Intelligent sampling and sample preparation method and system for coal in power plant

Abstract

The invention relates to the technical field of coal sampling and intelligent management, and discloses an intelligent sampling method and system for coal in a power plant, and the method comprises the following steps: intercepting a coal sample from a coal flow through an automatic sampling device, processing the coal sample through automatic crushing, screening and division devices in sequence, and drying the divided coal sample through a drying device, the method comprises the following steps: drying a coal sample, detecting the moisture content through an on-line all-water tester, sealing and packaging the dried coal sample through packaging equipment, loading and unloading in batches and recycling waste materials, monitoring the whole sampling and sample preparation process in real time by an intelligent control system, and carrying out pretreatment, feature extraction and visual display on uploaded data. According to the invention, automation and intellectualization of the whole process of sampling and sample preparation are realized, the sampling efficiency and accuracy are improved while the quality of the coal sample is ensured, and remarkable economic benefits and environmental protection values are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of coal sampling and intelligent management, and particularly relates to a power plant coal intelligent sampling and preparation method and system. BACKGROUND

[0002] In the traditional process of power plant coal sampling and preparation, the links of sampling, crushing, screening, sub-sampling, drying, packaging and the like mostly rely on manual operation or partial automation equipment, which not only is inefficient, but also is easily affected by human factors, leading to uneven sampling, inaccurate data and the like, and although the partial automation equipment improves the efficiency to a certain extent, the links lack cooperativeness, and the intelligent control and optimization of the whole process cannot be realized.

[0003] In the traditional drying process of coal samples, the drying process and moisture detection are usually carried out separately, after the coal samples are treated by the drying equipment, manual sampling is needed and the samples are sent to the laboratory for moisture detection, which not only is time-consuming and laborious, but also easily leads to changes in moisture content due to sample transfer and changes in detection environment, thereby affecting the accuracy of the detection results, in addition, the traditional drying equipment cannot adjust the drying parameters in real time according to the actual moisture content of the coal samples, which may lead to over-drying or insufficient drying, affecting the quality of the coal samples.

[0004] In the traditional sampling and preparation process, the loading and unloading of the packaged coal samples and the disposal of the waste materials mostly rely on manual operation, which not only is inefficient, but also easily leads to problems such as confusion of the batches of coal samples and damage to the coal samples during the loading and unloading process.

[0005] In the traditional sampling and preparation process, the operating personnel can only understand the running state of the equipment through the simple indicator light or display screen of the equipment, and lack comprehensive monitoring and data analysis of the whole sampling and preparation process, such a decentralized monitoring mode not only is difficult to find and solve problems in time, but also cannot optimize and trace the sampling and preparation process, leading to difficulty in further improving the quality and efficiency of the sampling and preparation. SUMMARY

[0006] The present application aims at solving the problems in the prior art and provides a power plant coal intelligent sampling and preparation method and system.

[0007] In order to achieve the above-mentioned purpose, the present application adopts the following technical scheme: a power plant coal intelligent sampling and preparation method and system, comprising the following steps: Step S1, intercepting a coal sample from a coal flow by an automatic sampling device; Step S2, crushing the coal sample by an automatic crushing device to obtain a crushed coal sample; Step S3, screening the crushed coal sample by an automatic screening device to obtain a screened coal sample; Step S4, the screened coal sample is processed by an automatic splitting device to obtain a split coal sample; Step S5, the split coal sample is processed by a drying device to obtain a dried coal sample, and the moisture content is detected by an online total water tester; Step S6, the dried coal sample is sealed and packaged by a packaging device to obtain a packaged coal sample; Step S7, the packaged coal sample is batched and unloaded, and the waste generated during the sampling process is recycled; Step S8, the data uploaded during the sampling process is preprocessed and feature extracted by an intelligent control system, and the sampling process is visually displayed.

[0008] Further, in step S1, the following sub-steps are further included: S1-1, preset the operating parameters of the automatic sampling device, the automatic sampling device includes a sampling head, a sampling arm, a driving device and a sampling control module, the operating parameters include a sampling mode and a sampling frequency, the automatic sampling device intercepts a coal sample from a coal flow according to the preset operating parameters, and the intercepted coal sample is transported to a crushing device; S1-2, during the operation of the automatic sampling device, the coal quality data of the coal flow is monitored in real time by a multi-modal sensor, and the coal quality data is transmitted to an intelligent control system, the multi-modal sensor includes a moisture sensor, an ash sensor and a sulfur sensor, the coal quality data includes the moisture content, the ash content and the sulfur content of the coal flow; S1-3, the coal quality data is processed and analyzed by a sampling control module to obtain the coal quality change, and the operating parameters of the automatic sampling device are adjusted according to the coal quality change.

[0009] Further, in step S2, the following sub-steps are further included: S2-1, the image of the coal sample is captured by an industrial camera, and the image of the coal sample is analyzed by an image analysis method to obtain the initial particle size of the coal sample; S2-2, the operating parameters of the automatic crushing device are set according to the initial particle size of the coal sample, the automatic crushing device includes a crusher, a distribution device and a crushing control module, the operating parameters include a feeding speed, a distribution device rotating speed, a crusher rotating speed and a crushing intensity; S2-3, the automatic crushing device crushes the coal sample according to the set operation parameters to obtain the crushed coal sample and crushing waste, and the crushing control module is used to monitor the crushing process in real time to obtain crushing monitoring data and upload the crushing monitoring data to the intelligent control system, the crushing monitoring data including the time of inputting the coal sample into the automatic crushing device, the initial particle size of the coal sample, the operation parameters of the automatic crushing device and the time of discharging the crushed coal sample.

