes:

[0033] The dynamic concentration fluctuation range monitoring algorithm calculates the upper and lower limits of concentration fluctuation by combining the fluctuation amplitude factor and the time modulation function, and defines the concentration fluctuation range by the upper and lower limits of the dynamic mass concentration of the tailings paste.

[0034] Preferably, the S3 specifically includes:

[0035] The calculation formula for the concentration fluctuation range is:

[0036]

[0037] in, It indicates the maximum value of concentration fluctuation, i.e. the upper limit of the dynamic mass concentration of tailings paste; It indicates the minimum value of concentration fluctuation, i.e. the lower limit of the dynamic mass concentration of tailings paste; Indicates the dynamic mass concentration of tailings paste; represents the volatility factor; It means that the periodic fluctuation of concentration in time is simulated by a sine function; represents the fluctuation frequency; represents the time modulation function.

[0038] The beneficial effects of the technical solution of the present invention are:

[0039] 1. By arranging an array of acoustic and microseismic sensors, the acoustic and microseismic signals in the tailings paste can be collected in real time. The frequency feature extraction algorithm is used to extract frequency features from the acoustic and microseismic signals. The signals provided by different types of sensors can be integrated to avoid neglecting local information and fully reflect the internal physical state of the tailings paste. The square processing and Fourier transform methods are used to eliminate the negative value effect and extract components of different frequencies, thereby enhancing the energy performance of the signal and accurately reflecting the physical state inside the tailings paste.

[0040] 2. By combining the frequency characteristics with the total energy of the acoustic wave signal and the microseismic signal, the comprehensive propagation velocity calculation algorithm can accurately reflect the propagation characteristics of the tailings paste. The coupling correction coefficient is used to adjust the mapping relationship between the frequency characteristics and the comprehensive propagation velocity of the tailings paste, thereby improving the calculation accuracy of the comprehensive propagation velocity of the tailings paste and adapting to the changes in the propagation velocity during the tailings paste filling process.

[0041] 3. Based on the comprehensive propagation velocity of tailings paste, the dynamic density calculation algorithm combined with the physical properties of paste particles (such as particle size distribution and friction angle) can accurately calculate the dynamic density of tailings paste. The particle size distribution factor and friction angle correction term are introduced to make the calculation of the dynamic density of tailings paste fit the actual physical state of tailings paste and accurately consider the interaction between paste particles.

[0042] 4. The dynamic mass concentration of the tailings paste is calculated using the dynamic density, solid density and water density of the tailings paste, combined with the concentration correction factor. The calculation of the dynamic mass concentration can accurately reflect the thickness of the tailings paste. The introduction of the cosine adjustment term takes into account the concentration fluctuations of the tailings paste under different conditions, further optimizes the calculation of the dynamic mass concentration, and can adapt to the rapid changes in the concentration of the tailings paste, thereby enhancing the accuracy of the tailings paste filling system in controlling the fluidity and concentration of the tailings paste.

[0043] 5. The dynamic concentration fluctuation range monitoring algorithm can accurately calculate the maximum and minimum values ​​of the concentration fluctuation by real-time monitoring of the dynamic mass concentration of the tailings paste. The fluctuation amplitude factor and time modulation function are introduced to adjust the amplitude and frequency of the concentration fluctuation. It can reflect the changing trend of the tailings paste concentration in real time and ensure accurate grasp of the concentration fluctuation. The introduction of the time modulation function enhances the nonlinear characteristics of the concentration fluctuation monitoring, so that the dynamic mass concentration of the tailings paste conforms to the actual dynamic changes and can cope with the concentration fluctuations under different working environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 The present invention provides a flow chart of an online monitoring method for tailings paste filling concentration. DETAILED DESCRIPTION

[0045] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0047] The specific scheme of the method for online monitoring filling concentration of tailings paste provided by the present invention is described in detail below with reference to the accompanying drawings.

