Online monitoring and predicting system for ash deposition quality of reaction tower

Abstract

The invention discloses an online monitoring and predicting system for ash deposition quality of a reaction tower, which belongs to the technical field of industrial equipment monitoring and is characterized in that a signal testing module is connected with a frequency analysis module through wireless transmission equipment; the frequency analysis module is a frequency analysis processor, and analyzes the vibration signal based on a structural dynamics basic dynamic equation to obtain the current ash deposition mass; the quality prediction module is integrated in the frequency analysis processor, and combines historical quality data, finite element analysis data, flue gas input data and working state data to correct quality and predict a quality increase trend; and the frequency analysis processor is connected with the terminal display module through the wireless transmission device. According to the system, a reaction tower three-dimensional finite element model is established, a sensitivity matrix of ash deposition quality and frequency change is constructed, and inversion solution is carried out, so that high-precision synchronous inversion of ash deposition space distribution and total mass is realized, meanwhile, real-time monitoring and intelligent trend prediction are realized, and the reliability and range adaptability of the system are improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of industrial equipment monitoring, and particularly relates to a reaction tower accumulated dust mass online monitoring and prediction system. BACKGROUND

[0002] In the semi-dry flue gas deacidification process, the reaction tower is one of the core equipment, and a large amount of solid dust will be generated in the deacidification process inside the tower and gradually attached to the tower wall to form accumulated dust. In order to ensure the safe operation of the equipment, the accumulated dust mass inside the reaction tower needs to be effectively monitored. At present, the commonly used accumulated dust mass monitoring methods in the industry mainly include manual experience judgment method, force sensor direct measurement method and built-in liquid level meter detection method. Among them, the manual experience judgment method depends on the technical personnel to qualitatively evaluate the accumulated dust condition by observing the working current of the reaction tower and the ash conveying amount of the ash outlet. This method does not need to add special detection equipment, is simple to implement, and has a certain field applicability. The force sensor direct measurement method directly obtains the overall mass information of the reaction tower by installing a force sensor on the support structure, can realize quantitative measurement, and has high directness and reliability. The built-in liquid level meter detection method indirectly calculates the accumulated dust mass by measuring the material level height in the tower, which can provide more intuitive mass information under certain working conditions.

[0003] However, the above existing technologies still have many deficiencies. The manual experience judgment method is greatly affected by subjective factors, and it is difficult to realize the accurate quantification of the accumulated dust mass. Moreover, the information is lagging behind, and the change trend of the accumulated dust cannot be reflected in real time, which is not conducive to the early discovery of safety hazards. Although the force sensor direct measurement method can realize quantitative detection, the range of the sensor is limited, and it is difficult to adapt to the measurement demand of nearly one hundred tons of accumulated dust in the reaction tower. At the same time, the service life of the force sensor is short under the harsh working conditions in the industrial field, the test conditions are harsh, and the installation and maintenance cost is high. The built-in liquid level meter detection method is prone to failure because the liquid level meter is in a harsh environment of high temperature, corrosion and accumulated dust attachment inside the reaction tower for a long time, which leads to a shortened equipment life and insufficient reliability, and it is difficult to meet the requirements of long-term stable online monitoring. SUMMARY

[0004] To solve the above technical problems, the present application provides a reaction tower accumulated dust mass online monitoring and prediction system to solve the problems existing in the above existing technologies.

[0005] To achieve the above purpose, the present application provides a reaction tower accumulated dust mass online monitoring and prediction system, which comprises: It comprises a signal test module, a frequency analysis module, a mass prediction module and a terminal display module. The signal test module is connected with the frequency analysis module through a wireless transmission device. The frequency analysis module is a frequency analysis processor, configured to analyze the reaction tower vibration signal measured by the signal testing module based on a basic dynamic equation of structure dynamics, so as to obtain the current reaction tower ash deposition mass; The mass prediction module is integrated in the frequency analysis processor, configured to correct the current ash deposition mass obtained by the frequency analysis module in combination with historical mass data, finite element analysis data, flue gas emission data and working state data, and predict the mass growth trend; The frequency analysis processor is connected with the terminal display module through a wireless transmission device, configured to wirelessly transmit data to the terminal display module for display; The frequency analysis module obtains the spatial distribution and total mass of the reaction tower ash deposition through the following steps: A three-dimensional finite element dynamic model of the reaction tower is established, and the wall surface of the reaction tower is divided into a plurality of discrete regions, each region corresponding to an ash deposition mass parameter; Based on the three-dimensional finite element dynamic model, the sensitivity of each ash deposition mass parameter to each modal frequency is calculated to form a sensitivity matrix; The measured frequency of the first K modes of the reaction tower is obtained through the signal testing module, and the frequency offset from the reference frequency is calculated; The relationship formula of the frequency offset is used for inverse solution to obtain the ash deposition mass parameter vector of each region, so as to determine the spatial distribution and total mass of the ash deposition.

