Material level detection method, device and system for deep conical thickener and readable storage medium

Abstract

The invention relates to the technical field of material level detection, in particular to a material level detection method, device and system for a deep conical thickener and a readable storage medium. An obvious temperature difference exists on the cylinder wall of the deep conical thickener due to the difference of heat conduction coefficients between an upper suspension in a material and tailing slurry, a temperature diagram of the deep conical cylinder wall is formed according to the imaging characteristics of an infrared imaging thermodetector, and a corresponding temperature interval which is formed by radiating heat to the cylinder wall after the tailing slurry sinks serves as a material level area; and the feeding position detection by using the infrared imaging thermodetector is realized. The purpose is to solve the problem of how to detect the tailing slurry level in the deep conical thickener.

Description

Technical Field

[0001] The present application relates to the technical field of material level detection, and particularly to a material level detection method, device, system and readable storage medium for a deep conical thickener. Background Art

[0002] The deep conical thickener is a common device in the paste filling process, and its main function is to concentrate the tailings slurry with a suitable concentration to prepare the paste. The material enters the charging barrel of the thickener through the feed pipe. Under the action of gravity, the solid particles gradually sink to the bottom to form the tailings slurry, while the clarified supernatant overflows from the upper part.

[0003] The level of the tailings slurry in the thickener has a great influence on the tailings slurry. If the level is too high or too low, it is easy to cause the concentration of the tailings slurry not to meet the standard. Therefore, it is necessary to detect the level of the tailings slurry in real time during the process of preparing the ore slurry. There are mainly two traditional detection methods. One is the manual detection method, in which the operator observes the surface position of the material in the thickener to judge the level; the other is the instrument detection method, in which the level detection equipment such as ultrasonic waves and radar is used to scan the thickener to estimate the level inside the thickener.

[0004] However, manual detection is prone to safety problems and the detection efficiency is insufficient. Moreover, ultrasonic and radar level detection equipment is prone to data drift phenomena in the detection of tailings slurry containing metal ions, resulting in inaccurate detection.

[0005] Therefore, there is an urgent need for an efficient and accurate method for detecting the level of the tailings slurry in a deep conical thickener. Summary of the Invention

[0006] The main purpose of the present application is to provide a material level detection method for a deep conical thickener, aiming to solve the problem of how to detect the level of the tailings slurry in a deep conical thickener.

[0007] To achieve the above object, a material level detection method for a deep conical thickener provided by the present application includes:

[0008] Obtaining a temperature map obtained by the infrared imaging temperature measuring instrument in real time collecting the barrel wall of the deep conical thickener;

[0009] Determining the image area corresponding to the target temperature data in the target temperature range in the temperature map as the material level area, where the target temperature range is the temperature range at which the heat of the tailings slurry after sinking to the lower side of the barrel wall is conducted to the barrel wall;

[0010] Determining the scale value corresponding to the scale line associated with the uppermost layer of the material level area as the material level value corresponding to the tailings slurry in the charging barrel.

[0011] Optionally, before the step of determining the image area corresponding to the target temperature data in the target temperature range in the temperature map as the material level area, the following steps are further included:

[0012] Determine whether the image area corresponding to the target temperature data is within a preset material level area;

[0013] If so, determine the image area corresponding to the target temperature data as the material level area;

[0014] Otherwise, after waiting for a preset duration, execute again the step of determining whether the image area corresponding to the target temperature data is within the preset material level range. If it is still not within the preset material level range, regard the target temperature data as abnormal data and eliminate it.

[0015] Optionally, the step of determining whether the image area corresponding to the target temperature data is within a preset material level area includes:

[0016] Determine whether the pixel coordinates of the image area are located within the pixel coordinate range corresponding to the preset material level area;

[0017] If so, determine that the image area is within the preset material level area;

[0018] Otherwise, determine that it is not.

