A performance detection system for an automobile exhaust purifier

Abstract

This invention relates to the field of exhaust gas testing technology and discloses a performance testing system for automotive exhaust gas purifiers. The system includes a gas source unit for providing test gas to the purifier under test; a heating unit for controllably heating the purifier under test during the testing process; a first pressure sensor located at the air inlet of the purifier under test; a second pressure sensor located at the air outlet of the purifier under test; and a flow sensor connected in series in the air inlet or outlet channel of the purifier under test. This invention constructs a stepped testing process combining cold and hot states. Basic sealing screening is first completed at room temperature, and hot state testing is only performed after the cold state test is passed. This avoids the ineffective use of defective products in the hot state testing stage and ensures reasonable control of testing efficiency and energy consumption, achieving systematic verification of the purifier's sealing performance across the entire temperature range.

Description

Technical Field

[0001] This invention relates to the field of exhaust gas testing technology, and in particular to a performance testing system for automotive exhaust gas purifiers. Background Technology

[0002] The automotive exhaust purifier is a core component of the vehicle emission control system, and its performance directly affects the vehicle's emission levels. Before leaving the factory, the purifier must undergo rigorous performance testing, with sealing testing being particularly critical. The quality of the threads and sealing surface of the oxygen sensor mounting bracket on the purifier's housing directly impacts the overall sealing performance.

[0003] In existing technologies, the detection method typically involves filling the purifier with gas at a certain pressure at room temperature (cold state) and judging the sealing performance by detecting pressure drop or leakage. However, some products with defects such as extremely fine thread burrs or uneven sealing surfaces may temporarily "fill in" the burrs or unevenness under cold conditions due to the contraction effect of the metal material, thus passing the cold-state airtightness test. But in the high-temperature operating environment after actual vehicle installation, the purifier housing and sensor base expand unevenly due to heat, amplifying these tiny original defects, leading to gas leakage, and consequently causing serious problems such as excessive emissions and inaccurate oxygen sensor signals. Existing detection methods cannot effectively identify such hidden defects that are "qualified in the cold state but fail in the hot state." Summary of the Invention

[0004] This invention provides a performance testing system for automotive exhaust purifiers to solve existing technical problems, addressing the issue that existing technologies cannot effectively detect thermal micro-leakage caused by minor manufacturing defects.

[0005] To solve the above-mentioned technical problems, according to one aspect of the present invention, more specifically, a performance testing system for automotive exhaust purifiers, comprising: The gas supply unit is used to provide the test gas to the purifier under test. A heating unit is used to controllably heat the air purifier under test during the testing process; The first pressure sensor is located at the air inlet of the air purifier under test; The second pressure sensor is located at the air outlet of the air purifier under test; A flow sensor is connected in series in the air intake or air outlet channel of the air purifier under test. The control and data analysis unit is electrically connected to the gas source unit, heating unit, first pressure sensor, second pressure sensor and flow sensor, respectively. The control and data analysis unit is configured to execute a cold detection mode and a hot detection mode, and calculate a hot leakage characteristic value based on the real-time flow data and pressure data collected in the hot detection mode to determine the hot sealing performance of the purifier under test.

[0006] Furthermore, the cold-state detection mode includes: controlling the gas source unit to charge the purifier under test with detection gas at a preset pressure, and determining whether its cold-state sealing performance is qualified based on the signals from the first pressure sensor, the second pressure sensor, and the flow sensor.

[0007] Furthermore, the hot-state detection mode is activated only after the cold-state sealing performance has been determined to be satisfactory.

[0008] Furthermore, the thermal detection mode includes: controlling the heating unit to heat the air purifier under test, causing its temperature to rise from the initial temperature. Rise to target temperature The flow rate value of the flow sensor is continuously recorded during the heating process. and the real-time pressure value of the second pressure sensor .

[0009] Furthermore, the control and data analysis unit calculates the characteristic values ​​of thermal leakage. The formula is: ; in, Indicates the initial time. The baseline flow rate; Indicates the initial time. Export pressure; This represents the pressure change compensation coefficient; Indicates real-time temperature Related thermal expansion compensation factors.

[0010] Furthermore, the pressure change compensation coefficient is obtained by pre-calibration on a standard leak-free purifier; the control and data analysis unit is also configured to determine that the hot-state sealing of the purifier under test is unqualified when the hot-state leakage characteristic value exceeds a preset leakage threshold.

