Multipath sensor testing apparatus and multipath sensor testing method

Abstract

The application discloses a multi-channel sensor testing device and a multi-channel sensor testing method, and belongs to the technical field of sensor testing. The multi-channel sensor testing device comprises a sensor interface module configured to access multiple to-be-tested sensors in parallel to provide working power for the multiple to-be-tested sensors, wherein the to-be-tested sensors comprise gas sensors or particulate matter sensors; and a control module configured to establish a communication connection with the accessed multiple to-be-tested sensors to collect measurement data of each to-be-tested sensor in parallel and evaluate data consistency among the multiple to-be-tested sensors based on the measurement data. In this way, parallel batch testing of multiple channels can be realized, the production line testing efficiency is greatly improved, the testing requirements of two types of sensors in different fields are met, the application range of the equipment is effectively improved, the consistency of the same batch of sensors is acquired in real time, abnormal channels are identified, and the accuracy and intelligent level of sensor performance evaluation are significantly improved.

Description

Technical Field

[0001] This application relates to the field of sensor testing technology, and in particular to a multi-channel sensor testing device and a multi-channel sensor testing method. Background Technology

[0002] Gas sensors and particulate matter sensors are widely used in environmental monitoring and industrial safety testing. During sensor aging tests, a large number of sensors need to undergo concentration detection and performance evaluation.

[0003] However, sensor testing equipment in related technologies suffers from numerous technical shortcomings. On the one hand, the number of test channels is limited: current testing fixtures mostly adopt a single-channel design, resulting in low testing efficiency and failing to meet the needs of batch testing on production lines. On the other hand, there is a lack of parallel data comparison and evaluation mechanisms: current testing fixtures have weak data processing capabilities, only able to present raw measurement values, and cannot perform statistical analysis, making it difficult to simultaneously evaluate the data consistency and deviation between multiple sensors. Summary of the Invention

[0004] This application provides a multi-channel sensor testing device, a multi-channel sensor testing method, a multi-channel sensor testing equipment, a multi-channel sensor testing system, and a computer-readable storage medium to solve at least one of the aforementioned technical problems.

[0005] The multi-channel sensor testing apparatus of this application includes: The sensor interface module is configured to connect multiple sensors under test in parallel to provide operating power to the multiple sensors under test, including gas sensors or particulate matter sensors. The control module is configured to establish communication connections with multiple access sensors under test (SUTs) to acquire measurement data from each SUT in parallel and to evaluate the data consistency among the multiple SUTs based on the measurement data.

[0006] In the multi-channel sensor testing device of this application, firstly, by setting a sensor interface module, multiple sensors under test can be connected in parallel, breaking the efficiency bottleneck of traditional single-channel testing, enabling parallel batch testing of multiple channels, and greatly improving the testing efficiency of the production line; secondly, it supports the connection of gas sensors or particulate matter sensors, which can meet the testing needs of two different types of sensors, effectively expanding the applicability of the equipment and significantly reducing equipment investment and maintenance costs; thirdly, by setting a control module to establish a communication connection with multiple sensors under test, it can collect measurement data from each channel in parallel, and evaluate the data consistency between multiple sensors based on these measurement data. It can obtain the consistency status of sensors in the same batch in real time and identify abnormal channels, significantly improving the accuracy and intelligence level of sensor performance evaluation.

[0007] In some embodiments, the multi-sensor testing apparatus further includes a button module configured to receive a type selection command for a gas sensor or a particulate sensor. The control module is further configured to: determine the sensor type of the multiple sensors under test according to the type selection instruction, and configure the communication protocol parameters corresponding to the sensor type in order to establish a communication connection with the multiple sensors under test.

[0008] This application's implementation utilizes a button module to receive type selection commands, enabling the control module to automatically configure the corresponding communication protocol parameters. This solution supports flexible switching between gas sensor and particulate matter sensor testing modes, and achieves compatibility with both types of sensors using a single device, avoiding the cumbersome process of replacing different testing equipment and reducing equipment investment costs.

[0009] In some implementations, the multi-channel sensor testing device further includes a power supply module, a level conversion module, and a communication conversion circuit; Multiple sensors under test are electrically connected to the power module through a sensor interface module and a level conversion module to obtain operating power. The control module establishes communication connections with the multiple sensors under test via a communication conversion circuit to acquire measurement data from each sensor in parallel.

[0010] This application's implementation, through the cooperation of a level conversion module and a power supply module, enables precise multi-level power supply to different hardware modules within a multi-channel sensor testing device, ensuring the stable operation of multiple sensors under test. Furthermore, the use of a communication conversion circuit to construct a parallel communication architecture guarantees the reliability and real-time performance of synchronous multi-channel data acquisition.

[0011] The multi-channel sensor testing method of this application, applied to the multi-channel sensor testing apparatus of any of the above embodiments, includes: Establish communication connections with multiple connected sensors under test; Parallel acquisition of measurement data from each sensor under test; The consistency of data among multiple sensors under test is evaluated based on measurement data.

[0012] This application's implementation achieves synchronous, automated batch testing of multiple sensors by acquiring multiple measurement data in parallel and evaluating the data consistency among the various sensors under test. This method effectively identifies abnormal channels and triggers alarms, improving testing efficiency and data comparison accuracy.

[0013] In some implementations, the multi-sensor testing method further includes: The sensor type of the multiple sensors under test is determined based on the type selection command; Establish communication connections with multiple connected sensors under test, including: Configure the communication protocol parameters corresponding to the sensor type to establish communication connections with multiple sensors under test.

[0014] This application's implementation dynamically identifies the sensor type based on a type selection command and automatically configures the corresponding communication protocol parameters, enabling flexible switching between gas sensor and particulate matter sensor testing modes. This method allows a single device to meet the testing needs of both types of sensors, avoiding the cumbersome process of changing different testing equipment and reducing equipment investment costs.

[0015] In some implementations, evaluating data consistency among multiple sensors under test based on measurement data includes: Based on the measurement data of each sensor under test, the average value of each sensor under test within a preset statistical period is calculated. Based on the measurement data of multiple sensors under test, the total average value of multiple sensors under test within a preset statistical period is calculated. Based on the deviation between the single-channel average value and the total average value of multiple channels, determine whether the data consistency of each sensor under test within the preset statistical period is qualified.

[0016] This application's implementation method achieves quantitative analysis of the measurement performance of multiple sensors under test by calculating the average value of a single channel and the total average value of multiple channels, and by evaluating the consistency based on the deviation between the two. This method effectively reduces the interference from fluctuations in single instantaneous data, providing reliable data processing capabilities for accurately identifying abnormal sensor channels.