[0006] Preferably, the signal testing module comprises sensors arranged at each measuring point of the reaction tower, signal amplifiers connected with the sensors, and data collectors connected with the signal amplifiers.

[0007] Preferably, the sensor is an external sensor.

[0008] Preferably, the construction of the three-dimensional finite element dynamic model is based on the geometric parameters, material parameters and boundary conditions of the reaction tower.

[0009] Preferably, the sensitivity matrix is calculated in the following manner: ; ; Wherein, is an item of the sensitivity matrix, i.e. the differential of the unit mass change to the frequency, is the modal frequency of each order, is each ash deposition mass parameter, is a partial differential operator, is the sensitivity matrix.

[0010] Preferably, the frequency offset is calculated in the following manner: wherein is the measured frequency, is the reference frequency, is the previous K modal frequency.

[0011] Preferably, the mass prediction module is configured to fuse the current dust mass obtained by the frequency analysis module with the historical mass data, finite element analysis data, flue gas emission data and working state data to correct the current dust mass and predict the mass growth trend.

[0012] Preferably, the terminal display module comprises a mobile phone, a computer or a Pad display device.

[0013] Preferably, the structural dynamics basic dynamic equation is: M·a+C·v+K·x=F(t); wherein M is a system mass matrix, C is a damping matrix, K is a stiffness matrix, a is an acceleration vector, v is a velocity vector, x is a displacement vector, F(t) is an external excitation force vector, and · is a multiplication sign.

[0014] Preferably, the system is suitable for online monitoring and prediction of the mass of a deacidification tower, a desulfurization tower, a bag-type dust collector, a concrete mixing station, a sedimentation tank, a water tower, a cooling tower or a grain storage silo.

[0015] Compared with the prior art, the present application has the following advantages and technical effects: The present application can accurately output the spatial distribution map and total mass of the dust in the reaction tower based on the vibration signals measured by the external sensor by establishing a three-dimensional finite element dynamic model of the reaction tower, constructing a sensitivity matrix of the dust mass parameters and the frequency changes of multiple modes, and inversely solving the relationship. The present application solves the problem that the prior art cannot quantitatively evaluate the spatial distribution of dust.

[0016] The present application can not only correct the current dust mass in real time, but also predict the future mass growth trend by integrating the mass prediction module in the frequency analysis processor, fusing the historical mass data, finite element analysis data, flue gas emission data and working state data, and feeding back the results to the terminal display module in real time through the wireless transmission device, thereby overcoming the defects of information lag and inability to warn in the traditional method.

[0017] The present application indirectly obtains the dust mass by measuring the vibration signals of the reaction tower by using the external signal testing module, thereby avoiding placing the sensor (such as a force sensor or a liquid level meter) directly in the harsh environment of high temperature, corrosion and dust adhesion inside the reaction tower, and significantly improving the environmental adaptability and long-term working life of the monitoring system.

[0018] The present application is based on the basic dynamic equation of structural dynamics, and indirectly obtains the accumulated ash mass by measuring and analyzing the vibration speed / acceleration signal of the reaction tower, which is not limited by the inherent range of direct measurement elements such as force sensors, and can adapt to the monitoring demand of nearly hundred tons of accumulated ash mass in the reaction tower.

[0019] The technical scheme of the monitoring and prediction system of the present application is based on the general dynamic principle of mass-frame system, so that it is not only suitable for the reaction tower, but also can be applied to the mass online monitoring and prediction of similar structures such as deacidification tower, desulfurization tower, bag-type dust collector, concrete mixing station, sedimentation tank, water tower, cooling tower, grain storage silo, etc. BRIEF DESCRIPTION OF DRAWINGS

[0020] The accompanying drawings, which form a part of the present application, are intended to provide further understanding of the present application, and the illustrative embodiments of the present application and their description serve the purpose of explaining the present application. The accompanying drawings should not be regarded as a limitation of the present application. In the drawings: Figure 1 The specific implementation structure diagram of the reaction tower accumulated ash mass online monitoring and prediction system of the embodiment of the present application; Figure 2 The structure framework diagram of the reaction tower accumulated ash mass online monitoring and prediction system of the embodiment of the present application; Figure 3 The finite element model of the reaction tower and the interval setting diagram of the accumulated ash area of the embodiment of the present application; Among them, 1, sensor; 2, signal amplifier; 3, data collector; 4, wireless transmission device; 5, frequency analysis processor; 6, wireless transmission device; 7, terminal display module. DETAILED DESCRIPTION

