JP2008209107A - Method for monitoring refractory on furnace bottom in melting furnace - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a method for monitoring a refractory on a furnace bottom in a melting furnace, which easily and accurately measures the erosion amount of the refractory, and with which an appropriate operation plan can be drawn. <P>SOLUTION: This method for monitoring the refractory on the furnace bottom in the melting furnace includes measuring the erosion amount of the refractory 18 on the furnace bottom of the melting furnace 10 wherein a slug layer 22 and a metal layer 23 are deposited due to melting a treatment object. In this method, a standard position A is set at a position in an upper part of the melting furnace 10 where no refractory exists; before operation of the melting furnace 10, an initial distance H from the standard position A to the boundary face between the metal layer 23 and the refractory 18 on the furnace bottom is obtained; the slug layer 22 is removed to expose a metal face when the furnace is not operated; and a distance H<SB>1</SB>from the standard position A to the metal face is measured. Further, elastic waves are transmitted from the metal face in the depth direction, and after performing noise eliminating treatment using a frequency with respect to a reflected wave waveform obtained from a reception sensor, a metal layer thickness H<SB>2</SB>is calculated based on the reflected wave waveform. The erosion amount of the refractory 18 on the furnace bottom is calculated by comparing the total of the distance H<SB>1</SB>and the metal thickness H<SB>2</SB>with the initial distance H. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention can accurately measure the amount of erosion of the bottom refractory installed in the melting furnace, and thus can be effectively utilized for correction and planning of the operation plan such as the replacement timing of the bottom refractory. The present invention relates to a furnace bottom refractory monitoring method.

  The need for melting furnaces for melting incineration residues, municipal waste, industrial waste, etc. is increasing from the viewpoint of detoxifying, reducing the volume and recycling of waste. Known melting furnaces include a burner type melting furnace for melting an object to be processed using heavy oil or the like as a fuel, an electric resistance type melting furnace and a plasma type melting furnace for melting an object to be processed using electricity as a heat source.

  As an example, a plasma melting furnace will be described with reference to FIG. The plasma melting furnace 50 has a main electrode 51 suspended from the top of the furnace and a furnace bottom electrode 52 disposed on the furnace bottom 59, and a plasma is generated by applying a DC voltage 53 between these two electrodes. Generate an arc. And the to-be-processed object dropped in the furnace main body 54 from the charging hopper 55 is heated and melted by plasma heat. The object to be processed is melted and molten slag 56 and molten metal 57 having a specific gravity larger than that are accumulated in the furnace main body 54 and discharged from the outlet 58. Since the inside of the furnace main body 54 is maintained at a high temperature, the inside of the furnace body 54 is formed by a refractory material 60, and the refractory material 60 is covered with a casing 63 made of a steel plate. The fireproof structure of the bottom of the furnace includes a configuration in which an arch-like brick 61 that is resistant to erosion is disposed on the inner side in contact with the molten metal, and a refractory brick 62 is disposed between the brick 61 and the casing 63.

In a melting furnace, molten metal or molten slag may leak from the inside of the furnace, and there is a risk of a steam explosion or the like, so the furnace bottom is often not cooled with water. However, in the case of natural air cooling, the cooling is weak and the refractory is eroded by metal or slag.
Therefore, it is important to accurately grasp the erosion of the furnace bottom refractory and make an operation plan according to this. Conventionally, when grasping the amount of erosion of the bottom refractory, as shown in FIG. 36, the metal layer 57 is melted by the oxygen lance 70 during the outage to expose the surface of the bottom slab brick 61, and the thickness of the refractory is increased. I was measuring. However, since the metal layer is thick and hard, there is a problem that it takes time to remove. Moreover, if a lance etc. are used for metal removal, the bottom brick 61 may be damaged and the refractory brick 61 which was healthy may have to be replaced.

  On the other hand, Patent Document 1 (Patent No. 3385831) calculates the temperature distribution of the bottom brick, the flow of the metal melt, and the temperature distribution based on the mass balance equation, momentum balance equation and energy balance equation of the furnace. However, there is disclosed a method for estimating a furnace bottom erosion line in which the temperature distribution of a refractory brick with the progress of time is obtained and the wear of the brick is determined based on this temperature distribution. This is an apparatus for determining the erosion of the bottom brick during the operation of the melting furnace, and it is possible to predict the wear line of the bottom brick.

Japanese Patent No. 3385831

However, the method described in Patent Document 1 still has a problem that the erosion status of the furnace bottom refractory cannot be accurately grasped. Also, even when trying to measure the thickness of the refractory under the furnace bottom metal, if the metal was blown using a lance as in the past, the furnace bottom brick could be damaged as described above, which was healthy. Refractory bricks may also have to be replaced.
Therefore, in view of the above-mentioned problems of the prior art, the present invention can measure the bottom refractory erosion amount with high accuracy without removing the metal layer and monitor the bottom refractory of the melting furnace. The object is to provide an object monitoring method.

Therefore, in order to solve such a problem, the present invention is a melting furnace in which a slag layer is deposited on the bottom of the furnace and a metal layer is deposited therebelow by melting the object to be processed put in the furnace. In the melting furnace bottom refractory monitoring method for measuring the erosion amount of the bottom refractory,
Set a reference position at a position where no refractory exists above the melting furnace,
Before the operation of the melting furnace, obtain an initial distance H from the reference position to the boundary surface between the metal layer and the furnace bottom refractory,
Wherein when deactivation furnace melting furnace, to expose the metal surface by removing the slag layer, thereby measuring the distance H ₁ to the metal surface from the reference position, the elastic waves transmitted in the depth direction from the metal surface Then, after performing noise removal processing using the frequency for the reflected wave waveform obtained by the receiving sensor, the metal layer thickness H ₂ is obtained based on the reflected wave waveform,
The total amount of the distance H ₁ and the metal thickness H ₂ is compared with the initial distance H to determine the amount of erosion of the bottom refractory.

According to the present invention, it is possible to grasp the amount of erosion of the furnace bottom refractory without removing the metal layer during the furnace shutdown. Further, by using elastic waves that are not easily affected by impurities and voids, it is possible to accurately measure the thickness of the bottom refractory.
Furthermore, according to the present invention, by performing noise removal processing using frequency, reflection returning from other than the metal layer-refractory interface such as a reflected wave from a metal layer crack or a reflected wave from a furnace wall. Since a configuration that removes noise components that appear due to waves is employed, measurement accuracy can be improved.

Further, the metal layer thickness H ₂ is the measured reflected wave waveform acoustic wave in the depth direction from the metal surface by the transmission to the receiving sensor, and the expected value range of the metal layer thickness and reflection wave velocity The first band pass filter having the frequency band calculated from the above is subjected to the noise removal processing by filtering, and the frequency of the reflected wave is obtained by frequency analysis of the reflected wave waveform obtained by the filter processing, and obtaining the metal layer thickness H ₂ based on the frequency.
According to the present invention, when the reflected wave reference point is obtained, the first reflected band is filtered by the first band-pass filter, so that the waveform only in the frequency band in which the peak is estimated to occur is obtained. Processing can be performed, and peak frequency detection accuracy is improved.

A second band-pass filter set in a higher frequency band than the first band-pass filter, and performing a filtering process with the second band-pass filter in a previous stage of performing frequency analysis of the reflected wave; It is characterized in that it is determined that a crack exists in the metal layer when a peak due to the reflected wave is generated in the reflected wave waveform on the high frequency side obtained by the filtering process.
According to the present invention, when the reflected wave reference point is obtained, a peak on the high frequency side caused by the metal layer crack is detected, and if the peak is detected, it is determined that a crack exists in the metal layer. By taking measures such as changing the position, it is possible to improve measurement errors due to metal layer cracking.