[0017] In some implementations, the consistency of data from each sensor under test within a preset statistical period is determined based on the deviation between the single-channel average and the total average of multiple channels, including: The benchmark value for consistency determination is determined based on the total average value of multiple paths; Determine whether the average value of each single-channel sensor under test is within a preset proportional threshold range centered on the reference value; If the average value of a single channel is within the preset proportional threshold range, the data consistency of the sensor under test in the corresponding channel is deemed to be qualified. If the average value of a single channel exceeds the preset ratio threshold range, the data consistency of the sensor under test in the corresponding channel within the preset statistical period is deemed unqualified.

[0018] This application's implementation method, by setting a benchmark value and a preset proportional threshold range, determines the range of single-channel average values, achieving a precise quantitative assessment of sensor data consistency. This method provides an objective basis for qualification judgment, accurately and efficiently identifying abnormal sensors whose measurement performance deviates from the overall test benchmark.

[0019] In some implementations, based on the measurement data of each sensor under test, the average value of each sensor under test within a preset statistical period is calculated, including: Based on the measurement data of each sensor under test, the first single-channel average value and the second single-channel average value of each sensor under test in the first preset statistical period and the second preset statistical period are calculated respectively. Based on the measurement data from multiple sensors under test, the overall average value of the multiple sensors under test within a preset statistical period is calculated, including: Based on the measurement data of multiple sensors under test, the first total average value of multiple sensors under test in the first preset statistical period and the second total average value of multiple sensors in the second preset statistical period are calculated. Based on the deviation between the single-channel average and the multi-channel total average, determine whether the data consistency of each sensor under test within a preset statistical period is acceptable, including: Based on the first deviation between the first single-channel average value and the first multi-channel total average value, determine whether the data consistency of each sensor under test within the first preset statistical period is qualified; Based on the second deviation between the second single-channel average value and the second multi-channel total average value, determine whether the data consistency of each sensor under test within the second preset statistical period is qualified; The duration of the second preset statistical period is longer than that of the first preset statistical period.

[0020] This application's implementation method introduces two preset statistical periods, one long and one short, to calculate the single-channel average and the multi-channel total average, and performs dual deviation judgment. This scheme balances the timeliness of data monitoring with the accuracy of test evaluation, effectively filters out misjudgments caused by instantaneous data fluctuations, and improves the reliability of multi-channel sensor testing.

[0021] In some implementations, the multi-sensor testing method further includes: Displays measurement data from each sensor under test, including the first single-channel average value, the second single-channel average value, the first multi-channel total average value, the second multi-channel total average value, the first deviation case, and the second deviation case, among any one or more of these.

[0022] This application's implementation method achieves comprehensive visualization of multi-channel parallel test data by comprehensively presenting measurement data, multi-cycle single-channel average values, multi-cycle multi-channel total average values, and corresponding deviations on a display screen. This method allows testers to intuitively monitor the working status and consistency performance of all sensors under test.

[0023] In some implementations, the multi-sensor testing method further includes: Real-time updates of measurement data from each sensor under test; When the first preset statistical period is reached, the first single-path average value is updated; After updating the first single-path average, update the first multi-path total average. When the second preset statistical period is reached, the second single-path average value is updated; After updating the second single-path average, update the second multi-path total average.

[0024] This application employs a hierarchical refresh strategy, sequentially updating measurement data, single-channel average values, and multi-channel total average values ​​according to different cycle sequences. This method balances the real-time nature of data monitoring with the accuracy of long-term statistics, resulting in a clear and organized presentation of test data and providing a reliable data update process for the performance evaluation of batches of sensors under test.

[0025] The multi-channel sensor testing device according to the embodiments of this application is applied to the multi-channel sensor testing apparatus of any of the above embodiments. The multi-channel sensor testing device includes: A module is established to create communication connections with multiple connected sensors under test. The acquisition module is used to acquire measurement data from each sensor under test in parallel. The evaluation module is used to evaluate the data consistency among multiple sensors under test based on measurement data.

[0026] The multi-channel sensor testing system of this application includes one or more processors and a memory. The memory stores a computer program. When the computer program is executed by the processor, it implements the multi-channel sensor testing method of any of the above embodiments.

[0027] The computer-readable storage medium of the present application embodiment stores a computer program thereon, which, when executed by a processor, implements the multi-channel sensor testing method of any of the above embodiments.

[0028] In summary, the multi-channel sensor testing device, multi-channel sensor testing method, multi-channel sensor testing equipment, multi-channel sensor testing system, and computer-readable storage medium of this application, firstly, by setting a sensor interface module, can connect multiple sensors under test in parallel, breaking the efficiency bottleneck of traditional single-channel testing, enabling parallel batch testing of multiple channels, and greatly improving production line testing efficiency; secondly, it supports the connection of gas sensors or particulate matter sensors, which can meet the testing needs of two different types of sensors, effectively expanding the applicability of the equipment and significantly reducing equipment investment and maintenance costs; thirdly, by setting a control module to establish a communication connection with multiple sensors under test, it can collect measurement data from each channel in parallel, and evaluate the data consistency between multiple sensors based on these measurement data, and can obtain the consistency status of sensors in the same batch in real time and identify abnormal channels, significantly improving the accuracy and intelligence level of sensor performance evaluation.

[0029] Additional aspects and advantages of embodiments of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of embodiments of this application. Attached Figure Description

[0030] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, wherein: Figure 1 This is a schematic diagram of a multi-channel sensor testing device according to certain embodiments of this application; Figure 2 This is a schematic diagram of the structure of a multi-channel sensor testing device according to certain embodiments of this application; Figure 3 This is a schematic diagram of the structure of a multi-channel sensor testing device according to certain embodiments of this application; Figure 4 This is a flowchart illustrating a multi-channel sensor testing method according to certain embodiments of this application; Figure 5 This is a schematic diagram of a multi-channel sensor testing device according to certain embodiments of this application; Figure 6 This is a schematic diagram of the modules of a multi-channel sensor test system according to certain embodiments of this application; Figure 7 This is a schematic diagram illustrating the connection state between a computer-readable storage medium and a processor according to certain embodiments of this application.

[0031] Explanation of reference numerals in the attached figures: Multi-channel sensor testing device 100, sensor interface module 10, control module 20, button module 30, power supply module 40, level conversion module 50, communication conversion circuit 60, display control module 70, alarm indication module 80, main control circuit board 101, low voltage source 102, housing 103, display screen 104, sensor under test 200, multi-channel sensor testing equipment 300, setup module 310, acquisition module 320, evaluation module 330, multi-channel sensor testing system 400, processor 410, memory 420, computer-readable storage medium 500, computer program 510, processor 520. Detailed Implementation

[0032] The embodiments of this application will be further described below with reference to the accompanying drawings. The same or similar reference numerals in the drawings denote the same or similar elements or elements having the same or similar functions throughout. Furthermore, the embodiments of this application described below with reference to the accompanying drawings are exemplary and are only used to explain the embodiments of this application, and should not be construed as limiting this application.