[0021] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0022] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a group of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0023] Embodiment one As Figures 1-2As shown, the embodiment firstly proposes a method of combining finite element structure model and multi-order, multi-point inherent frequency change of dust deposition inversion evaluation, through establishing a three-dimensional finite element dynamic model of the reaction tower, setting parameterized mass units of dust deposition at key positions of the tower body, laying out multi-point sensors to obtain multi-order inherent frequency changes, and inverting and solving the "dust deposition at each position-inherent frequency change sensitivity matrix" calculated by the finite element model and the measured frequency offset, so as to obtain the spatial distribution position and mass of the dust deposition of the reaction tower. The method constitutes a structure dynamics multi-parameter inversion system, compared with the existing rough empirical estimation method based on single-point single-order frequency change, can realize high-precision prediction of dust deposition position and dust deposition degree at the same time, and significantly improves the accuracy and reliability of dust deposition evaluation.

[0024] The embodiment provides a reaction tower dust deposition mass online monitoring and prediction system, which comprises a signal testing module, a frequency analysis module, a mass prediction module and a terminal display module. Specifically, the signal testing module is a speed / acceleration testing module in the Figure 2 The signal testing module is connected with the frequency analysis module through a wireless transmission device 4, the mass prediction module is integrated in a frequency analysis processor 5 in the frequency analysis module, and the frequency analysis processor 5 is connected with the terminal display module 7 through a wireless transmission device 6 for data transmission.

[0025] The signal testing module comprises sensors 1, signal amplifiers 2 and data collectors 3 arranged at each measuring point (a-f) and used for measuring the vibration speed signal of the reaction tower. The sensor 1 is a front-end speed / acceleration sensor. The measured vibration speed signal is transmitted to the frequency analysis module through a wireless transmission device 4, and the frequency analysis module is a frequency analysis processor 5 used for analyzing the measured vibration signal of the reaction tower, so as to obtain the current dust deposition mass of the reaction tower. The mass prediction module is a computer analysis software integrated in the frequency analysis processor 4, and the data used include historical mass data, finite element analysis data, flue gas discharge data and working state data, which are used to predict the more accurate mass and mass growth trend in combination with the current mass. The historical mass data are records of all measured masses and corresponding working conditions, the finite element analysis data are simulation results of modal analysis of the reaction tower structure under different additional masses, which are verified and supplemented with each other, and the flue gas discharge data and working state data are actual working conditions of the reaction tower. The mass obtained by the frequency analysis processor is corrected in combination with all the data, and the more accurate mass and mass growth trend are obtained.

[0026] The signal testing module is connected with the frequency analysis module through a wireless transmission device; Further, the signal testing module comprises sensors arranged at each measuring point of the reaction tower, signal amplifiers connected with the sensors, and data collectors connected with the signal amplifiers.

[0027] Further, the sensors are external sensors.

[0028] Specifically, the sensors comprise speed sensors and acceleration sensors. The signal testing module comprises front-end speed / acceleration sensors arranged at each measuring point, signal amplifiers, and data collectors, for measuring the vibration speed signals of the reaction tower.

[0029] The frequency analysis module is a frequency analysis processor, configured to analyze the vibration signals of the reaction tower measured by the signal testing module based on a basic dynamic equation of structural dynamics, to obtain the current ash deposition mass of the reaction tower. Further, the basic dynamic equation of structural dynamics is: M·a+C·v+K·x=F(t); wherein M is a system mass matrix, C is a damping matrix, K is a stiffness matrix, a is an acceleration vector, v is a speed vector, x is a displacement vector, F(t) is an external excitation force vector, and · is a multiplication sign.

[0030] Specifically, the basic dynamic equation of structural dynamics is also a basic principle for obtaining the ash deposition mass of the reaction tower. When the ash deposition mass of the reaction tower changes, the damping matrix and the stiffness matrix do not change. By measuring the vibration speed signals of the reaction tower and analyzing the signal data, a series of dynamic parameters of the vibration of the reaction tower can be obtained.

