Fuel blind box sampling system and method for thermal power plant

Abstract

The present application relates to coal sampling equipment control technical field, the present application provides thermal power plant fuel blind box formula sampling system and method, including control device vehicle code and time stamp generation random discrete sequence is collected, total sampling weight threshold is split into a plurality of initial sampling weight set value and corresponding secondary compensation weight set value, logical scheduling module is according to the above set value output scheduling instruction, control equipment device switching blanking channel corresponding sampling barrel, the present application is completed by two rounds of random non-equal distribution mechanism complementary sampling, breaks the conventional continuous sampling rule, hides the equipment running track, effectively prevents artificial prediction and malicious intervention adulteration, effectively guarantees the objectivity and fairness of the coal quality acceptance work in the plant.

Description

Technical Field

[0001] This invention relates to the field of coal sampling equipment control technology, and in particular to a blind-box sampling system and method for fuel in thermal power plants. Background Technology

[0002] When a thermal power plant receives coal transported from outside, it needs to perform an incoming coal sampling and acceptance operation. Existing incoming coal sampling systems typically use a continuous sampling mode, that is, the sampling equipment continuously collects samples of the same batch of coal in a fixed time sequence, and the extracted coal will eventually fall into specific collection bins in sequence.

[0003] Because uneven quality distribution is common within the stockpile of coal transported in the same batch, continuous sampling at fixed times can easily lead to overly concentrated coal sampling points. This concentration means that the coal collected in individual collection bins cannot accurately reflect the true quality of the entire batch of coal entering the plant, resulting in poor representativeness of coal samples obtained through continuous sampling.

[0004] Continuous sampling, accompanied by consistent equipment operation patterns, allows external personnel to observe and record the sequence of equipment actions, thus enabling them to predict the equipment's operational trajectory. Based on this clear sequence, external personnel can accurately estimate the specific collection bin number where the coal collected during a particular time period will ultimately fall. However, once the correspondence between time parameters and collection bins is established, it creates opportunities for human intervention. Subsequent human interference and adulteration will severely undermine the objectivity and impartiality of the incoming coal quality acceptance process. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a blind-box sampling system and method for fuel in thermal power plants. This invention solves the technical problem that existing continuous sampling patterns are easily inferred, resulting in poor representativeness of coal samples and susceptibility to human intervention.

[0006] To solve the above-mentioned technical problems, the specific contents of the present invention are as follows: In a first aspect, the present invention provides a fuel blind box sampling system for thermal power plants, comprising an equipment device and a control device, wherein the control device is connected to the equipment device; The device includes a sampling execution component, a sample collection component, and a material discharge channel. The sample collection component is equipped with multiple sampling barrels. The sampling execution component extracts coal samples from external coal and discharges the coal samples into the material discharge channel. The material discharge channel is connected to the corresponding sampling barrel. The sample collection component switches the sampling barrel corresponding to the material discharge channel. The control device includes a data acquisition module, a parameter mapping module, and a logic scheduling module; The data acquisition module collects the vehicle identification code sequence and the current timestamp, and sends the vehicle identification code sequence and the current timestamp to the parameter mapping module. The parameter mapping module receives the vehicle identification code sequence and the current timestamp. The parameter mapping module presets a total sampling weight threshold. The parameter mapping module calculates and generates a random seed based on the vehicle identification code sequence and the current timestamp. The parameter mapping module generates a random discrete sequence based on the random seed. The parameter mapping module splits the total sampling weight threshold into multiple initial sampling weight settings according to the random discrete sequence. The parameter mapping module subtracts each initial sampling weight setting from the total sampling weight threshold to obtain multiple corresponding secondary compensation weight settings. The parameter mapping module sends the multiple initial sampling weight settings and the multiple secondary compensation weight settings to the logic scheduling module. The logic scheduling module receives multiple initial sampling weight settings and multiple secondary compensation weight settings. The logic scheduling module sends a material dropping scheduling instruction to the equipment based on the multiple initial sampling weight settings and multiple secondary compensation weight settings. The equipment receives the material dropping scheduling instruction and switches the sampling bucket corresponding to the material dropping channel according to the material dropping scheduling instruction.