[0048] Refer to the attached Figure 1, which shows a flow chart of an online monitoring method for tailings paste filling concentration provided by an embodiment of the present invention, the method comprising the following steps:

[0049] S1. Real-time acquisition of acoustic wave signals and microseismic signals, and extraction of features of the acquired acoustic wave signals and microseismic signals using a frequency feature extraction algorithm to obtain frequency features; based on the frequency features, the comprehensive propagation velocity of the tailings paste is calculated using a comprehensive propagation velocity calculation algorithm;

[0050] An acoustic sensor array is arranged at a designated location of the tailings paste filling pipeline to collect acoustic wave signals in the tailings paste. The collected acoustic wave signals are recorded as , Indicates The acoustic wave sensor The sound wave signals collected at all times, Indicates the number of the acoustic wave sensor, , represents the number of acoustic wave sensors in the acoustic wave sensor array, is a time variable, which is used to represent the acquisition time of the acoustic wave signal and the microseismic signal. At the same time, a microseismic sensor array is arranged to collect the microseismic signals generated by the movement and collision of particles inside the tailings paste. The collected microseismic signals are recorded as , Indicates Microseismic sensors in The microseismic signals collected at all times, Indicates the number of the microseismic sensor. , represents the number of microseismic sensors in the microseismic sensor array;

[0051] The frequency feature extraction algorithm is used to extract the features of the collected acoustic wave signals and microseismic signals, and the frequency features are extracted to reflect the dynamic state inside the tailings paste body;

[0052] The frequency feature extraction algorithm performs square processing on the collected acoustic wave signals and microseismic signals, and the square processing can eliminate the influence of negative values, thereby ensuring that the acoustic wave signals and microseismic signals have positive energy representation in subsequent processing; by summing the squares of all acoustic wave signals and microseismic signals, the global energy characteristics inside the tailings paste can be obtained as a whole, which can fully reflect the comprehensive effects of acoustic waves and microseismic waves in the tailings paste, avoiding focusing only on the local information of a certain type of sensor;

[0053] The frequency characteristics inside the tailings paste are further extracted by Fourier transform, wherein the Fourier transform uses a sine basis function to decompose the signal and calculate the contribution of each frequency component. The characteristics of different frequencies can reflect the different physical states inside the tailings paste.

[0054] The frequency feature extraction formula is:

[0055]

[0056] in, Indicates A frequency feature is used to reflect the frequency characteristics inside the tailings paste; Indicates time from arrive Integration is used to calculate the acoustic wave signal and microseismic signal in the entire acquisition period Frequency characteristics within Indicates The acoustic wave sensor The sound wave signals collected at all times; Indicates Microseismic sensors in Microseismic signals collected at all times; and Represent the square of the acoustic wave signal and the microseismic signal respectively, which are used to eliminate the negative value part of the signal and enhance the energy of the signal; It means to sum the squares of the acoustic wave signals collected by all acoustic wave sensors. represents the number of acoustic wave sensors in the acoustic wave sensor array; It means to sum the squares of the microseismic signals collected by all microseismic sensors. represents the number of microseismic sensors in the microseismic sensor array; Represents the sine basis function used for Fourier transform, representing the frequency The fundamental frequency is a specific frequency number; Indicates that in the cycle The phase of the inner sine wave is changed by changing the frequency , different frequency components can be extracted; Indicates the time period of the acquired signal, which is used to normalize the frequency of the sine wave to ensure that the calculation of each frequency component is performed within the same time scale to avoid frequency deviation;

[0057] By combining the acoustic signal and microseismic signal for frequency analysis, the physical state of the tailings paste can be fully and accurately reflected;

[0058] Based on the frequency characteristics, the comprehensive propagation velocity of tailings paste is calculated by the comprehensive propagation velocity calculation algorithm;

[0059] The comprehensive propagation velocity calculation algorithm combines the frequency characteristics with the total energy of the acoustic wave signal and the microseismic signal at all frequencies to calculate the comprehensive propagation velocity of the tailings paste, and uses the coupling correction coefficient to adjust the mapping relationship between the frequency characteristics and the comprehensive propagation velocity of the tailings paste;

[0060] The calculation formula for the comprehensive propagation velocity of tailings paste is:

[0061]

[0062] in, It indicates the comprehensive propagation velocity of tailings paste; Indicates A frequency feature is used to reflect the frequency characteristics inside the tailings paste; It represents the sum of the squares of all frequency characteristics, reflecting the total energy of acoustic and microseismic signals at all frequencies, and further reflects the overall intensity of wave propagation in the tailings paste body; Represents the number of frequency features; Represents the coupling correction coefficient, which is used to adjust the mapping relationship between the frequency characteristics and the comprehensive propagation velocity of the tailings paste. It can be set according to the specific implementation scenario and is not limited here; Represents the total energy of the sound wave signal; represents the total energy of microseismic signal;