Further, the metal layer thickness H ₂ is measured by transmitting an elastic wave in the depth direction from the metal surface and measuring a reflected wave waveform with a receiving sensor installed on the metal surface, and the elastic layer is used as the noise removal process. The percussion-side waveform is measured by a percussion-side reception sensor attached to the percussion device that transmits the wave, the cross-correlation between the percussion-side waveform and the reflected wave waveform is obtained, and the cross-correlation data is analyzed by frequency analysis. And the metal layer thickness H ₂ is obtained based on the frequency.
According to the present invention, the presence or absence of a metal layer crack is detected in advance by a reception sensor for high-frequency measurement, and when it is determined that there is no metal layer crack, by measuring the reflected wave reference point, the metal layer crack It is possible to avoid in advance the deterioration of measurement accuracy due to the occurrence of.

Furthermore, it has two receiving sensors installed equidistantly across the percussion device that transmits the elastic wave, and after multiplying two reflected waves respectively measured by the receiving sensor, The frequency is obtained.
According to the present invention, even if there is a metal layer crack at a specific position, the reflected wave from the metal layer crack is canceled because the return time is different, and the reflected wave from the metal layer-furnace bottom brick interface has a period. It is not canceled because it is the same. For this reason, only the reflected wave from a metal layer-furnace bottom brick interface can be detected, and the detection accuracy of the peak frequency can be improved.

Before obtaining the metal layer thickness, the elastic wave velocity inherent to the metal layer is measured from the velocity of the elastic wave propagating in the horizontal direction of the metal layer, and the elastic wave velocity is used as the reflected wave velocity. characterized in that so as to obtain the metal layer thickness H _2.
Thus, by obtaining the elastic wave velocity specific to the metal layer in the previous stage of the thickness measurement, it becomes possible to perform highly accurate measurement regardless of the component and input amount of the workpiece.

In addition, a plurality of percussion devices and corresponding reception sensors are installed at different distances so that the reflection positions of the elastic waves are the same, and a percussion section and a reception section are provided directly above the reflection positions. A percussion device is installed, and the metal layer thickness is obtained based on a plurality of waveform data obtained by the receiving sensor and a reflected wave arrival time obtained by the receiving unit. To do.
According to the present invention, it is possible to obtain the depth and the average sound speed by measuring the arrival time of the reflected wave, with the place that is equidistant from the reference position immediately above the reflection position as the excitation point-reception point. The metal layer thickness or the furnace bottom refractory erosion amount can be obtained with higher accuracy, and further the furnace bottom refractory erosion amount can be obtained with high accuracy.

Further, a velocity waveform is acquired from the waveform data, and a wave is directly extracted from the velocity waveform, and a reflected wave is extracted based on the reflected wave arrival time, and fitting is performed using the average velocity and depth of the reflected wave as parameters. The metal layer thickness is obtained by processing.
At this time, a plurality of the reception sensors that receive the elastic waves are installed on a substantially straight line at regular intervals, and the metal layer thickness is measured using a surface exploration measurement method based on a plurality of waveform data detected by the plurality of reception sensors. It is preferable to determine the thickness.
According to the present invention, based on waveform data obtained by a plurality of receiving sensors installed on a substantially straight line at regular intervals, the sound velocity of the metal layer and the metal layer thickness are obtained using the surface exploration measurement method. Highly accurate measurement is possible. In addition, according to this method, a result in which the state of the bottom of the furnace can be easily grasped is obtained.

  In addition, by appropriately using the above-described invention, the erosion amount of the furnace bottom refractory is measured in detail by another method while the melting furnace is closed, and the operation plan of the melting furnace is based on the measured erosion amount. It is preferable to make a new plan or make a major correction. By obtaining the amount of refractory erosion in detail during the outage, it is possible to make an optimal operation plan, and safe and smooth operation is possible.

  As described above, according to the present invention, it is possible to provide a bottom refractory monitoring method for a melting furnace that can easily and accurately measure the erosion amount of the bottom refractory. In other words, the amount of erosion of the bottom refractory can be ascertained without removing the metal layer during the outage, and the bottom refractory can be accurately used by using elastic waves that are not easily affected by impurities and voids. It becomes possible to measure the thickness. Furthermore, according to the present invention, by adopting a configuration that removes the reflected wave from other than the metal layer-refractory interface such as the reflected wave from the metal layer crack by performing noise removal processing using the frequency. Therefore, the measurement accuracy can be improved.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the drawings. However, the dimensions, materials, shapes, relative arrangements, and the like of the components described in this embodiment are not intended to limit the scope of the present invention unless otherwise specified, but are merely illustrative examples. Not too much.
1 to 3 are diagrams according to Embodiment 1-1 of the present invention, FIGS. 4 to 8 are diagrams illustrating noise removal processing using a first bandpass filter, and FIGS. 9 to 12 are receptions on the consultation side. FIG. 13 is a diagram illustrating noise removal processing using a sensor, FIG. 13 is a diagram illustrating noise removal processing using a first bandpass filter and a percussion side reception sensor, and FIGS. 14 to 16 are noise removal using high-frequency measurement. FIG. 17 to FIG. 19 are diagrams for explaining noise removal processing using a two-point consultation method, FIG. 20 to FIG. 28 are diagrams according to Example 1-2, and FIG. 29 to FIG. FIGS. 34 and 35 according to Example 1-3 are diagrams according to Example 2 of the present invention.

In this embodiment, the stable operation of the furnace is performed by monitoring the erosion state of the bottom refractory, and this includes a configuration for directly measuring the erosion amount of the bottom refractory or the metal layer thickness. There is a configuration in which the furnace bottom is indirectly monitored by measuring the above, and this will be specifically described in Examples 1 and 2 below. Both methods are used when the reactor is closed. The third embodiment is a method for making and correcting an appropriate furnace operation plan based on the furnace refractory erosion amount or metal layer thickness obtained in the first and second embodiments.
In this embodiment, a melting furnace that melts incineration residue, municipal waste, or industrial waste is targeted, and is particularly suitable for an ash melting furnace that processes ash after incineration of waste. In the following examples, a plasma melting furnace is described as an example, but unless otherwise specified, in addition to the plasma melting furnace, an electric resistance melting furnace, a burner melting furnace, a swirl The present invention can be applied to all melting furnaces such as a melting furnace and a reflection melting furnace.

  Embodiment 1 will be described with reference to FIGS. Example 1 shows a method of monitoring the bottom of the furnace using elastic waves. In Example 1-1, the thickness of the metal layer is measured, and the measured thickness of the metal layer is used to measure the furnace bottom refractory. The amount of erosion is being sought. Moreover, Example 1-2 and Example 1-3 are modifications of Example 1-1.

(Example 1-1)
First, a plasma melting furnace 10 in which a furnace bottom monitoring apparatus according to this embodiment is installed will be described with reference to FIG. This is a configuration common to Examples 1-1 to 1-3 described later.
In the plasma melting furnace 10, a main electrode 11 is suspended from a furnace lid of a furnace body 14, and a furnace bottom electrode 12 is inserted from the furnace bottom to face the main electrode 11. The main electrode 11 can be moved up and down by a movable device (not shown), and the furnace bottom electrode 12 is fixed to the furnace body 14. In the plasma ash melting furnace 10, a direct current is passed between these electrodes by a direct current power source to generate a plasma arc 24 in the furnace. An object to be processed input from the input hopper 21 is dropped into the furnace from an object input port 20 provided on the furnace wall, melted by plasma arc heat and Joule heat of current flowing between the electrodes, and melted. The slag 22 accumulates at the furnace bottom. In addition, a molten metal 23 is formed in the lower portion of the molten slag 22 due to a difference in specific gravity. After melting, it is discharged from the tap 25 as appropriate.
The side wall and the inside of the lid of the furnace body 14 are formed of an irregular refractory material 15, and an arcuate refractory brick 18 that is resistant to erosion is disposed on the inside of the furnace bottom 17. Established. The outer surface of these refractories is covered with a casing 16 made of steel plate. The structure of each refractory is not particularly limited to the above.

