Catalytic element test matching system

Abstract

The invention discloses a catalytic element test matching system, and relates to the technical field of catalytic element testing, and the system comprises the following components: an element access and isolation module, a signal acquisition and processing module, a voltage precision control module, an element performance evaluation module, an element matching decision module and a man-machine interaction prompt module. According to the invention, through close combination of hardware closed-loop feedback regulation and a software intelligent control algorithm in the voltage precision control module, hyperfine control of the power supply voltage is realized, and voltage fluctuation is strictly limited in a minimum range, so that measurement errors caused by voltage fluctuation in a traditional manual test are effectively avoided, and meanwhile, the test accuracy is improved. And the element performance evaluation module can deeply evaluate the performance state of the catalytic element based on high-quality data acquisition and scientific judgment logic, so that the accuracy and reliability of a test result are ensured.

Description

Technical Field

[0001] The invention relates to the technical field of catalytic element testing, in particular to a catalytic element testing matching system. Background Art

[0002] As an indispensable key component in modern industry, catalytic elements play a vital role in many fields such as chemical industry, environmental protection, and energy. Their performance is directly related to the overall operation effect and efficiency of related systems. Therefore, it is particularly important to accurately and efficiently test and match catalytic elements. With the advancement of science and technology and the development of the industry, the types and application scenarios of catalytic elements are becoming increasingly rich, and the requirements for testing and matching technology are becoming higher and higher. Traditional testing and matching methods can no longer meet the strict requirements of modern industrial production and scientific research fields for catalytic element performance evaluation and reasonable matching. There is an urgent need for an innovative, highly automated catalytic element testing and matching system that can ensure high precision and high efficiency.

[0003] The testing and matching of traditional catalytic components mainly rely on manual operation. However, this method has many inherent defects. On the one hand, it is difficult for humans to accurately control the power supply voltage, and voltage fluctuations are inevitable in actual operation, resulting in large errors in the measured electrical parameters of the components, which cannot accurately reflect the true performance of the components. On the other hand, when matching components, humans need to rely on experience and the naked eye to compare the various parameters of a large number of components. The process is cumbersome and time-consuming, and it is very easy to cause unreasonable matching due to the subjectivity and limitations of human judgment, which in turn affects the stability and working efficiency of the entire system in subsequent use. In addition, the traditional method also faces problems such as low testing efficiency, insufficient testing accuracy, and poor matching effect. It is difficult to meet the urgent needs of modern industrial large-scale production and scientific research for fast and accurate testing and matching of catalytic components.

[0004] In view of the above problems, it is necessary to optimize the existing catalytic element test and matching system, and realize orderly access, precise testing and scientific matching of catalytic elements through hardware components such as adjustable constant voltage source and relay array, and software logic such as component channel control program and signal acquisition driver. Therefore, it is of great significance to develop a catalytic element test and matching system that can comprehensively realize the above characteristics. Summary of the invention

[0005] The purpose of the present invention is to make up for the deficiencies of the prior art and to provide a catalytic element test and matching system, which can achieve orderly access, precise testing and scientific matching of catalytic elements through hardware components such as adjustable constant voltage sources and relay arrays and software logic such as element channel control programs and signal acquisition drivers. At the same time, the system also has a high-efficiency operation mode and a high degree of automation, which can significantly reduce the errors and uncertainties caused by manual intervention and improve the accuracy and reliability of test matching.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a catalytic element test and matching system, the system comprising the following components: an element access and isolation module, a signal acquisition and processing module, a voltage precision control module, an element performance evaluation module, an element matching decision module and a human-computer interaction prompt module;

[0007] The component access and isolation module uses an adjustable constant voltage source as the power supply basis at the hardware level, and each relay of the relay array corresponds to a single component access channel, and realizes channel switching with the help of precise connection with the microcontroller unit, so that all components are fully isolated and only a single component is connected to the test circuit at a time. At the software level, the component channel control program running in the MCU uses a relay switching optimization algorithm that comprehensively considers the component test time, current and voltage fluctuations, calculates the optimal component access sequence through a quantitative formula, controls the opening and closing of the relays in sequence, and connects each catalytic component to the test circuit in turn;

[0008] In terms of hardware, the signal acquisition and processing module uses high-precision analog-to-digital conversion chips and circuit design layouts to accurately capture the voltage signals at both ends of the component at key nodes of the test circuit in real time. The current detection circuit relies on high-precision sensors and adaptive conditioning circuits to accurately detect the working current of the component. In terms of software, the signal acquisition driver coordinates the voltage acquisition port and the current detection circuit to work synchronously and convert the collected analog signals into digital signals. The data preprocessing program successively uses adaptive filtering algorithms and calibration compensation algorithms to eliminate signal deviations caused by hardware factors, comprehensively improve the quality of the collected signals, and provide reliable data support for subsequent component performance evaluation and other operations.

[0009] In terms of hardware, the voltage precision control module builds an electrical connection link between the adjustment interface of the adjustable constant voltage source and the MCU, which can not only receive the control instructions of the MCU, but also is equipped with a voltage feedback detection circuit to feed back the output voltage situation to the MCU in real time, forming a closed-loop control mechanism. In terms of software, the voltage monitoring and adjustment program adopts a control algorithm, comprehensively considers the voltage deviation and its change rate, integrates the conventional control quantity determined by the proportional, integral, and differential coefficients, and the additional control quantity inferred by the fuzzy logic according to the deviation situation, generates a final control signal to act on the adjustment interface, and fine-tunes the output voltage of the adjustable constant voltage source;

[0010] The component performance evaluation module is responsible for using the collected voltage and current data as the basic data source in terms of hardware. In the software, the resistance calculation and change monitoring program calculates the component resistance value in real time according to Ohm's law, and uses the resistance stability evaluation algorithm based on dynamic time regularization to comprehensively judge the resistance stability by analyzing the distance between the resistance sequences collected at different times. The catalytic completion judgment program uses a catalytic completion judgment algorithm with multi-parameter fusion, combined with a preset threshold to consider the performance evolution of the component during the entire test process, and judge the catalytic completion time node of the catalytic component. When the component reaches the expected stable state, it is determined that it meets the requirements for entering the matching link.