[0007] Furthermore, in the thermal power plant fuel blind box sampling system of the present invention, the equipment further includes a weighing monitoring component and a station sensing component. The weighing monitoring component is disposed at the bottom of the sample collection component and collects the weight simulation signal of the coal sample inside the sampling bucket. The weighing monitoring component sends the weight simulation signal to the control device. The station sensing component is deployed on the side of the sample collection component and collects the position signal of the material discharge channel relative to the sampling bucket. The station sensing component sends the position signal to the logic scheduling module.

[0008] Furthermore, in the thermal power plant fuel blind box sampling system of the present invention, the control device further includes a protocol encapsulation module and an analog-to-digital conversion module. The analog-to-digital conversion module receives the weight analog signal, converts the weight analog signal into a weight digital signal, and sends the weight digital signal to the logic scheduling module. The logic scheduling module receives the weight digital signal and the position signal, compares the weight digital signal, the position signal, a currently extracted initial sampling weight setting value, and the corresponding secondary compensation weight setting value, and outputs a material dropping scheduling command. The logic scheduling module sends the material dropping scheduling command to the protocol encapsulation module, which receives the material dropping scheduling command, converts the material dropping scheduling command into an encrypted data packet, and sends the encrypted data packet to the device.

[0009] Furthermore, in the thermal power plant fuel blind box sampling system of the present invention, the parameter mapping module includes a hash calculation unit. The hash calculation unit receives the vehicle identification code sequence and the current timestamp. The hash calculation unit performs hash calculation on the vehicle identification code sequence and the current timestamp to generate the random seed. The parameter mapping module obtains the random seed output by the hash calculation unit and generates the random discrete sequence based on the random seed.

[0010] Furthermore, in the thermal power plant fuel blind box sampling system of the present invention, the parameter mapping module further includes a data segmentation unit. The data segmentation unit acquires the random discrete sequence, extracts the total sampling weight threshold, and splits the total sampling weight threshold into multiple initial sampling weight settings according to the weight ratio of the random discrete sequence. The sum of the values ​​of the multiple initial sampling weight settings is less than the total sampling weight threshold.

[0011] Furthermore, in the thermal power plant fuel blind box sampling system of the present invention, the logic scheduling module includes a buffer area, the parameter mapping module constructs a first data array from multiple initial sampling weight settings, the parameter mapping module constructs a second data array from multiple secondary compensation weight settings, the parameter mapping module sends the first data array and the second data array to the logic scheduling module, the logic scheduling module receives the first data array and the second data array, and the logic scheduling module stores the first data array and the second data array in the buffer area.

[0012] Furthermore, in the thermal power plant fuel blind box sampling system of the present invention, the logic scheduling module is configured to extract an initial sampling weight setting value from the first data array. The logic scheduling module compares the weight digital signal with the currently extracted initial sampling weight setting value. When the weight digital signal value is equal to the currently extracted initial sampling weight setting value value, the logic scheduling module outputs the material dispensing scheduling instruction. The logic scheduling module sends the material dispensing scheduling instruction to the sample collection component. The sample collection component receives the material dispensing scheduling instruction and switches the sampling bucket corresponding to the material dispensing channel according to the material dispensing scheduling instruction.

[0013] Furthermore, in the thermal power plant fuel blind box sampling system of the present invention, the logic scheduling module further includes an interrupt processing unit and an index pointer unit. When the logic scheduling module outputs the material feeding scheduling command, the interrupt processing unit is activated. The interrupt processing unit controls the index pointer unit to increment its value. The index pointer unit extracts the next initial sampling weight setting value from the first data array for the next comparison.

[0014] Furthermore, in the thermal power plant fuel blind box sampling system of the present invention, the logic scheduling module is configured to generate and output a spatial reset signal after the index pointer unit completes the reading of the first data array. The logic scheduling module sends the spatial reset signal to the sample collection component. The sample collection component receives the spatial reset signal and shifts the material dropping channel to the first sampling bucket according to the spatial reset signal. The logic scheduling module controls the index pointer unit to extract a secondary compensation weight setting value from the second data array. The logic scheduling module compares the extracted secondary compensation weight setting value with the weight digital signal to output the material dropping scheduling command again. The logic scheduling module stops outputting the material dropping scheduling command after completing the comparison of the second data array.

