A method and system for assessing the quality of reclaimed rubber based on conductivity detection

Abstract

The application provides a regenerated rubber quality evaluation method and system based on conductivity detection, and belongs to the technical field of material testing, and comprises the following steps: collecting transient detection data and steady-state detection data of a regenerated rubber sample, and determining a transient detection process and a steady-state detection process; obtaining a use label set of the regenerated rubber sample, standard rubber data of each use label in the use label set, and mechanical grade data, collecting transient detection data and steady-state detection data of each standard regenerated rubber sample in the standard rubber data of each use label; determining use evaluation data of each use label, a carbon black fitting function and a molecular chain fitting function; obtaining a use label of a regenerated rubber sample to be evaluated, and determining a grade label of the regenerated rubber sample to be evaluated. The self-adaptive switching of fast screening and accurate judgment is realized, the evaluation accuracy is guaranteed, the detection efficiency is improved, and the conductivity detection is upgraded to a standardized quality evaluation method with clear physical mechanism support.

Description

Technical Field

[0001] This invention relates to the field of materials testing technology, and in particular to a method and system for quality assessment of reclaimed rubber based on conductivity detection. Background Technology

[0002] Since its inception in the mid-19th century, the quality assessment of the recycled rubber industry has long relied on offline destructive testing methods such as Mooney viscosity, tensile strength, and elongation at break, requiring lengthy processes including mixing, vulcanization, and sample preparation. In the late 20th century, electrical testing of carbon black-filled rubber gradually emerged. The DC low-voltage resistance method, due to its simple apparatus, became the traditional laboratory standard, but it could only obtain steady-state resistance values. AC impedance spectroscopy, through broadband scanning to analyze conductivity and polarization mechanisms, has become the mainstream high-precision technology; however, a single measurement takes tens of minutes and requires precise electrode contact. Although it can be combined with intelligent sensors to achieve real-time monitoring and adaptive adjustment of electrode contact status, it still struggles to meet the needs of rapid testing on production lines. While time-domain dielectric spectroscopy can capture relaxation behavior during dynamic processing, it is mostly used in research rather than quality inspection, and the deployment of online dielectric monitoring with integrated intelligent sensors at the industrial level is still immature. Microwave resonant cavity perturbation, as a cutting-edge non-destructive rapid testing technology, can achieve non-contact measurement, but it is severely limited by sample shape and thickness. The large-scale application of recycled rubber in tires, hoses and other fields has created an urgent need for rapid batch-by-batch quality inspection.

[0003] Therefore, the present invention provides a method and system for quality assessment of reclaimed rubber based on conductivity detection. Summary of the Invention

[0004] This invention provides a method and system for quality assessment of reclaimed rubber based on conductivity detection. It integrates the transient thermal conductivity response and steady-state current relaxation response of a thermoelectric composite probe, establishing a dual-modal electrical fingerprint system for reclaimed rubber quality assessment. Utilizing the inherent difference in response speed between carbon black network and molecular chain polarization under thermal and electrical excitation, it achieves parallel characterization of carbon black skeleton integrity and molecular chain mobility, eliminating the mutual misjudgment of under-regeneration and over-regeneration caused by the ambiguity of the U-shaped curve in the single-point resistance method. It enables adaptive switching between rapid screening and precise judgment modes, significantly improving detection efficiency while ensuring assessment accuracy, thus upgrading conductivity detection into a standardized quality assessment method with clear physical mechanism support.

[0005] In a first aspect, the present invention provides a method for quality assessment of recycled rubber based on conductivity detection, comprising: Step 1: Based on the thermoelectric composite probe, collect transient and steady-state detection data of the reclaimed rubber sample to determine the transient and steady-state detection procedures; Step 2: Obtain the set of application labels for the recycled rubber samples, the standard rubber compound data and mechanical grade data for each application label in the application label set, and collect the transient and steady-state test data for each standard recycled rubber sample in the standard rubber compound data for each application label. Step 3: Based on the mechanical grade data of each application label, the transient test data and steady-state test data of each standard reclaimed rubber sample in the standard rubber compound data, determine the application evaluation data, carbon black fitting function and molecular chain fitting function for each application label. Step 4: Obtain and, based on the application label of the reclaimed rubber sample to be evaluated, the application evaluation data of the application label, the carbon black fitting function, and the molecular chain fitting function, conduct testing and quality assessment on the reclaimed rubber sample to be evaluated, and determine the grade label of the reclaimed rubber sample to be evaluated.

[0006] According to the present invention, a method for quality assessment of reclaimed rubber based on conductivity detection is provided, step 1 of which includes: The thermoelectric composite probe is vertically pressed onto the surface of the recycled rubber sample with a preset constant pressure value. The thermoelectric composite probe includes at least a coaxially integrated four-probe electrode, a micro Peltier element, and a temperature detection element. Based on the temperature detection element in the thermoelectric composite probe, the contact temperature value between the thermoelectric composite probe and the rubber sample is collected at the contact time point. Obtain the indoor temperature value and determine whether the temperature difference between the indoor temperature value and the contact temperature value of the rubber sample is greater than the preset temperature difference value; If the temperature difference is greater than or equal to a preset temperature difference value, a high-frequency AC signal is applied to the reclaimed rubber sample within a first set time interval after the contact time point, and transient detection data is collected based on a set transient sampling frequency. After the first set time interval ends, a DC step voltage is applied to the reclaimed rubber sample, and a low-speed, high-precision ADC is started to collect steady-state detection data based on a set steady-state sampling frequency. The transient detection data includes transient current values ​​and transient temperature values ​​at multiple transient sampling time points, and the steady-state detection data includes steady-state current values ​​and steady-state temperature values ​​at multiple steady-state sampling time points. If the temperature difference is less than the preset temperature difference value, the transient detection data is determined to be empty. After the contact time point, a DC step voltage is applied to the detected reclaimed rubber sample, and a low-speed, high-precision ADC is started to collect steady-state detection data based on the set steady-state sampling frequency.

[0007] According to the present invention, a method for quality assessment of reclaimed rubber based on conductivity detection, step 1 further includes: Based on the transient current and transient temperature values ​​at every two adjacent transient sampling time points in the transient detection data, calculate the transient temperature coefficient of the next adjacent transient sampling time point in every two adjacent transient sampling time points; If the transient temperature coefficient is less than the preset temperature change threshold, it is determined that the thermal driving force of the transient sampling time point corresponding to the transient temperature coefficient is insufficient, and the label of the transient sampling time point corresponding to the transient temperature coefficient is determined to be invalid; otherwise, the label of the transient sampling time point corresponding to the transient temperature coefficient is determined to be retained. Based on the transient temperature coefficients and labels of all transient sampling time points in the transient detection data, a transient thermal conductivity point map is plotted. The horizontal axis of the transient thermal conductivity point map represents the transient sampling time points within the first set time interval, and the vertical axis represents the transient temperature coefficient. Transient sampling time points with invalid labels are grayed out in the transient thermal conductivity point map, while transient sampling time points with retained labels are greened out. Connect all the green points in the transient thermal conductivity point diagram in chronological order of the transient sampling time points to form a curve and determine the transient thermal conductivity curve; The sliding window length and sliding step size are determined based on the first set time interval and the transient sampling frequency, and multiple transient time windows of the transient thermal conductivity point map are determined. Based on the transient thermal conductivity point plot and transient thermal conductivity curve, the average transient temperature coefficient and the maximum coefficient of each transient time window are determined. Based on the average transient temperature coefficient of adjacent transient time windows, determine the mean change rate of the next adjacent transient time window between two adjacent transient time windows; Based on the maximum coefficient of adjacent transient time windows, determine the maximum coefficient change rate of the next adjacent transient time window between two adjacent transient time windows; Starting from the first transient time window, a first judgment condition and a second judgment condition are sequentially applied to each transient time window. The first transient time window that simultaneously satisfies both the first and second judgment conditions is marked as the molecular chain activation start window. The center of all transient sampling time points within the transient time window preceding the molecular chain activation start window is marked as the carbon black stabilization end time. The average transient temperature coefficient of the transient time window preceding the molecular chain activation start window is used as the transient carbon black adaptive value. The first judgment condition is that the absolute value of the mean change rate of the transient time window is less than the absolute value of the maximum coefficient change rate. The second judgment condition is that the maximum coefficient of the transient time window is less than or equal to the maximum coefficient of the next transient time window, and the average transient temperature coefficient of the transient time window is less than or equal to the average transient temperature coefficient of the next transient time window. Identify the peak transient temperature coefficient and the peak transient sampling time point from the transient thermal conductivity curve; Based on the carbon black stabilization end time, peak transient temperature coefficient, and peak transient sampling time point, the transient molecular chain adaptive value is determined.

[0008] According to the present invention, a method for quality assessment of reclaimed rubber based on conductivity detection, step 1 further includes: If the temperature difference between the steady-state temperature values ​​of two adjacent steady-state sampling time points in the first consecutive specified number of steady-state detection data is less than 0.1℃, the latest steady-state sampling time among the first consecutive specified number of adjacent steady-state sampling time points is determined as the sufficient thermal equilibrium time point, and the steady-state temperature value corresponding to the latest sufficient thermal equilibrium time point is determined as the reference temperature value. Based on the steady-state sampling frequency and the steady-state current value at every two adjacent steady-state sampling time points in the steady-state detection data, the steady-state current change rate at the next steady-state sampling time point in every two adjacent steady-state sampling time points is determined. If the steady-state current change rate is lower than the preset steady-state change threshold for a second consecutive specified number of steady-state sampling time points, the latest steady-state sampling time for the second consecutive specified number of steady-state sampling time points is determined as the rollback trigger time point, and the continuous acquisition of steady-state detection data is stopped. Extract all steady-state current values ​​from the first steady-state sampling time point to the corresponding steady-state trigger time point in the steady-state detection data to determine the steady-state analysis data; Based on steady-state analysis data and reference temperature values, determine the correction current value based on the reference temperature value at each steady-state sampling time point in the steady-state analysis data; Based on the corrected current values ​​at all steady-state sampling time points in the steady-state analysis data, a corrected current decay curve is plotted, where the horizontal axis of the corrected current decay curve represents all steady-state sampling time points in the steady-state analysis data, and the vertical axis represents the corrected current value. KWW fitting was performed on the correction current decay curve to determine the steady-state carbon black contribution value and the steady-state molecular chain contribution value.