[0011] The component matching decision module is based on multi-dimensional matching rules and takes black components as the benchmark to clearly set specific matching standards covering resistance ratio, electrical characteristics, environmental performance and electromagnetic compatibility. The matching component search and statistics program uses a matching component search algorithm based on graph theory. According to the rules defined by the graph model construction, it comprehensively traverses and searches in the set of white components that have completed performance evaluation, selects white components that meet all set conditions, and counts their number and records feature information. The sorting and matching execution program adopts a comprehensive weight dynamic sorting algorithm, and sorts the selected matching white components according to the corresponding formula based on comprehensive considerations such as matching conflict conditions and key electrical characteristics adaptation degree factors, and performs component matching operations in sequence according to the sorting results. After each match, it updates the relevant information including the status of the matched components, the details of the remaining components to be matched, and the matching sequence adjustment, and re-sorts the loop operation until the matching of all components is completed;

[0012] In terms of hardware, the human-computer interaction prompt module is installed in the indicator light group, and conveys the current working status of the system and the test and matching progress of the components by presenting different colors and flashing modes. In terms of software, the status prompt program monitors the component test and matching related information fed back by each module in the system, and sends corresponding control signals to the indicator light group according to the prompt rules. The operator performs the component pick-up and placement operations according to the signals.

[0013] Furthermore, at the software level, the component access and isolation module uses a relay switching optimization algorithm that comprehensively considers component test time, current and voltage fluctuations in the component channel control program running in the MCU, and its calculation formula is: Among them, n represents the optimization index of the nth possible component access sequence, N is the total number of catalytic components to be tested, T i (n) refers to the time spent testing the i-th component under the n-th connection sequence, λ is the weight coefficient of the current fluctuation, I i (n) represents the average working current of the component in the stable test phase when testing the i-th component under the n-th connection sequence, is the average current value of all components under test in normal working state, μ is the weight coefficient of voltage fluctuation, M represents the number of key nodes selected in the test circuit for monitoring voltage fluctuation, ΔV j (n) is the voltage fluctuation value at the jth monitoring node under the nth access sequence.

[0014] Furthermore, the data preprocessing program in the signal acquisition and processing module successively uses an adaptive filtering algorithm and a calibration compensation algorithm to eliminate signal deviations caused by hardware factors. The formula of the adaptive filtering algorithm is: Among them, y(k) represents the filtered signal value output at time k after adaptive filtering, x(k) is the original signal collected at time k, P is the order of the filter, and a i (k) is the i-th adaptive filter coefficient at time k, Q(k) represents the filtering error at time k, d(k) is the desired noise-free signal, η is the learning rate parameter, and the calibration compensation algorithm formula is: V calibrated =V raw -V offset (T)-K T ×(T-T0)×V ref , where V calibrated Indicates the accurate voltage signal value obtained after calibration and compensation, V raw is the original uncalibrated voltage signal value, V offset (T) is the zero drift voltage offset function related to temperature T, K T is the temperature coefficient of voltage or current, T represents the actual ambient temperature or the operating temperature of the hardware, T0 is the set reference temperature, V ref is the reference voltage value.

[0015] Furthermore, the voltage precision control module uses a control algorithm to generate a final control signal, and the control algorithm formula is: Where u(k) represents the control signal output at time k, p , K i , K d are proportional, integral, and differential coefficients respectively, e(k) is the voltage deviation at time k, that is, the target voltage V target The actual measured current voltage V actuαl The difference between (k) and e(k) = V target -V actuai (k), Δu Fuzzy (k) is the additional control quantity output by the fuzzy logic controller at time k, which is obtained through fuzzy inference rules based on the input voltage deviation e(k) and its change rate Δe(k)=e(k)-e(k-1).

[0016] Furthermore, the component performance evaluation module uses a resistance stability evaluation algorithm based on dynamic time warping, and its calculation formula is: ΔR DTW =DTW(R n , R n+1 )≤∈ DTW , where DTW(R n , R n+1 ) represents the distance between the resistance series collected for the nth time and the n+1th time calculated based on the dynamic time warping algorithm, and I and J are the resistance series R n and R n+1 The length, w ij is the path weight matrix element in the dynamic time warping algorithm, d(r i , r j ) is the distance metric function between the i-th and j-th resistance values ​​in the resistor series, ΔR DTW Represents the resistance change evaluated based on the DTW algorithm, ∈ DTW is a preset resistance stability judgment threshold based on the DTW algorithm. If the resistance value changes, that is, ΔR DTW Greater than∈ DTW , indicating that the component has not yet reached a stable performance state. At this time, the program will promptly feedback the corresponding information to the component access and isolation module, informing it to continue to power on and activate the component to further stabilize the component performance. If the resistance value does not change, that is, ΔR DTW′ Less than or equal to ∈ DTW , it means that the component has reached a relatively stable state under the current test conditions, and it is determined that the component has completed the performance test of this stage and meets the conditions for entering the matching stage, thereby achieving accurate control of the component performance status.

[0017] Furthermore, the catalytic completion judgment program of the component performance evaluation module uses a multi-parameter fusion catalytic completion judgment algorithm, combined with a preset threshold to consider the performance evolution of the component during the entire test process, and judges the catalytic completion time node of the catalytic component. The algorithm formula is: Among them, T c It is the catalytic completion time judgment index of the catalytic element. α, β, γ, and δ are the weighted coefficients of the resistance change rate, current change rate, voltage change rate, and other parameter change amounts. m, n, o, and p represent the number of resistance, current, voltage, and other related parameters involved in the calculation. Represents the rate of change of the i-th resistance-related parameter over time, R avg is the average value of all resistance-related parameters involved in the calculation, Indicates the rate of change of the jth current-related parameter over time, I avgis the average value of all current-related parameters involved in the calculation, represents the rate of change of the kth voltage-related parameter over time, V avg Represents the average value of all voltage-related parameters involved in the calculation, ΔC l Indicates the change of the lth other related parameters, T th is the pre-set catalytic completion time judgment threshold, which is different from the calculated T c A comparison is performed to determine whether the components have reached a stable state for matching.