[0015] Secondly, the fuel blind-box sampling method for thermal power plants provided by the present invention is applied to the fuel blind-box sampling system for thermal power plants as described above, including: Step 1: The data acquisition module collects the vehicle identification code sequence and the current timestamp, and sends the vehicle identification code sequence and the current timestamp to the parameter mapping module; Step 2: The parameter mapping module receives the vehicle identification code sequence and the current timestamp, calculates and generates a random seed based on the vehicle identification code sequence and the current timestamp, and generates a random discrete sequence based on the random seed; Step 3: The parameter mapping module divides the preset total sampling weight threshold into multiple initial sampling weight settings according to the random discrete sequence, and subtracts each of the initial sampling weight settings from the total sampling weight threshold to obtain multiple corresponding secondary compensation weight settings. Step 4: The parameter mapping module sends multiple initial sampling weight settings and multiple secondary compensation weight settings to the logic scheduling module. The logic scheduling module receives multiple initial sampling weight settings and multiple secondary compensation weight settings, and sends a material unloading scheduling command to the equipment based on the multiple initial sampling weight settings and multiple secondary compensation weight settings. Step 5: The device receives the material feeding scheduling instruction, switches the sampling bucket corresponding to the material feeding channel through the sample collection component according to the material feeding scheduling instruction, and extracts coal samples from the external coal through the sampling execution component and puts the coal samples into the material feeding channel to connect to the corresponding sampling bucket.

[0016] Beneficial effects of this invention; This invention generates random seeds and discrete sequences by collecting vehicle identification codes and current timestamps, transforming the originally fixed and continuous sampling time pattern into material distribution control based on random weight parameters. External personnel cannot predict the specific sampling bin number into which the coal collected during a particular time period will ultimately fall by observing the execution sequence of equipment actions. This mechanism completely eliminates the correlation between the time of a single material drop and the source of the coal in the collection bin, effectively eliminating the possibility of human intervention and adulteration, and ensuring the objectivity and impartiality of the incoming coal quality acceptance process.

[0017] This invention employs a two-round complementary sampling mechanism combining an initial sampling weight setting and a secondary compensation weight setting. While ensuring that the total weight collected by each individual sampling bucket reaches the total sampling weight threshold, the composition ratio of the coal sample within the bucket is completely randomized. This mechanism avoids the over-concentration of sampling points caused by traditional fixed-time continuous sampling modes, enabling the coal samples collected in individual collection buckets to more accurately and comprehensively reflect the true quality distribution of the entire batch of transported coal, significantly improving the representativeness of the obtained coal samples.

[0018] This invention introduces a high-strength encrypted communication mechanism. The protocol encapsulation module of the control device converts the material feeding scheduling command into encrypted data packets before sending them to the equipment for execution. This mechanism effectively prevents the scheduling command from being maliciously tampered with or intercepted during communication transmission, further enhancing the overall anti-interference capability, operational data integrity, and control security of the sampling system. Attached Figure Description

[0019] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on the accompanying drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the blind-box sampling method for fuel in thermal power plants according to the present invention. Detailed Implementation

[0021] To make the technical solution of the present invention clearer, the present invention will be clearly and completely described below with reference to specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. The present invention provided by various embodiments will be described in detail below with reference to the accompanying drawings. To better understand the purpose of the present invention, the present invention will be described in further detail below.

[0022] In a first aspect, the present invention provides a fuel blind box sampling system for thermal power plants, comprising an equipment device and a control device, wherein the control device is connected to the equipment device; The device includes a sampling execution component, a sample collection component, and a material discharge channel. The sample collection component is equipped with multiple sampling barrels. The sampling execution component extracts coal samples from external coal and discharges the coal samples into the material discharge channel. The material discharge channel is connected to the corresponding sampling barrel. The sample collection component switches the sampling barrel corresponding to the material discharge channel. The control device includes a data acquisition module, a parameter mapping module, and a logic scheduling module; The data acquisition module collects the vehicle identification code sequence and the current timestamp, and sends the vehicle identification code sequence and the current timestamp to the parameter mapping module. The parameter mapping module receives the vehicle identification code sequence and the current timestamp. The parameter mapping module presets a total sampling weight threshold. The parameter mapping module calculates and generates a random seed based on the vehicle identification code sequence and the current timestamp. The parameter mapping module generates a random discrete sequence based on the random seed. The parameter mapping module splits the total sampling weight threshold into multiple initial sampling weight settings according to the random discrete sequence. The parameter mapping module subtracts each initial sampling weight setting from the total sampling weight threshold to obtain multiple corresponding secondary compensation weight settings. The parameter mapping module sends the multiple initial sampling weight settings and the multiple secondary compensation weight settings to the logic scheduling module. The logic scheduling module receives multiple initial sampling weight settings and multiple secondary compensation weight settings. The logic scheduling module sends a material dropping scheduling instruction to the equipment based on the multiple initial sampling weight settings and multiple secondary compensation weight settings. The equipment receives the material dropping scheduling instruction and switches the sampling bucket corresponding to the material dropping channel according to the material dropping scheduling instruction.