In the first embodiment, when a melting furnace is shut down, a percussion device 35 that oscillates an elastic wave by performing a medical examination on a metal surface exposed by removing the solidified slag layer 22, and reflection of an elastic wave reflected on the metal surface And a waveform measuring device 36 for acquiring the waveform of the reflected wave. In addition, the waveform measuring device 36 includes a calculation unit (not shown) in which various calculation processes described later operate according to a program stored in advance. The calculation unit may be installed as a calculation device separately from the waveform measurement device 36. In this case, the calculation unit is connected to the waveform measurement device 36, and the waveform data from the waveform measurement device is input, and the metal layer thickness or Obtain the amount of erosion of the furnace bottom refractory, etc. by arithmetic processing.
Here, the elastic wave is a wave having a low frequency that is generated when a medium (metal layer) is hit by the percussion device 35.
In addition, a position that is not affected by refractory erosion is set as the reference position A above the slag surface of the furnace body 14. As the reference position A, for example, the insertion hole of the main electrode 11 and the insertion hole 38 of the auxiliary electrode 39 are suitable.

In the furnace bottom refractory monitoring method in the embodiment 1-1, first, when the melting furnace 10 is closed, at least a part of the slag layer 22 in the furnace is removed to expose the metal surface. If the metal surface has large irregularities, scrape it with a grinder to create a smooth surface. In this embodiment, as another method for exposing the metal surface, the melting furnace 10 is tilted before the outage, and at least a part of the slag layer and the upper metal layer is discharged, and then the melting furnace 10 is returned to the original state. You may make it cool rapidly by returning to a horizontal state.
Here, physical properties such as elastic wave velocity (reflected wave velocity) and attenuation characteristic inherent to the metal layer 23 are obtained. When obtaining the elastic wave velocity, as shown in FIG. 2A, first, the receiving sensors 37a and 37b are set apart from the metal surface by a predetermined distance. A percussion device 35 is installed on the reception sensor 37a side so as to be spaced apart from the reception sensor 37a, and a metal surface is perceived. The elastic wave propagated in the lateral direction on the surface of the metal layer 23 is received with a time difference between the reception sensor 37a and the reception sensor 37b. Based on this time difference, the inherent elastic wave velocity of the metal layer 23 is obtained.

Since the physical properties of the metal layer 23 change depending on the ash component and the amount of ash, it is possible to accurately measure the thickness of the refractory by acquiring the characteristics specific to the metal layer 23 in advance as described above. .
Moreover, since the ultrasonic wave generally used in the thickness measurement has a high frequency of several MHz, a relatively thin one can be measured, but when the thickness exceeds 500 mm as in the metal layer 23, it cannot be measured because it is attenuated. Since the elastic wave has few attenuations at several kHz, the thickness of the metal layer 23 can be measured by using the elastic wave. However, since the metal layer 23 in the melting furnace 10 has impurities and voids, a suitable frequency is set according to this. When an iron ball is used for the percussion device 35, it is preferable to change the frequency depending on the size of the iron ball.

Next, as shown in FIG. 2 (b), the metal surface is examined by the percussion device 35 to generate an elastic wave in the metal layer 23, and the elastic wave traveling in the depth direction is the metal layer-furnace bottom brick. The waveform of the reflected wave reflected at the boundary surface is received by the reception sensor 37 and input to the waveform measuring device 36. The elastic wave generated by the impact of the percussion device 35 spreads on the hemisphere centering on the percussion device 35, is reflected by the furnace bottom refractory surface facing the metal surface, and the reflected wave reaches the reception sensor 37. Further, this reflected wave is further reflected on the receiving surface and travels toward the bottom surface. In this way, multiple reflections are repeated between the metal layer surface and the metal layer-furnace bottom brick interface, and vibration with a period of time for the reflected wave to reciprocate through the metal layer is measured. As for the waveform of the reflected wave, the period of percussion is initially observed, but the vibration having a specific period gradually becomes dominant. The period of this multiple reflected wave is subjected to waveform processing by Fourier transform or the like and subjected to frequency analysis, and the thickness H ₂ of the metal layer 23 is estimated. At this time, it is preferable to use FFT analysis (Fast Fourier Transform) or MEM analysis (Maximum Entropy Method) for waveform processing.
That is, the amplitude and time waveforms as shown in FIG. 3A are obtained by the receiving sensor 37, and the waveform of the amplitude and frequency as shown in FIG. can get. From the frequency of the metal layer 23 obtained here, the metal layer thickness H ₂ can be calculated by using the following formula (1).
d = v / 2f (1)
Here, d: metal layer thickness (H ₂ ), v: elastic wave velocity of the metal layer, and f: natural frequency.

On the other hand, previously obtained distances H ₁ from the reference position A, which is set in the furnace body upward to the metal layer upper surface (the boundary surface of the metal layer and the slag layer). A value H ₁ + H ₂ obtained by summing the distance H ₁ from the reference position A to the upper surface of the metal layer and the metal layer thickness H _2, and an initial distance from the reference position A determined in advance to the furnace bottom refractory surface By comparing with H, the erosion amount of the bottom refractory can be calculated. That is, it can be estimated that the furnace bottom refractory is eroded by the amount H ₁ + H _{2 obtained} by adding the distance H ₁ and the metal layer thickness H ₂ increased from the initial distance.
The initial distance H may be acquired from the design drawing of the melting furnace, or may be acquired by actual measurement after construction of the melting furnace.

Further, in such a melting furnace 10, erosion on the tap outlet side is severe, so it is preferable to monitor at least the amount of erosion of the bottom refractory on the tap outlet side.
In addition, since the ash input side is less eroded, measure the amount of erosion at at least two points on the tap outlet side and the ash input side, and compare these to determine the amount of erosion of the bottom refractory on the tap outlet side. You may make it do.
As described above, it is preferable to determine the erosion rate of the bottom refractory when the furnace is closed, calculate the erosion rate from the plasma time (ash charging time, ash charging amount), and determine the next operation period.

  According to the present embodiment, it is possible to grasp the amount of erosion of the bottom refractory without removing the metal layer 23 during the outage. Further, by using elastic waves that are not easily affected by impurities and voids, it is possible to accurately measure the thickness of the bottom refractory. Furthermore, by obtaining the elastic wave velocity specific to the metal layer in the previous stage of the thickness measurement, it becomes possible to perform highly accurate measurement regardless of the component and input amount of the object to be processed.

In the present embodiment, the melting furnace 10 is tilted before the melting furnace 10 is closed, and after the slag layer 22 and the metal upper layer containing a large amount of Fe in the metal layer 23 are discharged, the melting furnace is returned to the original state. It is preferable to return to a horizontal state and cool rapidly.
During the operation of the melting furnace 10, the metal layer 23 includes a Cu rich layer (specific gravity 7.6) that contains a large amount of Cu and has a high specific gravity, and a Fe rich layer that contains a large amount of Fe and has a low specific gravity. It is divided into (specific gravity 7.0). When the melting furnace 10 is stopped as it is, the Fe-rich layer having a high melting point is first solidified in the upper layer of the metal layer, and then the Cu-rich layer in the lower layer having a low melting point is solidified. In some cases, stress is generated, and separation occurs at the boundary between the Fe rich layer and the Cu rich layer, thereby generating a space. In order to prevent this, the upper slag layer is tilted immediately before the melting furnace 10 is shut down and the upper slag layer is discharged as much as possible, and the Fe rich layer is also discharged as much as possible. It is effective to mix and rapidly cool the Fe rich layer and Cu rich layer, and the rapid cooling can prevent the Fe rich layer and the Cu rich layer from re-separating.

  In the above configuration, it is assumed that the thickness of the metal layer is obtained using the waveform of the reflected wave returning from the metal layer-furnace bottom brick boundary surface among the reflected wave waveforms, but cracks occur in the middle of the metal layer ( If there is a metal layer crack), the reflected wave returned from the part where the metal layer crack exists, or the reflected wave returned from other than the metal layer-furnace brick interface is mistakenly applied to the metal layer. -If it is recognized as a reflected wave from the furnace bottom brick interface, a measurement error may occur. In addition, since the reflected wave from the metal layer crack appears in the waveform as a noise component, it is difficult to accurately detect the peak frequency representing the frequency of the metal layer thickness when the detected waveform is subjected to frequency analysis.