[0019] Optionally, after the step of obtaining the temperature map obtained by the infrared imaging thermometer by real-time collecting the barrel wall of the deep conical thickener, the following steps are further included:

[0020] Determine the image area corresponding to the second target temperature data in the second target temperature range in the temperature map as the overflow area, where the second target temperature range is greater than the target temperature range;

[0021] Determine the scale value corresponding to the scale line associated with the lowermost layer of the overflow area as the material level value of the upper suspension liquid in the charging barrel.

[0022] Optionally, before the step of determining the image area corresponding to the second target temperature data in the second target temperature range in the temperature map as the overflow area, the following steps are further included:

[0023] Determine whether the image area corresponding to the second target temperature data is within a preset overflow area;

[0024] If so, determine the area corresponding to the target temperature data as the overflow area;

[0025] Otherwise, after waiting for a preset duration, the step of determining whether the image area corresponding to the second target temperature data is within a preset overflow area is executed again. If it is still not within the preset overflow area, the second target temperature data is regarded as abnormal data and excluded.

[0026] Optionally, the step of determining whether the image area corresponding to the second target temperature data is within a preset overflow area includes:

[0027] Determining whether the pixel coordinates of the image area are within the pixel coordinate interval corresponding to the preset overflow area;

[0028] If so, it is determined that the image area is within the preset overflow area;

[0029] Otherwise, it is determined that it is not.

[0030] In addition, to achieve the above object, the present application further provides a material level detection device, and the material level detection device includes:

[0031] A temperature acquisition module, configured to obtain a temperature map of the cylinder wall of a deep conical thickener collected in real time by an infrared imaging thermometer;

[0032] A material level area determination module, configured to determine, as the material level area, the image area corresponding to the target temperature data within a target temperature range in the temperature map;

[0033] A material level value detection module, configured to determine, as the material level value corresponding to the tailings slurry in the loading cylinder, the scale value corresponding to the scale line associated with the uppermost layer of the material level area.

[0034] In addition, to achieve the above object, the present application further provides a material level detection system, and the material level detection system includes: a memory, a processor, and a material level detection program for a deep conical thickener stored on the memory and executable on the processor. When the material level detection program for the deep conical thickener is executed by the processor, the steps of the material level detection method for the deep conical thickener as described above are implemented.

[0035] In addition, to achieve the above object, the present application further provides a computer-readable storage medium, on which a material level detection program for a deep conical thickener is stored. When the material level detection program for the deep conical thickener is executed by a processor, the steps of the material level detection method for the deep conical thickener as described in any one of the above are implemented.

[0036] The present application at least has the following beneficial effects:

[0037] By utilizing the difference in the thermal conductivity coefficients between the supernatant liquid and the tailings slurry in the material, there will be an obvious temperature difference on the cylinder wall of the deep conical thickener. By taking advantage of the imaging characteristics of the infrared imaging thermometer, a temperature map of the deep conical cylinder wall is formed. The temperature range corresponding to the heat radiation from the settled tailings slurry to the cylinder wall is used as the material level area, thereby realizing the detection of the material level using the infrared imaging thermometer. Brief Description of the Drawings

[0038] Figure 1 Schematic diagram of the position of the scale line provided on the charging cylinder of the deep conical thickener related to the embodiment of the present application;

[0039] Figure 2 Schematic diagram of the positional relationship between the infrared imaging thermometer and the charging cylinder related to the embodiment of the present application

[0040] Figure 3 Schematic flow chart of the first embodiment of the material level detection method for the deep conical thickener according to the present application;

[0041] Figure 4 Schematic diagram of the supernatant liquid and the tailings slurry after stratification related to the embodiment of the present application;

[0042] Figure 5 Schematic diagram of the architecture of the material level detection device related to the embodiment of the present application;

[0043] Figure 6 Schematic diagram of the architecture of the hardware operating environment of the material level detection system related to the embodiment of the present application.

