A self-aware road surface sensor full life cycle reliability evaluation system

Abstract

This invention relates to the field of sensor reliability assessment technology, specifically to a full lifecycle reliability assessment system for a self-sensing road surface sensor. The system includes: an operating signal acquisition module that obtains an effective voltage sequence through differential denoising; a deviation accumulation construction module that converts the sequence into a continuous deviation drift trajectory; a threshold self-induction calibration module that updates the judgment threshold in real time based on the drift trend; a fluctuation section identification module that compares instantaneous fluctuations with adaptive tolerance to extract stable operating sections; and a lifecycle reliability assessment module that determines the relationship between accumulated deviation and the threshold, dividing the lifecycle into stages. This invention, through precise sampling and voltage difference analysis, removes invalid data and retains valid information, accurately tracks sensor status and identifies drift trends, employs an adaptive adjustment mechanism to cope with performance fluctuations, improves overall reliability, accurately divides stable operating cycles, achieves detailed reliability assessment, and promptly identifies performance degradation stages, thereby realizing a scientific assessment of the sensor's entire lifecycle.

Description

Technical Field

[0001] This invention relates to the field of sensor reliability assessment technology, and in particular to a full life cycle reliability assessment system for a self-sensing road surface sensor. Background Technology

[0002] The field of sensor reliability assessment technology encompasses sensor operational status recording, lifecycle information management, and reliability status analysis. This technology primarily focuses on the systematic management and evaluation of sensor operational information during long-term use. Its core content involves continuously recording and organizing data generated during the sensor's manufacturing, installation, and operation phases, and periodically analyzing sensor reliability based on historical operational information and phase-specific status divisions. This results in a comprehensive reliability assessment system covering the design, deployment, and operation phases.

[0003] Specifically, the self-sensing road surface sensor lifecycle reliability assessment system is a technical system used to record and evaluate the reliability status of embedded road surface sensors throughout their service life. It involves recording sensor installation information, operational status information, and collecting historical operational data. Combined with initial sensor calibration information and operational phase data, it comprehensively organizes relevant information from the sensor's manufacturing completion, on-site installation, and operation and maintenance phases. Its technical aspects cover sensor basic information registration, operational time recording, historical status recording, and fault event recording. Through data archiving, chronological recording, and operational phase division, it assesses the reliability status of the road surface sensor throughout its entire lifecycle.

[0004] Existing technologies primarily focus on information registration, historical data archiving, and periodic status organization. While these technologies can effectively preserve data throughout the sensor's entire lifecycle, they lack detailed analysis of fluctuations, deviations, and performance degradation processes in operating signals. In practical applications, these technologies tend to conflate environmental interference, random noise, and performance degradation, leading to over-reliance on post-hoc statistics for reliability analysis. This hinders the timely identification of early inaccuracies and gradual degradation, thus affecting the accuracy of lifespan assessment, maintenance timing, and operational status evaluation. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a full life-cycle reliability assessment system for self-sensing road surface sensors.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a self-sensing road surface sensor full life cycle reliability assessment system, the system comprising: The signal acquisition module receives sensor voltages, forms a sequence of adjacent voltage differences and converts them to absolute values, filters out invalid periods by comparing them with a preset noise voltage range, retains effective voltage amplitudes and arranges them continuously to form a sequence of effective operating amplitudes of the sensor. Deviation accumulation construction module: Based on the effective operating amplitude sequence of the sensor, the voltage amplitude is obtained and the deviation is generated by corresponding to the preset calibration reference voltage. The drift trend is distinguished by the increase or decrease of adjacent deviations, and the cumulative deviation change is expanded along the time sequence to form a deviation drift accumulation trajectory. Threshold self-sensing calibration module: Based on the cumulative trajectory of deviation drift, the cumulative deviation corresponds to the preset initial deviation threshold. It shows a drift trend according to the direction of deviation. When it expands in the positive direction, the drift judgment threshold is raised, and when it falls back in the reverse direction, the drift judgment threshold is lowered. It continuously updates the drift judgment threshold for each sampling period to form an adaptive drift judgment threshold sequence. Fluctuation segment identification module: It obtains the instantaneous fluctuation state from the effective operating amplitude sequence of the sensor, converts the drift judgment threshold into the corresponding amplitude fluctuation tolerance range, and generates a stable operating cycle by comparing and defining the start and end of the stable extension stage, thus forming a set of stable operating segments.

[0007] As a further aspect of the present invention, the system also includes a life reliability assessment module, specifically: Lifetime reliability assessment module: The stable operating cycle is established by the set of stable operating segments, so that the cumulative deviation and the drift judgment threshold are correlated in time. Based on the conditions, the stable operating stage and the performance degradation stage are divided, and the stages are continuously connected to form the sensor lifetime stage division result.