[0009] According to the present invention, a method for quality assessment of reclaimed rubber based on conductivity detection, step 2 includes: Obtain the set of application labels for the recycled rubber samples, and obtain the standard rubber compound data and mechanical grade data for each application label in the application label set. The standard rubber compound data includes multiple standard recycled rubber samples whose temperature difference with the indoor temperature is greater than a preset temperature difference value, and the mechanical grade data includes the mechanical requirement data for each grade label. Each standard reclaimed rubber sample in the standard rubber compound data for each application label is designated as a test reclaimed rubber sample. Transient test data of each standard reclaimed rubber sample in the standard rubber compound data for each application label are collected to determine the transient thermal conductivity curve, transient carbon black adaptive value, and transient molecular chain adaptive value of each standard reclaimed rubber sample. At the same time, steady-state test data of each standard reclaimed rubber sample in the standard rubber compound data for each application label are collected to determine the correction current decay curve, carbon black current contribution value, and molecular chain current contribution value of each standard reclaimed rubber sample. Destructive testing was performed on each standard reclaimed rubber sample in the standard rubber compound data for each application label to determine the performance value of each mechanical property for each standard reclaimed rubber sample; The grade label of the standard reclaimed rubber sample is determined based on the mechanical grade data for each application label and the performance values ​​of all mechanical properties of each standard reclaimed rubber sample in the standard rubber compound data.

[0010] According to the present invention, a method for quality assessment of reclaimed rubber based on conductivity detection, step 3 includes: Based on the carbon black current contribution values ​​of all standard reclaimed rubber samples in the standard rubber compound data for each application label and the grade label, determine the carbon black current contribution range for each grade label for each application label. Based on the molecular chain point flow contribution values ​​of all standard reclaimed rubber samples in the standard rubber compound data for each application label and the grade label, determine the molecular chain flow contribution range for each grade label for each application label; Based on the carbon black current contribution range and molecular chain current contribution range of all grade labels for each application, the application evaluation data for each application label is determined. For each standard reclaimed rubber sample in the standard rubber compound data for each application label, a double exponential function was fitted to determine the first transient index and the second transient index based on the transient thermal conductivity curve, as well as the first steady-state index and the second steady-state index based on the corrected current decay curve for each standard reclaimed rubber sample. The ratio of the first transient index to the first steady-state index of each standard reclaimed rubber sample in the standard rubber compound data for each application label is calculated as the fast component time constant of the standard reclaimed rubber sample. At the same time, the ratio of the second transient index to the second steady-state index of each standard reclaimed rubber sample in the standard rubber compound data for each application label is calculated as the slow component time constant of the standard reclaimed rubber sample. Based on the fast component time constant and slow component time constant of all standard reclaimed rubber samples in the standard rubber compound data for each application label, the fast component time range and slow component time range for each application label are determined. If the fast component time constant of the standard reclaimed rubber sample belongs to the fast component time range of the corresponding application label, and the slow component time constant belongs to the slow component time range of the corresponding application label, the trend label of the standard reclaimed rubber sample is determined to be consistent; otherwise, the trend label of the standard reclaimed rubber sample is determined to be inconsistent. A reliable detection model was constructed based on transient thermal conductivity spectra and trend labels of all standard recycled rubber samples for each application label. Based on the transient carbon black adaptive value and carbon black current contribution value of standard reclaimed rubber samples with consistent trend labels for each application label, the carbon black fitting function for each application label is determined. At the same time, based on the transient molecular chain adaptive value and molecular chain current contribution value of standard reclaimed rubber samples with consistent trend labels for each application label, the molecular chain fitting function for each application label is determined.

[0011] According to the present invention, a method for quality assessment of reclaimed rubber based on conductivity detection, step 4 includes: Obtain the application label of the recycled rubber sample to be evaluated to confirm that the recycled rubber sample to be evaluated is a test recycled rubber sample; Collect transient detection data of the recycled rubber sample to be evaluated. If the transient detection data is not empty, determine the transient thermal conductivity curve, transient carbon black adaptive value, and transient molecular chain adaptive value of the recycled rubber sample to be evaluated based on the transient detection data. The transient thermal conductivity curve of the reclaimed rubber sample to be evaluated is input into the reliable detection model. If the output result of the reliable detection model is reliable, the carbon black current contribution value of the reclaimed rubber sample to be evaluated is determined based on the transient carbon black adaptive value and carbon black fitting function of the reclaimed rubber sample to be evaluated. At the same time, the molecular chain current contribution value of the reclaimed rubber sample to be evaluated is determined based on the transient molecular chain adaptive value and molecular chain fitting function of the reclaimed rubber sample to be evaluated. If the output of the reliable detection model is unreliable, collect steady-state detection data of the recycled rubber sample to be evaluated, and determine the carbon black current contribution value and molecular chain current contribution value of the recycled rubber sample to be evaluated. Based on the application label, carbon black current contribution value, molecular chain current contribution value, and application evaluation data of the application label of the reclaimed rubber sample to be evaluated, the grade label of the reclaimed rubber sample to be evaluated is determined.

[0012] Secondly, the present invention provides a quality assessment system for recycled rubber based on conductivity detection, comprising: Detection module: Based on the thermoelectric composite probe, transient and steady-state detection data of reclaimed rubber samples are collected to determine the transient and steady-state detection processes; Acquisition Module: Acquires the set of application labels for reclaimed rubber samples, standard rubber compound data and mechanical grade data for each application label in the application label set, and collects transient and steady-state test data for each standard reclaimed rubber sample in the standard rubber compound data for each application label; Determine the module: Based on the mechanical grade data of each application label, the transient test data and steady-state test data of each standard reclaimed rubber sample in the standard rubber compound data, determine the application evaluation data, carbon black fitting function and molecular chain fitting function for each application label. Evaluation module: Based on the application label of the reclaimed rubber sample to be evaluated, the application evaluation data of the application label, the carbon black fitting function, and the molecular chain fitting function, the module performs testing and quality evaluation on the reclaimed rubber sample to be evaluated, and determines the grade label of the reclaimed rubber sample to be evaluated.

[0013] Compared with the prior art, the beneficial effects of this application are as follows: By fusing the transient thermal conductivity response and steady-state current relaxation response of a thermoelectric composite probe, a dual-modal electrical fingerprint system for assessing the quality of reclaimed rubber was established. Utilizing the inherent difference in response speed between carbon black network and molecular chain polarization under thermal and electrical excitation, parallel characterization of carbon black skeleton integrity and molecular chain mobility was achieved, eliminating the mutual misjudgment of under-regeneration and over-regeneration caused by the U-shaped curve ambiguity in the single-point resistance method. Adaptive switching between rapid screening and precise judgment modes was realized, significantly improving detection efficiency while ensuring assessment accuracy, thus upgrading conductivity detection into a standardized quality assessment method with clear physical mechanism support. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0015] Figure 1 This is a schematic flowchart of a method for evaluating the quality of reclaimed rubber based on conductivity detection, provided in an embodiment of the present invention.

[0016] Figure 2 This is a schematic diagram of the structure of a geological structure feature analysis device for complex strata mining faces provided in an embodiment of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0018] Example 1: This invention provides a method for quality assessment of reclaimed rubber based on conductivity detection, such as... Figure 1 As shown, it includes: Step 1: Based on the thermoelectric composite probe, collect transient and steady-state detection data of the reclaimed rubber sample to determine the transient and steady-state detection procedures; Step 2: Obtain the set of application labels for the recycled rubber samples, the standard rubber compound data and mechanical grade data for each application label in the application label set, and collect the transient and steady-state test data for each standard recycled rubber sample in the standard rubber compound data for each application label. Step 3: Based on the mechanical grade data of each application label, the transient test data and steady-state test data of each standard reclaimed rubber sample in the standard rubber compound data, determine the application evaluation data, carbon black fitting function and molecular chain fitting function for each application label. Step 4: Obtain and, based on the application label of the reclaimed rubber sample to be evaluated, the application evaluation data of the application label, the carbon black fitting function, and the molecular chain fitting function, conduct testing and quality assessment on the reclaimed rubber sample to be evaluated, and determine the grade label of the reclaimed rubber sample to be evaluated.

[0019] In this embodiment, the thermoelectric composite probe is a composite sensor device that integrates a temperature sensing element with a four-probe electrode. The core function of this probe is to simultaneously apply a high-frequency AC signal and a DC step voltage signal to a reclaimed rubber sample at the same pressing position and under the same contact state, and to acquire the corresponding response signals. Transient detection data refers to the current and temperature values ​​acquired at a high sampling frequency within a very short time after the probe is pressed. Steady-state detection data refers to the current and temperature values ​​continuously acquired at a lower sampling frequency after the transient detection ends with the application of a DC step voltage. This data is used to record the slow relaxation process of charge carriers in the carbon black network and the rubber matrix. A transient detection procedure is performed on the transient detection data to determine the transient thermal conductivity curve, transient carbon black adaptive value, and transient molecular chain adaptive value of the tested rubber sample. A steady-state detection procedure is performed on the steady-state detection data to determine the steady-state carbon black contribution value and the steady-state molecular chain contribution value of the tested rubber sample.

[0020] In this embodiment, after outlier removal from the carbon black current contribution values ​​of all standard samples within each grade label under each application label, the minimum and maximum values ​​are calculated as the carbon black current contribution interval for that grade. The same processing is applied to the molecular chain current contribution values ​​to obtain the molecular chain current contribution interval. These two intervals together constitute the application evaluation data for that application. Simultaneously, the transient thermal conductivity curve and corrected current decay curve of each standard sample are fitted with a double exponential function to extract their respective exponential parameters. The ratio of the transient first exponent to the steady-state first exponent is used as the fast component time constant, and the ratio of the transient second exponent to the steady-state second exponent is used as the slow component time constant. The component time constants were determined, and the normal ranges of the fast and slow component time constants for all standard samples under this application were identified. Samples whose fast and slow component time constants both fell within the corresponding ranges were marked as having consistent trends. Only the transient thermal conductivity point maps of samples with consistent trends were used to construct a reliable detection model based on dynamic time regularization distance. The mapping relationship between the transient carbon black adaptive value and the carbon black current contribution value of samples with consistent trends was used to determine the carbon black fitting function, and the mapping relationship between the transient molecular chain adaptive value and the molecular chain current contribution value was used to determine the molecular chain fitting function. Samples with inconsistent trends were not included in the construction of any model or function.

[0021] Obtain the intended use label of the reclaimed rubber sample to be evaluated and treat it as a test sample. Then, collect transient detection data for the sample. If the transient detection data is not empty, it indicates that the temperature difference conditions meet the physical feasibility requirements for transient detection. Based on the transient detection data, determine the transient thermal conductivity curve, transient carbon black adaptive value, and transient molecular chain adaptive value of the sample. Input the transient thermal conductivity curve into a reliable detection model for morphological comparison. If the model output is reliable, it indicates that the thermoelectric coupling synchronization of the sample is normal. Directly use the carbon black fitting function to convert the transient carbon black adaptive value into a carbon black current contribution value, and use the molecular chain fitting function to convert the transient molecular chain adaptive value into a molecular chain electric current. The current contribution value is calculated as follows: If the reliable model output is unreliable, it indicates that the transient thermal conductivity of the sample has deviated from the normal state of the optimal regeneration window. The transient conversion result is abandoned, and steady-state detection data is collected instead. The carbon black current contribution value and molecular chain current contribution value of the sample are directly determined through the steady-state analysis process. Finally, regardless of whether the contribution value is obtained through the fast screening path or the steady-state precision judgment path, the corresponding application evaluation data is retrieved based on the application label of the sample. The carbon black contribution value and molecular chain contribution value are compared with the contribution range of each grade label. Only when both contribution values ​​fall into the corresponding range of a certain grade are the sample determined to belong to that grade and the final grade label is output as the quality evaluation conclusion.