[0010] Further, in step S3, the following sub-step is further included: S3-1, presetting operation parameters of the automatic screening device, the automatic screening device including a first screen, a second screen, a first discharge port, a second discharge port, a bottom discharge port, a screen vibration device and a screening control module, the operation parameters including a screen vibration frequency, a feeding speed and a discharging speed; S3-2, the automatic screening device screens the crushed coal sample according to the operation parameters to obtain the screened coal sample and screening waste, the screened coal sample including a large particle size coal sample, a medium particle size coal sample and a small particle size coal sample, the screening process including: retaining the large particle size coal sample through the first screen and discharging the large particle size coal sample through the first discharge port; retaining the medium particle size coal sample through the second screen and discharging the medium particle size coal sample through the second discharge port; discharging the small particle size coal sample through the bottom discharge port; S3-3, the screening control module is used to monitor the screening process in real time to obtain screening monitoring data and upload the screening monitoring data to the intelligent control system, the screening monitoring data including the time of inputting the crushed coal sample into the automatic screening device, the operation parameters of the automatic screening device and the time of discharging the screened coal sample through each discharge port.

[0011] Further, in step S4, the following sub-step is further included: S4-1, presetting operation parameters of the automatic sample splitting device, the automatic sample splitting device including a sample splitter, a vibration device, a collection device and a sample splitting control module, the operation parameters including a sample splitting ratio, a vibration frequency, a feeding speed and a discharging speed; S4-2, the automatic sample splitting device splits the screened coal sample according to the operation parameters to obtain the split coal sample and splitting waste, and monitors the splitting process in real time to obtain splitting monitoring data and upload the splitting monitoring data to the intelligent control system, the splitting monitoring data including the time of inputting the screened coal sample into the automatic sample splitting device, the operation parameters of the automatic sample splitting device and the time of discharging the split coal sample.

[0012] Further, in step S5, the following sub-step is further included: S5-1, presetting operation parameters of the drying device, the drying device comprising a drying box, a hot air device, a stirring device, and a drying control module, the operation parameters comprising a drying temperature, a drying time, and a hot air flow rate; S5-2, drying the split coal sample according to the operation parameters of the drying device to obtain a dried coal sample and dried waste, and monitoring the drying process in real time to obtain drying monitoring data and upload the drying monitoring data to the intelligent control system, the drying monitoring data comprising a time when the split coal sample is input into the drying device, the operation parameters of the drying device, and a time when the dried coal sample is discharged; S5-3, sampling the dried coal sample in batches by the automatic sampling device to obtain a test sample for moisture detection; S5-4, presetting operation parameters of the online total water tester and a moisture content standard for calibration, the operation parameters comprising a test temperature and a test time, and the online total water tester detecting the moisture of the test sample according to the preset operation parameters by an infrared absorption method to obtain a sample moisture content; S5-5, comparing the sample moisture content with the moisture content standard for calibration to determine whether the sample moisture content is qualified, if yes, conveying the split coal sample of the sample corresponding batch to the packaging device, and if no, returning the split coal sample of the sample corresponding batch to the drying device for re-drying.

[0013] Further, in step S6, the following sub-steps are further included: S6-1, presetting operation parameters of the packaging device, the packaging device comprising a packaging container, a sealing device, a filling device, and a packaging control module, the operation parameters comprising a filling speed, a sealing pressure, and a packaging time; S6-2, sealing and packaging the dried coal sample according to the operation parameters of the packaging device to obtain a packaged coal sample and packaging waste, and monitoring the sealing and packaging process in real time by the packaging control module to obtain packaging monitoring data and upload the packaging monitoring data to the intelligent control system, the packaging monitoring data comprising a time when the dried coal sample is input into the packaging device, the operation parameters of the packaging device, and a time when the packaged coal sample is discharged; S6-3, printing a bar code on each batch of the packaged coal sample by a printer, the bar code being used for marking the batch of the packaged coal sample.

[0014] Further, in step S7, the following sub-steps are further included: S7-1, temporarily storing the packaged coal sample in a silo, and extracting the batch of the packaged coal sample by a fixed bar code scanner; S7-2, the packaged coal sample is transferred from the bunker to the transport vehicle by the automatic loading and unloading robot, and the loading and unloading process is monitored in real time by a sensor to obtain loading and unloading monitoring data, which includes the storage time, transfer time and operator information of each batch of coal sample stored in the bunker and is uploaded to the intelligent control system; S7-3, the waste material generated in the sampling process is temporarily stored in a waste material bunker, the waste material includes crushing waste material, screening waste material, reduction waste material, drying waste material and packaging waste material, and the source and storage time of the waste material are recorded; S7-4, the composition of the waste material is analyzed by infrared spectroscopy to determine whether it contains valuable recyclable components, if so, the waste material containing valuable components is recycled, if not, the waste material not containing valuable components is treated harmlessly.