[0033] Please see Figures 1 to 3 The multi-channel sensor testing device 100 of this application includes a sensor interface module 10 and a control module 20. The sensor interface module 10 is configured to connect to multiple sensors under test 200 in parallel to provide operating power to the sensors 200. The sensors under test 200 include gas sensors or particulate matter sensors. The control module 20 is configured to establish a communication connection with the connected multiple sensors under test 200 to acquire measurement data from each sensor 200 in parallel, and to evaluate the data consistency among the multiple sensors under test 200 based on the measurement data.

[0034] Specifically, the multi-channel sensor testing device 100 can be used for performance testing and calibration of gas sensors and particulate matter sensors in fields such as environmental monitoring and industrial safety testing.

[0035] The sensor interface module 10 can adopt a multi-channel independent architecture, such as a ten-channel independent architecture, to achieve parallel synchronous testing of multiple sensors under test 200 (more than ten times more efficient than the traditional single-channel mode, suitable for batch testing scenarios on production lines). The sensors under test 200 include gas sensors or particulate matter sensors. The gas sensor can be a methane (CH4) sensor, and the particulate matter sensor can be a fine particulate matter (PM2.5) sensor. 2.5 Sensors. Through the sensor interface module 10, working power can be provided to each connected sensor under test 200, ensuring the normal and stable operation of the sensor under test 200 during the testing process.

[0036] The control module 20, as the core control module, can be a microcontroller unit (MCU). The control module 20 establishes communication connections with each of the multiple connected sensors under test (SUTs) 200, thereby acquiring real-time measurement data from each SUT 200 in parallel. The control module 20 also possesses multi-dimensional data processing capabilities, enabling it to perform statistical analysis on the real-time measurement data from each SUT 200 and identify abnormal channels, thus accurately evaluating the data consistency performance of each SUT 200 under the same test environment.

[0037] It is understandable that the aging test of sensors requires concentration detection and performance evaluation of a large number of sensors. However, the sensor testing equipment in related technologies has many technical shortcomings. On the one hand, the number of test channels is limited: current test fixtures mostly adopt a single-channel design, resulting in low testing efficiency and failing to meet the needs of batch testing on production lines. On the other hand, there is a lack of parallel data comparison and evaluation mechanisms: current test fixtures have weak data processing capabilities, only able to present raw measurement values, unable to perform statistical analysis, and therefore difficult to simultaneously evaluate the data consistency and deviation between multiple sensors.

[0038] In the multi-channel sensor testing device 100 of this application, firstly, by setting up a sensor interface module 10, multiple sensors under test 200 can be connected in parallel, breaking the efficiency bottleneck of traditional single-channel testing, and realizing parallel batch testing of multiple channels, which greatly improves the testing efficiency of the production line; secondly, it supports the connection of gas sensors or particulate matter sensors, which can meet the testing needs of two different types of sensors, effectively improving the applicability of the equipment and significantly reducing the equipment investment and maintenance costs; thirdly, by setting up a control module 20 to establish a communication connection with multiple sensors under test 200, it can collect measurement data of each channel in parallel, and evaluate the data consistency between multiple sensors based on these measurement data. It can obtain the consistency status of sensors in the same batch in real time and identify abnormal channels, which significantly improves the accuracy and intelligence level of sensor performance evaluation.

[0039] Please see Figures 1 to 3 In some embodiments, the multi-channel sensor testing device 100 further includes a button module 30, which is configured to receive a type selection command for a gas sensor or a particulate matter sensor. The control module 20 is further configured to: determine the sensor type of the multiple sensors under test 200 connected according to the type selection command, and configure communication protocol parameters corresponding to the sensor type to establish a communication connection with the multiple sensors under test 200.

[0040] Specifically, the button module 30 can be configured with physical buttons for operation by the tester. The button module 30 can not only control the multi-channel sensor test device 100 to start or pause measurement, but also receive type selection commands input by the tester, thereby switching between gas sensor test mode and particulate matter sensor test mode.

[0041] After receiving the type selection command from the button module 30, the control module 20 can determine whether the currently connected multi-channel sensor under test 200 is a gas sensor or a particulate matter sensor. Based on the confirmed sensor type, the control module 20 will automatically reconfigure the communication protocol parameters that match the sensor type. After completing the configuration of the communication protocol parameters, the control module 20 can establish a stable and correct communication connection for the selected type of multi-channel sensor under test 200 to ensure the accuracy of subsequent data acquisition and consistency determination. Through the above settings, the different communication protocol requirements of different types of sensor under test 200 can be met when connected.

[0042] This embodiment utilizes a button module 30 to receive type selection commands, enabling the control module 20 to automatically configure the corresponding communication protocol parameters. This solution supports flexible switching between gas sensor testing modes and particulate matter sensor testing modes, and achieves compatibility with both types of sensors using a single device, avoiding the cumbersome process of changing different testing equipment and reducing equipment investment costs.

[0043] Please see Figure 1 In some embodiments, the multi-channel sensor testing device 100 further includes a power supply module 40, a level conversion module 50, and a communication conversion circuit 60. Multiple sensors under test 200 are electrically connected to the power supply module 40 via the sensor interface module 10 and the level conversion module 50 to obtain operating power. The control module 20 establishes communication connections with each of the connected multiple sensors under test 200 via the communication conversion circuit 60 to acquire measurement data from each sensor under test 200 in parallel.

[0044] Specifically, a low-voltage source 102 can be used to power the multi-channel sensor testing device 100. The low-voltage source 102 can input +12V DC power to the power module 40. After receiving the input DC power, the power module 40, in conjunction with the level conversion module 50, converts the electrical energy into different levels of operating voltage. As an example, the level conversion module 50 can include chips of model ME3116, LM2596, and AMS1117. These chips convert electrical energy into +5V screen power, +5V sensor power, and +3.3V MCU power, respectively, to power the various modules of the multi-channel sensor testing device 100. Among them, the multiple sensors under test 200, after being connected through the sensor interface module 10, obtain +5V sensor power as operating power. The +5V screen power is used to power the display screen 104 (described later). The +3.3V MCU power is used to power the control module 20. After the system is powered on, the control module 20 initializes the hardware configuration and loads the display interface.