[0011] Furthermore, the control and data analysis unit introduces a temperature weighting function into the formula for calculating the hot leakage characteristic value to form an enhanced hot leakage characteristic value: ; In the above formula, This represents the characteristic value of enhanced hot leakage; Represents the temperature weighting function; When the enhanced hot leakage characteristic value exceeds the preset leakage threshold, the hot sealing performance of the purifier under test is determined to be unqualified.

[0012] Furthermore, the control and data analysis unit identifies occasional or uncommon abnormal operating conditions and outputs a judgment result by executing at least one of the following judgment modes: A1. Calculate the rate of change of pressure difference between the first pressure sensor and the second pressure sensor under a leak-free closed state. If the rate of change exceeds the preset first threshold, it is determined that there is sensor drift or blockage abnormality. A2. Monitor the dynamic response between the actual power of the heating unit and the temperature feedback in real time. If the response time deviates from the preset calibration curve by more than the second threshold, it is determined that the heating unit has local aging or poor contact. A3. Perform a short-time Fourier transform on the flow sensor signal to extract non-stationary characteristic components in the spectrum. If there are components whose frequency drifts with time and whose amplitude exceeds the third threshold, it is determined that there is intermittent leakage caused by thermal loosening of the clamp.

[0013] Furthermore, in discrimination mode A3, an intermittent leakage characteristic index is constructed. as follows: ; In the above formula, Indicates flow rate signal The short-time Fourier transform spectrum; This indicates the preset intermittent leakage characteristic frequency band; This represents a weighting function based on the rate of temperature change. Among them, when When the threshold is exceeded, an abnormal operating condition caused by intermittent thermal leakage is determined.

[0014] A method for testing the performance of an automotive exhaust purifier, specifically including the following steps: S1. Perform a cold-state sealing test on the air purifier under test; S2. If the cold-state sealing is qualified, the heating unit is started to controllably raise the temperature of the air purifier under test. S3. During the heating process, the outlet pressure data and gas flow data of the purifier under test are collected in real time. S4. Based on the outlet pressure data and gas flow data, construct a hot leakage characteristic value model and calculate the hot leakage characteristic value; S5. Compare the calculated hot leakage characteristic value with the preset leakage threshold. If it exceeds the preset leakage threshold, the hot sealing performance of the purifier under test is determined to be unqualified.

[0015] The present invention provides a performance testing system for automotive exhaust purifiers. Compared with existing technologies, the advantages achieved by this method are as follows: 1. This invention constructs a stepped testing process that combines cold and hot states. First, basic sealing screening is completed at room temperature. Only after passing the cold state test is the hot state test performed. This avoids the ineffective use of unqualified products in the hot state test and ensures reasonable control of testing efficiency and energy consumption, thus realizing a systematic verification of the sealing performance of the purifier across the entire temperature range.

[0016] 2. By introducing a hot-state leakage feature value algorithm based on real-time pressure and temperature compensation, this invention can effectively isolate non-leakage flow changes caused by gas thermal expansion and system pressure fluctuations, thereby accurately extracting hot-state micro-leakage signals caused by minor manufacturing defects, and significantly improving the ability to identify latent defects such as "cold-state qualified, hot-state failed".

[0017] 3. By introducing a temperature weighting function into the hot leakage characteristic value, this invention can enhance the signal for leakage behavior within a specific temperature range, enabling the system to dynamically adjust the detection sensitivity according to the thermal expansion characteristics of different materials, thereby further improving the reliability of detecting minor leaks in critical temperature ranges.

[0018] 4. This invention focuses the detection on local areas such as the oxygen sensor mounting base that are susceptible to uneven thermal expansion. By combining a controllable heating unit with multi-sensor collaborative data acquisition, it achieves a true simulation of the air purifier's sealing performance under actual high-temperature operating conditions, effectively avoiding emission exceedances and sensor signal inaccuracies caused by hot leakage after vehicle installation. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the structure of the present invention; Figure 2 This is a flowchart of the present invention. Detailed Implementation

[0020] To make the technical solution of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0021] Example 1 refer to Figure 1 , Figure 2 A performance testing system for an automotive exhaust purifier includes an air source unit 1, a heating unit 2, a first pressure sensor 3, a second pressure sensor 4, a flow sensor 5, and a control and data analysis unit 6. The purifier under test 7 is fixed by a clamp, and its upstream oxygen sensor mounting base 8 and downstream oxygen sensor mounting base 9 remain in their original state without sensors installed, simulating the sealing surface of the actual mounting base.