Therefore, in Example 1-1, in addition to the above-described configuration, a configuration for removing a noise component generated by a reflected wave from other than a metal layer-furnace bottom brick boundary surface such as a reflected wave from a metal layer crack is provided. . The following methods can be used for noise removal processing.
(1) Noise removal processing using the first bandpass filter, (2) Noise removal processing using the percussion side reception sensor, (3) Noise removal processing using high-frequency measurement, (4) Point-to-point consultation method Is a method using at least one of the noise removal processing using the above or a combination of these processing.

(1) Noise removal processing using the first band-pass filter FIGS. 4 to 7 show noise removal processing using the first band-pass filter. FIG. 5 shows a raw waveform of the reflected wave input to the waveform measuring device 36 in the device configuration shown in FIG. This reflected wave is subjected to waveform analysis by FFT analysis, MEM analysis, etc., and frequency analysis is performed. In this configuration, a first band pass filter having a predetermined frequency band is set before waveform processing of the reflected wave is performed. The noise component is removed by filtering the reflected wave waveform with the first bandpass filter, and then the waveform processing is performed for frequency analysis. As a result, when the reflected wave reference point is obtained, the peak frequency detection system can be improved by performing waveform processing only in the frequency band in which the peak is estimated to occur. The reflected wave reference point refers to the return time of the reflected wave when measurement is performed with the percussion device 35 as close as possible to the percussion point (striking point) and the receiving sensor 37.

The frequency band of the first bandpass filter is determined by the reflected wave from the metal layer-furnace bottom brick boundary surface according to the above equation (1) from the expected value range of the metal layer thickness based on the furnace structure and the reflected wave velocity. Calculate and set the frequency band where the peak occurs.
The expected value range of the metal layer thickness is defined as the displacement width from the metal layer thickness when the refractory brick is not eroded (initial state) to the metal layer thickness when the refractory brick is eroded to the maximum. The reflected wave velocity is a velocity measurement value on the metal surface as shown in FIG. 2A, and is preferably in a range including an estimated measurement amplitude.
For example, when the metal layer thickness is 200 to 400 mm and the reflected wave velocity is 3000 to 4000 m / s, the frequency band of the first bandpass filter is 3.75 to 7.5 kHz.

  Here, with reference to FIG. 4, the flow of the noise removal process using a 1st band pass filter is demonstrated. First, the frequency band of the first bandpass filter is set. Then, the reflected wave waveform is measured by the reception sensor 37 (S1), and the reflected wave waveform input to the waveform measuring device 36 is filtered by the first band pass filter (S2). Further, the reflected wave waveform subjected to the filter processing is subjected to waveform analysis by FFT analysis, MEM analysis, etc., and frequency analysis is performed (S3), and the reflected wave reference point is obtained to detect the peak frequency. The metal layer thickness d is obtained from the reflected wave velocity and the peak frequency according to the above equation (1), and the refractory erosion amount is obtained based on the metal layer thickness as described above.

FIG. 6 shows the FFT analysis result of the reflected wave waveform when the filter processing by the first bandpass filter is not performed. This is the result of FFT analysis of the raw waveform shown in FIG. According to the figure, many reflected waves returning from other than the metal layer-furnace bottom brick interface are detected, so that many peak frequencies occur, and the peak of the reflected wave from the metal layer-furnace brick interface It is difficult to accurately detect the frequency.
On the other hand, FIG. 7 shows the FFT analysis result of the reflected wave waveform when the filter processing by the first band pass filter is performed. As shown in the figure, since the noise component is removed, the peak frequency of the reflected wave from the metal layer-furnace bottom brick boundary surface can be accurately detected, and the measurement accuracy can be improved.

Further, as a method for setting the frequency band of the first bandpass filter in the present embodiment, a data table based on the metal layer thickness may be used. The data table is stored in advance in a calculation unit of the waveform processing device 36 or a storage unit of a calculation device installed separately. The data table has a plurality of expected metal value ranges and reflected wave velocities, and is a table in which frequency bands corresponding to these are set. The optimum frequency band is automatically selected by inputting the metal layer thickness and the reflected wave velocity in the melting furnace to be monitored using the data table.
FIG. 8 shows an example of a data table used for setting the first bandpass filter. As shown in the figure, the data table has a configuration in which an expected value range of a plurality of metal layer thicknesses, a plurality of reflected wave velocities, and an optimal frequency band corresponding to these ranges are set.
Once the data table is set in this way, it is not necessary to calculate and obtain the frequency band every time when obtaining the metal layer thickness or the furnace bottom refractory erosion amount, and the optimum frequency band can be determined easily and quickly. It can be acquired. In addition, since this data table has a plurality of metal layer thicknesses and reflected wave velocities, and these are appropriately selected, the data table can also be applied to melting furnaces having different structures.

When the bottom surface of the melting furnace 10 is curved or inclined, the metal layer thickness varies depending on the horizontal position in the melting furnace, so the metal layer thickness at the position to be measured is selected from the data table, A frequency band may be set for each position.
Further, a plurality of data tables corresponding to the horizontal position of the melting furnace 10 may be set, and the corresponding data table may be extracted by selecting the measurement position. In particular, since the plasma melting furnace 10 often employs a structure in which the metal layer thickness differs in the furnace radial direction, a plurality of data tables corresponding to positions in the furnace radial direction may be provided.
Furthermore, the amount of erosion by which the bottom refractory changes in time series may be estimated, and a data table in which frequency bands are set along the time series may be used. In this case, a frequency band corresponding to at least the operation period is set. That is, the amount of erosion that the bottom refractory erodes as the operation continues from the start of operation is estimated to obtain the expected value range of the metal layer thickness at that time, and the optimum frequency band is determined from the expected value range and the reflected wave velocity. Ask for. Then, the obtained numerical values are set as a data table, and when the metal layer thickness or the furnace bottom refractory erosion amount is actually obtained, the optimum frequency band is selected by inputting the operation period. .

(2) Noise removal processing using a percussion side reception sensor FIGS. 9 to 12 show noise removal processing using a percussion side reception sensor.
FIG. 9 shows the apparatus configuration. In this embodiment, a percussion-side reception sensor 37c is attached to the percussion apparatus 35, and a noise component such as a reflected wave due to metal layer cracking using a waveform (hereinafter referred to as a percussion-side waveform) received by the percussion-side reception sensor 37c. It is the structure which removes.
As shown in FIG. 10, the reflected wave waveform is measured by the reception sensor 37 installed on the metal surface (S11), and the consultation-side waveform is measured by the consultation-side reception sensor 37c attached to the consultation device 35. (S12). The reflected wave waveform appears as shown in FIG. 5, and the percussion side waveform appears as shown in FIG. Here, a part of the percussion side waveform shown in FIG. 11 is cut out, and the cross-correlation between the cut-out portion A and the reflected wave waveform is acquired (S13). A cross-correlation graph as shown in FIG. 12 is obtained by the cross-correlation (S14). The cutout portion A from the percussion side waveform is preferably a portion where a sine wave shape of the initial waveform appears.
Then, the cross-correlation data is subjected to waveform analysis by FFT analysis, MEM analysis or the like to perform frequency analysis (S15), a reflected wave reference point is obtained, and (1) noise removal processing using a first bandpass filter Similarly, the amount of refractory erosion is obtained.

FIG. 13 shows a processing flow when both (1) noise removal processing using the first bandpass filter and (2) noise removal processing using the perception side receiving sensor are used.
First, the reflected wave waveform is measured by the receiving sensor 37 installed on the metal surface (S21), and the filter process is performed by the first band pass filter (S22). Then, a cross-correlation is obtained from the reflected wave waveform after the filtering process and the consultation-side waveform measured by the consultation-side receiving sensor 37c attached to the consultation device 35 (S23), and the obtained cross-correlation data Is subjected to waveform analysis by FFT analysis, MEM analysis, etc., and frequency analysis is performed (S24), a reflected wave reference point is obtained, and (1) refractory in the same manner as the noise removal processing using the first bandpass filter. Find the amount of erosion.
As another method, the order of the above processing steps may be reversed and the filter processing by the first band pass filter may be performed after obtaining the cross-correlation.

  According to these noise removal processes, the peak frequency detection accuracy can be improved by performing the waveform process only in the frequency band in which the peak is estimated to occur when the reflected wave reference point is obtained.

