CN115343318A - Passive ash content appearance remote calibration system based on wireless communication - Google Patents
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Abstract
The invention provides a passive ash content instrument remote calibration system based on wireless communication, belongs to the field of coal, and is used for solving the problem that coal in different areas and under different conditions adopts a unified detection standard. The system comprises a region division module, an ash analysis module, a force setting module and a history evaluation module, wherein the region division module is used for dividing a coal region to obtain a plurality of regions to be detected, the history evaluation module is used for analyzing the history detection condition of coal in the regions to be detected, the force evaluation value of the regions to be detected is obtained through analysis, the force setting module is used for setting the detection force of the regions to be detected, the ash analysis module is used for analyzing the ash condition of a coal sample, and a coal ash abnormal signal or a coal ash normal signal is generated through analysis. The invention can carry out differential detection on the coal ash content in different areas based on historical detection data.
Description
Technical Field
The invention relates to the field of coal, in particular to a passive ash content instrument remote calibration system based on wireless communication.
Background
The method is a method commonly adopted by the rapid coal quality on-line analyzer, and radioactive elements used by the method have the characteristics of low energy level, long service time, small dose and the like, so that the method is safe and reliable, and a radioactive source does not need to be replaced in the service life;
in the prior art, the common problems of coal ash content detection are as follows: aiming at the coals in different areas and under different conditions, unified detection standards, namely the same sample number, abnormal rate and the like are adopted, and corresponding ash content detection measures are not set aiming at actual conditions;
therefore, a passive ash analyzer remote calibration system based on wireless communication is provided.
Disclosure of Invention
In order to make up for the defects, the invention provides a passive ash analyzer remote calibration system based on wireless communication, and aims to solve the problem of how to perform differential detection on coal ash content in different areas based on historical detection data.
The embodiment of the invention provides a passive ash content instrument remote calibration system based on wireless communication, which comprises a passive ash content instrument and a processor arranged in the passive ash content instrument, wherein the processor is respectively and electrically connected with a server, a data acquisition module and an alarm terminal through leads; the user terminal is used for inputting the number of the area to be detected and sending the number to the big data module, and the big data module is used for acquiring historical detection data of the area to be detected and sending the historical detection data of the area to be detected to the historical evaluation module according to the number; the historical evaluation module is used for analyzing the historical detection condition of the coal in the region to be detected, analyzing the historical detection condition to obtain a force evaluation value of the region to be detected and feeding the force evaluation value back to the server, and the server sends the force evaluation value of the region to be detected to the force setting module; the force setting module is used for setting the detection force of the area to be detected, setting the detection grade of the area to be detected and feeding the detection grade back to the server, and the server sets corresponding detection parameters for the area to be detected according to the detection grade; the data acquisition module acquires coal data of a corresponding number of coal samples in the area to be detected by combining detection parameters and sends the coal data to the processor, the processor sends the coal data to the server, and the server sends the coal data to the ash content analysis module; the ash content analysis module is used for analyzing the ash content of the coal sample and analyzing to generate a coal ash content abnormal signal or a coal ash content normal signal.
In a specific embodiment, the historical detection data is the detection times of the to-be-detected area, the detection time of each detection, the number of samples and the sample abnormality rate; the detection parameters comprise a sample standard ash content, a sample standard number and a sample standard abnormal rate; the coal data includes the weight, moisture content, ash content, calorific value, coulomb sulfur content, and fixed carbon content of the coal sample.
In a specific embodiment, the analysis process of the history evaluation module is specifically as follows: acquiring the detection times, detection interval time, sample average number and sample abnormal average rate of the area to be detected; and calculating a strength evaluation value of the to-be-detected area.
In a specific embodiment, the setting process of the force setting module is as follows: acquiring a strength evaluation value of the area to be detected; and comparing the strength evaluation value with a strength evaluation threshold value, and judging that the detection grade of the to-be-detected area is a third detection grade, a second detection grade or a first detection grade.