[0044] The realization, functional features, and advantages of the purpose of the present application will be further described in conjunction with the embodiments with reference to the drawings. Detailed Embodiments

[0045] To better understand the above technical solution, the exemplary embodiments of the present disclosure will be described in more detail below with reference to the drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0046] First Embodiment

[0047] In this embodiment, referring to Figure 1 the schematic diagram of the position of the scale line provided on the charging cylinder of the deep conical thickener shown, the charging cylinder of the deep conical thickener is provided with a scale line, and the scale line is provided at a position that can be detected by the infrared imaging thermometer (such as on the side wall of the charging cylinder in the figure).

[0048] In addition, referring to Figure 2Schematic diagram of the positional relationship between the shown infrared imaging thermometer and the charging cylinder. The infrared imaging thermometer 2 in the material level detection system is arranged outside the deep conical thickener, and the detection range needs to cover the cylinder wall of the installed charging cylinder 1.

[0049] Referring to Figure 3 , in this embodiment, the method for detecting the material level of the deep conical thickener includes the following steps:

[0050] Step S10, obtaining the temperature map of the cylinder wall of the deep conical thickener collected in real time by the infrared imaging thermometer;

[0051] In this embodiment, the cylinder wall of the deep conical thickener is collected in real time by the infrared imaging thermometer arranged outside the deep conical thickener to obtain the temperature map of the cylinder wall.

[0052] It should be noted that as time changes, for the materials poured into the charging cylinder, the solid particles gradually sink to the bottom to form tailings slurry, while the liquid with a smaller density forms a relatively clear supernatant floating on the upper side of the tailings slurry, forming a stratification as Figure 4 shown. Since the heat transfer coefficients of the tailings slurry and the supernatant in the slurry of the charging cylinder are different, and the heat conductivity of the supernatant is greater than that of the tailings slurry, when the heat of both conducts to the cylinder wall of the charging cylinder at the same time, there will be an obvious temperature difference on the cylinder wall - that is, the temperature of the cylinder wall in the supernatant part will be higher than that of the cylinder wall in the tailings slurry.

[0053] Therefore, by collecting the temperature on the cylinder wall of the deep conical thickener with the infrared imaging thermometer, in the formed temperature map, the part with a higher temperature is regarded as the image area where the supernatant is located, and the part with a lower temperature is regarded as the image area where the tailings slurry is located.

[0054] Step S20, determining the image area corresponding to the target temperature data in the target temperature range in the temperature map as the material level area, where the target temperature range is the temperature range at which the heat of the tailings slurry after sinking to the lower side of the cylinder wall conducts to the cylinder wall;

[0055] Furthermore, since the concentration of the tailings slurry is only related to the material level height of the tailings slurry, in this embodiment, only the position of the tailings slurry in the charging cylinder is concerned, and the position of the supernatant in the charging cylinder is not concerned.

[0056] In this embodiment, the temperature range at which the heat of the tailings slurry after sinking to the lower side of the cylinder wall conducts to the cylinder wall is selected as the target temperature range. Optionally, the specific value of this target temperature range can be obtained by measuring the fluctuation range of the temperature on the cylinder wall when the tailings slurry completely sinks to the bottom of the charging cylinder.

[0057] Step S30: Determine the scale value corresponding to the scale line associated with the uppermost layer of the material level area as the material level value of the tailings slurry in the loading cylinder.

[0058] Further, ideally, in the target temperature range, the image area corresponding to the target temperature data should be located in the lower area of the temperature map, that is, the material level area. Determine the scale value corresponding to the scale line associated with the uppermost layer of the material level area as the material level value of the tailings slurry in the loading cylinder, and then complete the material level detection.

[0059] Exemplarily, such as Figure 4 the material level value of the medium tailings slurry is 5.7 meters.

[0060] Optionally, for how to determine the scale value corresponding to the scale line associated with the uppermost layer of the material level area. It can be determined by manual comparison. Read the position of the uppermost layer of the material level area displayed on the infrared imaging thermometer, and the corresponding scale value on the cylinder wall is used as the material level value of the tailings slurry.