[0022] The beneficial effects of the above technical solution are as follows: By integrating the transient thermal conductivity response and steady-state current relaxation response of the thermoelectric composite probe, a dual-modal electrical fingerprint system for reclaimed rubber quality assessment is established. Utilizing the inherent difference in response speed between carbon black network and molecular chain polarization under thermal and electrical excitation, parallel characterization of carbon black skeleton integrity and molecular chain mobility is achieved, eliminating the mutual misjudgment of under-regeneration and over-regeneration caused by the ambiguity of the U-shaped curve in the single-point resistance method. Adaptive switching between rapid screening and precise judgment modes is realized, significantly improving detection efficiency while ensuring assessment accuracy, and upgrading conductivity detection into a standardized quality assessment method with clear physical mechanism support.

[0023] Example 2: This invention provides a method for quality assessment of reclaimed rubber based on conductivity detection. Step 1 includes: The thermoelectric composite probe is vertically pressed onto the surface of the recycled rubber sample with a preset constant pressure value. The thermoelectric composite probe includes at least a coaxially integrated four-probe electrode, a micro Peltier element, and a temperature detection element. Based on the temperature detection element in the thermoelectric composite probe, the contact temperature value between the thermoelectric composite probe and the rubber sample is collected at the contact time point. Obtain the indoor temperature value and determine whether the temperature difference between the indoor temperature value and the contact temperature value of the rubber sample is greater than the preset temperature difference value; If the temperature difference is greater than or equal to a preset temperature difference value, a high-frequency AC signal is applied to the reclaimed rubber sample within a first set time interval after the contact time point, and transient detection data is collected based on a set transient sampling frequency. After the first set time interval ends, a DC step voltage is applied to the reclaimed rubber sample, and a low-speed, high-precision ADC is started to collect steady-state detection data based on a set steady-state sampling frequency. The transient detection data includes transient current values ​​and transient temperature values ​​at multiple transient sampling time points, and the steady-state detection data includes steady-state current values ​​and steady-state temperature values ​​at multiple steady-state sampling time points. If the temperature difference is less than the preset temperature difference value, the transient detection data is determined to be empty. After the contact time point, a DC step voltage is applied to the detected reclaimed rubber sample, and a low-speed, high-precision ADC is started to collect steady-state detection data based on the set steady-state sampling frequency.

[0024] In this embodiment, the thermoelectric composite probe is a composite sensor device that integrates a four-probe electrode, a miniature Peltier element, and a temperature sensing element coaxially. The four-probe electrode is used to apply an electrical signal to the rubber sample and simultaneously measure the response current to eliminate interference from wire resistance and contact resistance. The miniature Peltier element is used to actively control the temperature of the contact surface when needed. The temperature sensing element, such as a PT1000 thin-film thermistor, is used to sense the temperature change between the probe and the rubber contact surface in real time. The purpose of pressing the probe vertically against the sample surface with a preset constant pressure value is to ensure that the contact state between the electrode and the rubber remains consistent during each test, avoiding fluctuations in contact resistance due to different pressures that could affect the stability and comparability of the electrical signal. The preset constant pressure value is usually pre-calibrated based on the probe structure and rubber hardness, for example, 5N, to ensure that the electrode can pierce the surface oil film and form a stable electrical contact with the internal carbon black network.

[0025] In this embodiment, the indoor temperature value is obtained, which represents the ambient temperature of the thermoelectric composite probe before it is pressed. At the same time, the temperature value of the contact surface of the rubber sample is obtained through the temperature detection element integrated in the probe. The two are subtracted and the absolute value is taken to obtain the temperature difference. The temperature difference is used to determine whether transient detection is physically feasible under the current conditions. Its essence is to determine whether the natural temperature difference between the probe and the rubber is sufficient to generate a recognizable thermal shock signal.

[0026] In this embodiment, when the temperature difference is greater than or equal to a preset temperature difference value, transient detection is deemed feasible. Within a first preset time interval after the contact time point, a high-frequency AC signal is applied to the tested reclaimed rubber sample. The purpose of the high-frequency AC signal is to excite and measure the instantaneous response of the carbon black network to temperature changes without inducing molecular chain dipole polarization. The transient detection data includes transient current values ​​and transient temperature values ​​at multiple transient sampling time points. After the first preset time interval ends, a DC step voltage is applied to the tested reclaimed rubber sample. Simultaneously, a low-speed, high-precision ADC is activated, and steady-state detection data is acquired based on a preset steady-state sampling frequency. The purpose of the DC step voltage is to excite the slow relaxation process of charge carriers in the carbon black network and the rubber matrix. The steady-state detection data includes steady-state current values ​​and steady-state temperature values ​​at multiple steady-state sampling time points. Transient detection and steady-state detection are sequential in time but the excitation signals are different. The former uses thermal shock to obtain a rapid response, while the latter uses a DC electric field to obtain the relaxation process.

[0027] In this embodiment, the first set time interval ranges from 3 to 10 seconds, with a recommended value of 5 seconds. This value is determined based on the fact that the effective response time of transient thermal shock is approximately 2 to 5 seconds. The thermal response of the carbon black network reaches its peak and enters a plateau phase within 0.5 to 2 seconds after compression. The molecular chain thermal activation peak appears in the 1 to 3 second range. By 5 seconds, the thermal shock response has essentially subsided. Extending the window further would introduce invalid tail noise data, while shortening the window would truncate the molecular chain thermal activation peak, resulting in incomplete molecular chain characteristic information in the transient thermal conductivity curve. Therefore, 5 seconds is the preferred value that strikes a balance between fully capturing thermal response information and improving detection efficiency.

[0028] In this embodiment, the transient sampling frequency ranges from 20Hz to 100Hz, with 50Hz being the recommended value. This value is determined based on the fact that the time width of the molecular chain activation peak in the transient thermal conductivity curve is typically 0.5 to 2 seconds, and its rise and fall edges change rapidly. A sampling frequency of 50Hz corresponds to a sampling interval of 0.02 seconds, which allows for the collection of 25 to 100 sampling points in this peak region. This is sufficient to completely describe the peak shape characteristics and ensure peak positioning accuracy. However, sampling points below 50Hz are too few, leading to the loss of peak details, while sampling frequencies above 50Hz are too large, and the introduced high-frequency noise exceeds the signal gain. Therefore, 50Hz is an optimal balance point between signal resolution and data redundancy.

[0029] In this embodiment, the steady-state sampling frequency ranges from 5Hz to 20Hz, with 10Hz being the recommended value. This value is determined based on the fact that the time scale of the current relaxation process in the steady-state stage is on the order of tens of seconds and the current change is relatively smooth. A sampling frequency of 10Hz corresponds to a sampling interval of 0.1 seconds, and a total of 600 sampling points are collected within a 60-second detection window, which is sufficient to completely depict the shape of the current decay curve and ensure the KWW fitting accuracy. However, if the sampling points are too few when the frequency is below 10Hz, it will affect the feature extraction of the fast relaxation component. If the frequency is above 20Hz, the redundant data collected exceeds the actual needs of subsequent gating judgment and fitting analysis and increases the storage and processing burden. Therefore, 10Hz is the optimized value that meets the minimum signal-to-noise ratio requirements for KWW fitting accuracy and real-time calculation of the gating change rate without generating data redundancy.

[0030] In this embodiment, the preset temperature difference value can be 3°C. Within the 0-5 second transient detection window after the probe is pressed, the thermal shock generated by the natural temperature difference between the probe and the rubber is needed to excite the thermal response signal of the carbon black network. The magnitude of the temperature difference directly determines the intensity of the thermal shock. When the temperature difference is less than 3°C, the temperature change rate within 5 seconds after the probe contacts the rubber is usually less than 0.5°C per second. At this time, the thermal shock energy is insufficient to make the carbon black network generate a sufficiently large thermal current change rate response. When the temperature difference reaches more than 3°C, the thermal shock is sufficient to generate a significant molecular chain thermal activation peak within the 0-5 second window. The amplitude of this peak is at least more than three times the baseline noise, making the distinction between the carbon black plateau segment and the molecular chain peak segment on the transient thermal conductivity curve sufficiently statistically significant.

[0031] The beneficial effects of the above technical solution are as follows: It acquires both transient and steady-state detection data of reclaimed rubber samples based on a thermoelectric composite probe. It can adaptively acquire dual-mode signals according to temperature differences, enhancing the environmental adaptability of the detection method.

[0032] Example 3: This invention provides a method for quality assessment of reclaimed rubber based on conductivity detection. Step 1 further includes: Based on the transient current and transient temperature values ​​at every two adjacent transient sampling time points in the transient detection data, calculate the transient temperature coefficient of the next adjacent transient sampling time point in every two adjacent transient sampling time points; If the transient temperature coefficient is less than the preset temperature change threshold, it is determined that the thermal driving force of the transient sampling time point corresponding to the transient temperature coefficient is insufficient, and the label of the transient sampling time point corresponding to the transient temperature coefficient is determined to be invalid; otherwise, the label of the transient sampling time point corresponding to the transient temperature coefficient is determined to be retained. Based on the transient temperature coefficients and labels of all transient sampling time points in the transient detection data, a transient thermal conductivity point map is plotted. The horizontal axis of the transient thermal conductivity point map represents the transient sampling time points within the first set time interval, and the vertical axis represents the transient temperature coefficient. Transient sampling time points with invalid labels are grayed out in the transient thermal conductivity point map, while transient sampling time points with retained labels are greened out. Connect all the green points in the transient thermal conductivity point diagram in chronological order of the transient sampling time points to form a curve and determine the transient thermal conductivity curve; The sliding window length and sliding step size are determined based on the first set time interval and the transient sampling frequency, and multiple transient time windows of the transient thermal conductivity point map are determined. Based on the transient thermal conductivity point plot and transient thermal conductivity curve, the average transient temperature coefficient and the maximum coefficient of each transient time window are determined. Based on the average transient temperature coefficient of adjacent transient time windows, determine the mean change rate of the next adjacent transient time window between two adjacent transient time windows; Based on the maximum coefficient of adjacent transient time windows, determine the maximum coefficient change rate of the next adjacent transient time window between two adjacent transient time windows; Starting from the first transient time window, a first judgment condition and a second judgment condition are sequentially applied to each transient time window. The first transient time window that simultaneously satisfies both the first and second judgment conditions is marked as the molecular chain activation start window. The center of all transient sampling time points within the transient time window preceding the molecular chain activation start window is marked as the carbon black stabilization end time. The average transient temperature coefficient of the transient time window preceding the molecular chain activation start window is used as the transient carbon black adaptive value. The first judgment condition is that the absolute value of the mean change rate of the transient time window is less than the absolute value of the maximum coefficient change rate. The second judgment condition is that the maximum coefficient of the transient time window is less than or equal to the maximum coefficient of the next transient time window, and the average transient temperature coefficient of the transient time window is less than or equal to the average transient temperature coefficient of the next transient time window. Identify the peak transient temperature coefficient and the peak transient sampling time point from the transient thermal conductivity curve; Based on the carbon black stabilization end time, peak transient temperature coefficient, and peak transient sampling time point, the transient molecular chain adaptive value is determined.