[0063] The comprehensive propagation velocity of tailings paste calculated by the comprehensive propagation velocity calculation algorithm can accurately reflect the actual propagation velocity of tailings paste;

[0064] S2. According to the comprehensive propagation velocity of the tailings paste, the dynamic density calculation algorithm is used, combined with the physical properties of the paste particles, to calculate the dynamic density of the tailings paste; by obtaining the dynamic density, solid density and water density of the tailings paste, combined with the concentration correction factor, the dynamic mass concentration of the tailings paste is calculated;

[0065] According to the comprehensive propagation velocity in the tailings paste, the dynamic density of the tailings paste is calculated using the dynamic density calculation algorithm and combined with the physical properties of the paste particles;

[0066] The dynamic density calculation algorithm introduces the cube of the comprehensive propagation velocity of the tailings paste, and amplifies the influence of the comprehensive propagation velocity of the tailings paste on the dynamic density of the tailings paste through the cubic term; and uses the exponential decay factor to describe the decay of the dynamic density of the tailings paste as the comprehensive propagation velocity increases;

[0067] The dynamic density calculation algorithm introduces a particle size distribution factor, which is calculated based on the particle size information of the paste particles, such as the minimum particle size, maximum particle size and average particle size of the particles in the paste, which is obtained through experimental measurement. The particle size distribution factor describes the unevenness of the paste particle size. The wider the particle size distribution of the paste particles, the more complex the friction and contact mode between the paste particles, thereby affecting the dynamic density of the tailings paste.

[0068] The dynamic density calculation algorithm introduces a friction angle correction term. The friction angle reflects the friction between the paste particles. The larger the friction angle, the stronger the mutual friction between the paste particles, which affects the fluidity and density of the tailings paste.

[0069] The calculation formula of the dynamic density of tailings paste is:

[0070]

[0071] in, It indicates the dynamic density of tailings paste, which is the physical property of tailings paste in dynamic state; It represents the particle distribution dynamic factor, which is used to reflect the influence of the arrangement and distribution of particles in the tailings paste on the dynamic density of the tailings paste. It can be set according to the specific implementation scenario and is not limited here. It indicates the comprehensive propagation velocity of tailings paste; It represents the cube of the comprehensive propagation velocity of tailings paste. Through the cubic term, it amplifies the influence of the comprehensive propagation velocity of tailings paste on the dynamic density of tailings paste. represents the exponential decay factor, which is used to describe the decay of the dynamic density of tailings paste with the increase of the integrated propagation velocity; It is a physical property parameter of tailings paste, which is a positive number and is used to describe the intrinsic properties of tailings paste. It adjusts the influence of the comprehensive propagation velocity of tailings paste on the dynamic density of tailings paste. It can be set according to the specific implementation scenario and is not limited here. It represents the particle size distribution factor, which describes the unevenness of the paste particle size. The wider the particle size distribution of the paste, the more complicated the friction and contact between the particles, which affects the dynamic density of the tailings paste. The calculation formula is: , through the maximum particle size of the paste particles , minimum particle size and average particle size To correct the dynamic density of the tailings paste, so that the influence of the uneven distribution of particles in the tailings paste on the dynamic density of the tailings paste is accurately considered; It represents the friction angle correction term, which is related to the dynamic and static friction angle of paste particles. The friction angle reflects the friction force of the interaction between paste particles. The larger the friction angle, the stronger the mutual friction between paste particles, which affects the fluidity and density of tailings paste. Representing the tangent function, the influence of the friction angle on the dynamic density of the tailings paste presents a nonlinear relationship, which can truly reflect the interaction force between the paste particles; represents a constant term, so that the influence of the friction angle is appropriately magnified or reduced; It indicates the dynamic and static friction angle of paste particles, reflecting the magnitude of the interaction force between paste particles during movement;

[0072] The dynamic mass concentration of tailings paste is calculated by obtaining the dynamic density, solid density and water density of the tailings paste and combining the concentration correction factor;

[0073] By performing a difference calculation between the dynamic density of the tailings paste and the density of water, the density difference of the tailings paste relative to water is obtained, which has a certain proportional relationship with the difference between the solid density of the tailings paste and the density of water; a concentration correction factor is introduced, combined with the comprehensive propagation speed of the tailings paste, to further correct the concentration calculation results;

[0074] The calculation formula for the dynamic mass concentration of tailings paste is:

[0075]