[0022] Testing process: 1. Cold State Detection: Control unit 6 controls air source unit 1 to open, filling the purifier under test 7 with dry compressed air to the specified pressure. (e.g., 50 kPa). After the pressure stabilizes, turn off the gas supply and monitor the pressure decay rate. If the pressure drop is less than the threshold within a specified time (e.g., 60 seconds), the pressure will be reduced. If the cold-state sealing is deemed satisfactory, the system will proceed to the hot-state testing mode.

[0023] 2. Hot-state testing: After passing the cold-state test, heating unit 2 is activated, using a wrap-around heating strip to heat the housing of the purifier 7 under test, especially the oxygen sensor mounting area (8, 9). A temperature rise program is set, for example, starting at 25°C and increasing to 400°C at a rate of 5°C / min. Throughout the heating process, control unit 6 continuously records the readings of flow sensor 5 at a high sampling rate (e.g., 10Hz). The pressure value of the second pressure sensor 4 .

[0024] Control unit 6 has a built-in core algorithm for calculating thermal leakage characteristic values. This feature is designed to eliminate normal flow variations caused by gas thermal expansion, thereby accurately extracting micro-leakage signals caused by defects.

[0025] Hot leakage characteristic value The calculation formula is: ; in, Indicates time At that time, the real-time gas flow rate detected by the flow sensor; Indicates the initial time. The gas flow rate (when the gas is in a stable, cold state) is used as the reference flow rate. Indicates time At that time, the real-time outlet pressure detected by the second pressure sensor; Indicates the initial time. Export pressure; This represents the compensation coefficient for the impact of pressure changes on flow rate, which is obtained by pre-calibration on a standard leak-free purifier; Indicates real-time temperature The relevant thermal expansion compensation factor is used to correct the contribution of gas volume expansion due to temperature increase to the flow meter reading. Indicates the start time point of the hot detection mode; Indicates that the target temperature has been reached. The point in time.

[0026] Algorithm explanation: The core idea of ​​this algorithm is that, under ideal conditions with no leakage, the flow rate change measured by the flow sensor is mainly caused by two factors: first, the thermal expansion of the gas (due to...). The two factors are (1) correction and (2) internal system pressure fluctuations. For qualified products, the flow rate value after correction for these two factors should always be close to the baseline flow rate. Therefore, the calculated eigenvalues It will be very small.

[0027] When minor defects exist, the mounting base expands unevenly due to heat as the temperature rises, causing the gap at the defect to gradually increase and resulting in leakage. The additional gas flow caused by the leakage cannot be fully compensated by the two correction terms mentioned above, leading to a difference between the corrected flow rate and the actual flow rate. This results in a persistent deviation between them.

[0028] By integrating the square of the deviation over the entire heating period, this weak but persistent signal can be amplified to form a significant signal. Value. A reasonable leakage threshold is determined through experiments. ,when In this way, defective products with thermal micro-leakage can be accurately identified.

[0029] During the heating process, the raw flow signal measured by the flow sensor is decomposed into two parts: "flow changes caused by normal physical phenomena" and "abnormal flow caused by defects and leaks." The abnormal part is then amplified through integration to identify micro-leakage. Specifically: 1. Physical Model and Basic Assumptions During the heating process, the gas flow rate inside it... It will be affected by the following three main factors: (1) Leakage flow This is the target signal we want to detect. Defects (such as micro-gaps caused by uneven thermal expansion) cause gas to leak from the inside of the purifier to the outside.

[0030] (2) Flow rate changes caused by pressure fluctuations During the heating process, the internal pressure of the system It will change. According to gas dynamics, the flow rate through a fixed orifice (such as the flow meter itself or the system's inherent path) is related to the pressure difference. When the outlet pressure changes, the flow meter reading will change even without leakage.