[0018] Furthermore, the matching component search and statistical program in the component matching decision module uses a matching component search algorithm based on graph theory, and its algorithm formula is: Where G represents the constructed graph model, which is used to describe the potential matching relationship between catalytic elements. V is the vertex set of graph G, which consists of all black element sets E. b And white element set E w E is the edge set of graph G, edge (v i , v j ) represents the vertex v i and v j The represented component satisfies the matching condition, MatchCond(v i , v j ) is a custom matching condition judgment function, input two component vertices v i and v j , it is determined whether a match can be made according to various pre-set matching requirements. M is the maximum matching result found on the graph G by the maximum matching algorithm MaximalMatching in graph theory, that is, the set of matching pairs of white components and black components that meet the matching conditions finally searched.

[0019] Furthermore, the sorting and matching execution program adopts a comprehensive weight dynamic sorting algorithm to sort the selected matching white components according to the corresponding formula by comprehensively considering the matching conflict situation and the key electrical characteristics adaptation degree factors. The algorithm formula is: Among them, S i represents the comprehensive ranking score of the i-th matching white element, ω1, ω2, ω3 are the weight coefficients corresponding to different influencing factors, N i Indicates that there is a potential matching conflict with the i-th matching white element, C i represents the specific parameter value of the i-th matching white component in a key electrical characteristic, C max represents the maximum parameter value allowed for the key electrical characteristic in the current application scenario, T represents the number of time points involved in calculating the performance stability of the component, ΔP it represents a performance parameter of the i-th matching white element at the t-th time point, Pavg It is the average change in the corresponding performance parameters of all components involved in the calculation.

[0020] Compared with the prior art, this catalytic element testing and matching system has the following beneficial effects:

[0021] 1. The present invention realizes ultra-fine control of the power supply voltage through the close combination of hardware closed-loop feedback regulation and software intelligent control algorithm in the voltage precision control module, strictly limits the voltage fluctuation within a very small range, thereby effectively avoiding the measurement error caused by voltage fluctuation in traditional manual testing. At the same time, the component performance evaluation module is based on high-quality data acquisition and scientific judgment logic, and can deeply evaluate the performance status of the catalytic component to ensure the accuracy and reliability of the test results.

[0022] 2. The present invention realizes a highly automated process from connecting the catalytic element to the test circuit to completing performance evaluation and element matching, and then prompting the operator to pick up and place the element through the coordinated operation of various functional modules. This not only significantly shortens the overall test matching cycle and improves work efficiency, but also minimizes the subjective uncertainty and operational errors caused by human intervention.

[0023] Other advantages, objectives and features of the present invention will be set forth in part in the following description and, in part, will be apparent to those skilled in the art based on an examination of the following or may be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 A matching system flow chart for testing a catalytic element;

[0026] Figure 2 A test schematic diagram of a catalytic element test matching system. DETAILED DESCRIPTION

[0027] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation mode, structure, characteristics and effects of the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments.

[0028] Embodiment 1

[0029] In the field of automobile exhaust purification, catalysts play a key role. The performance of the catalytic elements inside them directly affects the exhaust purification effect. During the production process of automobile catalysts, a large number of catalytic elements need to be tested and matched to ensure that the assembled catalysts can efficiently and stably purify automobile exhaust and meet strict environmental emission standards.

[0030] Select an adjustable constant voltage source with an output voltage accuracy of ±0.1mV and an adjustment range of 0-10V, and use relays with fast response, high reliability and contact withstand voltage of 30V to build a relay array. At the same time, a high-precision analog-to-digital conversion chip with a resolution of 16 bits and a sampling rate of 100kHz is equipped for the voltage acquisition port, etc. Connect each hardware module according to rigorous circuit design principles and standardized wiring rules to ensure stable electrical connections, stable signal transmission and good electromagnetic compatibility. At the same time, record the developed program integrating the software functions of each module into the microcontroller unit (MCU), and perform relevant parameter initialization settings, such as setting the initial output voltage of the adjustable constant voltage source to 5V, setting the resistance ratio range of the component matching to [0.9-1.1], and setting the indicator light prompt rules in detail according to different colors and flashing modes corresponding to different test matching stages, so that the system can carry out the test matching work of the automobile exhaust purification catalytic element according to the predetermined logic.

[0031] Connect the automobile exhaust purification catalytic components to be tested to the system, and use the component channel control program in the component access and isolation module to plan the access sequence using the relay switching optimization algorithm. Assuming that there are 100 catalytic components to be tested (N=100), the program will comprehensively consider the estimated test time T for each component. i (n) (for example, depending on the component specifications, the test time of a single component is expected to vary between 0.1 and 0.5 seconds), component operating current I i (n) The normal operating current range of automobile exhaust purification catalytic components is about 0.1-0.3A. Through a small number of sample tests, it is statistically determined that it is about 0.2A) and the voltage fluctuation ΔV at the key nodes in the circuit when connected j (n) (select 5 key monitoring nodes, M = 5) and other factors, and calculate the optimization index O of each possible access sequence n according to the following formula: π : Among them, the current fluctuation weight coefficient λ=0.3 and the voltage fluctuation weight coefficient μ=0.5 are constants determined through multiple experiments based on the importance of current and voltage stability requirements in the test of automobile exhaust purification catalytic elements. After determining the optimal access sequence, the MCU controls the relay to connect a single catalytic element to the test circuit in turn, ensuring that only one element is connected at a time to avoid mutual interference between elements, thus preparing for subsequent precise testing.