[0061] In the technical solution provided in this embodiment, by utilizing the difference in the heat conduction coefficients between the supernatant and the tailings slurry in the material, there will be an obvious temperature difference on the cylinder wall of the deep cone thickener. Use the imaging characteristics of the infrared imaging thermometer to form the temperature map of the deep cone cylinder wall, and use the temperature range corresponding to the heat radiation of the tailings slurry sinking to the cylinder wall as the material level area to realize the material level detection using the infrared imaging thermometer.

[0062] Second Embodiment

[0063] Based on the first embodiment, in this embodiment, the material level detection described in the first embodiment is mainly applied to the case where the material in the material cylinder has been separated up and down to form tailings slurry and supernatant after a period of precipitation. Considering that there may be a situation where the heat conduction of some incompletely separated materials to the temperature data on the cylinder wall has reached the target temperature range due to the incomplete separation of the tailings slurry and the supernatant. In addition, considering that the heat conductivity of the tailings slurry is weaker than that of the supernatant, the temperature range corresponding to the tailings slurry is smaller than the temperature range corresponding to the supernatant. Therefore, the temperature in the cylinder wall area where the supernatant is located will reach the target temperature range first during the heating process. To avoid misidentifying this area as the material level area, in this embodiment, it is further proposed that before step S20, it further includes:

[0064] Step S40: Determine whether the image area corresponding to the target temperature data is within the preset material level area;

[0065] Step S50: If so, determine the image area corresponding to the target temperature data as the material level area;

[0066] Step S60. Otherwise, after waiting for a preset duration, execute again the step of determining whether the image area corresponding to the target temperature data is within a preset material level range. If it is still not within the preset material level range, regard the target temperature data as abnormal data and eliminate it.

[0067] In this embodiment, in addition to introducing temperature for judgment in the first embodiment, judgment is also made based on the position of the image area of the temperature data.

[0068] In addition, when it is found that target temperature data reaching the target temperature range appears in an area outside the preset material level area, it may be:

[0069] First, the area where the supernatant is located reaches the target temperature range during the heating process;

[0070] Second, abnormal temperature conduction caused by incomplete separation between the tailings slurry and the supernatant.

[0071] Therefore, after waiting for a preset duration, determine again the position of the image area corresponding to the target temperature data. If it is the first case, after the preset duration, it is considered that the heat conduction process of the material has ended. Normally, the temperature corresponding to the wall area where the supernatant is located should be higher than the target temperature range, and the image position of the target temperature data within the target temperature range should be within the preset material level area.

[0072] If it is the second case, regard it as the second case. This case cannot be excluded without external interference, and directly regard the target temperature data as abnormal data and eliminate it.

[0073] Optionally, for how to determine whether the image area corresponding to the target temperature data is within the preset material level area, the following steps can be adopted:

[0074] Step S41, determine whether the pixel coordinates of the image area are within the pixel coordinate range corresponding to the preset material level area;

[0075] Step S42, if so, judge that the image area is within the preset material level area;

[0076] Step S43, otherwise, judge that it is not.

[0077] Third Embodiment

[0078] Based on the above embodiments, in this embodiment, the overflow area where the supernatant is located is judged. After the step S10, it further includes:

[0079] Step S70, determine the image area corresponding to the second target temperature data within the second target temperature range in the temperature map as the overflow area, where the second target temperature range is greater than the target temperature range;

[0080] Step S80: Determine the scale value corresponding to the scale line associated with the lowermost layer of the overflow area as the liquid level value of the supernatant in the charging cylinder.

[0081] It should be noted that since the thermal conductivity coefficient of the supernatant is relatively large, the second target temperature range associated with the overflow area should be greater than the target temperature range associated with the liquid level area. Therefore, it is specified that the second target temperature range is greater than the target temperature range.

[0082] Of course, the second target temperature range can also be obtained by measuring the fluctuation range of the temperature on the cylinder wall when the supernatant part in the measured material completely floats to the upper part of the charging cylinder.