[0031] (3) Changes in flow rate caused by thermal expansion of gas As temperature rises, the gas volume inside the purifier expands. With a fixed mass flow rate, the volumetric flow rate increases. The flow sensor (usually a volumetric flow meter) detects this increase in flow rate due to thermal expansion.

[0032] Therefore, the measured real-time traffic It can be represented as the sum of these three parts: ; in, It is the initial moment The baseline flow rate (at which point the system is in a cold, stable state with no leaks and no significant pressure / temperature fluctuations).

[0033] 2. Mathematical modeling of each component (1) Flow rate changes caused by pressure fluctuations

[0034] Assuming minimal pressure fluctuations, the flow rate through the system's inherent pathway is linearly related to the pressure difference. Here, the pressure difference primarily refers to the change in internal system pressure relative to atmospheric pressure. Since the inlet pressure is stably controlled by the gas source, the pressure difference change is mainly influenced by the outlet pressure. This is caused by fluctuations. Therefore, we can model it as follows: ; in, It is a proportionality coefficient. For simplicity, we combine this coefficient into a single parameter. and define: ; Here This is the pressure change compensation coefficient, which integrates... and And the inherent characteristics of the system. This can be obtained through calibration experiments on a standard leak-free purifier, i.e., under known leak-free and controlled heating conditions, by measuring... and Determined through regression analysis .

[0035] (2) Changes in flow rate caused by thermal expansion of gas

[0036] According to the ideal gas law Within a closed system (ignoring leakage), as the temperature rises, the gas volume... It will expand. In a volumetric flow meter, the change in reading is proportional to the rate of temperature change. Therefore, we can model it as follows: ; in, It is the thermal expansion compensation factor, which is related to real-time temperature. The relevant functions are used to accurately describe the effect of temperature changes on volumetric flow rate. This is because the coefficient of thermal expansion itself also varies with temperature (especially over a wide temperature range). It is typically a nonlinear function obtained through calibration or theoretical calculation, rather than a simple constant. Its core function, in order to simplify the formula, is to eliminate the influence of thermal expansion on the flow rate reading through temperature compensation.

[0037] 3. Reconstruction of leakage signals Substitute the above model into the measured flow rate expression, and solve for the leakage term by rearranging the terms. : ; Substituting the expressions for each component, we obtain the dimensionless leakage signal. : ; 4. Construct thermal leakage characteristic values

[0038] To accurately assess the cumulative effect of leakage throughout the heating process, we need a characteristic value that can amplify the weak but persistent signal. Directly to Integrating may be canceled out by positive and negative fluctuations, so we use the square integral method, which is similar to the energy integral in signal processing.

[0039] For qualified products, leakage items It should be 0 (or a very small noise term). For defective products, Throughout the temperature rise range arrive The internal bias will remain positive (or negative, depending on the model's construction direction). Squaring and then integrating can significantly amplify this persistent bias.

[0040] Therefore, the characteristic value of hot leakage is defined. for: ; It appears in multiplicative form after the pressure derivative term. This is actually a more compact expression, which implicitly includes... It not only compensates for pure thermal expansion, but also for the nonlinear effect of pressure changes caused by temperature variations on flow rate. A more precise derivation is: In real-world systems, the effects of pressure fluctuations and thermal expansion are not entirely independent. Pressure changes themselves are also temperature-dependent. Therefore, a more accurate model combines these two effects into a single temperature-pressure joint compensation term. The expression for the leakage signal can then be written as: ; at this time, As a composite compensation factor, its function is to superimpose a temperature-related weight onto the pressure change rate, enabling the entire compensation term to more accurately simulate flow rate changes under leak-free conditions. When the system is leak-free, When a thermal leak exists, .

[0041] The real-time flow signal measured by the flow sensor during the heating process Decomposed into baseline flow Flow rate changes caused by pressure fluctuations and flow rate changes caused by gas thermal expansion. and the leakage flow rate to be detected Four components. Among them, the pressure change compensation coefficient. and thermal expansion compensation factor All values ​​were obtained through prior calibration on a standard leak-free purifier, enabling precise isolation of "normal" flow variations caused by system pressure fluctuations and gas thermal expansion. Based on this, a hot-state leakage characteristic value was constructed by integrating the residual signal (i.e., the deviation between the actual flow rate and the normal flow rate model) over the entire heating range, thereby achieving energy accumulation and amplification of weak but persistent leakage signals.