In a specific embodiment, the detection strength of the first detection level is greater than the detection strength of the second detection level, and the detection strength of the second detection level is greater than the detection strength of the third detection level.
In a specific embodiment, the amount of sample standard ash of the first detection grade is less than the amount of sample standard ash of the second detection grade, which is less than the amount of sample standard ash of the third detection grade; the number of sample standards of the first detection grade is greater than the number of sample standards of the second detection grade, and the number of sample standards of the second detection grade is greater than the number of sample standards of the third detection grade; the standard sample abnormality rate of the first detection grade is lower than that of the second detection grade, and the standard sample abnormality rate of the second detection grade is lower than that of the third detection grade.
In a specific embodiment, the analysis process of the ash analysis module is specifically as follows: acquiring a real-time weight value, a moisture content, a coulomb sulfur content, a volatile component and a fixed carbon content of a coal sample; calculating the ash content of the coal samples, and comparing the ash content of all the coal samples with the standard ash content of the samples; if the ash content of the coal sample meets the standard ash content of the sample, the coal sample is marked as a normal coal sample, and if the ash content of the coal sample does not meet the standard ash content of the sample, the coal sample is marked as an abnormal coal sample; counting the number of the abnormal coal samples, and comparing the number of the abnormal coal samples with the standard number of the samples to obtain the real-time abnormal rate of the samples in the area to be detected; and if the real-time sample abnormality rate does not meet the standard sample abnormality rate, generating a coal ash abnormality signal, and if the real-time sample abnormality rate meets the standard sample abnormality rate, generating a coal ash normal signal.
In a specific embodiment, the ash analysis module feeds back a coal ash abnormal signal or a coal ash normal signal to the server; if the server receives a coal ash normal signal, no operation is performed; if the server receives coal ash abnormal signal, then send coal ash abnormal signal to user terminal with the treater, staff at user terminal end is used for looking over the appointed coal ash condition of waiting to examine the region, the treater generates alarm instruction after receiving coal ash abnormal signal and loads to the alarm terminal, the alarm terminal is arranged in treating to examine the coal ash condition of region and reports to the police.
Compared with the prior art, the invention has the beneficial effects that:
the coal ash content detection method comprises the steps of dividing a coal area through an area dividing module to obtain a plurality of areas to be detected, analyzing historical detection conditions of coal in the areas to be detected through a historical evaluation module, calculating to obtain a force evaluation value of the areas to be detected, sending the force evaluation value of the areas to be detected to a force setting module through the historical evaluation module, setting detection force of the areas to be detected through the force setting module to obtain detection levels of the areas to be detected, setting corresponding detection parameters for the areas to be detected through a server according to the detection levels, collecting coal data of corresponding quantity of coal samples in the areas to be detected according to the detection parameters, and finally analyzing ash content conditions of the coal samples through an ash content analysis module to generate coal ash content abnormal signals or coal ash content normal signals.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
FIG. 1 is an overall system block diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings of the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
Example 1
Referring to fig. 1, a passive ash meter remote calibration system based on wireless communication comprises a passive ash meter and a processor arranged in the passive ash meter, wherein the processor is respectively and electrically connected with a server, a data acquisition module and an alarm terminal through wires, the server is provided with a region division module, an ash analysis module, a force setting module, a history evaluation module, a big data module and a user terminal, and the region division module is used for dividing coal regions to obtain a plurality of regions to be detected and adding mark numbers and then sending the regions to the server; the user terminal is used for inputting the serial number of the area to be detected and sending the serial number to the big data module, and the big data module is used for acquiring historical detection data of the area to be detected and sending the historical detection data of the area to be detected to the historical evaluation module according to the serial number.
The historical evaluation module is used for analyzing the historical detection condition of the coal in the area to be detected, the force evaluation value of the area to be detected is obtained through analysis and fed back to the server, and the server sends the force evaluation value of the area to be detected to the force setting module; the strength setting module is used for setting the detection strength of the area to be detected, setting the detection grade of the area to be detected and feeding the detection grade back to the server, and the server sets corresponding detection parameters for the area to be detected according to the detection grade.