[0045] Data interaction between the control module 20 and the multiple sensors under test 200 relies on the communication conversion circuit 60. The communication conversion circuit 60 can be a bus-to-Universal Asynchronous Receiver / Transmitter (UART) circuit. Through the UART circuit, the control module 20 can establish parallel communication channels with, for example, ten connected sensors under test 200, thereby acquiring the measurement data of each sensor under test 200 in real time.

[0046] This embodiment of the application, through the cooperation of the level conversion module 50 and the power supply module 40, can achieve precise multi-level power supply to different hardware modules within the multi-channel sensor testing device 100, and ensure the stable operation of multiple sensors under test 200. Furthermore, by utilizing the communication conversion circuit 60 to construct a parallel communication architecture, the reliability and real-time performance of synchronous acquisition of multi-channel data are guaranteed.

[0047] Please see Figures 1 to 3In some embodiments, the main hardware architecture of the multi-channel sensor testing device 100 may include a main control circuit board 101, a low-voltage source 102, a housing 103, and a display screen 104. The aforementioned sensor interface module 10, control module 20, button module 30, power module 40, level conversion module 50, and communication conversion circuit 60 can all be integrated into the main control circuit board 101. Furthermore, the main control circuit board 101 may also integrate a display control module 70 and an alarm indication module 80. The housing 103 can be used to protect the internal components of the multi-channel sensor testing device 100 from damage. The display screen 104 can be used to display the measurement data of the sensor under test 200, as well as the single-channel average value, multi-channel total average value, and deviation status, as described later. The display control module 70 is used to connect an external display screen 104. The alarm indication module 80 is used to provide an alarm indication when there is a deviation in the data consistency among the multiple sensors under test 200.

[0048] Please see Figure 1 and Figure 4 The multi-channel sensor testing method of this application is applied to the multi-channel sensor testing apparatus 100 of any of the above embodiments. The multi-channel sensor testing method includes: S401. Establish a communication connection with the connected multi-channel sensor under test 200.

[0049] In the embodiments of this application, the control module 20 can establish parallel communication channels with each of the connected sensors under test 200 through the communication conversion circuit 60, thereby providing a basic link guarantee for subsequent data interaction and synchronous testing.

[0050] S402, Parallel acquisition of measurement data from each of the sensors under test 200.

[0051] In the embodiments of this application, after establishing a stable communication connection, the control module 20 can continuously perform real-time data reading operations on the sensors under test 200 on multiple independent channels. By performing data acquisition in parallel, real-time measurement data from all gas sensors or particulate matter sensors connected to the channels can be acquired simultaneously, thereby overcoming the limitations of the traditional single-channel testing mode and significantly improving the data acquisition speed in the batch testing process.

[0052] S403. Evaluate the data consistency among multiple sensors under test 200 based on measurement data.

[0053] In the embodiments of this application, after acquiring the measurement data, the control module 20 can perform synchronous processing and multi-dimensional statistical analysis on the parallel multi-channel data. For example, by analyzing the deviation between each channel's measurement data and the overall data, the consistency performance between sensors can be evaluated, thereby identifying sensor channels that may have faults or abnormal accuracy. In some embodiments, if the evaluation result indicates that the measurement data of a certain sensor under test 200 deviates from the overall consistency, the control module 20 will trigger the alarm indication module 80 to issue an alarm indication, so as to prompt the tester that the data collected by that sensor deviates from the overall consistency, thereby completing the performance verification of the sensor.

[0054] This application's implementation achieves synchronous, automated batch testing of multiple sensors by acquiring multiple measurement data channels in parallel and evaluating the data consistency among the 200 sensors under test. This method effectively identifies abnormal channels and triggers alarms, improving testing efficiency and data comparison accuracy.

[0055] In some implementations, the multi-sensor testing method further includes: S501. Determine the sensor type of the connected multi-channel sensor under test 200 according to the type selection instruction.

[0056] In the embodiments of this application, the tester can input a type selection command for either a gas sensor or a particulate sensor via the button module 30. Upon receiving this command, the control module 20 determines whether the sensor under test 200 connected to the current multi-channel independent test is a gas sensor or a particulate sensor. Accurate sensor type identification provides a basis for subsequently matching the appropriate communication rules.

[0057] Establish a communication connection with the accessed multi-channel sensor under test 200, including: S502. Configure the communication protocol parameters corresponding to the sensor type to establish a communication connection with the multiple sensors under test 200.

[0058] In the embodiments of this application, after the sensor types of the multiple sensors under test 200 are determined, the control module 20 can automatically reconfigure the communication protocol parameters that match that type. In some embodiments, since gas sensors and particulate matter sensors typically have different communication standards, the control module 20 can dynamically adjust the communication protocol parameters according to the selection result, and simultaneously clear previous measurement data during the configuration of the communication protocol parameters. After the configuration is completed, the control module 20 establishes a correct and stable communication connection with the connected multiple sensors under test 200 based on the communication protocol parameters.

[0059] This application's implementation dynamically identifies the sensor type based on a type selection command and automatically configures the corresponding communication protocol parameters, enabling flexible switching between gas sensor and particulate matter sensor testing modes. This method allows a single device to meet the testing needs of both types of sensors, avoiding the cumbersome process of changing different testing equipment and reducing equipment investment costs.

[0060] In some implementations, evaluating the data consistency among multiple sensors under test 200 based on measurement data includes: S601. Based on the measurement data of each sensor under test 200, calculate the single-channel average value of each sensor under test 200 within the preset statistical period.

[0061] In the embodiments of this application, the control module 20 can set a preset statistical period as a time window for data calculation during the continuous acquisition of measurement data from multiple independent channels. In some embodiments, within the preset statistical period, the control module 20 can summarize the continuous measurement data acquired by each sensor under test 200 and calculate its arithmetic mean, thereby obtaining a single-channel average value reflecting the measurement level of that sensor under test 200 during that period. By calculating the single-channel average value, random noise fluctuations in instantaneous measurement data can be effectively filtered out.

[0062] S602. Based on the measurement data of the multiple sensors under test 200, calculate the total average value of the multiple sensors under test 200 within a preset statistical period.

[0063] In the embodiments of this application, after acquiring the measurement data of each independent channel, the control module 20 further integrates and processes the global data. In some embodiments, the control module 20 can perform comprehensive calculations on the measurement data or corresponding single-channel average values ​​of all sensors under test 200 connected within the same preset statistical period, for example, calculating the overall average value of all channel data, and then obtaining the multi-channel total average value. The multi-channel total average value can objectively reflect the overall measurement benchmark level of the batch of multi-channel sensors under test 200 in the current test environment.