(3) Noise removal processing using high-frequency measurement FIGS. 14 to 16 show noise removal processing using high-frequency measurement. In this configuration, as pre-processing of the above configuration, a high-frequency waveform is extracted from the reflected wave using a second bandpass filter having a frequency band on the high-frequency side, and a metal layer crack is generated based on the high-frequency waveform. It shows a method of detecting the presence or absence.
FIG. 14 shows the apparatus configuration. In the present embodiment, the percussion apparatus 35 has a configuration in which a reception sensor 37d for high frequency measurement and a reception sensor 37e for low frequency measurement are installed in parallel on the metal surface.

With reference to FIG. 15, the processing flow of this configuration will be described.
First, a second band pass filter having a frequency band higher than that of the first band pass filter is set in advance, an elastic wave is oscillated by the percussion device 35, and then reflected by the reception sensor 37d for high frequency measurement. The wave waveform is measured (S31). The reflected wave waveform on the high frequency side is filtered by the second bandpass filter (S32), and the waveform after the filter processing is processed by FFT analysis, MEM analysis, etc., and frequency analysis is performed (S33). . FIG. 16 shows the FFT analysis result of the reflected wave waveform on the high frequency side.
The frequency band of the second bandpass filter is calculated from the metal depth (metal layer thickness) estimated to cause metal layer cracking and the reflected wave velocity. For example, when the metal layer thickness is 50 to 200 mm and the reflected wave velocity is 3000 to 4000 m / s, the predetermined frequency band is 7.5 to 30 kHz.

Then, it is determined whether or not a peak due to the reflected wave has occurred in the reflected wave waveform on the high frequency side (S34). If there is no peak, it is determined that there is no metal layer crack, and low frequency measurement is performed. The reflected wave waveform is measured by the reception sensor 37e (S35). The measured reflected wave waveform is filtered by the first bandpass filter (S36), and the waveform after the filter processing is processed by FFT analysis, MEM analysis, etc., and frequency analysis is performed (S37). Then, the reflected wave reference point is obtained, the peak frequency is detected, and the metal layer thickness is obtained. The frequency band of the first bandpass filter is as described above. For example, when the metal layer thickness is 200 to 400 mm and the reflected wave velocity is 3000 to 4000 m / s, the predetermined frequency band is 3.75 to 7.5 kHz.
On the other hand, when a peak exists in the reflected wave waveform on the high frequency side, it is determined that a metal layer crack exists (S38), the measurement at the metal layer position is not performed, the measurement position is changed (S39), and the above Repeat the process.

  According to this embodiment, the presence or absence of the metal layer crack 41 is detected in advance by the reception sensor for high-frequency measurement, and when it is determined that the metal layer crack 41 does not exist, by measuring the reflected wave reference point, It becomes possible to avoid the deterioration of measurement accuracy due to the occurrence of a metal layer crack in advance.

(4) Noise removal process using a two-point consultation method FIGS. 17 to 19 show a noise removal process using a two-point consultation method. In this configuration, a noise removal process using a two-point percussion method in which a midpoint between two reception sensors 37f and 37g is used as a percussion position is shown.
FIG. 17 shows an apparatus configuration. In the present embodiment, the two reception sensors 37f and 37g are separated from each other and installed on a metal surface, and a position that is substantially equidistant from the reception sensors 37f and 37g is the percussion position. It is set as the structure which provided the percussion apparatus 35.

18 and 19 show the processing flow of this configuration.
In FIG. 18, after the elastic wave is oscillated by the percussion apparatus 35, the reflected wave waveform is measured by the receiving sensor 37f on one side (S41), and the reflected wave waveform is similarly measured by the receiving sensor 37g on the other side. (S42). Then, the output value (S43) obtained by multiplying the reflected wave waveform measured by the reception sensor 37f and the reflected wave waveform measured by the reception sensor 37g is subjected to waveform processing by FFT analysis, MEM analysis, or the like. Analysis is performed (S44), the reflected wave reference point is obtained, the peak frequency is detected, and the metal layer thickness is obtained.
In FIG. 19, after the elastic wave is oscillated by the percussion device 35, the reflected wave waveform is measured by the reception sensor 37f on one side (S51), and the reflected wave waveform is subjected to frequency analysis such as FFT processing and MEM processing. (S52). Similarly, the reflected wave waveform is also measured at the reception sensor 37g on the other side (S53), and frequency analysis such as FFT processing and MEM processing is performed on the reflected wave waveform (S52). Then, the analysis result of the reception sensor 37f and the analysis result of the reception sensor 37g are multiplied (S55), the peak frequency is obtained (S56), and the metal layer thickness is obtained.

  According to these methods, even if there is a metal layer crack at a specific position, the reflected wave from the metal layer crack is canceled because the return time is different, and the reflected wave from the metal layer-furnace bottom brick interface is periodic. Are not canceled because they are the same. For this reason, only the reflected wave from a metal layer-furnace bottom brick interface can be detected, and the detection accuracy of the peak frequency can be improved.

(Example 1-2)
Next, an example 1-2 to which the above-described example 1-1 is applied will be described.
Referring to FIG. 20, Example 1-2 is a percussion device 35 that oscillates an elastic wave by percusing the upper surface of the metal layer 23 that is exposed by removing the solidified slag layer in the same manner as Example 1-1. And a receiving sensor 37 that receives the elastic wave reflected by the metal surface, and a waveform measuring device 36 (see FIG. 1) that is connected to the receiving sensor 37 and acquires the received waveform.

In Example 1-2, a plurality of combinations of a consultation position and a reception position where the reflection positions of the elastic waves are the same are set. Therefore, a plurality of the percussion devices 35 and the reception sensors 37 may be installed, or the positions of the percussion devices 35 and the reception sensors 37 are shifted so that the reflection positions are the same. Multiple points may be measured. FIG. 20 shows a configuration in which a plurality of percussion apparatuses 35 and reception sensors 37 are installed. The elastic wave generated by the percussion apparatus (1) 35 is received by the reception sensor (1 ′) 37, and the percussion apparatus (2 ) The elastic wave generated at 35 is received by the receiving sensor (2 ′). Percussion device (2) - the receiving sensor (2 ') a distance L ₂ of the percussion device (1) - receiving sensor (1' has taken longer than the distance L ₁₎ of the distance L between such the apparatus Measurements are made at different points. In addition, a percussion device 35 ′ including a reception sensor unit and a percussion unit is provided, and the percussion device 35 ′ is disposed immediately above the reflection position.

A plurality of waveform data obtained by the reception sensor 37 by the above-described device is input to the waveform measurement device 36, and an analysis process is performed by an analysis device (not shown) based on the waveform data to obtain an average velocity of elastic waves ( Average sound speed).
By applying the average sound speed obtained in Example 1-2 to Example 1-1, the metal layer thickness can be obtained more accurately, and further, the amount of erosion of the furnace bottom refractory can be obtained with high accuracy. Make it possible.

In general, the sound speed is distributed in the depth direction, and when the metal layer 23 is used as a medium, there is a difference of, for example, 2000 m / s in the upper part and 4000 m / s in the lower part. Therefore, in the case of a medium having a large sound velocity distribution, the error may be large if the metal layer thickness or the furnace bottom refractory erosion amount is calculated by applying Example 1-1 as it is. Further, as shown in Example 1-1, it is effective to use the velocity of the surface wave by an easy method, but actually, it is necessary to use the velocity in the depth direction instead of the surface wave.
Therefore, in Example 1-2, the depth and the average sound speed can be obtained by measuring the arrival time of the reflected wave using a place equidistant from the reference position as the excitation point-reception point. Alternatively, it is possible to estimate the furnace refractory erosion amount with high accuracy.

Here, a method for calculating the average sound speed from the waveform data obtained by the above-described apparatus will be described.
In the present embodiment, the waveform input to the waveform measuring device 36 via the reception sensor 37 is an acceleration waveform. FIG. 23 shows an example of the acceleration waveform. As shown in the figure, a plurality of waveforms having different distances L between consultation and reception points are obtained.
Next, the round-trip time of multiple reflection is obtained. This is obtained from the time from the percussion time of the percussion device 35 ′ to the reception of the reflected wave using the percussion device 35 ′ at the reference position shown in FIG.
FIG. 21 shows the relationship between the distance (the distance between the hitting point and the receiving point) in each of the direct wave, the surface wave, the reflected wave, and the refracted wave, and E in the figure is data at the reference position. Is the round-trip time for multiple reflections.