[0083] Similarly, for how to determine the scale value corresponding to the scale line associated with the lowermost layer of the overflow area, the position of the lowermost layer of the overflow area displayed on the infrared imaging thermometer can be read by manual comparison, and the corresponding scale value on the cylinder wall is used as the liquid level value of the supernatant.

[0084] Optionally, in order to further improve the accuracy of liquid level detection, in addition to judging the image position where the target temperature data is located as proposed in the second embodiment, in this embodiment, it is also proposed to judge the position of the second target temperature data to further clearly divide the overflow area and the liquid level area. Before step S70, it further includes:

[0085] Step S90: Determine whether the image area corresponding to the second target temperature data is within a preset overflow area;

[0086] Step S100: If so, determine the area corresponding to the target temperature data as the overflow area;

[0087] Step S110: Otherwise, wait for a preset time period and then execute again the step of determining whether the image area corresponding to the second target temperature data is within the preset overflow area. If it is still not within the preset overflow area, regard the second target temperature data as abnormal data and eliminate it.

[0088] Further and optionally, for how to determine whether the image area corresponding to the second target temperature data is within the preset overflow area, the following steps are adopted:

[0089] Step S91: Determine whether the pixel point coordinates of the image area are within the pixel point coordinate interval corresponding to the preset overflow area;

[0090] Step S92: If so, judge that the image area is within the preset overflow area;

[0091] Step S93: Otherwise, judge that it is not.

[0092] In addition, with reference to Figure 5 , this embodiment further provides a material level detection device, which includes:

[0093] A temperature acquisition module 100, configured to obtain a temperature map obtained by an infrared imaging thermometer in real time by collecting the cylinder wall of a deep conical thickener;

[0094] A material level area determination module 200, configured to determine, as the material level area, an image area corresponding to target temperature data within a target temperature range in the temperature map;

[0095] A material level value detection module 300, configured to determine, as the material level value corresponding to the tailings slurry in the loading cylinder, the scale value corresponding to the scale line associated with the uppermost layer of the material level area.

[0096] In addition, as an implementation solution, Figure 6 is a schematic diagram of the architecture of the hardware operating environment of the material level detection system involved in the embodiment solution of this application.

[0097] As Figure 6 shown, the material level detection system may include: a processor 1001, such as a CPU, a memory 1005, a user interface 1003, a network interface 1004, and a communication bus 1002. Among them, the communication bus 1002 is used to implement connection communication between these components. The user interface 1003 may include a display screen (Display) and an input unit such as a keyboard (Keyboard). Optionally, the user interface 1003 may further include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. Optionally, the memory 1005 may also be a storage device independent of the foregoing processor 1001.

[0098] Those skilled in the art can understand that Figure 6 the material level detection system architecture shown in

[0099] does not constitute a limitation on the material level detection system, and may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements. Figure 6 As

[0100] In Figure 6 In the material level detection system shown, the user interface 1003 is mainly used to connect to the terminal and communicate data with the terminal; the network interface 1004 is mainly used for the background server and communicates data with the background server; the processor 1001 can be used to call the material level detection program for the deep conical thickener stored in the memory 1005.

[0101] In this embodiment, the material level detection system includes: a memory 1005, a processor 1001, and a material level detection program for the deep conical thickener stored on the memory and executable on the processor, where:

[0102] When the processor 1001 calls the material level detection program for the deep conical thickener stored in the memory 1005, the following operations are performed:

[0103] Obtain the temperature map obtained by the infrared imaging temperature measuring instrument in real time collecting the barrel wall of the deep conical thickener;

[0104] Determine the image area corresponding to the target temperature data in the temperature map that is in the target temperature range as the material level area, where the target temperature range is the temperature range where the heat of the tailings slurry after sinking to the lower side of the barrel wall is conducted to the barrel wall;

[0105] Determine the scale value corresponding to the scale line associated with the uppermost layer of the material level area as the material level value corresponding to the tailings slurry in the charging barrel.