[0064] S603. Based on the deviation between the single-channel average value and the multi-channel total average value, determine whether the data consistency of each channel of the sensor under test 200 within the preset statistical period is qualified.

[0065] In embodiments of this application, the control module 20 can use the calculated multi-channel total average value as a reference for consistency evaluation. In some embodiments, the control module 20 can calculate the difference between the single-channel average value of each sensor under test 200 and the multi-channel total average value, and evaluate the measurement performance of each sensor under test 200 by analyzing the deviation represented by the difference. If the deviation is within the expected allowable limit, the data consistency of the sensor under test 200 in that channel is determined to be qualified; otherwise, if the deviation indicates that the deviation is too large, the data consistency of the sensor under test 200 in the corresponding channel is determined to be unqualified. This step provides a quantitative basis for identifying abnormal channels.

[0066] This application's implementation method achieves quantitative analysis of the measurement performance of multiple sensors under test (SUT) 200 by calculating the average value of a single channel and the total average value of multiple channels, and by evaluating the consistency based on the deviation between the two. This method effectively reduces the interference from fluctuations in single instantaneous data, providing reliable data processing capabilities for accurately identifying abnormal sensor channels.

[0067] In some implementations, the consistency of data from each sensor under test 200 within a preset statistical period is determined based on the deviation between the single-channel average and the total average of multiple channels, including: S701. Determine the benchmark value for consistency judgment based on the total average value of multiple paths.

[0068] In the embodiments of this application, the control module 20 uses the multi-channel total average value calculated within a preset statistical period as the reference center for evaluation. Taking a particulate matter sensor as the PM... 2.5 Taking the sensor test mode as an example, the control module 20 sets the latest multi-channel total average value as the benchmark value for consistency judgment. This benchmark value reflects the overall measurement level of the multiple sensors under test 200 within the current test cycle, providing a unified comparison basis for subsequent calculation of differences and judgment deviations.

[0069] S702. Determine whether the single-channel average value of each sensor under test 200 is within the preset proportional threshold range centered on the reference value.

[0070] In embodiments of this application, after determining the benchmark value for consistency judgment, the control module 20 can compare the single-channel average value of each test sensor 200 with the benchmark value. In some embodiments, the control module 20 can determine whether the single-channel average value is within a preset percentage threshold range centered on the benchmark value. For example, the set pass / fail standard is that the single-channel average value is within ±10% of the total average value of multiple channels. Assuming that the benchmark value calculated in a certain test is 60, then the control module 20 determines whether the single-channel average value of each test sensor 200 falls within the numerical range of 54 to 66.

[0071] S703. If the average value of a single channel is within the preset proportional threshold range, the data consistency of the sensor 200 under test in the corresponding channel is deemed to be qualified.

[0072] In the embodiments of this application, when the average value of a single channel of the sensor under test 200 meets the expected fluctuation range mentioned above, it indicates that the measurement performance of the sensor is highly close to the overall performance. Following the previous example, if the average value of a single channel of the sensor under test 200 is between 54 and 66, the control module 20 determines that the consistency of the sensor under test 200 in that channel meets the standard, that is, confirms that the data consistency of the sensor under test 200 is qualified, and no abnormality prompt is required.

[0073] S704. If the average value of a single channel exceeds the preset proportional threshold range, the data consistency of the sensor 200 under test in the corresponding channel within the preset statistical period is determined to be unqualified.

[0074] In the embodiments of this application, if the single-channel average value of a certain sensor under test 200 deviates significantly from the reference value, it indicates that its measurement performance differs abnormally from other sensors in the same batch. Following the aforementioned example, if the single-channel average value of the sensor under test 200 is less than 54 or greater than 66, the control module 20 determines that the consistency of the sensor under test 200 in that channel does not meet the standard, thereby confirming that the data consistency of the sensor under test 200 within the preset statistical period is unqualified.

[0075] This application's implementation method, by setting a benchmark value and a preset proportional threshold range, determines the range of single-channel average values, achieving a precise quantitative assessment of sensor data consistency. This method provides an objective basis for qualification judgment, accurately and efficiently identifying abnormal sensors whose measurement performance deviates from the overall test benchmark.

[0076] In some implementations, based on the measurement data of each sensor under test 200, the average value of each sensor under test 200 within a preset statistical period is calculated, including: S801. Based on the measurement data of each sensor under test 200, calculate the first single-channel average value and the second single-channel average value of each sensor under test 200 within the first preset statistical period and within the second preset statistical period.

[0077] In the embodiments of this application, the control module 20 can continuously collect data from each independent channel in real time. The first preset statistical period is set to 1 second, for example, and the second preset statistical period is set to 1 minute, for example. The control module 20 can calculate the 1-second average value of each channel of the sensor under test 200 as the first single-channel average value, and the 1-minute average value as the second single-channel average value, based on the measurement data of each channel of the sensor under test 200.

[0078] Based on the measurement data from the multiple sensors under test 200, the total average value of the multiple sensors under test 200 within a preset statistical period is calculated, including: S802. Based on the measurement data of the multiple sensors under test 200, calculate the first multi-channel total average value of the multiple sensors under test 200 within the first preset statistical period and the second multi-channel total average value within the second preset statistical period.

[0079] In embodiments of this application, the control module 20 can perform aggregation operations on global data at different time scales. In some embodiments, the control module 20 can calculate the 1-second total average value of all access channel measurement data once per second as the first multi-channel total average value; at the same time, with a 1-minute cycle, it can recalculate and update the 1-minute total average value based on the multi-channel measurement data collected within the cycle as the second multi-channel total average value.

[0080] Based on the deviation between the single-channel average value and the multi-channel total average value, determine whether the data consistency of each channel of the sensor under test 200 within the preset statistical period is qualified, including: S803. Based on the first deviation between the first single-channel average value and the first multi-channel total average value, determine whether the data consistency of each sensor under test 200 within the first preset statistical period is qualified.

[0081] In embodiments of this application, real-time consistency determination can be performed based on a first preset statistical period of relatively short duration. In some embodiments, the control module 20 can determine the first deviation by comparing the first single-channel average value with the first multi-channel total average value, thereby quickly evaluating and determining whether the data consistency of each sensor under test 200 meets the standard within a short period of time, and realizing rapid feedback of test data.

[0082] S804. Based on the second deviation between the second single-channel average value and the second multi-channel total average value, determine whether the data consistency of each sensor under test 200 within the second preset statistical period is qualified.