[0032] After the component is connected to the test circuit, the signal acquisition and processing module starts working. The voltage acquisition port and the current detection circuit synchronously collect the voltage and current signals of the component under the coordination of the signal acquisition driver. For example, the original voltage signal x(k) (in volts) and current signal (in amperes) of the component at a certain moment are collected. The data preprocessing program first uses an adaptive filtering algorithm to remove noise. The algorithm formula is as follows: Among them, the filter order P = 5 is determined based on the analysis of the noise frequency characteristics of the signal collected from the automobile exhaust purification catalytic element, and the learning rate parameter η = 0.01 is obtained through a large number of signal collection experiments under different working conditions. Then, in view of factors such as hardware temperature drift and zero drift, a calibration compensation algorithm is used to calibrate the collected voltage signal V raw For calibration, assume that the current ambient temperature T = 30 (obtained in real time by the temperature sensor), the reference temperature T0 = 25, and the reference voltage value V ref =5V, known voltage temperature coefficient K T = 0.001 and zero drift voltage offset function V offset (T) The value obtained through the previous calibration test at this temperature is 0.01V, so the calibrated voltage signal V calibrated The formula V calibrated =V raw -V offset (T)-K T ×(T-T0)×V ref After a series of calculations and processing, high-quality voltage and current signals that can accurately reflect the actual electrical characteristics of the components are obtained, providing a reliable data basis for subsequent performance evaluation.

[0033] The voltage precision control module monitors and adjusts the supply voltage in real time to ensure that it is stable within the appropriate range. During the test of automobile exhaust purification catalytic components, the target voltage V taarget =5V, the voltage monitoring and adjustment program controls the output voltage of the adjustable constant voltage source through the control algorithm. For example, at a certain time k, the actual measured current voltage V actual (k) = 4.995 V, then the voltage deviation e(k) = V target -V actual (k) = 0.005V, based on the proportionality coefficient K determined in advance through system modeling and experimental debugging p =0.5, integral coefficient K i =0.1, differential coefficient K d =0.05, and the additional control quantity Δu derived by the fuzzy logic controller based on the voltage deviation and its rate of change fuzzy (k) = 0.001, and the control signal u(k) is calculated according to the following formula: The MCU fine-tunes the adjustable constant voltage source through the adjustment interface according to the control signal, so that the supply voltage is always stable within the range of ±1mV of the target voltage to ensure high accuracy of the test and avoid affecting the component performance test results due to voltage fluctuations.

[0034] The component performance evaluation module evaluates the performance of the automobile exhaust purification catalytic component based on the collected and processed voltage and current data. The resistance calculation and change monitoring program first calculates the component resistance value according to Ohm's law, and uses the resistance stability evaluation algorithm based on dynamic time warping (DTW) to determine the resistance stability. For example, two sets of resistance sequences R of a component within a period of time are collected. n and R n+1 Each sequence contains 10 resistance data points (I = J = 10). By setting the distance metric function d(r i , r j ) is the absolute value of the resistance difference, and the DTW distance DTW (R n , R n+1 ): Assume that the resistance stability judgment threshold ∈ is determined in advance by analyzing the resistance series of a large number of automobile exhaust purification catalytic components in stable and unstable states. DTW =0.05Ω, if DTW(R n , R n+1 )≤∈ DTW , the resistance is considered stable. If DTW(R n , R n+1 )>∈ DTW , notifying the component access and isolation module to continue to power on and activate the component. At the same time, the catalytic completion judgment program adopts a multi-parameter fusion catalytic completion judgment algorithm to comprehensively consider the change rate of resistance, current, and voltage over time and other related parameters (such as the chemical characteristic parameters related to the catalytic activity of the component) to judge the catalytic completion time node. For example, 3 resistance-related parameters (m=3), 2 current-related parameters (n=2), 2 voltage-related parameters (o=2) and 1 chemical characteristic parameter (p=1) are selected to participate in the calculation. The weighted coefficients are determined to be α=0.3, β=0.2, γ=0.2, and δ=0.3 according to the importance of each parameter in reflecting the integrity of the catalytic process. The catalytic completion time judgment index T is calculated by the formula c : Assume that the catalytic completion time judgment threshold T is determined in advance through a large number of experiments. th =0.8, when T c ≤T th When , it is determined that the element has completed the catalytic process and meets the conditions for entering the matching stage.

[0035] The component matching decision module performs matching operations after the components meet the performance evaluation requirements. First, the matching standard setting program sets the matching standards based on the actual application requirements of automobile exhaust purification catalytic components. For example, taking the black components as the benchmark, the matching white component resistance ratio range is required to be [0.9-1.1], the capacitance difference is within ±0.1pF (considering the electrical characteristics matching between components), and the performance fluctuation does not exceed 596 within the common temperature range of automobile exhaust (-20℃-80℃) (considering environmental adaptability) and the electromagnetic compatibility between components is good (no electromagnetic interference), etc. The matching component search and statistical program uses an improved matching component search algorithm based on graph theory to construct a graph model G=(V, E), where the vertex set V is composed of all black component sets E b And white element set E w The edge set E is composed according to the custom matching condition judgment function MatchCond(v i , v j ) is determined. This function determines whether two components can be matched according to the various matching requirements set above. The maximum matching algorithm MaximalMatching (G) in graph theory is used to find the matching pair set M of all white components and black components that meet the conditions. Then, the sorting and matching execution program uses a comprehensive weight dynamic sorting algorithm to sort the selected matching white components. Assuming that a matching white component i has a number of other components N with potential matching conflicts i =3, its parameter value C in terms of key electrical characteristic capacitance i =2pF (the maximum allowable value of this characteristic in this application scenario is C max =3pF), the performance parameters related to performance stability over a period of time are calculated And the average change of all components in this performance parameter is P avg =0.2, according to the predetermined weight coefficients ω1 = 0.4, ω2 = 0.3, ω3 = 0.3, the comprehensive ranking score S is calculated according to the following formula i : Component matching operations are performed in sequence according to the sorting results. After each match, relevant information is updated and re-sorted until all components are matched.