The data acquisition module acquires coal data of a corresponding number of coal samples in the area to be detected by combining the detection parameters and sends the coal data to the processor, the processor sends the coal data to the server, and the server sends the coal data to the ash content analysis module; the ash content analysis module is used for analyzing the ash content of the coal sample and analyzing to generate a coal ash content abnormal signal or a coal ash content normal signal.
In the specific setting, the historical detection data comprises the detection times of the to-be-detected region, the detection time, the sample number and the sample abnormal rate of each detection, the detection parameters comprise the sample standard ash content, the sample standard number and the sample standard abnormal rate, and the coal data comprises the weight, the moisture content, the ash content, the heat productivity, the coulomb sulfur content and the fixed carbon content of the coal sample.
In the solution of this embodiment, the analysis process of the history evaluation module is specifically as follows: acquiring the detection times, the detection interval, the sample average and the sample abnormal average rate of a to-be-detected area; and calculating a strength evaluation value of the to-be-detected area.
When the force setting module is specifically set, the setting process of the force setting module is specifically as follows: acquiring a strength evaluation value of the area to be detected; and comparing the strength evaluation value with a strength evaluation threshold value, and judging that the detection grade of the to-be-detected area is a third detection grade, a second detection grade or a first detection grade.
In the solution of this specific embodiment, the detection strength of the first detection level is greater than the detection strength of the second detection level, and the detection strength of the second detection level is greater than the detection strength of the third detection level.
In specific setting, the standard ash content of the sample of the first detection level is less than that of the sample of the second detection level, and the standard ash content of the sample of the second detection level is less than that of the sample of the third detection level; the number of the sample standards of the first detection level is larger than that of the sample standards of the second detection level, and the number of the sample standards of the second detection level is larger than that of the sample standards of the third detection level; the standard sample abnormity rate of the first detection grade is less than that of the second detection grade, and the standard sample abnormity rate of the second detection grade is less than that of the third detection grade.
In this embodiment, the analysis process of the ash analysis module is specifically as follows: acquiring a real-time weight value, a moisture content, a coulomb sulfur content, a volatile component and a fixed carbon content of a coal sample; calculating the ash content of the coal samples, and comparing the ash content of all the coal samples with the standard ash content of the samples; if the ash content of the coal sample meets the standard ash content of the sample, the coal sample is marked as a normal coal sample, and if the ash content of the coal sample does not meet the standard ash content of the sample, the coal sample is marked as an abnormal coal sample; counting the number of the abnormal coal samples, and comparing the number of the abnormal coal samples with the standard number of the samples to obtain the real-time abnormal rate of the samples in the area to be detected; and if the real-time sample abnormality rate does not meet the standard sample abnormality rate, generating a coal ash abnormality signal, and if the real-time sample abnormality rate meets the standard sample abnormality rate, generating a coal ash normal signal.
In a specific embodiment, the ash analysis module feeds back a coal ash abnormal signal or a coal ash normal signal to the server; if the server receives a normal coal ash signal, no operation is performed; if the server receives the coal ash abnormal signal, the coal ash abnormal signal is sent to the user terminal and the processor, workers at the user terminal are used for checking the coal ash condition in the specified region to be detected, the processor generates an alarm instruction after receiving the coal ash abnormal signal and loads the alarm instruction to the alarm terminal, and the alarm terminal is used for alarming the coal ash condition in the region to be detected.
Example 2
Referring to fig. 1, in the present embodiment, a passive ash meter remote calibration system based on wireless communication is provided, including a passive ash meter and a processor disposed in the passive ash meter, where the processor is electrically connected to a server, a data acquisition module and an alarm terminal through wires, respectively, and the server is provided with a region division module, an ash analysis module, a force setting module, a history evaluation module, a big data module and a user terminal.
And the user terminal is used for registering and logging in the system after the staff inputs the personal information and sending the personal information to the server for storage. The personal information includes the name of the staff, the mobile phone number of the real-name authentication, the work number and the like. After registration and login are successful, the area dividing module is used for dividing the coal area to obtain a plurality of areas to be detected, the number u of the areas to be detected is added with a mark number u and then the areas to be detected are sent to the server, and u =1,2, \8230;, z and z are positive integers.