[0106] When the processor 1001 calls the material level detection program for the deep conical thickener stored in the memory 1005, the following operations are performed:

[0107] Determine whether the image area corresponding to the target temperature data is within the preset material level area;

[0108] If so, determine the image area corresponding to the target temperature data as the material level area;

[0109] Otherwise, wait for a preset time period and then execute again the step of determining whether the image area corresponding to the target temperature data is within the preset material level range. If it is still not within the preset material level range, regard the target temperature data as abnormal data and eliminate it.

[0110] When the processor 1001 calls the material level detection program for the deep conical thickener stored in the memory 1005, the following operations are performed:

[0111] Determine whether the pixel point coordinates of the image area are within the pixel point coordinate range corresponding to the preset material level area;

[0112] If yes, determining that the image area is within the preset material level area;

[0113] Otherwise, it is judged that it is not in.

[0114] When the processor 1001 calls the material level detection program for the deep conical thickener stored in the memory 1005, the following operations are performed:

[0115] determining an image area corresponding to second target temperature data in a second target temperature interval in the temperature map as an overflow area, wherein the second target temperature interval is larger than the target temperature interval;

[0116] The scale value corresponding to the scale line associated with the bottom layer of the overflow area is determined as the material level value corresponding to the upper suspension in the charging barrel.

[0117] When the processor 1001 calls the material level detection program for the deep conical thickener stored in the memory 1005, the following operations are performed:

[0118] determining whether the image area corresponding to the second target temperature data is within a preset overflow area;

[0119] If so, determining the area corresponding to the target temperature data as the overflow area;

[0120] Otherwise, after waiting for a preset time, the step of determining whether the image area corresponding to the second target temperature data is within the preset overflow area is performed again; if it is still not within the preset overflow area, the second target temperature data is regarded as abnormal data and discarded.

[0121] When the processor 1001 calls the material level detection program for the deep conical thickener stored in the memory 1005, the following operations are performed:

[0122] Determine whether the pixel coordinates of the image area are within the pixel coordinate interval corresponding to the preset overflow area;

[0123] If so, determining that the image area is within the preset overflow area;

[0124] Otherwise, it is judged that it is not in.

[0125] In addition, it can be understood by a person skilled in the art that all or part of the processes in the method for implementing the above embodiment can be completed by instructing the relevant hardware through a computer program. The computer program includes program instructions, and the computer program can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the material level detection system to implement the process steps of the embodiment of the above method.

[0126] Therefore, the present application also provides a computer-readable storage medium storing a material level detection program for a deep conical thickener. When the material level detection program for the deep conical thickener is executed by a processor, each step of the material level detection method for the deep conical thickener as described in the above embodiments is implemented.

[0127] Among them, the computer-readable storage medium may be various computer-readable storage media such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disc that can store program codes.

[0128] It should be noted that since the storage medium provided in the embodiments of the present application is the storage medium used to implement the method of the embodiments of the present application, those skilled in the art can understand the specific structure and variations of the storage medium based on the method introduced in the embodiments of the present application. Therefore, it will not be elaborated herein. Any storage medium used in the method of the embodiments of the present application belongs to the scope to be protected by the present application.

[0129] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0130] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the specified functions in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0131] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the specified functions in Figure 1 one or more flows and / or blocksFigure 1 The functions specified in one or more boxes.

[0132] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide for implementing the steps of the functions specified in one or more processes and / or boxes. Figure 1 One or more processes and / or boxes Figure 1 The steps of the functions specified in one or more boxes.

[0133] It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present application can be implemented by means of hardware including several different elements and by means of a suitably programmed computer. In a unit claim listing several devices, several of these devices can be embodied by the same item of hardware. The use of the words first, second, and third, etc. does not denote any order. These words can be interpreted as names.

[0134] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0135] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these modifications and variations.