  On the other hand, the acceleration waveform shown in FIG. 23 is once integrated and converted into a velocity waveform. This is because, as shown in FIG. 22, the acceleration waveform has a relatively complicated shape, and in order to make this visually clear, it is integrated once and converted into a velocity waveform. The velocity waveform obtained by this conversion process is as shown in FIG.

Then, a correlation coefficient is calculated from the obtained velocity waveform using a template waveform, and the arrival time of the reflected wave is obtained.
The template waveform is obtained by extracting a waveform from which a direct wave can be clearly discriminated from among a plurality of velocity waveforms shown in FIG. In the figure, the direct waveform of ch12 that can clearly discriminate the sine waveform is used as the template waveform. Other waveforms are not clear because the reflected waves overlap, and are not suitable as template waveforms.

  A correlation coefficient is calculated by template matching using the template waveform. The correlation coefficient is a well-known evaluation scale that represents the degree of similarity of shapes. If a part of the velocity waveform extracted from FIG. 24 has a high degree of similarity with respect to the template waveform, it approaches 1 and if the degree of similarity is low. Approaches -1. By performing this operation for all waveforms, the graph shown in FIG. 26 is obtained. In FIG. 26, waveforms represented by correlation coefficients are arranged from the top in order of increasing distance from the reference position. As can be seen from the figure, in all the graphs, the direct wave passes in the vicinity of the correlation coefficient 1, and the next appearing is the surface wave. However, the reflected wave cannot be clearly discriminated from the figure because a plurality of other waveforms are superimposed. Therefore, the reflected wave is registered using the graph shown in FIG. 25 which shows the FFT analysis result of the waveform data obtained by the reference position percussion apparatus 35 '. In FIG. 25, since the power spectrum representing the reflected wave exists at 3.78 kHz, it can be expected that the reflected wave appears at 265 μsec. Therefore, in FIG. 26, the position indicating the correlation coefficient −1 in the graph (a) closest to the reference position can be estimated as the reflected wave.

  From the correlation coefficient graph, the relationship between the distance of each wave and the time shown in FIG. 27 is obtained. The reflected wave passed 265 μsec at a distance of 0 mm, and a reflected wave represented by a solid line was obtained by the fitting process. On the other hand, the direct wave and the surface wave are represented by a straight line passing through 0 μsec at a distance of 0 mm, and it can be seen from the figure that the surface wave having a fast traveling speed has a larger slope than the direct wave having a slow traveling speed. Here, in the reflected wave fitting process, as shown in FIG. 28, the reflected wave velocity Vp2 and thickness d were used as two parameters, and the fitting process was performed by a known method such as the least square method. Thereby, the metal layer thickness d was determined to be 289 mm. At this time, since the measured value of the metal layer thickness d was 300 mm, the thickness error was suppressed to less than 5%, and it was found that the present example can obtain a highly accurate result.

  As described above, according to the first to second embodiments, the depth and the average sound speed can be obtained by measuring the arrival time of the reflected wave with the place equidistant from the reference position as the excitation point and the reception point. Therefore, the metal layer thickness or the furnace bottom refractory erosion amount can be obtained with higher accuracy, and furthermore, the furnace bottom refractory erosion amount can be obtained with high accuracy.

Further, also in this embodiment, when a metal layer crack exists, the reflected wave reference point may be shifted and an error may occur. Therefore, at least one of the noise removal processing configurations described in Example 1-1 is provided. That is, (1) noise removal processing using the first bandpass filter, (2) noise removal processing using the perception side receiving sensor, (3) noise removal processing using high-frequency measurement, (4) between two points It is set as the structure provided with the noise removal process which consists of a combination of at least any one among these noise removal processes using a percussion method, or these processes.
Thereby, it becomes possible to monitor the erosion amount of the refractory brick with high measurement accuracy.

(Example 1-3)
Next, Example 1-3 to which Example 1-1 described above is applied will be described.
Referring to FIG. 29, Example 1-3 is a percussion point where a top surface of metal layer 23 exposed by removing the solidified slag layer is permeated to oscillate an elastic wave (as in Example 1-1). Percussion device) 35, a reception sensor 37 that receives an elastic wave reflected by a metal surface, and a waveform measurement device 36 that is connected to the reception sensor 37 and acquires a received waveform.

In Example 1-3, a plurality of receiving sensors 37 are installed at different distances from the consultation point 35. In the figure, as an example, 31 sensors from the receiving sensors (1) to (31) are arranged on a substantially straight line at a constant interval Dmm.
First, among these receiving sensors 37, the receiving sensor (1) to the receiving sensor (16) are connected to the waveform measuring device 36. Then, the surface of the metal layer 23 is hit at the percussion point 35 to generate an elastic wave, which is received by 16 reception sensors 37 connected to the waveform measuring device 36. As a result, 16 pieces of waveform data are input to the waveform measuring device 36.
Next, the percussion point 35 is moved to the receiving sensor 37 side, and the receiving sensor (2) to the receiving sensor (17) are connected to the waveform measuring device 36, and waveform data is acquired in the same manner as described above. Similarly, the reception sensors 37 for receiving the waveforms are shifted one by one, and the percussion point 35 is moved in accordance with this, and the measurement is repeated.

Thus, in Example 1-3, the waveform data obtained by the above-described measurement operation is analyzed, and the sound velocity and the metal layer thickness of the metal layer are obtained by the surface wave exploration measurement method.
This surface wave exploration measurement method is a well-known method, and obtains the S wave velocity and the depth distribution from the dispersion characteristics of the Rayleigh wave phase velocity. This dispersion characteristic is shown in FIG. FIG. 30A is a graph showing the relationship between S wave velocity and frequency in different media, and FIG. 30B is a conceptual diagram thereof. As shown in these figures, when the medium is thin, the S wave velocity is low, and when it is thick, the S wave velocity is high. In addition, the soft wave medium has a low S wave velocity, and the hard medium has a high S wave velocity. Therefore, the S wave velocity is affected by the state and properties of the metal layer as a medium.

That is, when waveform data is acquired by the apparatus shown in FIG. 29, a graph having a plurality of waveforms as shown in FIG. 31 is obtained. From this, the phase velocity is obtained. Although the method for obtaining the phase velocity is well known, (1) Fourier series expansion, etc., (2) cross-correlation (cross-correlation), (3) CMP (Common Mid Point), (4) in The metal layer thickness and sound speed are obtained by using a known calculation such as version (inverse analysis).
In this process, the dispersion curve shown in FIG. 32 is calculated, and by analyzing the dispersion curve by the above method, a distribution diagram showing the speed as shown in FIG. 33 is obtained. From this, the boundary surface between the metal layer 23 and the furnace bottom refractory can be clearly distinguished. In the figure, a boundary surface is recognized at about 10 cm, which is the same as the actually measured value of 10 cm, so the error is almost zero.

  According to Example 1-3, the sound velocity of the metal layer and the metal layer thickness using the surface exploration measurement method based on waveform data obtained by a plurality of receiving sensors installed on a substantially straight line at regular intervals. By obtaining the above, it becomes possible to measure with high accuracy. Further, according to this method, as shown in FIG. 20, the state of the furnace bottom can be easily grasped, so that it can be said that the method is very suitable for monitoring the furnace bottom.

Furthermore, also in this embodiment, when a metal layer crack exists, the reflected wave reference point may be shifted and an error may occur. Therefore, at least one of the noise removal processing configurations described in the embodiment 1-1 is provided. That is, (1) noise removal processing using the first bandpass filter, (2) noise removal processing using the perception side receiving sensor, (3) noise removal processing using high-frequency measurement, (4) between two points It is set as the structure provided with the noise removal process which consists of a combination of at least any one among these noise removal processes using a percussion method, or these processes.
Thereby, it becomes possible to monitor the erosion amount of the refractory brick with high measurement accuracy.