[0023] Example 1 provides a blind box sampling system for fuel in a thermal power plant, including equipment and a control device. The control device and the equipment are connected via a communication cable.

[0024] The equipment includes a sampling execution component, a sample collection component, and a material discharge channel. The sampling execution component uses a spiral drilling sampler or a mechanical grab bucket to penetrate deep into the coal car's storage space, extract coal samples from the external coal, and then discharge the extracted samples into the material discharge channel. The material discharge channel uses a stainless steel guide funnel or chute, with its bottom opening connected to the corresponding sampling bucket's receiving cavity. The sample collection component uses a rotating disc bracket containing a drive motor and is equipped with multiple sampling buckets arranged in a circular array, such as eight stainless steel cylindrical sampling buckets. The control device outputs commands to the drive motor, which rotates and drives the rotating disc bracket, thereby completing the physical action of switching the sampling bucket corresponding to the material discharge channel.

[0025] The control device uses a programmable logic controller or an industrial control computer as the core processor and includes a data acquisition module, a parameter mapping module, and a logic scheduling module.

[0026] The data acquisition module uses an RFID reader to read the electronic tags attached to the coal transport vehicles entering the plant to obtain vehicle identification code sequences such as "V-883A". At the same time, it calls the system clock to obtain the current timestamp in UNIX format such as "1684739200" and sends the vehicle identification code sequence and the current timestamp to the parameter mapping module through the system bus.

[0027] The parameter mapping module's storage unit is preset with a total sampling weight threshold, for example, set to 50 kg. After receiving the vehicle identification code sequence and the current timestamp, the parameter mapping module performs character concatenation and logical operations based on the vehicle identification code sequence and the current timestamp to generate a random seed, and then calls a pseudo-random number generation algorithm to generate a random discrete sequence based on the random seed. Subsequently, the total sampling weight threshold is divided into multiple initial sampling weight settings according to the random discrete sequence; if applied to 3 sampling buckets, it can be divided into 10 kg, 15 kg, and 20 kg. Further, the parameter mapping module subtracts each initial sampling weight setting value from the total sampling weight threshold to obtain multiple corresponding secondary compensation weight settings, i.e., 50 minus 10, 15, and 20 respectively to obtain 40 kg, 35 kg, and 30 kg, and sends the calculated multiple initial sampling weight settings and multiple secondary compensation weight settings to the logic scheduling module.

[0028] After receiving multiple initial sampling weight settings and multiple secondary compensation weight settings, the logic scheduling module sends a material feeding scheduling command to the equipment based on the received values. The equipment's drive motor rotates according to the material feeding scheduling command to switch the sampling bucket corresponding to the material feeding channel. Through a two-round unequal weight distribution mechanism, the correlation between the single material feeding time and the source of coal in the collection bucket is broken, thereby achieving random sampling control.

[0029] Example 2 further includes a weighing monitoring component and a workstation sensing component to improve the system's sensing and monitoring mechanism.

[0030] The weighing monitoring component is located at the bottom of the sample collection component. It can be a resistance strain gauge load cell or a piezomagnetic load cell to collect the weight analog signal of the coal sample in the sampling bucket cavity, such as a voltage analog signal of 0 to 5 volts, and send the weight analog signal to the control device.

[0031] The station sensing component is deployed on the side structure of the sample collection component and adopts an infrared through-beam photoelectric switch or a Hall proximity switch. When a sampling bucket moves to the bottom of the material drop channel, the station sensing component collects the position signal of the material drop channel relative to the sampling bucket, such as a high-level pulse signal, and sends the position signal to the logic scheduling module to confirm the spatial alignment status of the sampling bucket.

[0032] In terms of signal processing and communication transmission, the control device in Example 3 also includes a protocol encapsulation module and an analog-to-digital conversion module.

[0033] The analog-to-digital conversion module uses a 24-bit high-precision analog-to-digital conversion chip. After receiving the weight analog signal, it converts the continuously changing weight analog signal into a discrete weight digital signal and sends the weight digital signal to the logic scheduling module.