[0036] During the entire test and matching process, the human-computer interaction prompt module provides real-time feedback to the operator on the system status and component test and matching progress. For example, when the system starts to test a batch of automobile exhaust purification catalytic components, the green indicator light in the indicator light group is always on, indicating that the test process has started normally. During the component matching stage, the yellow indicator light flashes to indicate that the matching operation is in progress. If there is an abnormal situation such as component short circuit, the red indicator light is always on to alert the operator to check and deal with it in time. The operator takes and places the components in time after the component matching is completed according to the indicator light prompts, ensuring the smooth progress of the entire test and matching process, and finally completing the efficient and high-precision test and matching of all automobile exhaust purification catalytic components for the subsequent assembly and production of automobile exhaust purification catalysts, thereby improving the overall quality of catalyst products and the exhaust purification effect.

[0037] Embodiment 2

[0038] In chemical production, the catalyst elements in the reactor play a decisive role in the rate and conversion rate of the chemical reaction. In order to ensure the efficient and stable operation of chemical production, a large number of catalyst elements produced in different batches need to be strictly tested and precisely matched.

[0039] An adjustable constant voltage source with an adjustable output voltage range of 0-20V and an accuracy of ±0.05mV is used (to adapt to the wide working voltage range of various catalyst elements in the chemical field). Relays with high insulation performance and contact withstand voltage of 50V are selected to construct a relay array to ensure the safety and reliability of component access in a complex chemical environment. A high-precision analog-to-digital conversion chip with a resolution of 18 bits and a sampling rate of 200kHz is used for the voltage acquisition port to ensure that the weak voltage signal changes of the components can be accurately collected. After the hardware modules are reasonably connected and the electrical performance is ensured to be good, the program integrating the software functions of each module is recorded into the MCU and initialized. For example, the initial output voltage of the adjustable constant voltage source is set to 10V (according to the initial working voltage setting of the common catalyst elements in the chemical reactor), the resistance ratio range of the element matching is determined to be [0.95-1.05] according to the chemical process requirements and preliminary experiments, and the indicator light prompt rules are set according to the chemical production operation process and safety specifications, so that the system can carry out the test matching work of the chemical catalyst elements according to the predetermined logic.

[0040] Connect the catalyst components of the chemical reactor to be tested to the system, and plan the access sequence through the component channel control program in the component access and isolation module. Assuming that there are 80 catalyst components to be tested (N=80), the program will comprehensively consider the test time T of each component. i (n) (Due to the complexity of chemical catalyst components, the test time of a single component is expected to be between 0.2 and 1 second), component operating current I i(n) (The operating current range of chemical catalyst components is generally around 0.05-0.5A. According to the statistics of the previous sample test, it is about 0.3A) and the voltage fluctuation ΔV of the key nodes in the circuit when connected j (n) (select 8 key monitoring nodes, M = 8) and other factors, and calculate the access order optimization index O according to the following formula π : Among them, the current fluctuation weight coefficient λ=0.4 and the voltage fluctuation weight coefficient μ=0.6 are constants determined through multiple tests on catalyst elements in a chemical production environment, based on the importance of current and voltage fluctuations on test accuracy and subsequent chemical reactions. After determining the optimal access sequence, the MCU controls the relays to connect the catalyst elements to the test circuit one by one according to this sequence, ensuring that only a single element is connected each time, effectively isolating the elements to avoid mutual interference, and creating good conditions for subsequent precise testing.

[0041] After the component is connected to the test circuit, the signal acquisition and processing module starts to operate. The voltage acquisition port and the current detection circuit synchronously collect the voltage and current signals of the catalyst component of the chemical reactor under the coordination of the signal acquisition driver. For example, after collecting the original voltage signal x(k) (in volts) and current signal (in amperes) of the component at a certain moment, the data preprocessing program first uses an adaptive filtering algorithm to denoise the signal. The formula of the adaptive filtering algorithm is: In the chemical production scenario, after analyzing the noise characteristics of the collected signal and a large number of experimental verifications, it is determined that the filter order P = 6 can better adapt to the signal denoising requirements, and the learning rate parameter η = 0.008 can ensure that the filtering algorithm converges quickly and maintains a stable filtering effect in this application environment. Subsequently, in view of the situation where hardware temperature drift, zero drift and other factors that may affect the signal accuracy in the chemical production environment, a calibration compensation algorithm is used to calibrate the collected voltage signal V raw For calibration, assume that the current ambient temperature T = 40 (the temperature of the chemical production site is obtained in real time through the temperature sensor), the reference temperature T0 = 20, and the reference voltage value V ref =10V, known voltage temperature coefficient K T = 0.0012 and the zero drift voltage offset function V obtained by the previous calibration test of the hardware at different temperatures offset (T) is 0.02V at this temperature, so the calibrated voltage signal V calibrated It can be calculated according to the following formula: V calibrated =V raw -V offset (T)-K T ×(T-T0)×V refAfter this series of signal acquisition and processing operations, high-quality voltage and current signals that accurately reflect the actual electrical characteristics of the catalyst components in the chemical reactor can be obtained, providing a reliable data basis for subsequent component performance evaluation, helping to accurately control the performance status of the components and ensure the effectiveness of the catalyst in chemical production.