[0083] In embodiments of this application, a stable consistency determination can be made based on a second preset statistical period of a relatively long duration. In some embodiments, the control module 20 can calculate the corresponding difference, i.e., the second deviation, by comparing the second single-channel average value with the latest second multi-channel total average value. Based on the second deviation, the control module 20 can accurately determine whether the data consistency of each sensor under test 200 is qualified within the long period. This long-period determination method can effectively smooth out accidental data errors.

[0084] The duration of the second preset statistical period is longer than that of the first preset statistical period.

[0085] In the embodiments of this application, the first preset statistical period and the second preset statistical period can form a time window that combines long and short periods. The first preset statistical period is, for example, the aforementioned 1 second, and the second preset statistical period is, for example, the aforementioned 1 minute.

[0086] This application's implementation method introduces two preset statistical periods, one long and one short, to calculate the single-channel average and the multi-channel total average, and performs dual deviation judgment. This scheme balances the timeliness of data monitoring with the accuracy of test evaluation, effectively filters out misjudgments caused by instantaneous data fluctuations, and improves the reliability of multi-channel sensor testing.

[0087] It should be noted that, regarding S803 and S804, how to determine whether the data consistency of each sensor under test 200 within the first preset statistical period is qualified based on the first deviation between the first single-channel average value and the first multi-channel total average value, and how to determine whether the data consistency of each sensor under test 200 within the second preset statistical period is qualified based on the second deviation between the second single-channel average value and the second multi-channel total average value, can be referred to the determination process of S701 to S704 above, and will not be explained further here.

[0088] In some implementations, the multi-sensor testing method further includes: S901 Displays measurement data of each sensor under test 200, including one or more of the following: first single-channel average value, second single-channel average value, first multi-channel total average value, second multi-channel total average value, first deviation case, and second deviation case.

[0089] In the embodiments of this application, the control module 20 can drive the external display screen 104 through the display control module 70 to present the aforementioned multi-dimensional test and calculation results to the tester. In some embodiments, the display screen 104 can clearly display the measurement data collected in real time by the sensor under test 200 on each independent channel. It is understood that if a significant abnormality occurs in the displayed value during operation (possibly because a serial port failed to initialize), the tester can press the reset button to restore the communication connection and data acquisition to normal.

[0090] Based on this, the display screen 104 can also display the first single-channel average value and the first multi-channel total average value calculated based on a first preset statistical period of 1 second, as well as the second single-channel average value and the second multi-channel total average value calculated based on a second preset statistical period of 1 minute.

[0091] In some embodiments, to facilitate testers' intuitive understanding of consistency performance, the display screen 104 can also directly display the specific difference corresponding to the first deviation or second deviation calculated based on the above average values ​​(i.e., the difference between the first single-channel average value and the first multi-channel total average value, and the difference between the second single-channel average value and the second multi-channel total average value). The multi-channel sensor testing device 100 effectively solves the traditional testing problem of weak data processing capabilities and only presenting raw values ​​by presenting any one or a combination of the above-mentioned multi-dimensional data.

[0092] This application's implementation method achieves comprehensive visualization of multi-channel parallel test data by comprehensively presenting measurement data, multi-cycle single-channel average values, multi-cycle multi-channel total average values, and corresponding deviations on the display screen 104. This method allows testers to intuitively monitor the working status and consistency performance of all sensors under test 200.

[0093] In some implementations, the multi-sensor testing method further includes: S1001: Real-time update of measurement data from each of the 200 sensors under test.

[0094] In embodiments of this application, data refreshing may employ a tiered strategy. In some embodiments, the control module 20 continuously acquires real-time measurement data from multiple independent channels throughout the entire testing process and keeps this measurement data constantly updated. This updating method ensures that testers can observe the most immediate changes in gas concentration measurement data or particulate matter concentration measurement data.

[0095] S1002. When the first preset statistical period is reached, update the first single-path average value.

[0096] In embodiments of this application, as real-time data is continuously acquired, the time advances to a shorter statistical window. In some embodiments, whenever the time reaches a first preset statistical period, for example, after 1 second, the control module 20 summarizes the measurement data of that channel within this period, calculates and refreshes the first single-channel average value of the corresponding channel. This operation ensures that the 1-second average value can closely follow the changes in real-time measurement data.

[0097] S1003. After updating the first single-path average value, update the first multi-path total average value.

[0098] In embodiments of this application, the calculation of the global total average depends on the acquisition of individual channel data. In some embodiments, after updating the first individual channel average for all channels, the control module 20 immediately performs a comprehensive calculation on these latest individual channel data to refresh the first multi-channel total average in real time. This calculation order ensures that the data basis of the real-time total average is always up-to-date.

[0099] S1004. When the second preset statistical period is reached, update the second single-path average value.

[0100] In embodiments of this application, the timing calculation and update also includes a longer statistical window. In some embodiments, whenever the time reaches the second preset statistical period, such as 60 seconds after the system is powered on and at the end of each subsequent 1-minute period, the control module 20 recalculates and updates the second single-channel average value of each sensor under test 200 on the display screen 104 based on the single-channel measurement data collected within this long period.

[0101] S1005. After updating the second single-path average, update the second multi-path total average.

[0102] In embodiments of this application, long-cycle global data is refreshed after long-cycle single-channel data is confirmed. In some embodiments, within each 1-minute cycle, the long-cycle total average calculated in the previous cycle is displayed first; after all second single-channel averages for the current cycle have been calculated, the control module 20 recalculates and updates the second multi-channel total average. The above update order takes into account both timeliness and accuracy.

[0103] This application employs a hierarchical refresh strategy, sequentially updating measurement data, single-channel average values, and multi-channel total average values ​​according to different cycle sequences. This method balances the real-time nature of data monitoring with the accuracy of long-term statistics, resulting in a clear and organized display of test data and providing a reliable data update process for the performance evaluation of a batch of 200 sensors under test.

[0104] Please see Figure 1 and Figure 5 The multi-channel sensor testing device 300 of this application embodiment is applied to the multi-channel sensor testing apparatus 100 of any of the above embodiments. The multi-channel sensor testing device 300 includes: Module 310 is used to establish a communication connection with the accessed multi-channel sensor under test 200; The acquisition module 320 is used to acquire measurement data from each of the sensors under test 200 in parallel. Evaluation module 330 is used to evaluate the data consistency among multiple sensors under test 200 based on measurement data.

[0105] This application's implementation achieves synchronous, automated batch testing of multiple sensors by acquiring multiple measurement data channels in parallel and evaluating the data consistency among the 200 sensors under test. This method effectively identifies abnormal channels and triggers alarms, improving testing efficiency and data comparison accuracy.