[0042] By decomposing and calibrating the physical model, it is possible to effectively distinguish between "flow changes caused by normal physical phenomena" and "abnormal flow caused by defect leakage," significantly reducing the false judgment rate and overcoming the technical bottleneck of traditional cold-state testing's inability to identify latent defects such as "cold-state pass, hot-state failure." Secondly, by constructing feature values ​​using square integrals, weak, continuous leakage signals are transformed into significant scalar values, greatly improving detection sensitivity. Furthermore, the stepped detection process combining cold and hot states, initiating hot-state testing only after cold-state pass, avoids the ineffective use of non-conforming products in the hot-state stage and achieves reasonable control of detection efficiency and energy consumption, providing a reliable technical means for the systematic verification of the air purifier's full-temperature-range sealing performance.

[0043] Example 2 In another preferred embodiment, the control and data analysis unit 6 can also be configured to calculate the characteristic values ​​of hot leakage. At this time, a weighting function based on the rate of temperature change is introduced. This focuses on leakage behavior within specific temperature ranges. Certain defects may be most pronounced in specific temperature ranges (e.g., 250℃ to 350℃) due to the greatest difference in the material's coefficient of thermal expansion. In such cases, the signal weighting in this range can be increased to improve detection sensitivity. The calculation formula is as follows: ; In the above formula, This represents the characteristic value of enhanced hot leakage; Represents the temperature weighting function; When the enhanced hot leakage characteristic value exceeds the preset leakage threshold At that time, In this way, defective products with thermal micro-leakage can be accurately identified.

[0044] By constructing a detection process that combines cold and hot conditions and introducing a dynamic leakage characteristic value algorithm based on temperature and pressure compensation, this system can accurately identify hot micro-leakage problems caused by extremely minor manufacturing defects that cannot be detected by traditional cold-state detection. This system effectively improves the reliability of automotive exhaust purifiers at the factory, avoiding the risks of excessive emissions and sensor failure after installation caused by hot-state leaks.

[0045] A temperature weighting function was introduced. An enhanced hot leakage characteristic value was constructed. Its implementation principle lies in: targeting the characteristic that different materials exhibit the greatest difference in thermal expansion coefficients and the most significant leakage behavior within a specific temperature range, a temperature weighting function was designed. By assigning higher weighting coefficients to key temperature ranges (such as 250℃ to 350℃), the contribution of the residual signal in this temperature range to the final feature value is amplified, thereby achieving dynamic focusing and directional enhancement of detection sensitivity.

[0046] By flexibly configuring the temperature weighting function, the system can adaptively adjust the detection sensitivity according to the differences in the materials of different purifier shells, oxygen sensor mounting bases, and their thermal expansion characteristics, concentrating detection resources on the temperature range where defects are most likely to be exposed, and further improving the reliability of detecting minor leaks in critical temperature ranges.

[0047] Meanwhile, this enhanced algorithm can optimize detection performance simply by adding a configurable weight function, which has high engineering practical value and flexibility, and provides differentiated precision detection capabilities for air purifiers of different models and materials.

[0048] Example 2 The control and data analysis unit monitors sensor signals and system status in real time during the detection process, identifies occasional or uncommon abnormal operating conditions, and outputs the judgment results. Specifically, the control and data analysis unit identifies occasional or uncommon abnormal operating conditions and outputs the judgment results by executing at least one of the following judgment modes: A1. Calculate the rate of change of pressure difference between the first pressure sensor and the second pressure sensor under a leak-free closed state. If the rate of change exceeds the preset first threshold, it is determined that there is sensor drift or blockage abnormality. A2. Monitor the dynamic response between the actual power of the heating unit and the temperature feedback in real time. If the response time deviates from the preset calibration curve by more than the second threshold, it is determined that the heating unit has local aging or poor contact. A3. Perform a short-time Fourier transform on the flow sensor signal to extract non-stationary characteristic components in the spectrum. If there are components whose frequency drifts with time and whose amplitude exceeds the third threshold, it is determined that there is intermittent leakage caused by thermal loosening of the clamp.