[0042] The voltage precision control module is responsible for high-precision control of the power supply voltage to ensure that it is stable within the appropriate range and meets the test requirements of the catalyst element of the chemical reactor. During the test, the target voltage V is set. target =10V, the voltage monitoring and adjustment program uses the control algorithm to adjust the output voltage of the adjustable constant voltage source. For example, at a certain time k, the actual measured current voltage V actval (k) = 9.998V, at this time the voltage deviation e(k) = V target -V actual (k) = 0.002V, based on the proportionality coefficient K determined in advance through system modeling and multiple experimental debugging in a chemical production environment p =0.6, integral coefficient K i =0.15, differential coefficient K d =0.08, combined with the additional control quantity Δu derived by the fuzzy logic controller based on the voltage deviation and its rate of change fuzzy (k) = 0.0005 (the additional control amount is dynamically generated based on the fuzzy inference rules and the actual situation of the current voltage deviation and change rate), and the control signal u(k) is calculated according to the following formula: Based on this control signal, the MCU fine-tunes the adjustable constant voltage source through the adjustment interface, so that the supply voltage is always stably maintained within the range of ±1mV of the target voltage, minimizing the error caused by voltage fluctuations in the performance test of the catalyst element in the chemical reactor, ensuring the high accuracy of the test, and ensuring that the obtained element performance data is true and reliable, providing a strong basis for subsequent judgment on whether the element is suitable for chemical production.

[0043] The component performance evaluation module conducts a comprehensive and accurate performance evaluation of the chemical reactor catalyst component based on the collected and processed high-quality voltage and current data. The resistance calculation and change monitoring program first calculates the resistance value of the component strictly according to Ohm's law, and then uses the resistance stability evaluation algorithm based on dynamic time warping (DTW) to determine the stability of the resistance. For example, for a certain chemical reactor catalyst component, two sets of resistance sequences R n and R n+1 Each sequence contains 12 resistance data points (I = J = 12), and the distance metric function d(r i , r j) is the absolute value of the resistance difference, and the DTW distance DTW (R n , R n+1 ): Assume that the resistance stability judgment threshold ∈ is determined by analyzing the resistance series of a large number of chemical reactor catalyst elements in stable and unstable states. DTW =0.06Ω, if DTW(R n , R n+1 )≤∈ DTW , then the resistance of the component is determined to be in a stable state. If DTW(R n , R n+1 )>∈ DTW , the component access and isolation module is notified to continue to power on and activate the component until the resistance reaches a stable state. At the same time, the catalytic completion judgment program adopts a multi-parameter fusion catalytic completion judgment algorithm, comprehensively considers the change rate of resistance, current, voltage over time and other parameters closely related to chemical catalytic reactions (such as changes in the active component content of the catalyst, changes in porosity and other chemical characteristic parameters), so as to judge the catalytic completion time node of the catalytic element. For example, 4 resistance-related parameters (mm=4), 3 current-related parameters (n=3), 3 voltage-related parameters (o=3) and 2 chemical characteristic parameters (p=2) are selected to participate in the calculation. According to the importance of each parameter in reflecting the integrity of the chemical catalytic process, the weighted coefficients are determined to be α=0.35, β=0.25, γ=0.2, and δ=0.2, respectively. The catalytic completion time judgment index T is calculated according to the following formula c : Assume that through a large number of chemical production experiments and statistical analysis of data of different catalyst components under standard test conditions, the catalytic completion time judgment threshold T is determined. th =0.9, when T c ≤T th When the catalyst is detected, it is determined that the component has completed the catalytic process and meets the conditions for entering the matching stage. This can ensure that only chemical reactor catalyst components that meet performance standards enter the subsequent matching process, ensuring the scientific and rational use of catalysts in chemical production.

[0044] After the catalyst element of the chemical reactor meets the performance evaluation conditions, the component matching decision module carries out the matching operation. First, the matching standard setting program combines the actual process requirements of chemical production, chemical reaction characteristics and long-term application experience of catalyst elements to set detailed and strict matching standards. For example, taking the black element as the benchmark, the resistance ratio range of the matched white element must be controlled within [0.95-1.05], and the inductance difference must be within ±0.05H (considering the matching of electrical characteristics between components, inductance has an impact on the electromagnetic field environment and reaction process in the chemical reactor), and the performance fluctuation does not exceed 8% within the common temperature range (0℃-150℃) and pressure range (1-10MPa) of chemical production (ensuring that the element can stably play a catalytic role under complex chemical working conditions). At the same time, there is no electromagnetic interference between the components and no thermal runaway caused by close proximity (ensuring chemical production safety and catalyst synergy effect). The matching component search and statistical program uses an improved matching component search algorithm based on graph theory to construct a graph model G=(V, E), where the vertex set V is composed of all black component sets E b And white element set E ω The edge set E is composed according to the custom matching condition judgment function MatchCond(v i , v j ) is determined by strictly following the various matching requirements set above to determine whether two components can match. The maximum matching algorithm MaximalMatching (G) in graph theory is used to find the matching pair set M of all white components and black components that meet the conditions. Then, the sorting and matching execution program uses a comprehensive weight dynamic sorting algorithm to sort the selected matching white components. For example, for a matching white component i, the number of other components with potential matching conflicts N i =2 (meaning that the component faces relatively few interference factors during the matching process), and its parameter value C in the key electrical characteristic inductance i =0.3H (the maximum allowable value of this characteristic in this chemical application scenario is C max =0.5H), and through monitoring and analyzing the parameters related to the stability of component performance over a period of time, we can obtain (Select 6 time points to comprehensively evaluate the stability of component performance, T = 6), and the average change of all components in this performance parameter P avg =0.15, according to the predetermined weight coefficients ω1 = 0.45, ω2 = 0.3, ω3 = 0.25, the comprehensive ranking score S is calculated according to the following formula i : Component matching operations are performed in sequence according to the sorting results. After each matching is completed, all information related to component matching is updated in a timely manner, including the status marks of matched components (clearly marked as matched to avoid repeated matching), details of the remaining components to be matched (quantity, characteristics of each component and current matching status, etc.), and dynamic adjustment of the entire matching sequence, and then re-sorted according to the sorting rules. This cycle is repeated until the matching of all chemical reactor catalyst components is completed, ensuring the scientificity and efficiency of the matching results and adapting to the actual needs of chemical production, thereby improving the overall synergistic effect of catalysts in chemical production and improving the output and quality of chemical products.