[0034] The logic scheduling module receives the weight digital signal and the position signal. When the position signal is in the in-position state, it compares the weight digital signal with the currently extracted initial sampled weight setting value and the corresponding secondary compensation weight setting value. When the weight digital signal is equal to the setting value, it outputs the material dropping scheduling command and sends the material dropping scheduling command to the protocol encapsulation module.

[0035] The protocol encapsulation module, through the TCP / IP network communication protocol component and the AES symmetric encryption algorithm code, converts the material feeding scheduling instruction into an encrypted data packet after receiving it, and sends it to the equipment to ensure the data integrity of the scheduling instruction in the communication line.

[0036] Example 4 describes the specific logical calculations for random number generation. The parameter mapping module includes a hash calculation unit.

[0037] The hash calculation unit employs the SHA-256 message digest algorithm processor. It receives the vehicle identification code sequence and the current timestamp, concatenates the string in the vehicle identification code sequence with the current timestamp, and performs SHA-256 hash calculation on the concatenated data to generate a 256-bit hash value as a random seed. The parameter mapping module obtains the random seed output by the hash calculation unit, substitutes the random seed into the Mason tween algorithm, and outputs a random discrete sequence based on the random seed.

[0038] As an extension of the data processing stage, Example 5 also includes a data segmentation unit in the parameter mapping module.

[0039] After acquiring the random discrete sequence, the data segmentation unit maps the sequence to a set of weight ratio coefficients, such as 0.2, 0.3, and 0.4. Simultaneously, it extracts the total sampling weight threshold, such as 100 kg. Based on the weight ratios of the random discrete sequence, the data segmentation unit breaks down the total sampling weight threshold into multiple initial sampling weight settings; that is, 100 kg multiplied by 0.2, 0.3, and 0.4 yields 20 kg, 30 kg, and 40 kg respectively. After this breakdown, the sum of the multiple initial sampling weight settings is 90 kg, which is less than the total sampling weight threshold of 100 kg, thus retaining the remaining weight limit for use in the secondary compensation program.

[0040] Example 6: The logic scheduling module includes a buffer area, which adopts a random access memory or a first-in-first-out register array.

[0041] The parameter mapping module arranges multiple initial sampling weight settings, such as 20 kg, 30 kg, and 40 kg, in sequence to construct the first data array, namely a one-dimensional array A[3]={20,30,40}; at the same time, it arranges multiple secondary compensation weight settings, such as 80 kg, 70 kg, and 60 kg obtained by subtracting the aforementioned values ​​from the total threshold of 100, in the same way to construct the second data array, namely a one-dimensional array B[3]={80,70,60}.

[0042] Subsequently, the parameter mapping module sends the first data array and the second data array to the logic scheduling module, which then writes and stores the received first data array and the second data array into the buffer for later execution.

[0043] In Example 7, during a single execution phase, the logic scheduling module is configured to extract an initial sample weight setting value from the first data array, for example, extracting the first element 20 kg from a one-dimensional array A.

[0044] As coal samples are continuously fed into the first sampling bin via the material feeding channel, the logic scheduling module compares the digital weight signal with the initial sample weight setting value in real time. When the digital weight signal value equals the initial sample weight setting value, a feeding scheduling command is output. After the feeding scheduling command is sent to the sample collection component, the motor driver controls the motor to rotate, causing the rotating disc bracket to rotate one station step angle, thereby completing the switching of the sampling bin corresponding to the feeding channel, so that the feeding channel is aligned with the second sampling bin to perform subsequent processes.

[0045] Example 8's logic scheduling module also includes an interrupt handling unit and an index pointer unit.

[0046] When the logic scheduling module outputs a material feeding scheduling command, the level transition of the command output port activates the interrupt handling unit to trigger a timer interrupt. The interrupt handling unit controls the increment of the count value of the index pointer unit, for example, incrementing the one-dimensional array pointer by 1. Subsequently, the index pointer unit extracts the next initial sampling weight setting value from the first data array, such as the second element 30 kg in one-dimensional array A, and uses the extracted initial sampling weight setting value as the new comparison benchmark for the next round of weight comparison. The same logic loop is executed until the first round of random sampling quota involving all sampling barrels is completed.