[0031] The frequency analysis module obtains the spatial distribution and total mass of the ash deposition of the reaction tower by the following steps: Step 1: establishing a three-dimensional finite element dynamic model of the reaction tower, and dividing the wall surface of the reaction tower into a plurality of discrete regions, each region corresponding to an ash deposition mass parameter; Further, the three-dimensional finite element dynamic model is constructed based on the geometric parameters, material parameters, and boundary conditions of the reaction tower.

[0032] Specifically, the geometric parameters, material parameters, and boundary conditions of the tower body are input into a finite element software (ANSYS, ABAQUS, or COMSOL, etc.), to obtain modal reference frequencies modal mode vectors .

[0033] As shown in Figure 3 , a schematic diagram of the finite element model of the reaction tower and the ash deposition interval setting. The wall surface of the reaction tower is divided into a plurality of discrete regions (such as 10-50), and each region is provided with an ash deposition mass parameter: ; In the finite element model, the dust deposition in each region is equivalent to an additional mass or an increased density block or thickness to make the dust deposition controllable, adjustable and invertible.

[0034] Step 2: Based on the three-dimensional finite element dynamic model, the sensitivity of each dust deposition mass parameter to each order modal frequency is calculated to form a sensitivity matrix; For each dust deposition region , a small perturbation is added , and the change in each order frequency is calculated: ; ; wherein, is an item of the sensitivity matrix, that is, the differential of the unit mass change to the frequency, is the modal frequency of each order, is each dust deposition mass parameter, is a partial differential operator, is the sensitivity matrix.

[0035] Step 3: The measured frequency of the first K order modal of the reactor is obtained through the signal test module, and the frequency offset thereof from the reference frequency is calculated; The first K order frequency is obtained through a multi-point sensor: K ; ; wherein, is the measured frequency, is the reference frequency, is the first K order modal. K

[0036] Step 4: The relationship of the frequency offset is used for inversion to obtain the dust deposition mass parameter vector of each region, so as to determine the spatial distribution and total mass of the dust deposition.

[0037] Specifically, the matrix form can be represented as: ; The inversion result directly gives the size, spatial distribution and total mass of the regional dust deposition.

[0038] The mass prediction module is integrated in the frequency analysis processor, which is used to correct the current dust deposition mass obtained by the frequency analysis module in combination with historical mass data, finite element analysis data, flue gas emission data and working state data, and predict the mass growth trend. ​​Further, the mass prediction module is used to fuse the current accumulated ash mass obtained by the frequency analysis module with the historical mass data, finite element analysis data, flue gas emission data and working state data to correct the current accumulated ash mass and predict the mass growth trend.

[0039] In particular, the mass prediction module is a computer analysis software integrated in the frequency analysis processor, and uses data including historical mass data, finite element analysis data, flue gas emission data and working state data to predict a more accurate current mass and mass growth trend in combination with the current obtained mass. The historical mass data is a record of all measured masses and corresponding working conditions, the finite element analysis data is a simulation result of modal analysis on the structure of the reaction tower under different additional masses, which is verified and supplemented by the measured data, and the flue gas emission data and working state data are actual working conditions of the reaction tower. All the data are combined to correct the mass obtained by the frequency analysis processor and obtain a more accurate current mass and mass growth trend.

[0040] The frequency analysis processor is connected with the terminal display module through a wireless transmission device, and is used to wirelessly transmit data to the terminal display module for display. Further, the terminal display module includes a mobile phone, a computer or a Pad display device.

[0041] In particular, the terminal display module includes a mobile phone, a computer, a Pad and the like display devices, and is used to display the analysis processing result. The mass prediction module wirelessly transmits data information to the terminal display device 7 through the wireless transmission device 6, and feeds back to the operator in real time, so as to achieve the effect of real-time monitoring and preventing troubles.

[0042] Further, the system is suitable for online monitoring and prediction of the mass of a deacidification tower, a desulfurization tower, a bag-type dust collector, a concrete mixing station, a sedimentation tank, a water tower, a cooling tower or a grain storage silo.

[0043] In particular, for structures similar to the mass-frame system, such as a deacidification / sulfur tower, a bag-type dust collector, a concrete mixing station, a sedimentation tank, a water tower, a cooling tower, a grain storage silo and the like, when it is difficult to measure the mass change thereof, the mass of the structure can be monitored and predicted online by using the system to prevent the influence of the mass change on the use efficiency or hidden dangers to safety.

[0044] The beneficial effects of the embodiment are as follows: The embodiment is aimed at the problem of not intuitive and accurate qualitative judgment of the accumulated ash mass by traditional human beings, and the vibration speed signal of the reaction tower is measured by the signal testing module to indirectly obtain the accumulated ash mass data of the reaction tower, and the mass prediction module can correct the mass in real time, which has the advantages of simple operation and accurate judgment.