[0015] Further, in step S8, the following substeps are further included: S8-1, the intelligent control system acquires sampling process data uploaded from the automatic sampling device, the automatic crushing device, the automatic screening device, the automatic reduction device, the drying device, the packaging device and the loading and unloading device, the sampling process data includes coal quality data, crushing monitoring data, screening monitoring data, reduction monitoring data, drying monitoring data, packaging monitoring data and loading and unloading monitoring data; S8-2, the sampling process data is cleaned and converted to obtain formatted sampling process data, and the sampling process data is analyzed and features are extracted by a support vector machine classification algorithm to obtain feature information of the sampling process; S8-3, according to the feature information of the sampling process, the whole process of the sampling process is visualized by Tableau.

[0016] An intelligent coal sampling system for power plants, characterized in that it comprises: Automatic sampling device: for intercepting coal samples from coal flow; Automatic crushing device: for crushing the intercepted coal sample to obtain crushed coal sample; Automatic screening device: for screening the crushed coal sample to obtain screened coal sample; Automatic reduction device: for reducing the screened coal sample to obtain reduced coal sample; Drying device: for drying the reduced coal sample to obtain dried coal sample; Packaging device: for sealing and packaging the dried coal sample to obtain packaged coal sample; Loading and unloading device: for batch loading and unloading of the packaged coal sample, and for recycling waste material generated in the sampling process; Intelligent control system: used for receiving the sampling and preparation process data uploaded by the above-mentioned equipment and carrying out data analysis, feature extraction and visual display of the sampling and preparation process.

[0017] The technical solution provided by the present application has at least the following beneficial effects: The present application realizes full-process automatic operation from coal flow sampling to packaged coal sample output by tightly integrating each link in the sampling and preparation process through full-process automation and intelligent design, which not only greatly improves the sampling and preparation efficiency and reduces manual intervention, but also improves the accuracy and reliability of coal sample treatment, and provides higher-quality samples for power plant coal quality analysis.

[0018] The present application realizes full-process automatic operation from coal flow sampling to packaged coal sample output by tightly integrating each link in the sampling and preparation process through full-process automation and intelligent design, which not only greatly improves the sampling and preparation efficiency and reduces manual intervention, but also improves the accuracy and reliability of coal sample treatment, and provides higher-quality samples for power plant coal quality analysis.

[0019] The present application realizes full-process automatic operation from coal flow sampling to packaged coal sample output by tightly integrating each link in the sampling and preparation process through full-process automation and intelligent design, which not only greatly improves the sampling and preparation efficiency and reduces manual intervention, but also improves the accuracy and reliability of coal sample treatment, and provides higher-quality samples for power plant coal quality analysis.

[0020] The present application realizes full-process automatic operation from coal flow sampling to packaged coal sample output by tightly integrating each link in the sampling and preparation process through full-process automation and intelligent design, which not only greatly improves the sampling and preparation efficiency and reduces manual intervention, but also improves the accuracy and reliability of coal sample treatment, and provides higher-quality samples for power plant coal quality analysis. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0022] Figure 1 A method flow chart is provided for the embodiment of the present application. Figure 2 A system structure diagram is provided for the embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to further illustrate the technical means and effects taken by the present application to achieve the predetermined object, the specific implementation, structure, features and effects of the power plant coal intelligent sampling method and system according to the present application are described in detail as follows in combination with the drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0025] The following embodiments are for illustrative purposes only and are not intended to limit the scope of the present application.

[0026] The specific scheme of the power plant coal intelligent sampling method and system provided by the present application is specifically described below in combination with the drawings.

[0027] Please refer to Figure 1 which shows a method flow chart of a power plant coal intelligent sampling method provided by an embodiment of the present application, the method includes the following steps: Step S1, intercepting a coal sample from a coal flow by an automatic sampling device; In step S1, the following sub-steps are further included: S1-1, presetting the operating parameters of the automatic sampling device, the automatic sampling device including a sampling head, a sampling arm, a driving device and a sampling control module, the operating parameters including a sampling mode and a sampling frequency, the automatic sampling device intercepting a coal sample from a coal flow according to the preset operating parameters and conveying the intercepted coal sample to a crushing device; S1-2, monitoring the coal quality data of the coal flow in real time by a multi-modal sensor during the working process of the automatic sampling device and transmitting the coal quality data to an intelligent control system, the multi-modal sensor including a moisture sensor, an ash sensor and a sulfur sensor, the coal quality data including the moisture content, the ash content and the sulfur content of the coal flow; S1-3, performing data processing and feature analysis on the coal quality data by the sampling control module to obtain the coal quality change condition and adjusting the operating parameters of the automatic sampling device according to the coal quality change condition.

[0028] It should be noted that the sampling head is used to directly contact the coal flow and intercept the coal sample, and its shape and size are designed according to the characteristics of the coal flow and the sampling requirements (for example, in the form of a shovel or a spoon), the sampling arm is connected with the sampling head and can be telescopic and rotatable, so that the sampling head can sample at different positions of the coal flow, and the driving device provides power for the movement of the sampling head and the sampling arm, and generally uses a motor or a hydraulic cylinder as the driving mode.