[0047] In Example 9, after the index pointer unit completes the reading operation of all elements in the first data array, the logic scheduling module generates and outputs a spatial reset signal, which is then sent to the sample collection component. Upon receiving the spatial reset signal, the driver of the sample collection component controls the motor to reverse or continuously rotate forward back to the initial zero-point coordinates, thereby shifting the material drop channel above the first sampling bucket.

[0048] Next, the logic scheduling module controls the index pointer unit to extract a secondary compensation weight setting value from the second data array, such as extracting the first element of the one-dimensional array B, 80 kg. While the material continues to be fed into the first sampling bucket via the feeding channel, the logic scheduling module compares the extracted secondary compensation weight setting value with the weight digital signal. When the weight of the coal sample added to the first sampling bucket reaches the secondary compensation weight setting value, the logic scheduling module outputs another feeding scheduling command, the control mechanism switches to the second sampling bucket, and extracts the second secondary compensation weight setting value to continue feeding.

[0049] After completing the comparison calculation of all elements in the second data array, the logic scheduling module stops outputting material feeding scheduling instructions. Through two rounds of data calls, the total weight of the first sampling bucket is 20 + 80 = 100 kg, the second sampling bucket is 30 + 70 = 100 kg, and the third sampling bucket is 40 + 60 = 100 kg. The total weight collected by all sampling buckets is equal to the total sampling weight threshold, while the proportion of coal samples distributed in individual sampling buckets is determined by a random discrete sequence. The two-stage material feeding allocation mechanism cuts off the correspondence between the time sequence and spatial position of the coal transport vehicle, eliminating the possibility of predicting the equipment's movement trajectory and ensuring the objectivity and authenticity of the sampling data.

[0050] Secondly, please refer to Figure 1 The fuel blind box sampling method for thermal power plants provided by this invention is applied to the fuel blind box sampling system for thermal power plants as described above, including: Step 1: The data acquisition module collects the vehicle identification code sequence and the current timestamp, and sends the vehicle identification code sequence and the current timestamp to the parameter mapping module; Step 2: The parameter mapping module receives the vehicle identification code sequence and the current timestamp, calculates and generates a random seed based on the vehicle identification code sequence and the current timestamp, and generates a random discrete sequence based on the random seed; Step 3: The parameter mapping module divides the preset total sampling weight threshold into multiple initial sampling weight settings according to the random discrete sequence, and subtracts each of the initial sampling weight settings from the total sampling weight threshold to obtain multiple corresponding secondary compensation weight settings. Step 4: The parameter mapping module sends multiple initial sampling weight settings and multiple secondary compensation weight settings to the logic scheduling module. The logic scheduling module receives multiple initial sampling weight settings and multiple secondary compensation weight settings, and sends a material unloading scheduling command to the equipment based on the multiple initial sampling weight settings and multiple secondary compensation weight settings. Step 5: The device receives the material feeding scheduling instruction, switches the sampling bucket corresponding to the material feeding channel through the sample collection component according to the material feeding scheduling instruction, and extracts coal samples from the external coal through the sampling execution component and puts the coal samples into the material feeding channel to connect to the corresponding sampling bucket.

[0051] In an embodiment of this invention, during the acceptance testing of coal at a thermal power plant, when a coal-carrying vehicle enters the sampling area, the data acquisition module reads the UHF electronic tag carried by the vehicle using an RFID reader to obtain the vehicle's identification code sequence; simultaneously, it retrieves the current timestamp issued by the network time protocol server. The data acquisition module inputs the obtained vehicle identification code sequence and the current timestamp into the hash calculation unit, which maps the extracted text-based coded data with the time-formatted data, outputting a highly disordered random seed. The parameter mapping module applies the generated random seed to drive a pseudo-random number generation algorithm, generating a random discrete sequence containing multiple normalized floating-point coefficients; furthermore, it uses the extracted normalized floating-point coefficients to dynamically divide the pre-configured national standard coal sample inspection quality upper limit threshold, independently assigning an initial sampling weight setting value and a complementary pairing secondary compensation weight setting value to each sampling bucket.

[0052] After entering the controlled sampling stage, the auger drilling mechanism of the sampling execution component continuously extracts coal from the coal car and places the extracted coal into a stainless steel guide funnel, which serves as the material discharge channel. Simultaneously, a resistance strain gauge load cell installed at the bottom of the sample collection component monitors the cumulative weight of the coal sample in the sampling bucket's containment cavity in real time; the resistance strain gauge load cell continuously generates changing voltage values ​​and sends these changing voltage values ​​as a weight analog signal to the control device.