First, the plasma melting furnace 10 in which the furnace bottom monitoring apparatus according to the present embodiment is installed will be described with reference to FIG. In the following second embodiment, detailed description of the same configuration as in the first embodiment will be omitted.
In the plasma melting furnace 10, a main electrode 11 is suspended from a furnace lid of a furnace body 14, and a furnace bottom electrode 12 is inserted from the furnace bottom to face the main electrode 11. The main electrode 11 can be moved up and down by a movable device (not shown), and the furnace bottom electrode 12 is fixed to the furnace body 14. In the plasma ash melting furnace 10, a direct current is passed between these electrodes by a direct current power source to generate a plasma arc 24 in the furnace. An object to be processed input from the input hopper 21 is dropped into the furnace from an object input port 20 provided on the furnace wall, melted by plasma arc heat and Joule heat of current flowing between the electrodes, and melted. The slag 22 accumulates at the furnace bottom. In addition, a molten metal 23 is formed in the lower portion of the molten slag 22 due to a difference in specific gravity. After melting, it is discharged from the tap 25 as appropriate.
The side wall and the inside of the lid of the furnace body 14 are formed of an irregular refractory material 15, and an arcuate refractory brick 18 that is resistant to erosion is disposed on the inside of the furnace bottom 17. Established. The outer surface of these refractories is covered with a casing 16 made of steel plate. The structure of each refractory is not particularly limited to the above.

In this embodiment, one or more temperature measuring means for measuring the slag temperature are provided. The type of temperature measuring means is not limited, but means for directly measuring the slag temperature using a thermometer such as a non-contact type thermometer represented by the radiation thermometer 31 or a contact type thermometer represented by a thermocouple, Means for estimating the slag temperature from the input amount of the processed material, means for estimating the slag temperature from the amount of heat dissipated in the cooling water for cooling the refractory, means for estimating the slag temperature from the supply voltage to the electrodes, or releasing the side wall of the furnace body Well-known methods such as means for estimating the slag temperature from the amount of heat can be mentioned. When calculating from the heat balance, the following formula (2) is used.
_{Q p = (C p T s} + H f) × M + Q r ··· (2)
Here, _{Q p:} heat input (power), _{C p:} specific heat of the object to be processed, _{H f:} latent heat of the object to be processed, M: throughput, _{Q r:} a furnace body heat radiation.

In the present embodiment, an erosion amount calculation device 30 is provided that calculates the refractory erosion amount from the slag temperature acquired by the thermometer side means.
This erosion amount calculating device 30 includes a storage unit 31 in which a correlation between a slag temperature and a furnace bottom refractory temperature obtained in advance and a furnace bottom refractory erosion rate equation obtained in advance are stored, The calculation part 32 which performs a calculation, the slag temperature input part 33 which inputs the slag temperature acquired by the thermometer side means, and the output part 34 are provided.

ここで、ｄｘ／ｄｔ：耐火物侵食速度、Ｔ_ｂ：炉底耐火物表面温度、Ｔ_ｓ：スラグ温度、Ａ，Ｂ：侵食速度式の定数、ａ，ｂ：炉底温度推定式の定数である。 A specific method of calculating the furnace refractory erosion amount will be described using the flow shown in FIG.
First, a correlation between the slag temperature and the bottom refractory temperature is obtained in advance and stored in the storage unit 31 (S101). Further, the erosion rate equation of the furnace bottom refractory is acquired in advance and stored in the storage unit 31 (S102). This erosion rate equation includes a method for obtaining by heat conduction analysis and a method for obtaining from an actual measurement value. An example of the erosion rate equation is shown in the following equation (3).

Where dx / dt: refractory erosion rate, T _b : furnace bottom refractory surface temperature, T _s : slag temperature, A and B: constants of erosion rate equation, a and b: constants of furnace bottom temperature estimation equation is there.

During operation of the melting furnace 10, the slag temperature is measured by the thermometer side means (S103). The slag temperature is input to the refractory material thickness calculation device 30 from the slag temperature input unit 33, and based on the correlation between the slag temperature and the furnace bottom refractory temperature stored in the storage unit 31, the calculation unit 32 calculates the slag temperature. The furnace bottom refractory temperature is estimated (S104). The correlation between the slag temperature and the furnace bottom refractory temperature is expressed by the following equation (4), for example. Using this equation (4), the furnace bottom refractory temperature is estimated from the measured slag temperature.
T _b = a × T _s + b (4)
Here, T _b : furnace bottom refractory surface temperature, T _s : slag temperature, a and b: constants of the furnace bottom temperature estimation formula.
And based on the erosion rate formula (3) stored in the memory | storage part 31, the erosion rate within a fixed time is calculated using the obtained furnace bottom refractory temperature (S105).
By integrating the calculated erosion amounts, the total erosion amount at the present time is obtained (S106). By repeating this at regular time intervals, the erosion amount of the bottom refractory can be obtained in real time.

  According to the present embodiment, since the erosion amount of the bottom refractory can be obtained from only the slag temperature, it is easy and high accuracy can be obtained. In addition, the amount of erosion can be obtained without stopping the melting furnace. Therefore, since the amount of erosion can be measured in real time without shutting down the reactor, the subsequent operation period can be reviewed. If the amount of erosion is small, the operation period can be extended.

Further, in the present embodiment, in order to improve accuracy, the temperature of the bottom refractory is estimated in consideration of the metal layer thickness in addition to the slag temperature. Constant a is a, b in the formula (4) are the amount of change that changes in accordance with the metal layer thickness, for example, to improve the temperature estimation accuracy of T _b by putting the following equations (5) .
a = c × d + e (5)
Here, a is a constant of formula (4), d is a metal layer thickness, c and e are coefficients.
As the metal layer thickness d approaches 0 mm, a approaches 1 and as d increases, a becomes smaller than 1. That is, as the metal layer thickness increases, the difference between the slag temperature and the furnace bottom refractory surface temperature increases.
Therefore, when the metal layer thickness is obtained, the metal layer thickness obtained by applying the first bandpass filter as described in Example 1 is applied to the above equation (5), whereby T _b The temperature estimation accuracy is improved, and as a result, the measurement accuracy of the furnace bottom refractory erosion amount can be improved.

Further, after estimating the erosion amount of the bottom refractory according to the second embodiment, the metal layer thickness is estimated using the estimated erosion amount of the bottom refractory, and the furnace using the first embodiment is used. The amount of erosion of the bottom refractory may be calculated.
In this case, first, as described in Example 2, after estimating the erosion amount of the bottom refractory using the erosion rate equation (formula (3)), the initial thickness of the metal layer is added to the estimated erosion amount. Then, the metal layer thickness is calculated. The calculated metal layer thickness is used for setting the frequency band of the first bandpass filter described in the first embodiment. As described above, the first bandpass filter is obtained from the expected value range of the metal layer thickness based on the furnace structure and the reflected wave velocity. At this time, the metal layer thickness estimated from the erosion rate equation is used. By applying to the expected range of the metal layer thickness, the first band pass filter can be set to an optimum value, and the measurement accuracy can be greatly improved.

A description will be given of a third embodiment in which the furnace bottom is monitored using the first and second embodiments.
In the third embodiment, the melting furnace 10 is shut down by maintenance or the like, and the amount of erosion of the furnace bottom refractory is measured in detail using the first or second embodiment during the outage. Based on the measured amount of erosion, a new melting furnace operation plan is created or the operation plan is revised significantly.
In this way, by obtaining the refractory erosion amount in detail during the furnace shutdown, it is possible to make an optimum operation plan, and safe and smooth operation is possible.

  Since the present invention can accurately monitor the bottom refractory of the melting furnace without removing the metal layer that is difficult to melt, a plasma melting furnace, an electric resistance melting furnace, a burner melting furnace, a swirl melting It can be applied to various melting furnaces such as furnaces and reflection melting furnaces.