[0029] The moisture sensor is used to measure the moisture content of the coal flow, and its principle is to emit microwave signals and detect the reflection signal strength in the coal flow, and calculate the moisture content of the coal flow according to the change of the reflection signal.

[0030] The ash content sensor is used to measure the ash content of the coal flow, and its principle is to emit microwave signals and detect the reflection signal strength in the coal flow, and calculate the moisture content of the coal flow according to the change of the reflection signal.

[0031] The sulfur content sensor is used to measure the sulfur content of the coal flow, and its principle is to emit microwave signals and detect the reflection signal strength in the coal flow, and calculate the moisture content of the coal flow according to the change of the reflection signal.

[0032] Step S2, crushing the coal sample by the automatic crushing device to obtain the crushed coal sample; In step S2, the following sub-steps are further included: S2-1, taking an image of the coal sample by an industrial camera, and analyzing the image of the coal sample by an image analysis method to obtain the initial particle size of the coal sample; S2-2, setting the operation parameters of the automatic crushing device according to the initial particle size of the coal sample, the automatic crushing device including a crusher, a distribution device and a crushing control module, the operation parameters including the feeding speed, the rotation speed of the distribution device, the rotation speed of the crusher and the crushing intensity; S2-3, the automatic crushing device crushing the coal sample according to the set operation parameters to obtain the crushed coal sample and the crushing waste, and the crushing control module monitoring the crushing process in real time to obtain the crushing monitoring data and upload it to the intelligent control system, the crushing monitoring data including the time of the coal sample input into the automatic crushing device, the initial particle size of the coal sample, the operation parameters of the automatic crushing device and the time of the crushed coal sample output.

[0033] It should be noted that the image analysis method refers to processing and analyzing the image of the coal sample by computer vision technology to obtain the particle size and other characteristic information of the coal sample, and in this patent, the image analysis method is used to detect the initial particle size of the coal sample before crushing, to provide a basis for subsequent crushing parameter adjustment, so as to realize accurate control of the particle size of the coal sample and ensure that the particle size of the crushed coal sample meets the requirements.

[0034] The crusher is a core component of the automatic crushing device, which is used for crushing the coal sample. Common types of crushers include jaw crushers or hammer crushers. The jaw crusher crushes the coal sample by reciprocating movement of the moving jaw and the fixed jaw, and the hammer crusher crushes the coal sample by impact of the high-speed rotating hammer head.

[0035] The function of the distributing device is to uniformly distribute the coal sample at the feed inlet of the crusher, so as to ensure that the coal sample can be uniformly fed into the crusher for crushing. The distributing device usually includes a distributing hopper, a distributing roller and a distributing vibrator. The distributing hopper is used for receiving and temporarily storing the coal sample. The distributing roller or the distributing vibrator uniformly spreads the coal sample to the feed inlet of the crusher by rotation or vibration.

[0036] Step S3, the crushed coal sample is screened by the automatic screening device to obtain a screened coal sample; In step S3, the following sub-steps are further included: S3-1, presetting the operation parameters of the automatic screening device, the automatic screening device including a first screen, a second screen, a first discharge outlet, a second discharge outlet, a bottom discharge outlet, a screen vibration device and a screening control module, the operation parameters including screen vibration frequency, feed speed and discharge speed; S3-2, the automatic screening device screens the crushed coal sample according to the operation parameters to obtain a screened coal sample and a screening reject, the screened coal sample including a large-size coal sample, a medium-size coal sample and a small-size coal sample, the screening process including: The large-size coal sample is retained by the first screen and discharged through the first discharge outlet; The medium-size coal sample is retained by the second screen and discharged through the second discharge outlet; The small-size coal sample is discharged through the bottom discharge outlet after passing through the first screen and the second screen; S3-3, the screening control module is used to monitor the screening process in real time to obtain screening monitoring data and upload the screening monitoring data to the intelligent control system, the screening monitoring data including the time when the crushed coal sample is input into the automatic screening device, the operation parameters of the automatic screening device and the time when the screened coal sample is discharged from each discharge outlet.

[0037] It should be noted that the screen is a core component of the screening device, which is used for classifying the particle size of the coal sample. The automatic screening device mentioned in this patent includes two screens, i.e. a first screen and a second screen. The aperture size of the screen determines the classification standard of the particle size of the coal sample, which is usually set according to the characteristics of the coal sample and the subsequent processing requirements. For example, if the large-size coal sample needs to be controlled to be greater than 10 mm, the aperture of the first screen can be set to be ≤10 mm. If the medium-size coal sample needs to be controlled to be between 5 mm and 10 mm, the aperture of the second screen can be set to be ≤5 mm.

[0038] The screen vibration device is used to generate vibration to make the coal sample uniformly distributed on the screen and accelerate through the screen. The vibration device usually includes motor, eccentric block and spring, etc. The motor generates vibration through the eccentric block, and the spring is used to support and adjust the vibration frequency.