[0053] Signal reception and command issuance are executed by the logic scheduling module, which continuously compares the weight digital signal after analog-to-digital conversion and noise reduction with the currently extracted initial sampling weight setting value. When the actual filling amount of the collected coal sample reaches the set initial target node, the logic scheduling module outputs a relay closing pulse level as a material discharge scheduling command. The control program drives the variable frequency motor of the sample collection component to rotate a specific angle according to the material discharge scheduling command, and combines the position signal sensed by the photoelectric switch to switch the next sampling bucket to be directly below the stainless steel guide funnel to receive the continuous coal flow.

[0054] After all sampling bins have completed the first round of filling, the logic scheduling module controls the disc support to reverse and reset to the initial reference position. Subsequently, the logic scheduling module sequentially calls all secondary compensation weight settings to control the motor to execute the second round of supplementary feeding program until the final weight of the coal sample in each sampling bin's containment chamber is equal to the upper limit threshold of the national standard coal sample inspection quality. The multi-segment non-equal distribution mechanism blocks the correspondence between the equipment's movement patterns and the spatial distribution of material drop in the conventional continuous sampling mode; external personnel cannot reverse-engineer the specific collection distribution location of a particular coal batch based on the equipment's continuous operating trajectory, thus cutting off the path of human intervention in the test samples at the source of industrial control execution.

Claims

1. A blind-box sampling system for fuel in thermal power plants, characterized in that, It includes equipment and a control device, wherein the control device is connected to the equipment. The device includes a sampling execution component, a sample collection component, and a material discharge channel. The sample collection component is equipped with multiple sampling barrels. The sampling execution component extracts coal samples from external coal and discharges the coal samples into the material discharge channel. The material discharge channel is connected to the corresponding sampling barrel. The sample collection component switches the sampling barrel corresponding to the material discharge channel. The control device includes a data acquisition module, a parameter mapping module, and a logic scheduling module; The data acquisition module collects the vehicle identification code sequence and the current timestamp, and sends the vehicle identification code sequence and the current timestamp to the parameter mapping module. The parameter mapping module receives the vehicle identification code sequence and the current timestamp. The parameter mapping module presets a total sampling weight threshold. The parameter mapping module calculates and generates a random seed based on the vehicle identification code sequence and the current timestamp. The parameter mapping module generates a random discrete sequence based on the random seed. The parameter mapping module splits the total sampling weight threshold into multiple initial sampling weight settings according to the random discrete sequence. The parameter mapping module subtracts each initial sampling weight setting from the total sampling weight threshold to obtain multiple corresponding secondary compensation weight settings. The parameter mapping module sends the multiple initial sampling weight settings and the multiple secondary compensation weight settings to the logic scheduling module. The logic scheduling module receives multiple initial sampling weight settings and multiple secondary compensation weight settings. The logic scheduling module sends a material dropping scheduling instruction to the equipment based on the multiple initial sampling weight settings and multiple secondary compensation weight settings. The equipment receives the material dropping scheduling instruction and switches the sampling bucket corresponding to the material dropping channel according to the material dropping scheduling instruction.

2. The fuel blind-box sampling system for thermal power plants according to claim 1, characterized in that, The device further includes a weighing monitoring component and a workstation sensing component. The weighing monitoring component is located at the bottom of the sample collection component and collects the weight simulation signal of the coal sample inside the sampling bucket. The weighing monitoring component sends the weight simulation signal to the control device. The workstation sensing component is deployed on the side of the sample collection component and collects the position signal of the material discharge channel relative to the sampling bucket. The workstation sensing component sends the position signal to the logic scheduling module.

3. The fuel blind-box sampling system for thermal power plants according to claim 2, characterized in that, The control device further includes a protocol encapsulation module and an analog-to-digital conversion module. The analog-to-digital conversion module receives the weight analog signal, converts the weight analog signal into a weight digital signal, and sends the weight digital signal to the logic scheduling module. The logic scheduling module receives the weight digital signal and the position signal, compares the weight digital signal, the position signal, a currently extracted initial sampled weight setting value, and the corresponding secondary compensation weight setting value, and outputs the material dropping scheduling instruction. The logic scheduling module sends the material dropping scheduling instruction to the protocol encapsulation module, which receives the material dropping scheduling instruction, converts the material dropping scheduling instruction into an encrypted data packet, and sends the encrypted data packet to the device.