[0106] In some embodiments, the multi-channel sensor testing device 300 further includes a determination module for: The sensor type of the multiple-channel sensor under test 200 is determined according to the type selection instruction; Module 310 is specifically used for: Configure the communication protocol parameters corresponding to the sensor type to establish a communication connection with the multiple sensors under test 200.

[0107] This application's implementation dynamically identifies the sensor type based on a type selection command and automatically configures the corresponding communication protocol parameters, enabling flexible switching between gas sensor and particulate matter sensor testing modes. This method allows a single device to meet the testing needs of both types of sensors, avoiding the cumbersome process of changing different testing equipment and reducing equipment investment costs.

[0108] In some implementations, the evaluation module 330 is specifically used for: Based on the measurement data of each sensor under test 200, the average value of each sensor under test 200 within the preset statistical period is calculated. Based on the measurement data of the multiple sensors under test 200, the total average value of the multiple sensors under test 200 within a preset statistical period is calculated. Based on the deviation between the single-channel average value and the total average value of multiple channels, determine whether the data consistency of each sensor under test 200 within the preset statistical period is qualified.

[0109] This application's implementation method achieves quantitative analysis of the measurement performance of multiple sensors under test (SUT) 200 by calculating the average value of a single channel and the total average value of multiple channels, and by evaluating the consistency based on the deviation between the two. This method effectively reduces the interference from fluctuations in single instantaneous data, providing reliable data processing capabilities for accurately identifying abnormal sensor channels.

[0110] In some implementations, the evaluation module 330 is specifically used for: The benchmark value for consistency determination is determined based on the total average value of multiple paths; Determine whether the average value of each channel of the sensor under test 200 is within the preset proportional threshold range centered on the reference value; If the average value of a single channel is within the preset proportional threshold range, the data consistency of the sensor 200 under test in the corresponding channel is deemed to be qualified. If the average value of a single channel exceeds the preset proportional threshold range, the data consistency of the sensor 200 under test in the corresponding channel within the preset statistical period is deemed unqualified.

[0111] This application's implementation method, by setting a benchmark value and a preset proportional threshold range, determines the range of single-channel average values, achieving a precise quantitative assessment of sensor data consistency. This method provides an objective basis for qualification judgment, accurately and efficiently identifying abnormal sensors whose measurement performance deviates from the overall test benchmark.

[0112] In some implementations, the evaluation module 330 is specifically used for: Based on the measurement data of each sensor under test 200, the first single-channel average value and the second single-channel average value of each sensor under test 200 in the first preset statistical period and the second preset statistical period are calculated respectively. Based on the measurement data of the multiple sensors under test 200, the first total average value of the multiple sensors under test 200 in the first preset statistical period and the second total average value of the multiple sensors under test 200 in the second preset statistical period are calculated. Based on the first deviation between the first single-channel average value and the first multi-channel total average value, determine whether the data consistency of each sensor under test 200 within the first preset statistical period is qualified; Based on the second deviation between the second single-channel average value and the second multi-channel total average value, determine whether the data consistency of each sensor under test 200 within the second preset statistical period is qualified. The duration of the second preset statistical period is longer than that of the first preset statistical period.

[0113] This application's implementation method introduces two preset statistical periods, one long and one short, to calculate the single-channel average and the multi-channel total average, and performs dual deviation judgment. This scheme balances the timeliness of data monitoring with the accuracy of test evaluation, effectively filters out misjudgments caused by instantaneous data fluctuations, and improves the reliability of multi-channel sensor testing.

[0114] In some embodiments, the multi-channel sensor testing device 300 further includes a display module for: Displays measurement data from each of the sensors under test 200, including the first single-channel average value, the second single-channel average value, the first multi-channel total average value, the second multi-channel total average value, the first deviation case, and the second deviation case, among any one or more of these.

[0115] This application's implementation method achieves comprehensive visualization of multi-channel parallel test data by comprehensively presenting measurement data, multi-cycle single-channel average values, multi-cycle multi-channel total average values, and corresponding deviations on the display screen 104. This method allows testers to intuitively monitor the working status and consistency performance of all sensors under test 200.

[0116] In some implementations, the multi-channel sensor testing apparatus 300 further includes an update module for: Real-time updates of measurement data from each of the 200 sensors under test; When the first preset statistical period is reached, the first single-path average value is updated; After updating the first single-path average, update the first multi-path total average. When the second preset statistical period is reached, the second single-path average value is updated; After updating the second single-path average, update the second multi-path total average.

[0117] This application employs a hierarchical refresh strategy, sequentially updating measurement data, single-channel average values, and multi-channel total average values ​​according to different cycle sequences. This method balances the real-time nature of data monitoring with the accuracy of long-term statistics, resulting in a clear and organized display of test data and providing a reliable data update process for the performance evaluation of a batch of 200 sensors under test.

[0118] It should be noted that the explanation of the multi-channel sensor testing method in the foregoing embodiments also applies to the multi-channel sensor testing device 300 in the embodiments of this application, and will not be elaborated here.

[0119] Please see Figure 6 The multi-channel sensor testing system 400 of this application includes one or more processors 410 and a memory 420, wherein the memory 420 stores a computer program. When the computer program is executed by the processor 410, the multi-channel sensor testing method of any of the above embodiments is implemented.

[0120] For example, when the computer program is executed by the processor 410, the following multi-sensor testing method is implemented: S401. Establish a communication connection with the connected multi-channel sensor under test 200; S402, Parallel acquisition of measurement data from each of the sensors under test 200; S403. Evaluate the data consistency among multiple sensors under test 200 based on measurement data.

[0121] For example, when the computer program is executed by the processor 410, the following multi-sensor testing method is implemented: S501. Determine the sensor type of the multiple-channel sensor under test 200 connected according to the type selection instruction; S502. Configure the communication protocol parameters corresponding to the sensor type to establish a communication connection with the multiple sensors under test 200.

[0122] It should be noted that the explanation of the multi-channel sensor testing method in the foregoing embodiments also applies to the multi-channel sensor testing system 400 in the embodiments of this application, and will not be elaborated here.

[0123] Please see Figure 7 The computer-readable storage medium 500 of this application embodiment stores a computer program 510 thereon. When the program is executed by the processor 520, the multi-channel sensor testing method of any of the above embodiments is implemented.

[0124] For example, when the program is executed by processor 520, the following multi-sensor testing method is implemented: S401. Establish a communication connection with the connected multi-channel sensor under test 200; S402, Parallel acquisition of measurement data from each of the sensors under test 200; S403. Evaluate the data consistency among multiple sensors under test 200 based on measurement data.