The user terminal is used for inputting the serial number of the area to be detected and sending the serial number to the big data module, and the big data module is used for acquiring historical detection data of the area to be detected and sending the historical detection data of the area to be detected to the historical evaluation module according to the serial number.
Specifically, the historical detection data includes the number of times of detection of the region to be detected, the detection time per detection, the number of samples, the sample abnormality rate, and the like.
The historical evaluation module is used for analyzing the historical detection condition of the coal in the region to be detected, and the analysis process is as follows:
step S1: acquiring the detection times of the area to be detected, and marking the detection times as JCu;
step S2: acquiring the detection time of the region to be detected in each detection and calculating the detection interval duration in each detection, adding the detection interval durations in each detection and taking the average value to obtain JTJu when the detection intervals of the region to be detected are uniform;
and step S3: acquiring the number of samples and the sample abnormality rate of the area to be detected in each detection, and adding and dividing the number of samples in each detection by the detection times to obtain the sample average number JYSu of the area to be detected;
and step S4: in a similar way, the sample abnormal rate in each detection is added and summed up, and is divided by the detection times to obtain the sample abnormal average rate JYLU of the area to be detected;
step S5: by the formula
Calculating to obtain a strength evaluation value LPu of the area to be detected; a1 and a2 are proportionality coefficients with fixed numerical values, and the values of a1 and a2 are both larger than zero.
The historical evaluation module feeds back the force evaluation value LPu of the region to be detected to the server, and the server sends the force evaluation value LPu of the region to be detected to the force setting module.
The strength setting module is used for setting the detection strength of the region to be detected, and the setting process is as follows:
step SS1: obtaining the calculated force evaluation value LPu of the area to be detected;
step SS2: if LPu is less than X1, the detection grade of the to-be-detected area is a third detection grade;
step SS3: if X1 is not more than LPu and less than X2, the detection level of the to-be-detected area is a second detection level;
and step SS4: if X2 is less than or equal to LPu, the detection level of the to-be-detected area is a first detection level; wherein X1 and X2 are both strength evaluation threshold values with fixed numerical values, and X1 is more than X2.
The force setting module feeds back the detection grade of the area to be detected to the server, and the server sets corresponding detection parameters for the area to be detected according to the detection grade. The detection parameters comprise a sample standard ash content, a sample standard number and a sample standard abnormal rate.
It can be understood that the detection strength of the first detection level is greater than that of the second detection level, and the detection strength of the second detection level is greater than that of the third detection level.
The standard ash content of the sample of the first detection level is less than that of the sample of the second detection level, and the standard ash content of the sample of the second detection level is less than that of the sample of the third detection level; the number of the sample standards of the first detection level is larger than that of the sample standards of the second detection level, and the number of the sample standards of the second detection level is larger than that of the sample standards of the third detection level; the standard sample abnormity rate of the first detection grade is less than that of the second detection grade, and the standard sample abnormity rate of the second detection grade is less than that of the third detection grade.
The data acquisition module combines the coal data of the corresponding quantity of coal samples in the area to be detected to detect the parameters, and sends the coal data of the coal samples to the processor, the processor sends the coal data to the server, and the server sends the coal data to the ash content analysis module. Specifically, the coal data includes the weight, moisture content, ash content, calorific value, coulomb sulfur content, fixed carbon content, and the like of the coal sample.
In specific implementation, the coal data of the coal sample can be obtained through related equipment such as a weight sensor, a moisture detection workstation, an ash content detection workstation, a heating value detection workstation, a coulomb sulfur content detection workstation and the like, the fixed carbon content means that the measured moisture, ash and volatile components are subtracted from the total weight by a laboratory method, the difference value is the percentage of the original sample carbon, and the fixed carbon content is the fixed carbon content. The size of the carbon-containing carbon-based composite material is increased along with the rise of the temperature of calcined charcoal, the carbon content of the charcoal is about 80% generally, and the heat productivity is measured by a double-barrel calorimeter, which is the prior art and is not described in detail.