[0076] in, It indicates the dynamic mass concentration of tailings paste, which is used to describe the ratio of the mass of solid matter in the tailings paste to the total mass, and reflects the thickness of the tailings paste; It indicates the dynamic density of tailings paste, which is the physical property of tailings paste in dynamic state; Indicates the density of water, which serves as a benchmark for tailings paste concentration; Indicates the solid density of tailings paste, which depends on the tailings material; Indicates the concentration correction factor, which is used to correct the calculation of the dynamic mass concentration of tailings paste. It can be set according to the specific implementation scenario and is not limited here; It represents the cosine adjustment term. Through the cosine function, the flow characteristics of the tailings paste can be adjusted, especially considering the fluctuation and change of the tailings paste concentration under different conditions; It indicates the comprehensive propagation velocity of tailings paste;

[0077] The calculation of the dynamic mass concentration of tailings paste takes into account the complex physical properties of tailings paste in a dynamic state, and can adapt to the rapid changes in tailings paste concentration during the tailings paste filling process;

[0078] S3. Use the dynamic concentration fluctuation range monitoring algorithm to monitor the dynamic mass concentration change of the tailings paste in real time and provide the fluctuation range of the tailings paste concentration;

[0079] Use the dynamic concentration fluctuation range monitoring algorithm to monitor the dynamic mass concentration changes of tailings paste in real time and provide the fluctuation range of tailings paste concentration;

[0080] The dynamic concentration fluctuation range monitoring algorithm calculates the upper and lower limits of concentration fluctuation by combining the fluctuation amplitude factor and the time modulation function. The upper limit of the dynamic mass concentration of the tailings paste represents the maximum value of the concentration fluctuation, and the lower limit of the dynamic mass concentration of the tailings paste represents the minimum value of the concentration fluctuation. The concentration fluctuation range is defined by the upper and lower limits of the dynamic mass concentration of the tailings paste.

[0081] The fluctuation amplitude factor is used to control the amplitude of concentration fluctuation and plays a role in regulating the concentration fluctuation range;

[0082] The time modulation function is closely related to the dynamic density and comprehensive propagation velocity of the tailings paste, and dynamically adjusts the concentration fluctuation degree by introducing the time variable;

[0083] The calculation formula for the concentration fluctuation range is:

[0084]

[0085] in, It indicates the maximum value of concentration fluctuation, i.e. the upper limit of the dynamic mass concentration of tailings paste; It indicates the minimum value of concentration fluctuation, i.e. the lower limit of the dynamic mass concentration of tailings paste; It indicates the dynamic mass concentration of tailings paste, which is used to describe the ratio of the mass of solid matter in the tailings paste to the total mass, and reflects the thickness of the tailings paste; Indicates the fluctuation amplitude factor, which is used to control the amplitude of concentration fluctuation. It can be set according to the specific implementation scenario and is not limited here; It means that the periodic fluctuation of concentration in time is simulated by a sine function; Indicates the fluctuation frequency, which is used to control the periodicity of concentration fluctuation; It represents the time modulation function, which reflects the regulation function of concentration fluctuation over time. It aims to introduce nonlinear modulation effect over time. The calculation formula is:

[0086]

[0087] in, It indicates the comprehensive propagation velocity of tailings paste; It indicates the dynamic density of tailings paste, which is the physical property of tailings paste in dynamic state; It means that nonlinear time effect is introduced through logarithmic function;

[0088] By real-time monitoring of the dynamic mass concentration changes of tailings paste, the upper and lower limits of concentration fluctuations can be accurately tracked, providing data support for further control and adjustment. This not only helps to timely identify abnormal changes in the dynamic mass concentration of tailings paste, but also has important guiding significance for concentration management in the production process of tailings paste, preventing the appearance of too thin or too thick paste, which affects the filling effect.

[0089] In summary, an online monitoring method for tailings paste filling concentration was completed.