[0039] Step S4, the sieved coal sample is processed by the automatic sample division device to obtain the divided coal sample; In step S4, the following sub-steps are further included: S4-1, preset the operation parameters of the automatic sample division device, the automatic sample division device includes a sample divider, a vibration device, a collection device and a sample division control module, and the operation parameters include a sample division ratio, a vibration frequency, a feeding speed and a discharging speed; S4-2, the automatic sample division device processes the sieved coal sample according to the operation parameters to obtain the divided coal sample and the sample division waste, and monitors the sample division process in real time to obtain sample division monitoring data and upload them to the intelligent control system. The sample division monitoring data includes the time when the sieved coal sample is input into the automatic sample division device, the operation parameters of the automatic sample division device and the time when the divided coal sample is discharged.

[0040] It should be noted that the sample divider is the core component of the automatic sample division device, which divides the coal sample according to the specified ratio through a specific mechanical structure (such as a rotary structure or a cutting structure).

[0041] The vibration device is used to make the coal sample uniformly distributed in the sample divider, which is usually composed of a motor and an eccentric block. The motor drives the eccentric block to generate vibration, so that the coal sample is uniformly distributed in the sample divider, ensuring the uniformity and accuracy of the sample division process.

[0042] The collection device is used to collect the divided coal sample and waste, which usually includes a plurality of collection grooves or containers for storing the divided coal sample and waste.

[0043] Step S5, the divided coal sample is dried by the drying device, and the moisture content is detected by the online total water tester to obtain the dried coal sample; In step S5, the following sub-steps are further included: S5-1, preset the operation parameters of the drying device, the drying device includes a drying box, a hot air device, a stirring device and a drying control module, and the operation parameters include a drying temperature, a drying time and a hot air flow; S5-2, the drying device dries the split coal sample according to the operation parameters to obtain a dried coal sample and dried waste, and monitors the drying process in real time to obtain drying monitoring data and upload the drying monitoring data to the intelligent control system, the drying monitoring data including the time when the split coal sample is input into the drying device, the operation parameters of the drying device, and the time when the dried coal sample is discharged; S5-3, sampling the dried coal sample in batches through the automatic sampling device to obtain a test sample for moisture detection; S5-4, presetting operation parameters of the online total water tester and a moisture content standard for calibration, the operation parameters including a test temperature and a test time, and the online total water tester detects the moisture of the test sample through the infrared absorption method according to the preset operation parameters to obtain a sample moisture content; S5-5, comparing the sample moisture content with the moisture content standard for calibration to determine whether the sample moisture content is qualified, if yes, the split coal sample corresponding to the batch of the sample is transported to the packaging device, and if no, the split coal sample corresponding to the batch of the sample is returned to the drying device for re-drying.

[0044] It should be noted that the drying box is the main part of the drying device, and a plurality of trays or supports are arranged in the drying box for placing the split coal sample, and the drying box usually has good heat preservation performance.

[0045] The hot air device usually includes a heater and a fan for providing hot air for the drying box to accelerate the evaporation of moisture of the split coal sample in the drying box.

[0046] The stirring device is usually driven by an electric motor, and the split coal sample in the drying box is stirred by stirring blades or stirring rods to ensure that the split coal sample is uniformly heated during the drying process and to improve the drying efficiency.

[0047] The online total water tester is an automatic device for real-time detection of the moisture content of a coal sample, which can quickly and accurately measure the moisture content of the coal sample to provide a basis for the control of the drying process to ensure that the discharged coal sample is fully dried.

[0048] The infrared absorption method is a method for determining the moisture content of a material by measuring the absorption intensity of infrared light by the material based on the absorption characteristics of water to specific wavelength infrared light. In the online total water test, the split coal sample is irradiated by an infrared light source, and the detector measures the absorption intensity of the infrared light by the split coal sample, and finally the moisture content is calculated based on the absorption intensity.

[0049] Step S6, sealing and packaging the dried coal sample through the packaging device to obtain a packaged coal sample; In step S6, the following sub-steps are further included: S6-1, preset the running parameters of the packaging device, the packaging device including a packaging container, a sealing device, a filling device, and a packaging control module, the running parameters including a filling speed, a sealing pressure, and a packaging time; S6-2, the packaging device seals and packages the dried coal samples according to the running parameters to obtain packaged coal samples and packaging waste, and the packaging control module is used to monitor the sealing and packaging process in real time to obtain packaging monitoring data and upload the packaging monitoring data to the intelligent control system, the packaging monitoring data including a time when the dried coal samples are input into the packaging device, the running parameters of the packaging device, and a time when the packaged coal samples are discharged; S6-3, a bar code is printed on each batch of packaged coal samples by a printer, and the bar code is used to mark the batch of the packaged coal samples.

[0050] It should be noted that the packaging container is used to contain the dried coal samples, and is usually made of corrosion-resistant and sealing materials (such as polyethylene, polypropylene, or glass).

[0051] The sealing device is used to ensure the sealing of the packaging container to prevent the coal samples from being damp or leaking, and usually includes a sealing cover, a sealing ring, and a sealing pressure adjusting device, the sealing cover is fixed on the packaging container by threads or buckles, the sealing ring ensures the sealing between the cover and the container, and the sealing pressure adjusting device is used to adjust the sealing pressure.

[0052] The filling device is used to fill the dried coal samples into the packaging container, and usually includes a hopper, a conveying pipe, and a vibrating device, the hopper is used to receive the coal samples, the conveying pipe conveys the coal samples to the packaging container, and the vibrating device uniformly distributes and fills the coal samples into the container by vibration.