[0049] In discrimination mode A3, an intermittent leakage characteristic index is constructed. as follows: ; In the above formula, Indicates flow rate signal The short-time Fourier transform spectrum; This indicates the preset intermittent leakage characteristic frequency band; This represents a weighting function based on the rate of temperature change; where, when When the threshold is exceeded, an abnormal operating condition caused by intermittent thermal leakage is determined.

[0050] During hot-state testing, the thermal expansion of the purifier may cause changes in the clamping force of the fixture, resulting in intermittent, minor loosening of the connection between the purifier under test and the testing pipeline. This loosening does not produce a continuous, stable leak; instead, under the combined effects of thermal stress and vibration, the leakage path appears to open and close intermittently. Traditional integral-type leakage characteristic values ​​are insensitive to this type of time-varying, non-stationary intermittent signal because positive and negative fluctuations or intermittent leaks are averaged or canceled out over long-term integration. Therefore, it is necessary to construct a characteristic index that can capture the time-frequency non-stationary characteristics of the signal, specifically for identifying intermittent leaks caused by thermal loosening of the fixture. Specifically: Step S1: For the acquired flow signal, in order to analyze its frequency components that change over time, a short-time Fourier transform is used, which is defined as: ; In the above formula, It is a window function of finite length (such as the Hanning window) used to extract local segments of a signal; The center time of the window function represents the time point of the analysis; For frequency variables; For a complex spectrum, its modulus squared Indicates the signal in time ,frequency The instantaneous power spectral density at that location.

[0051] Step S2: Through experimental observation and theoretical analysis, it can be concluded that: A stable low-frequency offset is generated in the flow signal, and its spectral energy is mainly concentrated in the extremely low frequency band close to 0Hz.

[0052] Due to the periodic or quasi-periodic opening and closing of the leakage channel, the flow signal will exhibit pulse-like fluctuations, and its spectral energy will be distributed in a certain characteristic frequency band. Within (e.g., 0.5Hz~5Hz), the specific frequency band is related to the heating rate, the stiffness of the fixture structure, and the thermal expansion characteristics.

[0053] Therefore, in order to identify intermittent leakage, it is necessary to focus on the signal energy within a specific frequency band.

[0054] Step S3: For the entire heating process Calculate in the characteristic frequency band Average instantaneous power within: ; This value represents the total energy in the signal that belongs to the intermittent leakage characteristic frequency band at time t.

[0055] To obtain the overall intermittent leakage intensity over the entire detection period, the time is averaged: ; Combining the two equations above, we get: ; By changing the order of integration (since the integration region is rectangular), we get: ; Furthermore, the total energy at frequency f is defined as: ; but: ; Step S4: The spectral energy of intermittent leakage is usually not uniformly distributed across the entire frequency band, but rather concentrated around a specific modulation frequency. To enhance detection sensitivity, we extract the frequency component with the strongest energy within that band, i.e., we take: ; But due to This represents the total energy, the value of which is related to the time duration. To obtain an intensity index decoupled from time, we use the time-averaged energy density: ; The strongest average power spectral density within the characteristic frequency band is: ; Step S5: The occurrence of intermittent leakage is closely related to the rate of temperature change. When the temperature rises rapidly, thermal expansion is intense, the degree of loosening of the clamps changes quickly, and the frequency and amplitude of intermittent leakage may increase; when the temperature is stable or changes slowly, the intermittent phenomenon may be weakened.

[0056] Therefore, it is necessary to weight the characteristic index according to the rate of temperature change (or the average rate of change during the entire heating process) to construct an intermittent leakage characteristic index. as follows: ; The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A performance testing system for automotive exhaust purifiers, characterized in that, include: The gas supply unit is used to provide the test gas to the purifier under test. A heating unit is used to controllably heat the air purifier under test during the testing process; The first pressure sensor is located at the air inlet of the air purifier under test; The second pressure sensor is located at the air outlet of the air purifier under test; A flow sensor is connected in series in the air intake or air outlet channel of the air purifier under test. The system also includes a control and data analysis unit, which is electrically connected to the gas source unit, heating unit, first pressure sensor, second pressure sensor, and flow sensor, respectively. During the detection process, the system monitors sensor signals and system status in real time, identifies occasional or uncommon abnormal operating conditions, and outputs the judgment results. The control and data analysis unit is configured to execute a cold detection mode and a hot detection mode, and calculate a hot leakage characteristic value based on the real-time flow data and pressure data collected in the hot detection mode to determine the hot sealing performance of the purifier under test.