[0090] The order of the embodiments of the invention is for description only and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0091] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0092] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A method for online monitoring of tailings paste filling concentration, characterized in that: The following steps are involved: S1: Real-time acquisition of acoustic wave signals and microseismic signals, and the use of frequency feature extraction algorithms to extract features from the acquired acoustic wave signals and microseismic signals to obtain frequency features; based on the frequency features, the comprehensive propagation velocity of the tailings paste is calculated using a comprehensive propagation velocity calculation algorithm; S2: According to the comprehensive propagation velocity of the tailings paste, a dynamic density calculation algorithm is used. In the process of implementing the dynamic density calculation algorithm, the dynamic density of the tailings paste is calculated by introducing the cubic and exponential attenuation factors of the comprehensive propagation velocity of the tailings paste, and combining the particle size distribution factor and the friction angle correction term. The specific formula is: ； in, Indicates the dynamic density of tailings paste; represents the dynamic factor of particle distribution; It indicates the comprehensive propagation velocity of tailings paste; It represents the cube of the comprehensive propagation velocity of tailings paste; represents the exponential decay factor; It is the physical property parameter of tailings paste; represents the particle size distribution factor; represents the friction angle correction term; represents the tangent function; represents a constant term; Indicates the dynamic and static friction angle of paste particles; By obtaining the dynamic density, solid density and water density of the tailings paste and combining it with the concentration correction factor, the dynamic mass concentration of the tailings paste is calculated. The specific formula is: ； in, Indicates the dynamic mass concentration of tailings paste; Indicates the density of water; Indicates the solid density of tailings paste; represents the concentration correction factor; represents the cosine adjustment term; S3: Use the dynamic concentration fluctuation range monitoring algorithm to monitor the dynamic mass concentration changes of the tailings paste in real time and provide the fluctuation range of the tailings paste concentration.

2. The method for online monitoring of tailings paste filling concentration according to claim 1, characterized in that: The S1 specifically includes: The frequency feature extraction algorithm squares the collected acoustic wave signals and microseismic signals and then sums them, and extracts the frequency features inside the tailings paste through Fourier transform. The Fourier transform uses a sine basis function to decompose the acoustic wave signals and microseismic signals and calculates the contribution of each frequency component.

3. The method for online monitoring of tailings paste filling concentration according to claim 2, characterized in that: The S1 specifically includes: The frequency feature extraction formula is: ； in, Indicates frequency characteristics; Indicates time from arrive Perform integration; Indicates The acoustic wave sensor The sound wave signals collected at all times; Indicates Microseismic sensors in Microseismic signals collected at all times; and represent the square of acoustic wave signal and microseismic signal respectively; It means to sum the squares of the acoustic wave signals collected by all acoustic wave sensors. represents the number of acoustic wave sensors in the acoustic wave sensor array; It means to sum the squares of the microseismic signals collected by all microseismic sensors. represents the number of microseismic sensors in the microseismic sensor array; represents the sine basis function used for Fourier transform; Indicates that in the cycle The phase of the inner sine wave; Indicates the time period of signal acquisition.

4. The method for online monitoring of tailings paste filling concentration according to claim 3, characterized in that: The S1 specifically includes: The comprehensive propagation velocity calculation algorithm calculates the comprehensive propagation velocity of the tailings paste by combining the frequency characteristics with the total energy of the acoustic signal and the microseismic signal, and uses the coupling correction coefficient to adjust the mapping relationship between the frequency characteristics and the comprehensive propagation velocity of the tailings paste.

5. The method for online monitoring of tailings paste filling concentration according to claim 4, characterized in that: The S1 specifically includes: The calculation formula for the comprehensive propagation velocity of tailings paste is: ； in, It indicates the comprehensive propagation velocity of tailings paste; Indicates frequency characteristics; It means summing the squares of all frequency features; Represents the number of frequency features; represents the coupling correction factor; Represents the total energy of the sound wave signal; Represents the total energy of microseismic signals.

6. The method for online monitoring of tailings paste filling concentration according to claim 1, characterized in that: The S3 specifically includes: The dynamic concentration fluctuation range monitoring algorithm calculates the upper and lower limits of concentration fluctuation by combining the fluctuation amplitude factor and the time modulation function, and defines the concentration fluctuation range by the upper and lower limits of the dynamic mass concentration of the tailings paste.

7. The method for online monitoring of tailings paste filling concentration according to claim 6, characterized in that: The S3 specifically includes: The calculation formula for the concentration fluctuation range is: ； in, It indicates the maximum value of concentration fluctuation, i.e. the upper limit of the dynamic mass concentration of tailings paste; It indicates the minimum value of concentration fluctuation, i.e. the lower limit of the dynamic mass concentration of tailings paste; Indicates the dynamic mass concentration of tailings paste; represents the volatility factor; It means that the periodic fluctuation of concentration in time is simulated by a sine function; represents the fluctuation frequency; represents the time modulation function.

Images