[0053] Step S7, the packaged coal samples are batched and unloaded, and the waste generated in the sampling process is recycled and treated; In step S7, the following sub-steps are further included: S7-1, the packaged coal samples are temporarily stored in a stock bin, and the batch of the packaged coal samples is extracted by a fixed bar code scanner; S7-2, the packaged coal samples are transferred from the stock bin to a transport vehicle by an automatic loading and unloading robot, and the loading and unloading process is monitored in real time by a sensor to obtain loading and unloading monitoring data, the loading and unloading monitoring data including a stock bin entry time of each batch of coal samples, a transfer time, and operator information and uploading the loading and unloading monitoring data to the intelligent control system; S7-3, the waste generated in the sampling process is temporarily stored in a waste stock bin, the waste including broken waste, screened waste, divided waste, dried waste, and packaged waste, and the source and stock bin entry time of the waste are recorded; S7-4, analyze the composition of the rejected material by infrared spectroscopy to determine whether it contains valuable recyclable components. If so, the rejected material containing valuable components is recycled. If not, the rejected material without valuable components is treated harmlessly.

[0054] It is worth noting that the fixed barcode scanner is an automatic device installed in a fixed position for quickly reading information in barcodes. It is commonly used in logistics, warehousing and production management, and can automatically identify and record batch information of goods. It has the characteristics of high efficiency, high accuracy and high automation, which can reduce manual operation and improve work efficiency.

[0055] The automatic loading and unloading robot is an automatic device that can automatically complete loading and unloading tasks. It is usually used in logistics, warehousing and production lines. It can automatically complete the transfer of goods from the warehouse to the transport vehicle according to the preset program or real-time instructions, which can effectively reduce the labor intensity and improve the accuracy and safety of the loading and unloading process.

[0056] Infrared spectroscopy is a spectral analysis technique used to analyze the composition of a substance. It determines the chemical composition and structure of a substance by measuring its absorption characteristics of infrared light. The principle is to use infrared light to irradiate the sample, and the detector measures the absorption intensity of the sample to the infrared light. According to the characteristics of the absorption spectrum, the chemical composition and functional groups contained in the sample are determined. It has the characteristics of rapidity, non-destructiveness and non-contact, and can quickly provide the composition information of the sample.

[0057] Recycling refers to the process of reprocessing and recycling discarded materials containing valuable components. The purpose is to extract useful components from discarded materials and reuse them for production or other purposes. It usually includes classification, screening, magnetic separation and flotation steps. The appropriate recycling process should be selected according to the composition and properties of the discarded material.

[0058] Harmless treatment refers to the treatment of discarded materials that do not contain valuable components. The purpose is to remove or convert harmful components in discarded materials into harmless substances. It usually includes physical treatment (such as landfill, incineration), chemical treatment (such as neutralization, oxidation-reduction) and biological treatment (such as composting, biodegradation). The appropriate harmless process should be selected according to the composition and properties of the discarded material.

[0059] Step S8, pre-process and feature extraction of the data uploaded during the sampling process by the intelligent control system, and visualize the sampling process; In step S8, the following sub-steps are included: S8-1, the intelligent control system acquires sampling and preparation process data uploaded from the automatic sampling device, the automatic crushing device, the automatic screening device, the automatic quartering device, the drying device, the packaging device and the loading and unloading device, and the sampling and preparation process data includes coal quality data, crushing monitoring data, screening monitoring data, quartering monitoring data, drying monitoring data, packaging monitoring data and loading and unloading monitoring data; S8-2, data cleaning and format conversion are performed on the sampling and preparation process data to obtain formatted sampling and preparation process data, data analysis and feature extraction are performed on the sampling and preparation process data through a classification algorithm of a support vector machine to obtain feature information of the sampling and preparation process; S8-3, according to the feature information of the sampling and preparation process, the Tableau is used to visually display the whole process of the sampling and preparation process.

[0060] It should be noted that data cleaning and format conversion are important steps of data preprocessing, and the purpose is to convert the collected original data into a format suitable for analysis and processing, data cleaning includes removing duplicate data, processing missing values, correcting error data and removing outliers, data format conversion includes data type conversion (converting data to integers, floating-point numbers or strings), data standardization (converting data to a unified range such as [0, 1]), and data encoding (converting categorical data to numerical form such as one-hot encoding or label encoding).

[0061] Support vector machine (SVM) is a powerful machine learning algorithm for data classification and regression analysis, in this patent, SVM is used for classification and feature extraction of sampling and preparation process data, and the working principle is to find the optimal segmentation hyperplane to divide the data into different categories, and to maximize the interval between categories to improve the accuracy and robustness of classification.

[0062] Tableau is a powerful data visualization tool for visually displaying complex data features in the form of graphs or charts, and it supports multiple data sources and provides rich visualization functions.