[0033] In this embodiment, the formula for calculating the transient temperature coefficient is expressed as follows: ; in, This represents the transient temperature coefficient at the i-th transient sampling time point. This represents the transient current value and transient temperature value at the i-th transient sampling time point. This represents the transient current value and transient temperature value at the (i-1)th transient sampling time point. It represents the time interval between two adjacent transient sampling points.

[0034] In this embodiment, when the transient temperature coefficient is less than the preset temperature change threshold, it indicates that the temperature near the sampling time point has hardly changed. The calculated temperature coefficient value at this time is unreliable, so the point is marked as invalid. Otherwise, it is marked as retained.

[0035] In this embodiment, the preset temperature change threshold is set to 0.05℃. This value is determined based on the effective resolution of the temperature sensing element and the actual noise level in the industrial testing environment. During transient detection, the calculation of the transient temperature coefficient requires dividing the current change between two adjacent points by the temperature change. When the temperature change between adjacent sampling points is less than 0.05℃, this change is close to or lower than the uncertainty range constituted by the effective resolution of the PT1000 temperature sensor in an industrial environment, plus circuit noise and quantization error. At this point, the calculated transient temperature coefficient will be drastically amplified because the denominator approaches zero. Regardless of the current change, it will produce unreliable results with drastic numerical fluctuations. This result is entirely dominated by measurement noise and no longer reflects the thermal response characteristics of the material itself. Therefore, only when the temperature change exceeds this threshold does the calculated temperature coefficient have a sufficient signal-to-noise ratio for subsequent analysis. Sampling points with a temperature change less than this threshold are judged as having insufficient thermal driving force and marked as invalid.

[0036] In this embodiment, after marking each sampling time point, a transient thermal conductivity point plot is drawn based on the transient temperature coefficients of all sampling time points in the transient detection data and their corresponding labels. The horizontal axis of the point plot represents the transient sampling time points within a first set time interval, and the vertical axis represents the transient temperature coefficient. Points with invalid labels are displayed in gray, while points with retained labels are displayed in green. Subsequently, all valid green points in the transient thermal conductivity point plot are connected sequentially according to the sampling time to form a continuous curve, which is the transient thermal conductivity curve.

[0037] In this embodiment, the sliding window length and sliding step size are determined based on a first set time interval and transient sampling frequency, and multiple transient time windows are determined on the transient thermal conductivity curve accordingly. The sliding window length is determined to ensure that the curve's trend within the window is representative while retaining enough data points for statistical calculations. The sliding step size is determined to ensure sufficient overlap between adjacent windows to avoid missing key inflection points. For each transient time window, the system calculates the average value of all transient temperature coefficients within the window as the average transient temperature coefficient of that window, and finds the maximum value of the transient temperature coefficient within the window as the maximum coefficient of the window. These two statistics reflect the overall level of the thermal response and the intensity of local extrema within the window, respectively.

[0038] In this embodiment, after obtaining the average and maximum values ​​for each window, the difference between the average values ​​of the subsequent transient time window and the preceding transient time window is calculated. This difference is then divided by the average value of the preceding transient time window to obtain the rate of change of the mean. This rate of change reflects the overall trend of the thermal response between adjacent windows. Similarly, based on the maximum values ​​of each of the two adjacent transient time windows, the rate of change of the maximum coefficient of the subsequent window relative to the preceding window is calculated. This rate of change reflects the trend of the intensity of local extrema of the thermal response between adjacent windows. These two rates of change characterize the evolution of the transient thermal conductivity curve between different windows from the dimensions of overall mean and local extrema, respectively.

[0039] In this embodiment, starting from the first transient time window, each window is evaluated sequentially based on two judgment conditions. The first judgment condition is that the absolute value of the mean change rate of the window is less than the absolute value of the maximum coefficient change rate. The second judgment condition is that the maximum coefficient of the window is less than or equal to the maximum coefficient of the next window, and the average transient temperature coefficient of the window is less than or equal to the average transient temperature coefficient of the next window. The physical basis for the first judgment condition is that the mean and maximum values ​​change synchronously within the carbon black-dominated period window, so their change rates are similar. When the molecular chain begins to generate local thermal activation peaks, the maximum value will jump rapidly due to the local peak, but the mean value remains stable because the peak proportion is small. At this time, the change rate of the mean will be significantly less than the change rate of the maximum coefficient. The physical basis for the second judgment condition is that once the thermal activation of the molecular chain begins, its intensity and range will continue to expand, manifested as the maximum value and average value of the next window not being lower than the current window. When both conditions are met simultaneously, it can be confirmed that the thermal activation of the molecular chain has been substantially started. The first window that simultaneously meets these two conditions is marked as the molecular chain activation start window, which marks the end of the carbon black-dominated period and the beginning of the molecular chain thermal activation.

[0040] In this embodiment, after determining the molecular chain activation initiation window, the window preceding this window is defined as the last window of the carbon black stabilization plateau period. The center time of all transient sampling time points within the preceding window is marked as the carbon black stabilization end time, which represents the time boundary of the end of the carbon black network's thermal response. The average value of all transient temperature coefficients within the preceding window is used as the transient carbon black adaptive value, which represents the average temperature sensitivity of the carbon black network when it reaches a stable state under thermal shock.

[0041] In this embodiment, the peak transient temperature coefficient, i.e. the global maximum value, and the peak transient sampling time point corresponding to the maximum value are identified from the transient thermal conductivity curve. The peak point represents the moment when the molecular chain thermal response is most intense.

[0042] In this embodiment, the transient molecular chain adaptive value is determined based on the carbon black stabilization end time, the peak transient temperature coefficient, and the peak transient sampling time. The core components of this value include the height of the peak temperature coefficient and the time span from the carbon black stabilization end time to the peak time. The former reflects the intensity of the molecular chain thermal activation, and the latter reflects the time required for the molecular chain to reach its maximum response from the start, i.e., the activation speed. The combination of the two constitutes the characteristic value describing the thermal activation state of the molecular chain.

[0043] In this embodiment, the molecular chain adaptive value is equal to the product of the difference between the peak transient sampling time and the carbon black stabilization end time and the peak transient temperature coefficient.

[0044] The beneficial effects of the above technical solution are as follows: A transient detection process is executed on the transient detection data to determine the transient thermal conductivity curve, transient carbon black adaptive value, and transient molecular chain adaptive value of the tested rubber sample. This achieves the separation of the carbon black-dominant period and the molecular chain activation period, eliminating the feature extraction distortion problem caused by differences in relaxation rates among different samples in the fixed time window method.

[0045] By calculating the transient temperature coefficient and using an adaptive sliding window criterion, the automatic separation of the carbon black-dominant period and the molecular chain activation period was achieved. A dual-condition joint judgment mechanism accurately identifies the starting window of molecular chain thermal activation and, in turn, locks the ending boundary of the carbon black stable plateau period. This allows for the extraction of carbon black adaptive values ​​and molecular chain adaptive values ​​with clear physical boundaries from the transient thermal conductivity curve. This eliminates the feature extraction distortion problem caused by differences in relaxation rates among different samples in the fixed-time-window method. The transient detection results accurately reflect the structural states of the carbon black network and molecular chains within the optimal regeneration window, providing physically clear and repeatable data for subsequent quality assessment.

[0046] Example 4: This invention provides a method for quality assessment of reclaimed rubber based on conductivity detection. Step 1 further includes: If the temperature difference between the steady-state temperature values ​​of two adjacent steady-state sampling time points in the first consecutive specified number of steady-state detection data is less than 0.1℃, the latest steady-state sampling time among the first consecutive specified number of adjacent steady-state sampling time points is determined as the sufficient thermal equilibrium time point, and the steady-state temperature value corresponding to the latest sufficient thermal equilibrium time point is determined as the reference temperature value. Based on the steady-state sampling frequency and the steady-state current value at every two adjacent steady-state sampling time points in the steady-state detection data, the steady-state current change rate at the next steady-state sampling time point in every two adjacent steady-state sampling time points is determined. If the steady-state current change rate is lower than the preset steady-state change threshold for a second consecutive specified number of steady-state sampling time points, the latest steady-state sampling time of the second consecutive specified number of steady-state sampling time points is determined as the rollback trigger time point, and the continuous acquisition of steady-state detection data is stopped. Extract all steady-state current values ​​from the first steady-state sampling time point to the corresponding steady-state trigger time point in the steady-state detection data to determine the steady-state analysis data; Based on steady-state analysis data and reference temperature values, determine the correction current value based on the reference temperature value at each steady-state sampling time point in the steady-state analysis data; Based on the corrected current values ​​at all steady-state sampling time points in the steady-state analysis data, a corrected current decay curve is plotted, where the horizontal axis of the corrected current decay curve represents all steady-state sampling time points in the steady-state analysis data, and the vertical axis represents the corrected current value. KWW fitting was performed on the correction current decay curve to determine the steady-state carbon black contribution value and the steady-state molecular chain contribution value.

[0047] In this embodiment, during steady-state detection, the steady-state temperature value at each steady-state sampling time point is continuously monitored. When the temperature difference between any two adjacent sampling points is less than 0.1 degrees Celsius for a specified number of consecutive times, it indicates that the probe and the rubber contact surface have reached a sufficient thermal equilibrium state, at which point the temperature no longer changes significantly. The first specified number of consecutive times can be 5. The latest sampling time point in this continuous sequence is recorded as the sufficient thermal equilibrium time point, and the temperature value corresponding to this moment is locked as the reference temperature value. The purpose of this reference temperature value is to serve as the sole reference point for all subsequent temperature correction calculations. All current values ​​will be converted to this reference temperature for comparison, thereby eliminating the interference of ambient temperature fluctuations on the measurement results.

[0048] In this embodiment, the steady-state current change rate reflects how fast the current decays over time and is a direct quantitative indicator for determining whether the relaxation process has ended.

[0049] In this embodiment, the formula for calculating the steady-state current change rate is expressed as: ; in, This represents the rate of change of steady-state current at the j-th steady-state sampling time point in the steady-state detection data. This represents the steady-state current value at the j-th steady-state sampling time point and the (j-1)-th steady-state sampling time point. This represents the time interval between two adjacent stable sampling time points.