[0125] For example, when the program is executed by processor 520, the following multi-sensor testing method is implemented: S501. Determine the sensor type of the multiple-channel sensor under test 200 connected according to the type selection instruction; S502. Configure the communication protocol parameters corresponding to the sensor type to establish a communication connection with the multiple sensors under test 200.

[0126] It should be noted that the explanation of the multi-sensor testing method in the foregoing embodiments also applies to the computer-readable storage medium 500 in the embodiments of this application, and will not be elaborated here.

[0127] In summary, the multi-channel sensor testing device 100, multi-channel sensor testing method, multi-channel sensor testing equipment 300, multi-channel sensor testing system 400, and computer-readable storage medium 500 of this application, firstly, by setting up the sensor interface module 10, multiple sensors under test 200 can be connected in parallel, breaking the efficiency bottleneck of traditional single-channel testing, enabling parallel batch testing of multiple channels, and greatly improving the testing efficiency of the production line; secondly, it supports the connection of gas sensors or particulate matter sensors, which can meet the testing needs of two different types of sensors, effectively expanding the applicability of the equipment and significantly reducing equipment investment and maintenance costs; thirdly, by setting up the control module 20 to establish a communication connection with the multiple sensors under test 200, it is possible to collect measurement data from each channel in parallel, and evaluate the data consistency between multiple sensors based on these measurement data, obtain the consistency status of sensors in the same batch in real time, and identify abnormal channels, significantly improving the accuracy and intelligence level of sensor performance evaluation.

[0128] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0129] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the function involved, as will be understood by those skilled in the art to which embodiments of this application pertain.

[0130] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable storage medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, a computer-readable storage medium can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable storage medium could be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0131] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0132] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it includes one or a combination of the steps of the method embodiments. Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc.

[0133] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application, the scope of which is defined by the claims and their equivalents.

Claims

1. A multi-channel sensor testing device, characterized in that, include: The sensor interface module is configured to connect multiple sensors under test in parallel to provide operating power to the multiple sensors under test, including gas sensors or particulate matter sensors. The control module is configured to establish a communication connection with the accessed multiple sensors under test to acquire measurement data from each of the sensors under test in parallel, and to evaluate the data consistency among the multiple sensors under test based on the measurement data.

2. The multi-channel sensor testing device according to claim 1, characterized in that, The multi-channel sensor testing device also includes a button module, which is configured to receive a type selection command for the gas sensor or the particulate sensor. The control module is further configured to: determine the sensor type of the multiple sensors under test according to the type selection instruction, and configure the communication protocol parameters corresponding to the sensor type to establish a communication connection with the multiple sensors under test.

3. The multi-channel sensor testing device according to claim 1, characterized in that, The multi-channel sensor testing device also includes a power supply module, a level conversion module, and a communication conversion circuit. The multiple sensors under test are electrically connected to the power module through the sensor interface module and the level conversion module to obtain the working power. The control module establishes communication connections with the multiple sensors under test via the communication conversion circuit to collect measurement data from each sensor in parallel.

4. A multi-channel sensor testing method, characterized in that, The multi-channel sensor testing apparatus according to any one of claims 1-3, wherein the multi-channel sensor testing method comprises: Establish communication connections with the multiple sensors under test that are connected; The measurement data of each of the sensors under test are acquired in parallel; The data consistency among the multiple sensors under test is evaluated based on the measurement data.

5. The multi-channel sensor testing method according to claim 4, characterized in that, The multi-channel sensor testing method also includes: The sensor type of the multiple sensors under test is determined according to the type selection instruction; Establishing a communication connection with the accessed multiple sensors under test includes: Configure communication protocol parameters corresponding to the sensor type to establish a communication connection with the multiple sensors under test.

6. The multi-channel sensor testing method according to claim 4, characterized in that, The evaluation of data consistency among the multiple sensors under test based on the measurement data includes: Based on the measurement data of each of the sensors under test, the average value of each sensor under test within a preset statistical period is calculated. Based on the measurement data of the multiple sensors under test, the total average value of the multiple sensors under test within the preset statistical period is calculated; Based on the deviation between the single-channel average value and the multi-channel total average value, determine whether the data consistency of each of the sensors under test within the preset statistical period is qualified.

7. The multi-channel sensor testing method according to claim 6, characterized in that, The step of determining whether the data consistency of each of the sensors under test within the preset statistical period is qualified based on the deviation between the single-channel average value and the multi-channel total average value includes: Based on the total average value of the multiple paths, a benchmark value for consistency determination is determined; Determine whether the single-channel average value of each of the sensors under test is within a preset proportional threshold range centered on the reference value; If the single-channel average value is within the preset ratio threshold range, then the data consistency of the sensor under test in the corresponding channel is determined to be qualified. If the single-channel average value exceeds the preset ratio threshold range, then the data consistency of the sensor under test in the corresponding channel within the preset statistical period is determined to be unqualified.

8. The multi-channel sensor testing method according to claim 6, characterized in that, The step of calculating the single-channel average value of each of the sensors under test within a preset statistical period based on the measurement data of each channel includes: Based on the measurement data of each of the sensors under test, the first single-channel average value and the second single-channel average value of each sensor under test in the first preset statistical period and the second preset statistical period are calculated respectively. The step of calculating the total average value of the multiple sensors under test within the preset statistical period based on the measurement data of the multiple sensors under test includes: Based on the measurement data of the multiple sensors under test, the first total average value of the multiple sensors under test in the first preset statistical period and the second total average value of the multiple sensors in the second preset statistical period are calculated. The step of determining whether the data consistency of each of the sensors under test within the preset statistical period is qualified based on the deviation between the single-channel average value and the multi-channel total average value includes: Based on the first deviation between the first single-channel average value and the first multi-channel total average value, determine whether the data consistency of each of the sensors under test within the first preset statistical period is qualified. Based on the second deviation between the second single-channel average value and the second multi-channel total average value, determine whether the data consistency of each of the sensors under test within the second preset statistical period is qualified; The duration of the second preset statistical period is longer than the duration of the first preset statistical period.

9. The multi-channel sensor testing method according to claim 8, characterized in that, The multi-channel sensor testing method also includes: Displays any one or more of the following: measurement data of each of the sensors under test, the first single-channel average value, the second single-channel average value, the first multi-channel total average value, the second multi-channel total average value, the first deviation case, and the second deviation case.

10. The multi-channel sensor testing method according to claim 8, characterized in that, The multi-channel sensor testing method also includes: The measurement data of each of the sensors under test are updated in real time. When the first preset statistical period is reached, the first single-path average value is updated; After updating the first single-path average, update the first multi-path total average; When the second preset statistical period is reached, the second single-path average value is updated; After updating the second single-path average, update the second multi-path total average.

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