[0045] In the entire test and matching process of the catalyst elements of the chemical reactor, the human-computer interaction prompt module plays an important role in information transmission and guidance. For example, when the system starts to test a batch of chemical catalyst elements, the green indicator light in the indicator light group lights up and remains on, indicating that the test process is started normally. The operator can observe this indicator light to know that the system is running normally. When entering the component matching link, the yellow indicator light begins to flash, intuitively reminding the operator that the component matching operation is currently being performed. If abnormal conditions such as component short circuit, overtemperature, and overpressure occur during the test (real-time monitoring is carried out by setting corresponding sensors in the system), the red indicator light will immediately light up, alerting the operator to take corresponding measures in time to deal with it. The operator can take and place the completed test matching components at the appropriate time according to the different status prompts presented by the indicator light, ensuring that the entire test matching process is carried out smoothly and orderly, ensuring the efficient completion of the catalyst element test matching work in chemical production, and thus laying a good foundation for the stable and efficient operation of chemical production.

[0046] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A catalytic element testing and matching system, characterized in that: The system includes the following components: component access and isolation module, signal acquisition and processing module, voltage precision control module, component performance evaluation module, component matching decision module and human-computer interaction prompt module; The component access and isolation module uses an adjustable constant voltage source as the power supply basis at the hardware level, and each relay of the relay array corresponds to a single component access channel, and realizes channel switching with the help of precise connection with the microcontroller unit, so that all components are fully isolated and only a single component is connected to the test circuit at a time. At the software level, the component channel control program running in the MCU uses a relay switching optimization algorithm that comprehensively considers the component test time, current and voltage fluctuations, calculates the optimal component access sequence through a quantitative formula, controls the opening and closing of the relays in sequence, and connects each catalytic component to the test circuit in turn; In terms of hardware, the signal acquisition and processing module uses high-precision analog-to-digital conversion chips and circuit design layouts to accurately capture the voltage signals at both ends of the component in real time at the key nodes of the test circuit. The current detection circuit relies on high-precision sensors and adaptive conditioning circuits to accurately detect the working current of the component. In terms of software, the signal acquisition driver coordinates the voltage acquisition port and the current detection circuit to work synchronously and convert the collected analog signals into digital signals. The data preprocessing program successively uses adaptive filtering algorithms and calibration compensation algorithms to eliminate signal deviations caused by hardware factors, improve the quality of the collected signals, and provide data support for subsequent component performance evaluation and other operations. In terms of hardware, the voltage precision control module builds an electrical connection link between the adjustment interface of the adjustable constant voltage source and the MCU, which can not only receive the control instructions of the MCU, but also is equipped with a voltage feedback detection circuit to feed back the output voltage situation to the MCU in real time, forming a closed-loop control mechanism. In terms of software, the voltage monitoring and adjustment program adopts a control algorithm, comprehensively considers the voltage deviation and its change rate, integrates the conventional control quantity determined by the proportional, integral, and differential coefficients, and the additional control quantity inferred by the fuzzy logic according to the deviation situation, generates a final control signal to act on the adjustment interface, and fine-tunes the output voltage of the adjustable constant voltage source; The component performance evaluation module is responsible for using the collected voltage and current data as the basic data source in terms of hardware. In the software, the resistance calculation and change monitoring program calculates the component resistance value in real time according to Ohm's law, and uses the resistance stability evaluation algorithm based on dynamic time regularization to comprehensively judge the resistance stability by analyzing the distance between the resistance sequences collected at different times. The catalytic completion judgment program uses a catalytic completion judgment algorithm with multi-parameter fusion, combined with a preset threshold to consider the performance evolution of the component during the entire test process, and judge the catalytic completion time node of the catalytic component. When the component reaches the expected stable state, it is determined that it meets the requirements for entering the matching link. The component matching decision module is based on multi-dimensional matching rules and takes black components as the benchmark to clearly set specific matching standards covering resistance ratio, electrical characteristics, environmental performance and electromagnetic compatibility. The matching component search and statistics program uses a matching component search algorithm based on graph theory. According to the rules defined by the graph model construction, it comprehensively traverses and searches in the set of white components that have completed performance evaluation, selects white components that meet all set conditions, and counts their number and records feature information. The sorting and matching execution program adopts a comprehensive weight dynamic sorting algorithm, and sorts the selected matching white components according to the corresponding formula based on comprehensive considerations such as matching conflict conditions and key electrical characteristics adaptation degree factors, and performs component matching operations in sequence according to the sorting results. After each match, it updates the relevant information including the status of the matched components, the details of the remaining components to be matched, and the matching sequence adjustment, and re-sorts the loop operation until the matching of all components is completed; In terms of hardware, the human-computer interaction prompt module is installed in the indicator light group, and conveys the current working status of the system and the test and matching progress of the components by presenting different colors and flashing modes. In terms of software, the status prompt program monitors the component test and matching related information fed back by each module in the system, and sends corresponding control signals to the indicator light group according to the prompt rules. The operator performs the component pick-up and placement operations according to the signals.

2. A catalytic element testing and matching system according to claim 1, characterized in that: At the software level, the component access and isolation module uses a relay switching optimization algorithm that comprehensively considers component test time, current and voltage fluctuations. The calculation formula is: Among them, n represents the optimization index of the nth possible component access sequence, N is the total number of catalytic components to be tested, T i (n) refers to the time spent testing the i-th component under the n-th connection sequence, λ is the weight coefficient of the current fluctuation, I i (n) represents the average working current of the component in the stable test phase when testing the i-th component under the n-th connection sequence, is the average current value of all components under test in normal working state, μ is the weight coefficient of voltage fluctuation, M represents the number of key nodes selected in the test circuit for monitoring voltage fluctuation, ΔV j (n) is the voltage fluctuation value at the jth monitoring node under the nth access sequence.