[0050] In this embodiment, when the rate of change of current at a specified number of consecutive sampling points is lower than a preset steady-state change threshold, it indicates that the current decay has slowed down to near stop, at which point the relaxation process is essentially complete. The latest sampling time point in this continuous sequence is recorded as the rollback trigger time point, and the continuous acquisition of steady-state detection data is immediately stopped, ensuring that the endpoint of data acquisition is determined by the physical relaxation rate of the material itself rather than a fixed time preset by the user.

[0051] In this embodiment, after the rollback is triggered, all steady-state current values ​​from the first steady-state sampling time point to the rollback trigger time point are extracted from the steady-state detection data. These data constitute complete steady-state analysis data, which includes the entire historical evolution process from the moment the DC voltage is applied to the complete end of relaxation.

[0052] In this embodiment, if the rollback command is not triggered within a preset maximum waiting time, such as 60 seconds, starting from the moment the DC step voltage is applied, the measurement is determined to have timed out, and an error is automatically reported and the system exits, indicating that the sample conductive network is abnormal or the probe has a contact failure.

[0053] In this embodiment, the current value of each sampling point in the steady-state analysis data is temperature-corrected based on the previously locked reference temperature value.

[0054] In this embodiment, based on steady-state analysis data and a reference temperature value, the correction current value at each steady-state sampling time point in the steady-state analysis data is determined, and the calculation formula is expressed as follows: ; in, This represents the corrected current value at the j-th steady-state sampling time point in the steady-state analysis data. This represents the steady-state temperature value at the j-th steady-state sampling time point in the steady-state analysis data. Indicates the reference temperature value. This indicates the steady-state sampling time point corresponding to the rollback trigger time point.

[0055] In this embodiment, This represents the average steady-state temperature at the rollback trigger time point and the two steady-state sampling time points prior to the rollback trigger time point. Within these 3 seconds, the temperature difference between the probe and the rubber has been less than 0.1℃, and both fast and slow relaxation have ended. The Seebeck effect has almost returned to zero, and the current is almost a horizontal straight line within the instrument's accuracy range.

[0056] In this embodiment, the steady-state current value contains components that do not change with relaxation, including the circuit's DC bias, residual interface polarization, and the Seebeck potential of the probe-rubber contact surface. These components persist after relaxation ends. The average steady-state temperature at the rollback trigger time and two preceding steady-state sampling times is taken as the total non-degradable background remaining after relaxation. Therefore, this fixed background is subtracted from the steady-state current value at each sampling point.

[0057] In this embodiment, in the field of reclaimed rubber, current transmission mainly relies on the tunneling effect and thermal emission between carbon black particles. Industry consensus and a large amount of experimental data show that the temperature coefficient of conductivity of carbon black-filled rubber compounds usually falls within the range of 0.005-0.1, with 0.008 being the generally accepted median default value.

[0058] In this embodiment, the conductivity of the rubber depends on the thermally assisted tunneling effect between carbon black particles. Higher temperatures increase the carrier transition probability, naturally leading to a rise in current amplitude. However, this increase is unrelated to the material's internal structure and is purely a pseudo-change caused by environmental temperature fluctuations. To ensure comparability of data measured in different seasons and environments, the steady-state current values ​​at all steady-state sampling points must be converted to the same reference temperature. The exponential function, derived from the first-order approximation of the Arrhenius equation, describes the exponential dependence of conductivity on temperature; for every 1°C increase in temperature, the current value increases by approximately 0.008. By uniformly converting the baseline-detached dynamic currents to the same temperature reference, the interference of temperature fluctuations on the carrier transition probability is completely eliminated, ensuring that subsequent relaxation component separation is based entirely on the differences in the material's microstructure.

[0059] In this embodiment, after point-by-point correction, a correction current decay curve is plotted. The horizontal axis of the curve represents all sampling time points in the steady-state analysis data, and the vertical axis represents the corrected current value. At this time, the curve only reflects the current change caused by carrier migration itself.

[0060] In this embodiment, during KWW fitting, three undetermined parameters are first determined: the initial amplitude characteristic relaxation time and the stretching exponent parameter. The initial amplitude physically represents the total response intensity at the instant the excitation is applied. The characteristic relaxation time represents the core timescale of the relaxation process, and the stretching exponent parameter reflects the width of the relaxation time distribution. When this parameter is close to 1, the relaxation tends to be a single exponential process, indicating that the system is relatively homogeneous. When this parameter is significantly less than 1, the relaxation exhibits a wide distribution characteristic, indicating that there are multiple processes with different rates superimposed within the system. The mathematical implementation of the fitting is to continuously adjust the values ​​of the three parameters through an iterative optimization algorithm to minimize the sum of squared residuals between the theoretical current value calculated according to the KWW function and the measured corrected current value. After iterative convergence, the optimal combination of fitting parameters for the sample under the detection conditions is obtained. After parameter extraction, the total relaxation needs to be decomposed into two components: carbon black contribution and molecular chain contribution. This decomposition is not directly performed by the KWW fitting itself, but rather based on the characteristic relaxation time and stretching index parameters in the fitting results for physical assignment. The electron tunneling and migration processes in the carbon black network relax extremely quickly, typically reaching equilibrium within a very short time after applying a DC voltage; the corresponding characteristic relaxation time belongs to the fast component range. Conversely, the polarization accumulation and molecular chain dipole orientation processes at the carbon black-rubber interface relax extremely slowly, with relaxation times often exceeding those of the carbon black process by an order of magnitude; these belong to the slow component range. The fitted characteristic relaxation times are then compared with a preset physical boundary time constant. The process compares and attributes the portion of the relaxation process faster than the threshold time to the contribution of the carbon black network, and the portion slower to the threshold time to the contribution of molecular chain polarization and interface relaxation. Specifically, the total initial amplitude is split from the complete relaxation function given by KWW fitting into the initial amplitude of the fast component dominated by carbon black and the initial amplitude of the slow component dominated by molecular chains according to the component weights corresponding to the characteristic relaxation times. These two initial amplitudes are output as the steady-state carbon black contribution value and the steady-state molecular chain contribution value, respectively. The carbon black contribution value directly reflects the integrity of the conductive framework, and the molecular chain contribution value directly reflects the polarization activity of the carbon black rubber interface and the dipole orientation ability of the molecular chains.

[0061] The beneficial effects of the above technical solution are as follows: Steady-state temperature monitoring enables adaptive locking of the reference temperature; a dynamic gating mechanism monitors the rate of change of current, automatically identifying the relaxation termination moment and triggering rollback acquisition, thus completely preserving the entire historical waveform from voltage application to relaxation termination. Point-by-point correction based on the reference temperature value eliminates the influence of ambient temperature drift on the relaxation curve, ensuring that the corrected current decay curve truly reflects the intrinsic process of carrier migration within the material. KWW fitting separates the fast-relaxing components of the carbon black skeleton from the slow-relaxing components of molecular chain polarization, providing carbon black contribution values ​​and molecular chain contribution values ​​with clear physical meaning for the quality assessment of carbon black-filled reclaimed rubber.

[0062] Example 5: This invention provides a method for quality assessment of reclaimed rubber based on conductivity detection. Step 2 includes: Obtain the set of application labels for the recycled rubber samples, and obtain the standard rubber compound data and mechanical grade data for each application label in the application label set. The standard rubber compound data includes multiple standard recycled rubber samples whose temperature difference with the indoor temperature is greater than a preset temperature difference value, and the mechanical grade data includes the mechanical requirement data for each grade label. Each standard reclaimed rubber sample in the standard rubber compound data for each application label is designated as a test reclaimed rubber sample. Transient test data of each standard reclaimed rubber sample in the standard rubber compound data for each application label are collected to determine the transient thermal conductivity curve, transient carbon black adaptive value, and transient molecular chain adaptive value of each standard reclaimed rubber sample. At the same time, steady-state test data of each standard reclaimed rubber sample in the standard rubber compound data for each application label are collected to determine the correction current decay curve, carbon black current contribution value, and molecular chain current contribution value of each standard reclaimed rubber sample. Destructive testing was performed on each standard reclaimed rubber sample in the standard rubber compound data for each application label to determine the performance value of each mechanical property for each standard reclaimed rubber sample; The grade label of the standard reclaimed rubber sample is determined based on the mechanical grade data of each application label and the performance values ​​of all mechanical properties of each standard reclaimed rubber sample in the standard rubber compound data.

[0063] In this embodiment, a set of application labels for the recycled rubber samples is obtained. This set refers to the sum of all categories of labels categorized according to the final application scenario of the recycled rubber, such as tire treads, sealing strips, shoe soles, and shock-absorbing pads. For each application label in the set, the system obtains its corresponding standard rubber compound data and mechanical grade data. The standard rubber compound data refers to multiple pre-selected standard recycled rubber samples for that application. These samples all meet the prerequisite that the temperature difference between the sample and the room temperature is greater than a preset value. This condition ensures that the transient detection data is not empty. For example, rubber fresh from the production line has a temperature of approximately 40℃-60℃, with a temperature difference greater than 3℃ from room temperature; if the rubber is cold, such as when it is taken out of storage in winter, the temperature is approximately 5℃, with a temperature difference greater than 3℃ from room temperature. The mechanical grade data refers to the mechanical requirements data corresponding to each pre-set quality grade for that application. The mechanical requirements data includes multiple mechanical indicators and the lower limit or range of each mechanical indicator.

[0064] In this embodiment, each standard reclaimed rubber sample is treated as a test sample, and a complete transient and steady-state testing process is performed. For transient testing, transient testing data for each standard sample is collected, and the transient thermal conductivity curve, transient carbon black adaptive value, and transient molecular chain adaptive value are determined. For steady-state testing, steady-state testing data for each standard sample is collected, and the carbon black current contribution value and molecular chain current contribution value of the correction current decay curve are determined.

[0065] In this embodiment, destructive testing is systematically performed on each standard reclaimed rubber sample in the standard rubber compound data for each application label. Destructive testing refers to a test method in which a load exceeding the elastic limit is applied to the sample using equipment such as a tensile testing machine, hardness tester, and vulcanizer until the sample breaks or is damaged. Through this test, the specific performance values ​​of the sample in various mechanical properties can be obtained, including but not limited to tensile strength, elongation at break, hardness, and tear strength. These mechanical property values ​​are the direct quantitative basis for subsequent classification of the sample into specific grades, and the value of each mechanical property reflects the physical performance of the sample in that dimension.

[0066] In this embodiment, after obtaining all mechanical performance values ​​for each standard sample, these performance values ​​are compared item by item based on the mechanical grade data for that application. The actual mechanical performance of the sample is compared with the mechanical requirements data corresponding to each grade label. Only when the performance values ​​of the sample in all mechanical indicators meet all the requirements of a certain grade are the sample assigned that grade label. If the sample meets grade A in some indicators but only grade B in others, the lowest grade met is taken as the final grade label for the sample according to the principle of the weakest link.