[0063] Please refer to Figure 2 , which shows a system structure diagram of an intelligent coal sampling and preparation system for a power plant according to an embodiment of the present application, and the system comprises: Automatic sampling device: for intercepting a coal sample from a coal flow; Automatic crushing device: for crushing the intercepted coal sample to obtain a crushed coal sample; Automatic screening device: for screening the crushed coal sample to obtain a screened coal sample; Automatic quartering device: for quartering the screened coal sample to obtain a quartered coal sample; Drying device: used for drying the split coal sample to obtain a dried coal sample; Sealing device: used for sealing the dried coal sample to obtain a sealed coal sample; Loading and unloading device: used for batch loading and unloading the sealed coal sample, and recycling the rejected material generated during the sampling and preparation process; Intelligent control system: used for receiving the sampling and preparation process data uploaded by the above devices and performing data analysis, feature extraction, and visual display of the sampling and preparation process.

[0064] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can still be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. An intelligent coal sampling method for power plants, characterized in that, The method comprises: Step S1, intercepting a coal sample from a coal flow by an automatic sampling device; Step S2, crushing the coal sample by an automatic crushing device to obtain a crushed coal sample; Step S3, screening the crushed coal sample by an automatic screening device to obtain a screened coal sample; Step S4, sub-sampling the screened coal sample by an automatic sub-sampling device to obtain a sub-sampled coal sample; Step S5, drying the sub-sampled coal sample by a drying device, and detecting the moisture content by an online total water tester to obtain a dried coal sample; Step S6, sealing and packaging the dried coal sample by a sealing and packaging device to obtain a packaged coal sample; Step S7, batch loading and unloading the packaged coal sample, and recycling the rejected material generated during the sampling and preparation process; Step S8, preprocessing and feature extraction of the data uploaded during the sampling and preparation process by an intelligent control system, and visualizing the sampling and preparation process.

2. The intelligent sampling and preparation method for power plant coal according to claim 1, wherein in step S1, the following sub-steps are further included: S1-1, presetting the operation parameters of the automatic sampling device, the automatic sampling device comprising a sampling head, a sampling arm, a driving device and a sampling control module, the operation parameters comprising a sampling mode and a sampling frequency, the automatic sampling device intercepting a coal sample from a coal flow according to the preset operation parameters and conveying the intercepted coal sample to the crushing device; S1-2, monitoring the coal quality data of the coal flow in real time by a multi-modal sensor during the operation of the automatic sampling device, and transmitting the coal quality data to the intelligent control system, the multi-modal sensor comprising a moisture sensor, an ash sensor and a sulfur sensor, the coal quality data comprising the moisture content, ash content and sulfur content of the coal flow; S1-3, performing data processing and feature analysis on the coal quality data by the sampling control module to obtain the coal quality change, and adjusting the operation parameters of the automatic sampling device according to the coal quality change.

3. The intelligent sampling and preparation method for power plant coal according to claim 1, wherein in step S2, the following sub-steps are further included: S2-1, capturing the image of the coal sample by an industrial camera, and analyzing the image of the coal sample by an image analysis method to obtain the initial particle size of the coal sample; S2-2, setting the operation parameters of the automatic crushing device according to the initial particle size of the coal sample, the automatic crushing device comprising a crusher, a distribution device and a crushing control module, the operation parameters comprising a feeding speed, a distribution device rotation speed, a crusher rotation speed and a crushing intensity; S2-3, the automatic crushing device crushing the coal sample according to the set operation parameters to obtain a crushed coal sample and a crushing rejected material, and monitoring the crushing process in real time by the crushing control module to obtain crushing monitoring data and upload the crushing monitoring data to the intelligent control system, the crushing monitoring data comprising the time of the coal sample input into the automatic crushing device, the initial particle size of the coal sample, the operation parameters of the automatic crushing device and the time of the crushed coal sample being discharged.

4. The intelligent sampling and preparation method for power plant coal according to claim 1, wherein ​ ​ Wherein in step S3, further comprising the following sub-steps: S3-1, preset the operation parameters of the automatic screening device, the automatic screening device comprising a first screen, a second screen, a first discharge port, a second discharge port, a bottom discharge port, a screen vibration device and a screening control module, the operation parameters comprising screen vibration frequency, feeding speed and discharge speed; S3-2, the automatic screening device screens the crushed coal sample according to the operation parameters to obtain a screened coal sample and screening waste, the screened coal sample comprising a large-size coal sample, a medium-size coal sample and a small-size coal sample, the screening process comprising: retaining the large-size coal sample through the first screen and discharging the large-size coal sample through the first discharge port; retaining the medium-size coal sample through the second screen and discharging the medium-size coal sample through the second discharge port; discharging the small-size coal sample through the bottom discharge port; S3-3, the screening control module monitors the screening process in real time to obtain screening monitoring data and upload the screening monitoring data to the intelligent control system, the screening monitoring data comprising the time when the crushed coal sample is input into the automatic screening device, the operation parameters of the automatic screening device and the time when the screened coal sample is discharged from each discharge port.

5. The intelligent coal sampling method for power plants according to claim 1, wherein: Wherein in step S4, further comprising the following sub-steps: S4-1, preset the operation parameters of the automatic sample splitting device, the automatic sample splitting device comprising a sample splitter, a vibration device, a collection device and a sample splitting control module, the operation parameters comprising sample splitting ratio, vibration frequency, feeding speed and discharge speed; S4-2, the automatic sample splitting device splits the screened coal sample according to the operation parameters to obtain a split coal sample and split waste, and monitors the splitting process in real time to obtain splitting monitoring data and upload the splitting monitoring data to the intelligent control system, the splitting monitoring data comprising the time when the screened coal sample is input into the automatic sample splitting device, the operation parameters of the automatic sample splitting device and the time when the split coal sample is discharged.