[0045] The online monitoring and prediction system can predict the dust accumulation quality in the reaction tower and the quality growth trend more accurately by combining historical data and working conditions through the quality prediction module, and can feed back the results processed by the frequency analysis processor to the operator in real time through the wireless transmission device, and has the advantages of real-time monitoring and early prediction.

[0046] The embodiment is aimed at the problems of small measurement range, short service life of force sensor and harsh test conditions of the traditional force sensor measurement method, indirectly obtains the dust accumulation quality of the reaction tower through the measurement of the vibration speed of the reaction tower by the front speed / acceleration sensor module, and transmits data by the wireless transmission device, has the advantages of small space occupation, long service life, and is not limited by the range.

[0047] The embodiment is aimed at the problems of short service life of the liquid level meter due to the harsh working environment, indirectly obtains the dust accumulation quality of the reaction tower by measuring the vibration speed signal of the reaction tower by the front speed / acceleration sensor, and has stable working environment and long service life.

[0048] The above is only the preferred specific embodiment of the present application, but the protection scope of the present application is not limited to this, any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A reaction tower ash deposition mass online monitoring and prediction system, characterized in that, The utility model relates to a kind of on-line monitoring and prediction system of reaction tower ash quality, including: signal test module, frequency analysis module, quality prediction module and terminal display module; The signal test module is connected with the frequency analysis module by wireless transmission device; The frequency analysis module is frequency analysis processor, for analyzing the vibration signal of reaction tower measured by the signal test module based on the basic dynamic equation of structural dynamics, to obtain the current reaction tower ash quality; The quality prediction module is integrated in the frequency analysis processor, for combining historical quality data, finite element analysis data, flue gas emission data and working state data, correcting the current ash quality obtained by the frequency analysis module, and predicting the quality growth trend; The frequency analysis processor is connected with the terminal display module by wireless transmission device, for wirelessly transmitting data to the terminal display module for display; Wherein, the frequency analysis module obtains the spatial distribution and total quality of reaction tower ash by the following steps: A three-dimensional finite element dynamic model of the reaction tower is established, and the wall surface of the reaction tower is divided into a plurality of discrete regions, each region corresponding to an ash quality parameter; Based on the three-dimensional finite element dynamic model, the sensitivity of each ash quality parameter to each modal frequency is calculated to form a sensitivity matrix; The measured frequency of the first K modes of the reaction tower is obtained by the signal test module, and the frequency offset from the reference frequency is calculated; The relationship formula of frequency offset is used to solve the ash quality parameter vector of each region, so as to determine the spatial distribution and total quality of the ash. The signal test module includes sensors arranged at each measuring point of the reaction tower, signal amplifiers connected to the sensors, and data collectors connected to the signal amplifiers.

2. The system of claim 1, wherein, The sensor is an external sensor.

3. The system of claim 2, wherein, The construction of the three-dimensional finite element dynamic model is based on the geometric parameters, material parameters and boundary conditions of the reaction tower.

4. The system of claim 1, wherein, The sensitivity matrix is calculated as follows:

5. The system of claim 1, wherein, The quality prediction module is used to fuse the current ash quality obtained by the frequency analysis module with the historical quality data, finite element analysis data, flue gas emission data and working state data to correct the current ash quality and predict the quality growth trend. ； ； wherein, is the term of the sensitivity matrix, i.e. the differential of the cell mass change with respect to the frequency, is the modal frequency of the respective order, is the respective soot mass parameter, is the partial differential operator, is the sensitivity matrix.

6. The system of claim 1, wherein, The frequency offset is calculated as follows: wherein is the measured frequency, is the reference frequency, is the previous K mode.

7. The system of claim 1, wherein, The terminal display module includes a mobile phone, a computer or a Pad display device.

8. The system of claim 1, wherein, The basic dynamic equation of structural dynamics is:

9. The system of claim 1, wherein, M·a+C·v+K·x=F(t); Where M is the system mass matrix, C is the damping matrix, K is the stiffness matrix, a is the acceleration vector, v is the velocity vector, x is the displacement vector, F(t) is the external excitation force vector, and · is the multiplication sign. The system is suitable for on-line monitoring and prediction of the quality of a deacidification tower, a desulfurization tower, a bag-type dust collector, a concrete mixing station, a sedimentation tank, a water tower, a cooling tower or a grain storage silo.

10. The system of claim 1, wherein, ​

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