The ash content analysis module is used for analyzing the ash content of the coal sample, and the analysis process is as follows:
the method comprises the following steps: acquiring a real-time weight value of a coal sample, and marking the real-time weight value as SZui, i =1,2, \8230, wherein x and x are positive integers, and i represents the number of the coal sample;
step two: acquiring the moisture content of a coal sample, and marking the moisture content as a SLui; obtaining the coulomb sulfur content of the coal sample, and marking the coulomb sulfur content as KLui;
step three: obtaining the volatile component of the coal sample, and marking the volatile component as HLui; obtaining the fixed carbon content of a coal sample, and marking the fixed carbon content as TLui;
step four: calculating the ash content FLUI of the coal sample by using a formula FLUI = SZui-SLu-KLui-HLui-TLui-alpha; alpha is a preset loss amount;
step five: comparing the ash content of all the coal samples with the standard ash content of the samples, and if the ash content of the coal samples meets the standard ash content of the samples, calibrating the coal samples into normal coal samples; if the ash content of the coal sample does not meet the standard ash content of the sample, marking the coal sample as an abnormal coal sample;
step six: counting the number of the abnormal coal samples, and comparing the number of the abnormal coal samples with the standard number of the samples to obtain the real-time abnormal rate of the samples in the area to be detected; in specific implementation, the standard ash content of the sample and the real-time abnormal rate of the sample are both range intervals;
step seven: if the real-time abnormal rate of the sample does not meet the standard abnormal rate of the sample, generating a coal ash abnormal signal; if the real-time abnormal rate of the sample meets the standard abnormal rate of the sample, generating a coal ash normal signal; the ash content analysis module feeds back the coal ash content abnormal signal or the coal ash content normal signal to the server; if the server receives a normal coal ash content signal, no operation is carried out; if the server receives the coal ash abnormal signal, the coal ash abnormal signal is sent to the user terminal and the processor, workers at the user terminal are used for checking the coal ash condition in the specified region to be detected, the processor generates an alarm instruction after receiving the coal ash abnormal signal and loads the alarm instruction to the alarm terminal, and the alarm terminal is used for alarming the coal ash condition in the region to be detected; and each region to be detected can be correspondingly provided with an alarm terminal.
Example 3
In this embodiment, a working method of a passive ash analyzer remote calibration system based on wireless communication is provided, and the working method specifically includes:
step S101, after registration and login are successful, a region dividing module divides a coal region to obtain a plurality of regions to be detected, the number u of the regions to be detected is added and then sent to a server, a user terminal inputs the number of the regions to be detected and sends the number to a big data module, the big data module obtains historical detection data of the regions to be detected and sends the historical detection data of the regions to be detected to a historical evaluation module according to the number;
step S102, analyzing the historical detection condition of coal in the region to be detected through a historical evaluation module to obtain the detection times JCu of the region to be detected, then obtaining the detection time of each detection of the region to be detected and calculating the detection interval duration of each detection, adding and summing the detection interval durations of each detection to obtain the average detection interval JTJu of the region to be detected, finally obtaining the number of samples and the sample abnormality rate of each detection of the region to be detected, adding and summing the number of samples of each detection and dividing the number of the samples by the detection times to obtain the number of the detection timesThe average sample number JYSu of the region is obtained by adding the sample abnormal rates in each detection and dividing the sum by the detection times to obtain the sample abnormal average rate JYLU of the region to be detected, and the average sample abnormal rate JYLU is obtained by a formula
Calculating to obtain a strength evaluation value LPu of the area to be detected, feeding the strength evaluation value LPu of the area to be detected back to the server by the history evaluation module, and sending the strength evaluation value LPu of the area to be detected to the strength setting module by the server;
step S103, setting the detection strength of the to-be-detected area by using a strength setting module, obtaining the strength evaluation value LPu of the to-be-detected area obtained by the calculation, if LPu is less than X1, the detection grade of the to-be-detected area is a third detection grade, if X1 is less than or equal to LPu and less than X2, the detection grade of the to-be-detected area is a second detection grade, if X2 is less than or equal to LPu, the detection grade of the to-be-detected area is a first detection grade, feeding the detection grade of the to-be-detected area back to a server by using the strength setting module, and setting corresponding detection parameters for the to-be-detected area by the server according to the detection grade;