6. The intelligent coal sampling method for power plants according to claim 1, wherein: Wherein in step S5, further comprising the following sub-steps: S5-1, preset the operation parameters of the drying device, the drying device comprising a drying box, a hot air device, a stirring device and a drying control module, the operation parameters comprising drying temperature, drying time and hot air flow; S5-2, the drying device dries the split coal sample according to the operation parameters to obtain a dried coal sample and drying waste, and monitors the drying process in real time to obtain drying monitoring data and upload the drying monitoring data to the intelligent control system, the drying monitoring data comprising the time when the split coal sample is input into the drying device, the operation parameters of the drying device and the time when the dried coal sample is discharged; S5-3, the automatic sampling device samples the dried coal sample in batches to obtain a test sample for moisture detection. S5-4, presetting operation parameters of the online total moisture tester and a moisture content standard for calibration, the operation parameters including a test temperature and a test time, and the online total moisture tester detecting moisture of the test sample by infrared absorption method according to the preset operation parameters to obtain a sample moisture content; S5-5, comparing the sample moisture content with the moisture content standard for calibration to determine whether the sample moisture content is qualified, if yes, conveying the sub-sampled coal sample of the sample corresponding batch to the packaging equipment, and if no, returning the sub-sampled coal sample of the sample corresponding batch to the drying equipment for re-drying.

7. The intelligent coal sampling method for power plants according to claim 1, wherein in step S6, the following sub-steps are further included: S6-1, presetting operation parameters of the packaging equipment, the packaging equipment including a packaging container, a sealing device, a filling device and a packaging control module, the operation parameters including a filling speed, a sealing pressure and a packaging time; S6-2, the packaging equipment sealing and packaging the dried coal sample according to the operation parameters to obtain packaged coal samples and packaging waste, and the packaging control module monitoring the sealing and packaging process in real time to obtain packaging monitoring data and upload the same to the intelligent control system, the packaging monitoring data including a time when the dried coal sample is input into the packaging equipment, the operation parameters of the packaging equipment and a time when the packaged coal sample is discharged; S6-3, printing a bar code on each batch of the packaged coal sample by a printer, the bar code being used for marking the batch of the packaged coal sample.

8. The intelligent coal sampling method for power plants according to claim 1, wherein in step S7, the following sub-steps are further included: S7-1, temporarily storing the packaged coal sample in a stock bin and extracting the batch of the packaged coal sample by a fixed bar code scanner; S7-2, transferring the packaged coal sample from the stock bin to a transport vehicle by an automatic loading and unloading robot and monitoring the loading and unloading process in real time by a sensor to obtain loading and unloading monitoring data, the loading and unloading monitoring data including a stock-in time, a transfer time and operator information of each batch of coal sample stored in the stock bin and uploading the same to the intelligent control system; S7-3, temporarily storing waste generated in the sampling process in a waste stock bin, the waste including crushing waste, screening waste, sub-sampling waste, drying waste and packaging waste, and recording a source and a stock-in time of the waste; S7-4, analyzing a composition of the waste by infrared spectrum analysis method to determine whether the waste contains valuable components that can be recycled, if yes, recycling the waste containing the valuable components, and if no, non-hazardous treatment of the waste not containing the valuable components.

9. The intelligent coal sampling method for power plants according to claim 1, wherein in step S8, the following sub-steps are further included: ​ ​ ​ S8-1, the intelligent control system acquires sampling and preparation process data uploaded from the automatic sampling device, the automatic crushing device, the automatic screening device, the automatic quartering device, the drying device, the packaging device and the loading and unloading device, wherein the sampling and preparation process data includes coal quality data, crushing monitoring data, screening monitoring data, quartering monitoring data, drying monitoring data, packaging monitoring data and loading and unloading monitoring data; S8-2, the sampling and preparation process data is subjected to data cleaning and format conversion to obtain formatted sampling and preparation process data, and the sampling and preparation process data is subjected to data analysis and feature extraction through a support vector machine classification algorithm to obtain feature information of the sampling and preparation process; S8-3, according to the feature information of the sampling and preparation process, the sampling and preparation process is visualized through Tableau.

10. An intelligent coal sampling system for power plants, characterized in that, The system comprises: an automatic sampling device for intercepting a coal sample from a coal flow; an automatic crushing device for crushing the intercepted coal sample to obtain a crushed coal sample; an automatic screening device for screening the crushed coal sample to obtain a screened coal sample; an automatic quartering device for quartering the screened coal sample to obtain a quartered coal sample; a drying device for drying the quartered coal sample to obtain a dried coal sample; a packaging device for sealing and packaging the dried coal sample to obtain a packaged coal sample; a loading and unloading device for loading and unloading the packaged coal sample in batches and recycling waste generated in the sampling and preparation process; an intelligent control system for receiving sampling and preparation process data uploaded from the above devices and performing data analysis, feature extraction and visualization of the sampling and preparation process.

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