[0067] The beneficial effects of the above technical solution are as follows: It obtains a set of application labels for reclaimed rubber samples, standard rubber compound data and mechanical grade data for each application label within the application label set, and collects transient and steady-state test data for each standard reclaimed rubber sample from the standard rubber compound data for each application label. This provides data support for determining the application evaluation data, carbon black fitting function, and molecular chain fitting function for each application label.

[0068] Example 6: This invention provides a method for quality assessment of reclaimed rubber based on conductivity detection. Step 3 includes: Based on the carbon black current contribution values ​​of all standard reclaimed rubber samples in the standard rubber compound data for each application label and the grade label, determine the carbon black current contribution range for each grade label for each application label. Based on the molecular chain point flow contribution values ​​of all standard reclaimed rubber samples in the standard rubber compound data for each application label and the grade label, determine the molecular chain flow contribution range for each grade label for each application label; Based on the carbon black current contribution range and molecular chain current contribution range of all grade labels for each application, the application evaluation data for each application label is determined. For each standard reclaimed rubber sample in the standard rubber compound data for each application label, a double exponential function was fitted to determine the first transient index and the second transient index based on the transient thermal conductivity curve, as well as the first steady-state index and the second steady-state index based on the corrected current decay curve for each standard reclaimed rubber sample. The ratio of the first transient index to the first steady-state index of each standard reclaimed rubber sample in the standard rubber compound data for each application label is calculated as the fast component time constant of the standard reclaimed rubber sample. At the same time, the ratio of the second transient index to the second steady-state index of each standard reclaimed rubber sample in the standard rubber compound data for each application label is calculated as the slow component time constant of the standard reclaimed rubber sample. Based on the fast component time constant and slow component time constant of all standard reclaimed rubber samples in the standard rubber compound data for each application label, the fast component time range and slow component time range for each application label are determined. If the fast component time constant of the standard reclaimed rubber sample belongs to the fast component time range of the corresponding application label, and the slow component time constant belongs to the slow component time range of the corresponding application label, the trend label of the standard reclaimed rubber sample is determined to be consistent; otherwise, the trend label of the standard reclaimed rubber sample is determined to be inconsistent. A reliable detection model was constructed based on transient thermal conductivity spectra and trend labels of all standard recycled rubber samples for each application label. Based on the transient carbon black adaptive value and carbon black current contribution value of standard reclaimed rubber samples with consistent trend labels for each application label, the carbon black fitting function for each application label is determined. At the same time, based on the transient molecular chain adaptive value and molecular chain current contribution value of standard reclaimed rubber samples with consistent trend labels for each application label, the molecular chain fitting function for each application label is determined.

[0069] In this embodiment, for each grade label under each application label, the carbon black current contribution values ​​of all standard reclaimed rubber samples within that grade are collected. The carbon black current contribution values ​​are the initial amplitudes of the carbon black components extracted from the corrected current decay curves through steady-state KWW fitting. Before determining the interval, outlier screening is first performed on all carbon black contribution values ​​within that grade. Specifically, a robust statistical method based on the absolute deviation of the median is used to calculate the median of the data set and the median of the absolute deviation of each data point from the median. Data points that deviate from the median by more than a set multiple are marked as outliers and removed. Only the minimum value of the remaining valid data is taken as the lower limit of the interval, and the maximum value is taken as the upper limit of the interval.

[0070] In this embodiment, the molecular chain current contribution value is processed using the same method as in the first section. Molecular chain current contribution values ​​of all standard samples within this level are collected. Similarly, outlier screening based on the absolute deviation of the median is performed on this set of values, and then the minimum and maximum values ​​of the valid data are taken to determine the molecular chain current contribution range for this level.

[0071] In this embodiment, the two intervals mentioned above are combined to form application evaluation data for each application label. This data defines a continuous tolerance interval for each grade label in both the carbon black contribution dimension and the molecular chain contribution dimension. The two intervals together form a two-dimensional electrical fingerprint rectangular region, with the horizontal axis representing the allowable range of carbon black contribution value and the vertical axis representing the allowable range of molecular chain contribution value. Each grade occupies a specific rectangular position in this two-dimensional space, and this region serves as a direct reference benchmark for subsequent determination of unknown sample grades.

[0072] In this embodiment, the transient thermal conductivity curve and the correction current decay curve of each standard sample are fitted with a double exponential function. This function is a superposition of two exponential terms, each containing an initial amplitude and a time constant parameter. The first term corresponds to the component with a faster response, and the second term corresponds to the component with a slower response. The superposition of the two terms approximates the decay pattern of the actual curve. The physical reason for choosing the double exponential model is that the response speeds of the carbon black network and molecular chains in reclaimed rubber differ by orders of magnitude. The response of the carbon black skeleton itself is a fast process, while the response of the carbon black rubber interface and molecular chain segments is a slow process. Both processes follow exponential decay laws and have significantly different time constants. The double exponential model is a minimizing mathematical description that can separate these two physical mechanisms. Using this fitting system, the first transient exponent (i.e., the time constant of the fast component) and the second transient exponent (i.e., the time constant of the slow component) are extracted from the transient thermal conductivity curve, and the first steady-state exponent and the second steady-state exponent are extracted from the correction current decay curve.

[0073] In this embodiment, the first transient index and the first steady-state index correspond to the response speed of the carbon black skeleton under thermal and electrical excitation, respectively. Dividing the two can eliminate the absolute numerical difference caused by the inherent speed of the formulation itself and highlight whether the relative relationship between thermal and electrical response speeds is kept synchronous. The ratio of the second transient index and the second steady-state index reflects whether the relative relationship between the response speed of the molecular chain and the interface layer is synchronized under thermal and electrical excitation.

[0074] In this embodiment, the fast component time constant and slow component time constant of all standard samples for each application are collected. For each set of values, outliers are removed using the same outlier screening method based on the absolute deviation of the median. The median of the remaining valid data, plus or minus a predetermined multiple, is taken as the normal time range boundary for that application. For samples with normal process fluctuations under the same formulation, the ratio of their thermal to electrical response rates should be concentrated within a stable range. This range represents the inherent distribution of the formulation under normal thermoelectric coupling conditions. Samples exceeding this range indicate that their thermoelectric coupling mechanism has deviated from the normal state.

[0075] In this embodiment, the fast component time constant of each standard reclaimed rubber sample is compared with the fast component time range for that application, and the slow component time constant is compared with the slow component time range. If both time constants fall within their respective ranges, the trend label for that sample is marked as consistent; otherwise, it is marked as inconsistent. Only when both ratios are stable simultaneously can it be proven that the sample's thermal conduction mechanism and charge transport mechanism share the same physical channel, i.e., the carbon black skeleton is continuous and uniform. If either ratio exceeds the range, it indicates that the sample structure has deviated from the optimal regeneration window.

[0076] In this embodiment, a reliable detection model is constructed based on the transient thermal conductivity spectra of all standard reclaimed rubber samples for each application label and trend labels. This model uses trend labels as supervision signals and divides the transient thermal conductivity curves of all standard samples into three category sets according to their trend labels: the consistent trend category corresponds to samples with the optimal regeneration window, the fast component time constant out of range category corresponds to samples with over-regeneration tendency, and the slow component time constant out of range category corresponds to samples with under-regeneration tendency. The morphological center and allowable variation boundary of each category are extracted from the transient thermal conductivity curves of each category set to form a three-part morphological classifier. In actual testing, the transient thermal conductivity curve of the reclaimed rubber sample to be evaluated is input into the three category spaces in the reliable detection model to calculate the morphological similarity, determine the category label and membership confidence. When the detection is in the consistent trend category and the confidence is higher than a preset threshold, the transient detection result is determined to be reliable. When the model output is in the fast component out of range or slow component out of range category, the transient detection result is determined to be unreliable. The reliable detection model uses supervised learning by incorporating trend labels from all standard samples, which fundamentally eliminates survivor bias caused by learning only consistent samples, enabling the model to identify and correctly reject over-reproduced and under-reproduced samples.

[0077] In this embodiment, when the sample's thermoelectric coupling is normal, there is a fixed linear ratio between the transient thermal sensitivity and steady-state conductivity of the carbon black network. The carbon black fitting function establishes a linear mapping relationship between the transient carbon black adaptive value and the carbon black current contribution value in all samples with consistent trend labels. Its form is that the carbon black current contribution value equals a proportionality coefficient multiplied by the transient carbon black adaptive value plus a constant term. The proportionality coefficient and constant term are obtained through linear regression. This function is established only on samples with consistent trends. The molecular chain fitting function uses the exact same linear mapping form, establishing a linear relationship between the transient molecular chain adaptive value and the molecular chain current contribution value in all samples with consistent trends. The molecular chain current contribution value equals a proportionality coefficient multiplied by the transient molecular chain adaptive value plus a constant term. This proportionality coefficient is used to convert the transiently measured molecular chain thermal activation characteristics into an equivalent steady-state molecular chain contribution value in rapid screening mode. Both fitting functions are calibrated only on samples within the optimal regeneration window with normal thermoelectric coupling.

[0078] In this embodiment, the transient thermal conductivity curve characterizes the sensitivity of current to temperature, and is the ratio of the rate of change of current to the rate of change of temperature, reflecting the severity of the internal structural response of the material after heating. The correction current decay curve characterizes the dissipation of the correction current value over time, representing the macroscopic rate at which charge carriers, including carbon black electrons and molecular chain ions, gradually approach equilibrium after a DC voltage is applied.

[0079] In this embodiment, when the standard reclaimed rubber sample is in an under-regenerated state, the carbon black particles are tightly wrapped by the undesulfurized rubber matrix. Heat conduction within the rubber is extremely slow and exhibits a gradual diffusion characteristic. Meanwhile, the charge, blocked by the insulating layer, almost instantaneously drops to zero. The transient thermal conductivity curve shows a flat, peakless shape, while the steady-state current curve shows a steep drop, indicating a disconnect between the two. When the sample is in an over-regenerated state, the carbon black particles re-flocculate into clusters. Localized thermal stress concentration causes a sharp peak in the transient thermal conductivity curve in the early stages, while multiple scattering of charge between the flocs causes the steady-state current curve to exhibit a slow, long-tailed decay, again indicating a disconnect between the two. In both cases, the physical pathways upon which the thermal response and electro-relaxation depend are inconsistent, making the transient rapid screening results unreliable. A steady-state precise judgment is necessary.

[0080] In this embodiment, when the standard reclaimed rubber sample is near the optimal regeneration window at the bottom of the U-shaped curve, the carbon black particles are neither over-encapsulated by the rubber nor severely flocculated. Instead, they form a continuous, dense, and uniform single natural skeleton network. This skeleton serves as both the main channel for heat conduction (phonon transmission along the carbon black particles) and the main channel for charge transport (electron tunneling between carbon black particles). At this point, heat and electricity face the same microstructural constraints, namely the relaxation time of the gaps between carbon black particles. The decay rate of heat in the skeleton is necessarily highly synchronized with the decay rate of charge in the skeleton: the rate of gap change caused by thermal expansion and contraction of the carbon black skeleton during heating, and the rate of charge decay across the same gap after applying an electric field, follow the same physical time constant. Therefore, the shape change of the transient thermal conductivity curve and the shape change of the steady-state current curve show a highly consistent trend, and the transient rapid screening results are reliable.