step S104, collecting coal data of a corresponding number of coal samples in the area to be detected by the data collection module in combination with the detection parameters, sending the coal data of the coal samples to a processor, sending the coal data to a server by the processor, and sending the coal data to an ash content analysis module by the server;
step S105, analyzing the ash content of the coal sample by using an ash content analysis module, obtaining a real-time weight value SZui, a water content SLu, a coulomb sulfur content KLui, a volatile component HLui and a fixed carbon content of the coal sample, calculating by a formula FLUi = SZui-SLu-KLui-HLui-TLui-alpha to obtain an ash content FLUi of the coal sample, comparing the ash content of all the coal samples with a sample standard ash content, calibrating the coal sample to be a normal coal sample if the ash content of the coal sample conforms to the sample standard ash content, marking the coal sample as an abnormal coal sample if the ash content of the coal sample does not conform to the sample standard ash content, counting the number of the abnormal coal sample, comparing the number of the abnormal coal sample with the number of the standard ash content to obtain a sample real-time abnormal rate of the area to be detected, generating a coal ash content abnormal signal if the real-time abnormal ash content of the coal sample does not conform to the sample standard ash content, generating a coal ash content abnormal signal if the real-time abnormal rate of the coal sample conforms to the abnormal rate of the standard ash content of the abnormal coal sample, sending the ash content to the abnormal coal sample to the normal coal sample to the ash content detection area to the alarm server, sending the ash content alarm server to the coal processing terminal, and sending the ash content alarm to the alarm server, and sending the alarm to the alarm server to the alarm.
The above formulas are all calculated by taking the numerical value of the dimension, the formula is a formula of the latest real situation obtained by collecting a large amount of data and performing software simulation, the preset parameters in the formula are set by the technical personnel in the field according to the actual situation, the weight coefficient and the scale coefficient are specific numerical values obtained by quantizing each parameter, and the subsequent comparison is convenient.
The above description is only an example of the present invention, and is not intended to limit the scope of the present invention, and various modifications and changes may be made to the present invention by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily think of the changes or substitutions within the technical scope of the present invention, and shall cover the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. A passive ash meter remote calibration system based on wireless communication is characterized by comprising a passive ash meter and a processor arranged in the passive ash meter, wherein the processor is respectively and electrically connected with a server, a data acquisition module and an alarm terminal through wires, the server is provided with a region division module, an ash analysis module, a force setting module, a history evaluation module, a big data module and a user terminal, and the region division module is used for dividing coal regions to obtain a plurality of regions to be detected and adding mark numbers and then sending the regions to the server; the user terminal is used for inputting the number of the area to be detected and sending the number to the big data module, and the big data module is used for acquiring historical detection data of the area to be detected and sending the historical detection data of the area to be detected to the historical evaluation module according to the number;
the historical evaluation module is used for analyzing the historical detection condition of the coal in the area to be detected, the force evaluation value of the area to be detected is obtained through analysis and fed back to the server, and the server sends the force evaluation value of the area to be detected to the force setting module; the force setting module is used for setting the detection force of the area to be detected, setting the detection grade of the area to be detected and feeding the detection grade back to the server, and the server sets corresponding detection parameters for the area to be detected according to the detection grade;
the data acquisition module acquires coal data of a corresponding quantity of coal samples in a region to be detected by combining detection parameters and sends the coal data to the processor, the processor sends the coal data to the server, and the server sends the coal data to the ash content analysis module; the ash content analysis module is used for analyzing the ash content of the coal sample and analyzing to generate a coal ash content abnormal signal or a coal ash content normal signal.