It is a side view which shows the basic composition of the apparatus which concerns on Example 1 of this invention. The propagation state of the elastic wave in the apparatus of Example 1-1 is represented typically, (a) is a figure explaining the measuring method of the elastic wave velocity of a metal layer, (b) is a figure explaining the thickness measuring method. It is. In the waveform obtained in Example 1-1, (a) shows before conversion and (b) shows after conversion. It is a flowchart of the noise removal process using the 1st band pass filter applied to Example 1-1. It is a wave form diagram of the reflected wave measured with the apparatus of Example 1-1. It is a figure which shows the analysis result which FFT-analyzed the waveform data of FIG. It is the graph which applied the 1st band pass filter to the analysis result of FIG. It is a figure which shows an example of the data table used for the setting of a 1st band pass filter. It is a side view of the apparatus provided with the percussion apparatus side receiving sensor of Example 1-1. It is a flowchart which shows the process which acquires a cross correlation graph. It is the wave form diagram measured with the percussion device side receiving sensor. It is a cross-correlation graph of the reflected wave measured on the metal surface and the percussion side reflected wave. It is a flowchart of the noise removal process using a 1st band pass filter and a percussion apparatus side receiving sensor. It is a side view of the apparatus provided with the 2nd band pass filter applied to Example 1-1. It is a flowchart of the metal layer crack determination process using the high frequency measurement applied to Example 1-1. It is a figure which shows the analysis result obtained by the 2nd band pass filter. It is a side view of an apparatus provided with two receiving sensors applied to Example 1-1. It is a flowchart of the metal layer crack determination process using the point-to-point percussion method applied to Example 1-1. It is a flowchart of the metal layer crack determination process which is a modification of FIG. It is a side view which shows the apparatus of Example 1-2 which is a modification of Example 2. FIG. It is a graph which shows the relationship between the distance of each wave obtained from the apparatus of FIG. 6, and time. It is a figure explaining the waveform of displacement, speed, and acceleration, and its correlation. It is a figure which shows an example of the acceleration waveform received with the sensor of FIG. It is a figure which shows the velocity waveform obtained by integrating the acceleration of FIG. It is a graph which shows the FFT analysis result of the waveform data obtained at the reference position. It is a figure explaining a correlation coefficient. It is the graph represented to the distance of each wave obtained in Example 1-2, and the relationship of time. It is a table | surface which shows a fitting result. It is a side view which shows the apparatus of Example 1-3 which is a modification of Example 2. FIG. It is a figure explaining the dispersion characteristic of the phase velocity of a Rayleigh wave, (a) is a graph which shows the relationship between the S wave velocity and frequency in a different medium, (b) is the conceptual diagram. It is a figure which shows an example of the acceleration waveform received with the sensor of FIG. It is a figure which shows the dispersion | distribution curve calculation result in Example 1-3. It is a figure which shows the surface exploration analysis result in Example 1-3. It is a side view which shows the whole structure of the apparatus which concerns on Example 2 of this invention. It is a flow of refractory erosion amount calculation in Example 2. It is a figure explaining the conventional refractory thickness measuring method. It is sectional drawing of a general plasma type melting furnace.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Melting furnace 11 Main electrode 12 Furnace electrode 14 Furnace main body 16 Iron skin 17 Furnace bottom 18, 19 Furnace brick 20 Processing object inlet 22 Slag layer 23 Metal layer 25 Outlet 28 Radiation thermometer 30 Erosion amount calculation apparatus 35 'percussion-receiving device 36, 46 Waveform measuring device 37, 37a-g Reception sensor 38 Insertion hole 39 Auxiliary electrode 40 Measuring hole 41 Metal layer crack 45 Oscillating device 46 Waveform measuring device 51 Frame 53 Strain gauge 61 Explosion-proof container 62 Iron casing Body 63, 67 Sensor (counter tube)
66 Radiation source 71 Ultrasonic transmitter (probe)
72 Receiving sensor (probe)
73 Ultrasonic measuring instrument

Claims (9)

A melting furnace that measures the amount of erosion of the bottom refractory in a melting furnace where a slag layer is deposited on the bottom of the furnace and a metal layer is deposited below it by melting the workpiece that has been put into the furnace. In the furnace bottom refractory monitoring method of
Set a reference position at a position where no refractory exists above the melting furnace,
Before the operation of the melting furnace, obtain an initial distance H from the reference position to the boundary surface between the metal layer and the furnace bottom refractory,
Wherein when deactivation furnace melting furnace, to expose the metal surface by removing the slag layer, thereby measuring the distance H ₁ to the metal surface from the reference position, the elastic waves transmitted in the depth direction from the metal surface Then, after performing noise removal processing using the frequency for the reflected wave waveform obtained by the receiving sensor, the metal layer thickness H ₂ is obtained based on the reflected wave waveform,
Said distance H ₁ and the metal thickness H ₂ meter, furnace bottom refractory monitoring method of the melting furnace, characterized in that to determine the amount of erosion of the by comparing the initial distance H furnace bottom refractories. The metal layer thickness H ₂ is calculated from the expected value range of the metal layer thickness and the reflected wave velocity, by measuring the reflected wave waveform measured by the receiving sensor by transmitting an elastic wave in the depth direction from the metal surface. Filtering the first bandpass filter having the frequency band thus obtained to perform the noise removal process, and analyzing the frequency of the reflected wave waveform obtained by the filter process to obtain the frequency of the reflected wave, The furnace bottom refractory monitoring method for a melting furnace according to claim 1, wherein the metal layer thickness H ₂ is obtained based on the following.   A second band-pass filter that is set in a higher frequency band than the first band-pass filter, and the second band-pass filter performs a filtering process before the frequency analysis of the reflected wave; 3. The bottom furnace refractory of a melting furnace according to claim 2, wherein when the peak due to the reflected wave occurs in the reflected wave waveform on the high frequency side obtained by the processing, it is determined that a crack exists in the metal layer. Object monitoring method. The metal layer thickness H ₂ is obtained by transmitting an elastic wave in a depth direction from the metal surface and measuring a reflected wave waveform with a receiving sensor installed on the metal surface. The percussion side waveform is measured by the percussion side reception sensor attached to the transmitting percussion device, the cross correlation between the percussion side waveform and the reflected wave waveform is obtained, and the frequency is obtained by frequency analysis of the cross correlation data. , furnace bottom refractory monitoring method of the melting furnace according to any one of claims 1 to 3, wherein the determination of the metal layer thickness H ₂ based on the frequency.   After having received two reception sensors installed at equal distances across the percussion device for transmitting the elastic wave, and multiplying two reflected waves respectively measured by the reception sensor as the noise removal processing The melting wave according to any one of claims 1 to 4, wherein a reflected wave that becomes a noise component other than a reflected wave from a metal layer-furnace bottom brick boundary surface is removed by obtaining the frequency. Monitoring method for bottom refractories. Before determining the thickness of the metal layer, the elastic wave velocity inherent to the metal layer is measured from the velocity of the elastic wave propagating in the horizontal direction of the metal layer, and the elastic wave velocity is used as the reflected wave velocity. furnace bottom refractory monitoring method of the melting furnace according to any one of claims 1 to 4, characterized in that so as to obtain a layer thickness H _2.   A percussion apparatus provided with a plurality of percussion apparatuses and corresponding reception sensors at different distances so that the reflection positions of the elastic waves are the same, and having a percussion section and a reception section directly above the reflection position The metal layer thickness is obtained based on a plurality of waveform data obtained by the receiving sensor and a reflected wave arrival time obtained by the receiving unit. Item 5. A method for monitoring a bottom refractory of a melting furnace according to any one of Items 1 to 4.   A velocity waveform is acquired from the waveform data, a direct wave is extracted from the velocity waveform, a reflected wave is extracted based on the reflected wave arrival time, and a fitting process is performed using the average velocity and depth of the reflected wave as parameters. The furnace bottom refractory monitoring method for a melting furnace according to claim 7, wherein the thickness of the metal layer is obtained as described above.   A plurality of receiving sensors that receive the elastic waves are installed on a substantially straight line at regular intervals, and the metal layer thickness is obtained using a surface exploration measurement method based on a plurality of waveform data detected by the plurality of receiving sensors. The furnace bottom refractory monitoring method for a melting furnace according to any one of claims 1 to 4, characterized in that it is configured as described above.

Images