Claims

1. A material level detection method for a deep conical concentrator, wherein a scale line is provided on the charging barrel of the deep conical concentrator, characterized in that: Applied to a material level detection system, the material level detection system includes an infrared imaging thermometer, and the method includes the following steps: Obtaining a temperature map obtained by collecting the temperature of the cylinder wall of the deep conical concentrator in real time by the infrared imaging thermometer; The image area corresponding to the target temperature data in the target temperature interval in the temperature map is determined as the material level area, wherein the target temperature interval is the temperature interval in which the heat of the tailings slurry after sinking to the lower side of the cylinder wall is transferred to the cylinder wall; The scale value corresponding to the scale line associated with the uppermost layer of the material level area is determined as the material level value corresponding to the tailings slurry in the charging barrel.

2. The method according to claim 1, characterized in that Before the step of determining the image area corresponding to the target temperature data in the target temperature range in the temperature map as the material level area, the method further includes: Determine whether the image area corresponding to the target temperature data is within a preset material level area; If so, the image area corresponding to the target temperature data is determined as a material level area; Otherwise, after waiting for a preset time, the step of determining whether the image area corresponding to the target temperature data is within the preset material level range is performed again. If it is still not within the preset material level range, the target temperature data is regarded as abnormal data and discarded.

3. The method according to claim 2, characterized in that The step of determining whether the image area corresponding to the target temperature data is within the preset material level area comprises: Determine whether the pixel coordinates of the image area are within the pixel coordinate interval corresponding to the preset material level area; If yes, determining that the image area is within the preset material level area; Otherwise, it is judged that it is not in.

4. The method according to claim 1, characterized in that After the step of obtaining the temperature map obtained by real-time acquisition of the temperature map of the cylinder wall of the deep conical concentrator by the infrared imaging thermometer, the method further includes: determining an image area corresponding to second target temperature data in a second target temperature interval in the temperature map as an overflow area, wherein the second target temperature interval is larger than the target temperature interval; The scale value corresponding to the scale line associated with the bottom layer of the overflow area is determined as the material level value corresponding to the upper suspension in the charging barrel.

5. The method according to claim 4, characterized in that Before the step of determining the image area corresponding to the second target temperature data in the second target temperature range in the temperature map as the overflow area, the step further includes: determining whether the image area corresponding to the second target temperature data is within a preset overflow area; If so, determining the area corresponding to the target temperature data as the overflow area; Otherwise, after waiting for a preset time, the step of determining whether the image area corresponding to the second target temperature data is within the preset overflow area is performed again; if it is still not within the preset overflow area, the second target temperature data is regarded as abnormal data and discarded.

6. The method according to claim 5, characterized in that The step of determining whether the image area corresponding to the second target temperature data is within the preset overflow area comprises: Determine whether the pixel coordinates of the image area are within the pixel coordinate interval corresponding to the preset overflow area; If so, determining that the image area is within the preset overflow area; Otherwise, it is judged that it is not in.

7. A material level detection device, characterized in that: The material level detection device comprises: A temperature acquisition module is used to obtain a temperature map obtained by an infrared imaging thermometer collecting the cylinder wall of a deep conical concentrator in real time; A material level zone determination module, used for determining an image area corresponding to target temperature data in a target temperature interval in the temperature map as a material level zone; The material level value detection module is used to determine the scale value corresponding to the scale line associated with the uppermost layer of the material level area as the material level value corresponding to the tailings slurry in the charging barrel.

8. A material level detection system, characterized in that: The material level detection system includes: a memory, a processor, and a material level detection program for a deep conical thickener stored in the memory and executable on the processor. When the material level detection program for the deep conical thickener is executed by the processor, the steps of the material level detection method for a deep conical thickener as described in any one of claims 1 to 7 are implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a material level detection program for a deep conical thickener, and when the material level detection program for a deep conical thickener is executed by a processor, the steps of the material level detection method for a deep conical thickener as described in any one of claims 1 to 7 are implemented.

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