4. The fuel blind-box sampling system for thermal power plants according to claim 3, characterized in that, The parameter mapping module includes a hash calculation unit. The hash calculation unit receives the vehicle identification code sequence and the current timestamp. The hash calculation unit performs hash calculation on the vehicle identification code sequence and the current timestamp to generate the random seed. The parameter mapping module obtains the random seed output by the hash calculation unit and generates the random discrete sequence based on the random seed.

5. The fuel blind-box sampling system for thermal power plants according to claim 4, characterized in that, The parameter mapping module further includes a data segmentation unit, which acquires the random discrete sequence, extracts the total sampling weight threshold, and splits the total sampling weight threshold into multiple initial sampling weight settings based on the weight ratio of the random discrete sequence. The sum of the values ​​of the multiple initial sampling weight settings is less than the total sampling weight threshold.

6. The fuel blind-box sampling system for thermal power plants according to claim 5, characterized in that, The logical scheduling module includes a buffer. The parameter mapping module constructs a first data array from multiple initial sampling weight settings and a second data array from multiple secondary compensation weight settings. The parameter mapping module sends the first data array and the second data array to the logical scheduling module. The logical scheduling module receives the first data array and the second data array and stores the first data array and the second data array in the buffer.

7. The fuel blind-box sampling system for thermal power plants according to claim 6, characterized in that, The logic scheduling module is configured to extract an initial sampling weight setting value from the first data array. The logic scheduling module compares the weight digital signal with the currently extracted initial sampling weight setting value. When the weight digital signal value is equal to the currently extracted initial sampling weight setting value value, the logic scheduling module outputs the material dropping scheduling instruction. The logic scheduling module sends the material dropping scheduling instruction to the sample collection component. The sample collection component receives the material dropping scheduling instruction and switches the sampling bucket corresponding to the material dropping channel according to the material dropping scheduling instruction.

8. The fuel blind-box sampling system for thermal power plants according to claim 7, characterized in that, The logic scheduling module further includes an interrupt handling unit and an index pointer unit. When the logic scheduling module outputs the material dropping scheduling instruction, the interrupt handling unit is activated. The interrupt handling unit controls the index pointer unit to increment its value. The index pointer unit extracts the next initial sampling weight setting value from the first data array for the next comparison.

9. The fuel blind-box sampling system for thermal power plants according to claim 8, characterized in that, The logic scheduling module is configured to generate and output a spatial reset signal after the index pointer unit completes reading the first data array. The logic scheduling module sends the spatial reset signal to the sample collection component. The sample collection component receives the spatial reset signal and shifts the material dropping channel to the first sampling bucket according to the spatial reset signal. The logic scheduling module controls the index pointer unit to extract a secondary compensation weight setting value from the second data array. The logic scheduling module compares the extracted secondary compensation weight setting value with the weight digital signal to output the material dropping scheduling instruction again. The logic scheduling module stops outputting the material dropping scheduling instruction after completing the comparison of the second data array.

10. A fuel blind-box sampling method for thermal power plants, applied to the fuel blind-box sampling system for thermal power plants as described in any one of claims 1 to 9, characterized in that, include: Step 1: The data acquisition module collects the vehicle identification code sequence and the current timestamp, and sends the vehicle identification code sequence and the current timestamp to the parameter mapping module; Step 2: The parameter mapping module receives the vehicle identification code sequence and the current timestamp, calculates and generates a random seed based on the vehicle identification code sequence and the current timestamp, and generates a random discrete sequence based on the random seed; Step 3: The parameter mapping module divides the preset total sampling weight threshold into multiple initial sampling weight settings according to the random discrete sequence, and subtracts each of the initial sampling weight settings from the total sampling weight threshold to obtain multiple corresponding secondary compensation weight settings. Step 4: The parameter mapping module sends multiple initial sampling weight settings and multiple secondary compensation weight settings to the logic scheduling module. The logic scheduling module receives multiple initial sampling weight settings and multiple secondary compensation weight settings, and sends a material unloading scheduling command to the equipment based on the multiple initial sampling weight settings and multiple secondary compensation weight settings. Step 5: The device receives the material feeding scheduling instruction, switches the sampling bucket corresponding to the material feeding channel through the sample collection component according to the material feeding scheduling instruction, and extracts coal samples from the external coal through the sampling execution component and puts the coal samples into the material feeding channel to connect to the corresponding sampling bucket.

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