2. The automotive exhaust gas purifier performance testing system according to claim 1, characterized in that: The cold-state detection mode includes: controlling the gas source unit to charge the purifier under test with detection gas at a preset pressure, and judging whether its cold-state sealing performance is qualified based on the signals of the first pressure sensor, the second pressure sensor and the flow sensor.

3. The automotive exhaust gas purifier performance testing system according to claim 2, characterized in that: The hot-state detection mode is activated only after the cold-state sealing is determined to be satisfactory.

4. The automotive exhaust gas purifier performance testing system according to claim 1, characterized in that: The thermal detection mode includes: controlling the heating unit to heat the air purifier under test, causing its temperature to rise from an initial temperature. Rise to target temperature The flow rate value of the flow sensor is continuously recorded during the heating process. and the real-time pressure value of the second pressure sensor .

5. The automotive exhaust gas purifier performance testing system according to claim 4, characterized in that: The control and data analysis unit calculates the characteristic value of hot leakage. The formula is: ； in, Indicates the initial time. The baseline flow rate; Indicates the initial time. Export pressure; This represents the pressure change compensation coefficient; Indicates real-time temperature Related thermal expansion compensation factors.

6. The automotive exhaust gas purifier performance testing system according to claim 5, characterized in that: The pressure change compensation coefficient is obtained by pre-calibration on a standard leak-free purifier; the control and data analysis unit is also configured to determine that the hot-state sealing of the purifier under test is unqualified when the hot-state leakage characteristic value exceeds the preset leakage threshold.

7. The automotive exhaust gas purifier performance testing system according to claim 5, characterized in that: The control and data analysis unit introduces a temperature weighting function into the formula for calculating the hot leakage characteristic value to form an enhanced hot leakage characteristic value: ； In the above formula, This represents the characteristic value of enhanced hot leakage; Represents the temperature weighting function; When the enhanced hot leakage characteristic value exceeds the preset leakage threshold, the hot sealing performance of the purifier under test is determined to be unqualified.

8. The automotive exhaust gas purifier performance testing system according to claim 1, characterized in that: The control and data analysis unit identifies occasional or uncommon abnormal operating conditions and outputs the discrimination result by executing at least one of the following discrimination modes: A1. Calculate the rate of change of pressure difference between the first pressure sensor and the second pressure sensor under a leak-free closed state. If the rate of change exceeds the preset first threshold, it is determined that there is sensor drift or blockage abnormality. A2. Monitor the dynamic response between the actual power of the heating unit and the temperature feedback in real time. If the response time deviates from the preset calibration curve by more than the second threshold, it is determined that the heating unit has local aging or poor contact. A3. Perform a short-time Fourier transform on the flow sensor signal to extract non-stationary characteristic components in the spectrum. If there are components whose frequency drifts with time and whose amplitude exceeds the third threshold, it is determined that there is intermittent leakage caused by thermal loosening of the clamp.

9. The automotive exhaust gas purifier performance testing system according to claim 8, characterized in that: In discrimination mode A3, an intermittent leakage characteristic index is constructed. as follows: ； In the above formula, Indicates flow rate signal The short-time Fourier transform spectrum; This indicates the preset intermittent leakage characteristic frequency band; This represents a weighting function based on the rate of temperature change. Among them, when When the threshold is exceeded, an abnormal operating condition caused by intermittent thermal leakage is determined.

10. A method for testing the performance of an automotive exhaust purifier, characterized in that, The automotive exhaust purifier performance testing system according to any one of claims 1-9, and the automotive exhaust purifier performance testing method specifically include the following steps: S1. Perform a cold-state sealing test on the air purifier under test; S2. If the cold-state sealing is qualified, the heating unit is started to controllably raise the temperature of the air purifier under test. S3. During the heating process, the outlet pressure data and gas flow data of the purifier under test are collected in real time. S4. Based on the outlet pressure data and gas flow data, construct a hot leakage characteristic value model and calculate the hot leakage characteristic value; S5. Compare the calculated hot leakage characteristic value with the preset leakage threshold. If it exceeds the preset leakage threshold, the hot sealing performance of the purifier under test is determined to be unqualified.

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