3. A catalytic element testing and matching system according to claim 1, characterized in that: The data preprocessing program in the signal acquisition and processing module successively uses an adaptive filtering algorithm and a calibration compensation algorithm to eliminate signal deviations caused by hardware factors. The formula of the adaptive filtering algorithm is: Among them, y(k) represents the filtered signal value output at time k after adaptive filtering, x(k) is the original signal collected at time k, P is the order of the filter, and a i (k) is the i-th adaptive filter coefficient at time k, Q(k) represents the filtering error at time k, d(k) is the desired noise-free signal, η is the learning rate parameter, and the calibration compensation algorithm formula is: V calibrated =V raw -V offset (T)-K T ×(T-T0)×V r x f , where V calibrated Indicates the accurate voltage signal value obtained after calibration and compensation, V raw is the original uncalibrated voltage signal value, V offset (T) is the zero drift voltage offset function related to temperature T, K T is the temperature coefficient of voltage or current, T represents the actual ambient temperature or the operating temperature of the hardware, T0 is the set reference temperature, V ref is the reference voltage value.

4. A catalytic element testing and matching system according to claim 1, characterized in that: The voltage precision control module uses a control algorithm to generate a final control signal, and the control algorithm formula is: Where u(k) represents the control signal output at time k, p , K i , K d are proportional, integral, and differential coefficients respectively, e(k) is the voltage deviation at time k, that is, the target voltage V target The actual measured current voltage V actuαl The difference between (k) and e(k) = V target -V actuai (k), Δu fuzzy (k) is the additional control quantity output by the fuzzy logic controller at time k, which is obtained through fuzzy inference rules based on the input voltage deviation e(k) and its change rate Δe(k)=e(k)-e(k-1).

5. A catalytic element testing and matching system according to claim 1, characterized in that: The component performance evaluation module uses a resistance stability evaluation algorithm based on dynamic time warping, and its calculation formula is: ΔR DTW =DTW(R n , r n+1 )≤∈ DTW , where DTW(R n , R n+1 ) represents the distance between the resistance series collected for the nth time and the n+1th time calculated based on the dynamic time warping algorithm, and I and J are the resistance series R n and R n+1 The length, w ij is the path weight matrix element in the dynamic time warping algorithm, d(r i , r j ) is the distance metric function between the i-th and j-th resistance values ​​in the resistor series, ΔR DTW Represents the resistance change evaluated based on the DTW algorithm, ∈ DTW is a preset resistance stability judgment threshold based on the DTW algorithm. If the resistance value changes, that is, ΔR DTW Greater than∈ DTW , indicating that the component has not yet reached a stable performance state. At this time, the program will promptly feedback the corresponding information to the component access and isolation module, informing it to continue to power on and activate the component to further stabilize the component performance. If the resistance value does not change, that is, ΔR DTW′ Less than or equal to ∈ DTW , it means that the component has reached a relatively stable state under the current test conditions, and it is determined that the component has completed the performance test of this stage and meets the conditions for entering the matching stage, thereby achieving accurate control of the component performance status.

6. A catalytic element testing and matching system according to claim 1, characterized in that: The catalytic completion judgment program of the component performance evaluation module uses a catalytic completion judgment algorithm of multi-parameter fusion, combined with a preset threshold to consider the performance evolution of the component during the entire test process, and judges the catalytic completion time node of the catalytic component. The algorithm formula is: Among them, T c It is the catalytic completion time judgment index of the catalytic element. α, β, γ, and δ are the weighted coefficients of the resistance change rate, current change rate, voltage change rate, and other parameter change amounts. m, n, o, and p represent the number of resistance, current, voltage, and other related parameters involved in the calculation. Represents the rate of change of the i-th resistance-related parameter over time, R avg is the average value of all resistance-related parameters involved in the calculation, Indicates the rate of change of the jth current-related parameter over time, I avg is the average value of all current-related parameters involved in the calculation, represents the rate of change of the kth voltage-related parameter over time, V avg Represents the average value of all voltage-related parameters involved in the calculation, ΔC l Indicates the change of the lth other related parameters, T th is the pre-set catalytic completion time judgment threshold, which is different from the calculated T c A comparison is performed to determine whether the components have reached a stable state for matching.

7. A catalytic element testing and matching system according to claim 1, characterized in that: The matching component search and statistical program in the component matching decision module uses a matching component search algorithm based on graph theory, and its algorithm formula is: Where G represents the constructed graph model, which is used to describe the potential matching relationship between catalytic elements. V is the vertex set of graph G, which consists of all black element sets E. b And white element set E w E is the edge set of graph G, edge (v i , v j ) represents the vertex v i and v j The represented component satisfies the matching condition, MatchCond(v i , v j ) is a custom matching condition judgment function, input two component vertices v i and v j , it is determined whether a match can be made according to various pre-set matching requirements. M is the maximum matching result found on the graph G by the maximum matching algorithm MaximalMatching in graph theory, that is, the set of matching pairs of white components and black components that meet the matching conditions finally searched.

8. A catalytic element testing and matching system according to claim 1, characterized in that: The sorting and matching execution program adopts a comprehensive weight dynamic sorting algorithm, and sorts the selected matching white components according to the corresponding formula by comprehensively considering the matching conflict situation and the key electrical characteristics adaptation degree factors. The algorithm formula is: Among them, S i represents the comprehensive ranking score of the i-th matching white element, ω1, ω2, ω3 are the weight coefficients corresponding to different influencing factors, N i Indicates that there is a potential matching conflict with the i-th matching white element, C i represents the specific parameter value of the i-th matching white component in a key electrical characteristic, C max represents the maximum parameter value allowed for the key electrical characteristic in the current application scenario, T represents the number of time points involved in calculating the performance stability of the component, ΔP it represents a performance parameter of the i-th matching white element at the t-th time point, P avg It is the average change in the corresponding performance parameters of all components involved in the calculation.

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