[0081] The beneficial effects of the above technical solution are as follows: Based on the statistical electrical contribution range of grade labels, discrete mechanical grades are transformed into continuous electrical tolerance boundaries, providing a clear quantitative scale for quality judgment. By extracting the time constants of the fast and slow components in transient and steady states through bi-exponential fitting and calculating their ratio, a time-range criterion describing the synchronicity of thermoelectric coupling between the carbon black framework and molecular chain interface is constructed. This criterion can adaptively screen standard samples where the heat conduction mechanism and charge transport mechanism are in the same physical channel. Incorporating consistent standard samples into the construction of reliable detection models and fitting functions fundamentally eliminates the contamination of the standard library by atypical structures such as under-regeneration or over-regeneration, ensuring the physical validity of conversion coefficients in the rapid screening mode and improving the anti-interference ability and model generalization of the evaluation method.

[0082] Example 7: This invention provides a method for quality assessment of reclaimed rubber based on conductivity detection. Step 4 includes: Obtain the application label of the recycled rubber sample to be evaluated to confirm that the recycled rubber sample to be evaluated is a test recycled rubber sample; Collect transient detection data of the recycled rubber sample to be evaluated. If the transient detection data is not empty, determine the transient thermal conductivity curve, transient carbon black adaptive value, and transient molecular chain adaptive value of the recycled rubber sample to be evaluated based on the transient detection data. The transient thermal conductivity curve of the reclaimed rubber sample to be evaluated is input into the reliable detection model. If the output result of the reliable detection model is reliable, the carbon black current contribution value of the reclaimed rubber sample to be evaluated is determined based on the transient carbon black adaptive value and carbon black fitting function of the reclaimed rubber sample to be evaluated. At the same time, the molecular chain current contribution value of the reclaimed rubber sample to be evaluated is determined based on the transient molecular chain adaptive value and molecular chain fitting function of the reclaimed rubber sample to be evaluated. If the output of the reliable detection model is unreliable, collect steady-state detection data of the recycled rubber sample to be evaluated, and determine the carbon black current contribution value and molecular chain current contribution value of the recycled rubber sample to be evaluated. Based on the application label, carbon black current contribution value, molecular chain current contribution value, and application evaluation data of the application label of the reclaimed rubber sample to be evaluated, the grade label of the reclaimed rubber sample to be evaluated is determined.

[0083] In this embodiment, the application label of the reclaimed rubber sample to be evaluated is obtained. This application label is selected by the operator from an existing set of applications based on the target application scenario of the batch of rubber. The application label determines which set of application evaluation data, carbon black fitting function, molecular chain fitting function, and reliable detection model will be retrieved subsequently. The sample to be evaluated is treated as a reclaimed rubber sample for testing, and transient detection data acquisition is performed. If the transient detection data of the sample is not empty, it indicates that the temperature difference between the room temperature and the sample contact temperature has reached a preset threshold in the temperature difference determination step, and the transient detection is deemed feasible, and the acquired transient detection data has physical validity.

[0084] In this embodiment, the transient thermal conductivity curve, transient carbon black adaptive value, and transient molecular chain adaptive value of the sample are determined based on the collected transient detection data. The transient thermal conductivity curve is then input into the reliable detection model. The reliable detection model calculates the deviation between the test curve and the standard curve determined by the model point by point and compares this deviation with the allowable fluctuation band stored in the model. If the deviation of the test curve at each time point falls within the allowable fluctuation band or the statistical value of the overall deviation is lower than a preset threshold, the transient thermal conductivity morphology of the sample is determined to be highly consistent with the standard state, and the model output result is reliable. If the test curve significantly deviates from the standard morphology curve and exceeds the allowable fluctuation band within a certain key time interval (e.g., an abnormal peak appears early or the later phase is excessively flat), the carbon black network or interface structure of the sample is determined to have undergone morphological changes, and the model output result is unreliable.

[0085] In this embodiment, the transient thermal conductivity curve of the reclaimed rubber sample to be evaluated is input into three category spaces in the reliable detection model to calculate morphological similarity, determine the category label and membership confidence level. When the detection is in the trend-consistent category and the confidence level is higher than a preset threshold, the transient detection result is determined to be reliable. When the model output is in the fast component out-of-range category or the slow component out-of-range category, the transient detection result is determined to be unreliable. When the model output result is reliable, the carbon black current contribution value of the sample to be evaluated is calculated based on the transient carbon black adaptive value and the carbon black fitting function. At the same time, the molecular chain current contribution value is calculated based on the transient molecular chain adaptive value and the molecular chain fitting function. This calculation process substitutes the transient carbon black adaptive value obtained from the transient detection into the carbon black fitting function calibrated by the trend-consistent sample, thereby obtaining an equivalent steady-state contribution value without performing time-consuming steady-state detection, achieving rapid quality assessment within approximately five seconds.

[0086] In this embodiment, if the output of the reliable detection model is unreliable, it indicates that the shape of the transient thermal conductivity curve of the current sample deviates significantly from the standard template. This means that the internal structure of the sample may be in a state of under-regeneration or over-regeneration, deviating from the optimal regeneration window. At this time, the fixed proportional relationship between the transient adaptive value and the steady-state contribution value has failed. The transient conversion result is abandoned, and the steady-state detection data of the sample is collected instead to determine the carbon black current contribution value and molecular chain current contribution value of the sample. This precise judgment mode takes about sixty seconds but can provide accurate and reliable quantitative results even under structural abnormalities.

[0087] In this embodiment, the corresponding application evaluation data is retrieved based on the application label of the sample to be evaluated. This data includes the carbon black current contribution range and the molecular chain current contribution range for each grade label under that application. The carbon black current contribution value and the molecular chain current contribution value of the sample are compared with the standard ranges of each grade. Only when both contribution values ​​fall within the corresponding range of a certain grade is the sample determined to belong to that grade. Finally, the grade label is output as the final conclusion of the quality evaluation of this batch of recycled rubber.

[0088] The beneficial effects of the above technical solution are as follows: By using a reliable detection model to perform pre-test reliability verification of transient detection results, intelligent adaptive switching between rapid screening and precise judgment evaluation modes is achieved. The rapid conversion channel is only activated when the transient results pass reliability verification. Once the transient thermal conductivity curve deviates from the standard template, it automatically switches to the steady-state precise judgment mode, ensuring both the detection efficiency of normal samples and avoiding the risk of misjudgment of abnormal samples. This dynamic decision-making mechanism ensures that each grade determination is based on the physical self-consistency of the data itself, improving the reliability and automation level of the evaluation results.

[0089] Example 8: This invention provides a quality assessment system for reclaimed rubber based on conductivity detection, such as... Figure 2 As shown, it includes: Detection module: Based on the thermoelectric composite probe, transient and steady-state detection data of reclaimed rubber samples are collected to determine the transient and steady-state detection processes; Acquisition Module: Acquires the set of application labels for reclaimed rubber samples, standard rubber compound data and mechanical grade data for each application label in the application label set, and collects transient and steady-state test data for each standard reclaimed rubber sample in the standard rubber compound data for each application label; Determine the module: Based on the mechanical grade data of each application label, the transient test data and steady-state test data of each standard reclaimed rubber sample in the standard rubber compound data, determine the application evaluation data, carbon black fitting function and molecular chain fitting function for each application label. Evaluation module: Based on the application label of the reclaimed rubber sample to be evaluated, the application evaluation data of the application label, the carbon black fitting function, and the molecular chain fitting function, the module performs testing and quality evaluation on the reclaimed rubber sample to be evaluated, and determines the grade label of the reclaimed rubber sample to be evaluated.

[0090] The beneficial effects of the above technical solution are as follows: By integrating the transient thermal conductivity response and steady-state current relaxation response of the thermoelectric composite probe, a dual-modal electrical fingerprint system for reclaimed rubber quality assessment is established. Utilizing the inherent difference in response speed between carbon black network and molecular chain polarization under thermal and electrical excitation, parallel characterization of carbon black skeleton integrity and molecular chain mobility is achieved, eliminating the mutual misjudgment of under-regeneration and over-regeneration caused by the ambiguity of the U-shaped curve in the single-point resistance method. Adaptive switching between rapid screening and precise judgment modes is realized, significantly improving detection efficiency while ensuring assessment accuracy, and upgrading conductivity detection into a standardized quality assessment method with clear physical mechanism support.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for quality assessment of reclaimed rubber based on conductivity detection, characterized in that, include: Step 1: Based on the thermoelectric composite probe, collect transient and steady-state detection data of the reclaimed rubber sample to determine the transient and steady-state detection procedures; Step 2: Obtain the set of application labels for the recycled rubber samples, the standard rubber compound data and mechanical grade data for each application label in the application label set, and collect the transient and steady-state test data for each standard recycled rubber sample in the standard rubber compound data for each application label. Step 3: Based on the mechanical grade data of each application label, the transient test data and steady-state test data of each standard reclaimed rubber sample in the standard rubber compound data, determine the application evaluation data, carbon black fitting function and molecular chain fitting function for each application label. Step 4: Obtain and, based on the application label of the reclaimed rubber sample to be evaluated, the application evaluation data of the application label, the carbon black fitting function, and the molecular chain fitting function, conduct testing and quality assessment on the reclaimed rubber sample to be evaluated, and determine the grade label of the reclaimed rubber sample to be evaluated.

2. The method for quality assessment of reclaimed rubber based on conductivity detection according to claim 1, characterized in that, Step 1 includes: The thermoelectric composite probe is vertically pressed onto the surface of the recycled rubber sample with a preset constant pressure value. The thermoelectric composite probe includes at least a coaxially integrated four-probe electrode, a micro Peltier element, and a temperature detection element. Based on the temperature detection element in the thermoelectric composite probe, the contact temperature value between the thermoelectric composite probe and the rubber sample is collected at the contact time point. Obtain the indoor temperature value and determine whether the temperature difference between the indoor temperature value and the contact temperature value of the rubber sample is greater than the preset temperature difference value; If the temperature difference is greater than or equal to a preset temperature difference value, a high-frequency AC signal is applied to the reclaimed rubber sample within a first set time interval after the contact time point, and transient detection data is collected based on a set transient sampling frequency. After the first set time interval ends, a DC step voltage is applied to the reclaimed rubber sample, and a low-speed, high-precision ADC is started to collect steady-state detection data based on a set steady-state sampling frequency. The transient detection data includes transient current values ​​and transient temperature values ​​at multiple transient sampling time points, and the steady-state detection data includes steady-state current values ​​and steady-state temperature values ​​at multiple steady-state sampling time points. If the temperature difference is less than the preset temperature difference value, the transient detection data is determined to be empty. After the contact time point, a DC step voltage is applied to the detected reclaimed rubber sample, and a low-speed, high-precision ADC is started to collect steady-state detection data based on the set steady-state sampling frequency.