2. The passive ash analyzer remote calibration system based on wireless communication as claimed in claim 1, wherein the historical detection data is the detection times of the area to be detected and the detection time, the number of samples and the sample abnormality rate of each detection;
the detection parameters comprise a sample standard ash content, a sample standard number and a sample standard abnormal rate;
the coal data includes the weight, moisture content, ash content, calorific value, coulomb sulfur content, and fixed carbon content of the coal sample.
3. The passive ash meter remote calibration system based on wireless communication according to claim 1, wherein the analysis process of the history evaluation module is as follows:
acquiring the detection times, detection interval time, sample average number and sample abnormal average rate of the area to be detected;
and calculating a strength evaluation value of the to-be-detected area.
4. The passive ash meter remote calibration system based on wireless communication according to claim 1, wherein the setting process of the force setting module is as follows:
acquiring a strength evaluation value of the area to be detected;
and comparing the strength evaluation value with a strength evaluation threshold value, and judging the detection grade of the to-be-detected region as a third detection grade, a second detection grade or a first detection grade.
5. The passive ash analyzer remote calibration system based on wireless communication of claim 4, wherein the detection strength of the first detection level is greater than the detection strength of the second detection level, and the detection strength of the second detection level is greater than the detection strength of the third detection level.
6. The wireless communication based remote calibration system for the passive ash meter according to claim 5, wherein the standard ash content of the sample of the first detection level is less than the standard ash content of the sample of the second detection level, and the standard ash content of the sample of the second detection level is less than the standard ash content of the sample of the third detection level; the number of sample standards of the first detection grade is greater than the number of sample standards of the second detection grade, and the number of sample standards of the second detection grade is greater than the number of sample standards of the third detection grade; the standard sample abnormality rate of the first detection grade is lower than that of the second detection grade, and the standard sample abnormality rate of the second detection grade is lower than that of the third detection grade.
7. The system for remotely calibrating a passive ash analyzer based on wireless communication as claimed in claim 1, wherein the analysis process of the ash analysis module is as follows:
acquiring a real-time weight value, a moisture content, a coulomb sulfur content, a volatile component and a fixed carbon content of a coal sample;
calculating the ash content of the coal samples, and comparing the ash content of all the coal samples with the standard ash content of the samples;
if the ash content of the coal sample meets the standard ash content of the sample, the coal sample is marked as a normal coal sample, and if the ash content of the coal sample does not meet the standard ash content of the sample, the coal sample is marked as an abnormal coal sample;
counting the number of the abnormal coal samples, and comparing the number of the abnormal coal samples with the standard number of the samples to obtain the real-time abnormal rate of the samples in the area to be detected;
and if the real-time sample abnormality rate does not meet the standard sample abnormality rate, generating a coal ash abnormality signal, and if the real-time sample abnormality rate meets the standard sample abnormality rate, generating a coal ash normal signal.
8. The remote calibration system of the passive ash meter based on the wireless communication is characterized in that the ash analysis module feeds back a coal ash abnormal signal or a coal ash normal signal to the server;
if the server receives a coal ash normal signal, no operation is performed;
if the server receives coal ash abnormal signal, then send coal ash abnormal signal to user terminal with the treater, staff at user terminal end is used for looking over the appointed coal ash condition of waiting to examine the region, the treater generates alarm instruction after receiving coal ash abnormal signal and loads to the alarm terminal, the alarm terminal is arranged in treating to examine the coal ash condition of region and reports to the police.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117119503A (en) * | 2023-10-18 | 2023-11-24 | 山西腾炎科技有限公司 | Intelligent mine data acquisition method based on 5G industrial Internet |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117119503A (en) * | 2023-10-18 | 2023-11-24 | 山西腾炎科技有限公司 | Intelligent mine data acquisition method based on 5G industrial Internet |
| CN117119503B (en) * | 2023-10-18 | 2024-01-23 | 山西腾炎科技有限公司 | Intelligent mine data acquisition method based on 5G industrial Internet |
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