3. The method for quality assessment of reclaimed rubber based on conductivity detection according to claim 2, characterized in that, Step 1 also includes: Based on the transient current and transient temperature values ​​at every two adjacent transient sampling time points in the transient detection data, calculate the transient temperature coefficient of the next adjacent transient sampling time point in every two adjacent transient sampling time points; If the transient temperature coefficient is less than the preset temperature change threshold, it is determined that the thermal driving force of the transient sampling time point corresponding to the transient temperature coefficient is insufficient, and the label of the transient sampling time point corresponding to the transient temperature coefficient is determined to be invalid; otherwise, the label of the transient sampling time point corresponding to the transient temperature coefficient is determined to be retained. Based on the transient temperature coefficients and labels of all transient sampling time points in the transient detection data, a transient thermal conductivity point map is plotted. The horizontal axis of the transient thermal conductivity point map represents the transient sampling time points within the first set time interval, and the vertical axis represents the transient temperature coefficient. Transient sampling time points with invalid labels are grayed out in the transient thermal conductivity point map, while transient sampling time points with retained labels are greened out. Connect all the green points in the transient thermal conductivity point diagram in chronological order of the transient sampling time points to form a curve and determine the transient thermal conductivity curve; The sliding window length and sliding step size are determined based on the first set time interval and the transient sampling frequency, and multiple transient time windows of the transient thermal conductivity point map are determined. Based on the transient thermal conductivity point plot and transient thermal conductivity curve, the average transient temperature coefficient and the maximum coefficient of each transient time window are determined. Based on the average transient temperature coefficient of adjacent transient time windows, determine the mean change rate of the next adjacent transient time window between two adjacent transient time windows; Based on the maximum coefficient of adjacent transient time windows, determine the maximum coefficient change rate of the next adjacent transient time window between two adjacent transient time windows; Starting from the first transient time window, a first judgment condition and a second judgment condition are sequentially applied to each transient time window. The first transient time window that simultaneously satisfies both the first and second judgment conditions is marked as the molecular chain activation start window. The center of all transient sampling time points within the transient time window preceding the molecular chain activation start window is marked as the carbon black stabilization end time. The average transient temperature coefficient of the transient time window preceding the molecular chain activation start window is used as the transient carbon black adaptive value. The first judgment condition is that the absolute value of the mean change rate of the transient time window is less than the absolute value of the maximum coefficient change rate. The second judgment condition is that the maximum coefficient of the transient time window is less than or equal to the maximum coefficient of the next transient time window, and the average transient temperature coefficient of the transient time window is less than or equal to the average transient temperature coefficient of the next transient time window. Identify the peak transient temperature coefficient and the peak transient sampling time point from the transient thermal conductivity curve; Based on the carbon black stabilization end time, peak transient temperature coefficient, and peak transient sampling time point, the transient molecular chain adaptive value is determined.

4. The method for quality assessment of reclaimed rubber based on conductivity detection according to claim 2, characterized in that, Step 1 also includes: If the temperature difference between the steady-state temperature values ​​of two adjacent steady-state sampling time points in the first consecutive specified number of steady-state detection data is less than 0.1℃, the latest steady-state sampling time among the first consecutive specified number of adjacent steady-state sampling time points is determined as the sufficient thermal equilibrium time point, and the steady-state temperature value corresponding to the latest sufficient thermal equilibrium time point is determined as the reference temperature value. Based on the steady-state sampling frequency and the steady-state current value at every two adjacent steady-state sampling time points in the steady-state detection data, the steady-state current change rate at the next steady-state sampling time point in every two adjacent steady-state sampling time points is determined. If the steady-state current change rate is lower than the preset steady-state change threshold for a second consecutive specified number of steady-state sampling time points, the latest steady-state sampling time for the second consecutive specified number of steady-state sampling time points is determined as the rollback trigger time point, and the continuous acquisition of steady-state detection data is stopped. Extract all steady-state current values ​​from the first steady-state sampling time point to the corresponding steady-state trigger time point in the steady-state detection data to determine the steady-state analysis data; Based on steady-state analysis data and reference temperature values, determine the correction current value based on the reference temperature value at each steady-state sampling time point in the steady-state analysis data; Based on the corrected current values ​​at all steady-state sampling time points in the steady-state analysis data, a corrected current decay curve is plotted, where the horizontal axis of the corrected current decay curve represents all steady-state sampling time points in the steady-state analysis data, and the vertical axis represents the corrected current value. KWW fitting was performed on the correction current decay curve to determine the steady-state carbon black contribution value and the steady-state molecular chain contribution value.

5. The method for quality assessment of reclaimed rubber based on conductivity detection according to claim 1, characterized in that, Step 2 includes: Obtain the set of application labels for the recycled rubber samples, and obtain the standard rubber compound data and mechanical grade data for each application label in the application label set. The standard rubber compound data includes multiple standard recycled rubber samples whose temperature difference with the indoor temperature is greater than a preset temperature difference value, and the mechanical grade data includes the mechanical requirement data for each grade label. Each standard reclaimed rubber sample in the standard rubber compound data for each application label is designated as a test reclaimed rubber sample. Transient test data of each standard reclaimed rubber sample in the standard rubber compound data for each application label are collected to determine the transient thermal conductivity curve, transient carbon black adaptive value, and transient molecular chain adaptive value of each standard reclaimed rubber sample. At the same time, steady-state test data of each standard reclaimed rubber sample in the standard rubber compound data for each application label are collected to determine the correction current decay curve, carbon black current contribution value, and molecular chain current contribution value of each standard reclaimed rubber sample. Destructive testing was performed on each standard reclaimed rubber sample in the standard rubber compound data for each application label to determine the performance value of each mechanical property for each standard reclaimed rubber sample; The grade label of the standard reclaimed rubber sample is determined based on the mechanical grade data for each application label and the performance values ​​of all mechanical properties of each standard reclaimed rubber sample in the standard rubber compound data.

6. The method for quality assessment of reclaimed rubber based on conductivity detection according to claim 5, characterized in that, Step 3 includes: Based on the carbon black current contribution values ​​of all standard reclaimed rubber samples in the standard rubber compound data for each application label and the grade label, determine the carbon black current contribution range for each grade label for each application label. Based on the molecular chain point flow contribution values ​​of all standard reclaimed rubber samples in the standard rubber compound data for each application label and the grade label, determine the molecular chain flow contribution range for each grade label for each application label; Based on the carbon black current contribution range and molecular chain current contribution range of all grade labels for each application, the application evaluation data for each application label is determined. For each standard reclaimed rubber sample in the standard rubber compound data for each application label, a double exponential function was fitted to determine the first transient index and the second transient index based on the transient thermal conductivity curve, as well as the first steady-state index and the second steady-state index based on the corrected current decay curve for each standard reclaimed rubber sample. The ratio of the first transient index to the first steady-state index of each standard reclaimed rubber sample in the standard rubber compound data for each application label is calculated as the fast component time constant of the standard reclaimed rubber sample. At the same time, the ratio of the second transient index to the second steady-state index of each standard reclaimed rubber sample in the standard rubber compound data for each application label is calculated as the slow component time constant of the standard reclaimed rubber sample. Based on the fast component time constant and slow component time constant of all standard reclaimed rubber samples in the standard rubber compound data for each application label, the fast component time range and slow component time range for each application label are determined. If the fast component time constant of the standard reclaimed rubber sample belongs to the fast component time range of the corresponding application label, and the slow component time constant belongs to the slow component time range of the corresponding application label, the trend label of the standard reclaimed rubber sample is determined to be consistent; otherwise, the trend label of the standard reclaimed rubber sample is determined to be inconsistent. A reliable detection model was constructed based on transient thermal conductivity spectra and trend labels of all standard recycled rubber samples for each application label. Based on the transient carbon black adaptive value and carbon black current contribution value of standard reclaimed rubber samples with consistent trend labels for each application label, the carbon black fitting function for each application label is determined. At the same time, based on the transient molecular chain adaptive value and molecular chain current contribution value of standard reclaimed rubber samples with consistent trend labels for each application label, the molecular chain fitting function for each application label is determined.

7. The method for quality assessment of reclaimed rubber based on conductivity detection according to claim 1, characterized in that, Step 4 includes: Obtain the application label of the recycled rubber sample to be evaluated to confirm that the recycled rubber sample to be evaluated is a test recycled rubber sample; Collect transient detection data of the recycled rubber sample to be evaluated. If the transient detection data is not empty, determine the transient thermal conductivity curve, transient carbon black adaptive value, and transient molecular chain adaptive value of the recycled rubber sample to be evaluated based on the transient detection data. The transient thermal conductivity curve of the reclaimed rubber sample to be evaluated is input into the reliable detection model. If the output result of the reliable detection model is reliable, the carbon black current contribution value of the reclaimed rubber sample to be evaluated is determined based on the transient carbon black adaptive value and carbon black fitting function of the reclaimed rubber sample to be evaluated. At the same time, the molecular chain current contribution value of the reclaimed rubber sample to be evaluated is determined based on the transient molecular chain adaptive value and molecular chain fitting function of the reclaimed rubber sample to be evaluated. If the output of the reliable detection model is unreliable, collect steady-state detection data of the recycled rubber sample to be evaluated, and determine the carbon black current contribution value and molecular chain current contribution value of the recycled rubber sample to be evaluated. Based on the application label, carbon black current contribution value, molecular chain current contribution value, and application evaluation data of the application label of the reclaimed rubber sample to be evaluated, the grade label of the reclaimed rubber sample to be evaluated is determined.

8. A quality assessment system for reclaimed rubber based on conductivity detection, characterized in that, A method for evaluating the quality of reclaimed rubber based on conductivity detection as described in any one of claims 1 to 7 includes: Detection module: Based on the thermoelectric composite probe, transient and steady-state detection data of reclaimed rubber samples are collected to determine the transient and steady-state detection processes; Acquisition Module: Acquires the set of application labels for reclaimed rubber samples, standard rubber compound data and mechanical grade data for each application label in the application label set, and collects transient and steady-state test data for each standard reclaimed rubber sample in the standard rubber compound data for each application label; Determine the module: Based on the mechanical grade data of each application label, the transient test data and steady-state test data of each standard reclaimed rubber sample in the standard rubber compound data, determine the application evaluation data, carbon black fitting function and molecular chain fitting function for each application label. Evaluation module: Based on the application label of the reclaimed rubber sample to be evaluated, the application evaluation data of the application label, the carbon black fitting function, and the molecular chain fitting function, the module performs testing and quality evaluation on the reclaimed rubber sample to be evaluated, and determines the grade label of the reclaimed rubber sample to be evaluated.

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