[0008] As a further embodiment of the present invention, the operating signal acquisition module includes a voltage receiving submodule, a difference noise detection submodule, and an amplitude arrangement submodule: Voltage receiving submodule: Receives the output voltage value of the piezoelectric sensor on the road surface, reads the time identifier corresponding to the continuous sampling period and records the voltage value of each sampling period in time stamp order, arranges the voltage value of each sampling period with the corresponding sampling time identifier, and writes it continuously into the sequence unit according to the sampling order to form a voltage arrangement state unfolded according to the sampling period, and obtains the original voltage change sequence. Noise verification submodule: Based on the original voltage change sequence, read the voltage records arranged before and after adjacent sampling periods, organize them into voltage difference records between consecutive sampling periods, perform amplitude-based processing on each voltage difference record, verify each amplitude-based voltage difference record against the preset noise voltage range, retain the voltage difference records corresponding to the sampling periods that exceed the preset noise voltage range, and remove the voltage difference records corresponding to the sampling periods that fall within the preset noise voltage range to obtain the effective period range; Amplitude arrangement submodule: Based on the effective period range, retrieve the voltage amplitude corresponding to each sampling period within the effective period range, write it sequentially into the amplitude arrangement unit according to the sampling time order, connect each reserved voltage amplitude record along the time sequence, and perform sequential connection for the missing positions to establish the effective operating amplitude sequence of the sensor.

[0009] As a further aspect of the present invention, the deviation accumulation construction module includes a deviation correspondence submodule, a trend identification submodule, and an accumulation extension submodule: Deviation Correspondence Submodule: Based on the effective operating amplitude sequence of the sensor, the voltage amplitude of each sampling period is called and expanded in the order of sampling time. The preset calibration reference voltage is retrieved and matched with the voltage amplitude of each sampling period item by item. The voltage amplitude position and the reference voltage position under the same sampling period are written into the corresponding mark unit. The corresponding contents in each mark unit are arranged in sequence along the sampling order to form the deviation correspondence quantity. Trend identification submodule: Based on the deviation corresponding amount, read the corresponding deviation amount arranged before and after adjacent sampling periods, verify the direction of change of each corresponding deviation amount before and after along the sampling time sequence, classify the upward extension record into the positive drift mark area, classify the downward fall record into the reverse drift mark area, and arrange each drift mark area continuously according to the sampling time sequence to obtain the drift direction sequence. The cumulative extension submodule: Based on the drift pointing sequence, it calls the drift marker corresponding to the same sampling period and retrieves the corresponding amount of deviation of the previous sampling period. Combined with the drift marker corresponding to the current sampling period, it determines the deviation change content of each sampling period. It continues the deviation change content of each sampling period in the order of sampling time, and merges the deviation change content of subsequent sampling periods into the corresponding arrangement position of the previous sampling period in sequence. It then arranges the deviation content of each sampling period continuously according to the sampling order to establish the deviation drift accumulation trajectory.

[0010] As a further aspect of the present invention, the threshold self-sensing calibration module includes a threshold correspondence submodule, a direction threshold adjustment submodule, and a sequence update submodule: Threshold Correspondence Submodule: Based on the deviation drift accumulation trajectory, read the accumulated deviation content of each sampling period, retrieve the preset initial deviation threshold, and correspond the accumulated deviation content of each sampling period with the preset initial deviation threshold item by item according to the sampling time sequence and write it into the threshold mark position. Then, arrange the sampling period threshold records written into the threshold mark positions in sequence along the sampling time to form a drift judgment threshold column. Directional threshold adjustment submodule: Based on the drift judgment threshold column, read the cumulative deviation content arranged before and after each sampling period, verify the direction of the deviation increment along the time series, classify the records extending towards the preset threshold trigger range into the positive drift area, classify the records in the falling direction into the negative drift area, perform upward adjustment on the current drift judgment threshold corresponding to the sampling period of the positive drift area, and perform downward adjustment on the current drift judgment threshold corresponding to the sampling period of the negative drift area to obtain the threshold adjustment result column; Sequence Update Submodule: Based on the threshold adjustment result column, read the drift judgment threshold content corresponding to each sampling period, write it into the corresponding period arrangement position in the order of sampling time, continue the drift judgment threshold content of the previous sampling period and the drift judgment threshold content of the next sampling period, continuously update the drift judgment threshold records of each sampling period along the sampling time sequence, and sequentially arrange the drift judgment threshold content of each sampling period to establish an adaptive drift judgment threshold sequence.

[0011] As a further aspect of the present invention, the fluctuation segment identification module includes a fluctuation formation submodule, a tolerance mapping submodule, a stage discrimination submodule, and a segment consolidation submodule: The fluctuation formation submodule reads the voltage amplitude content arranged before and after adjacent sampling periods based on the effective operating amplitude sequence of the sensor, connects the voltage amplitude content of the previous position and the voltage amplitude content of the next position according to the sampling time sequence, organizes the relationship of continuous voltage amplitude change, verifies the fluctuation direction for the voltage amplitude change state before and after each sampling period, and writes the voltage amplitude change content corresponding to each sampling period into the time sequence arrangement position in sequence to obtain the instantaneous fluctuation sequence. Tolerance mapping submodule: Based on the instantaneous fluctuation sequence, it calls the drift judgment threshold content of each sampling period in the adaptive drift judgment threshold sequence, converts the drift judgment threshold of each sampling period into the corresponding amplitude fluctuation tolerance range according to the sampling time order, writes the amplitude fluctuation tolerance range of each sampling period into the corresponding time sequence position, and arranges the amplitude fluctuation tolerance range of each sampling period in sequence along the sampling order to obtain the tolerance interval column; Stage discrimination submodule: Based on the tolerance interval column, read the amplitude fluctuation tolerance range content and the corresponding instantaneous fluctuation amplitude content in the instantaneous fluctuation sequence under the same sampling period, verify the instantaneous fluctuation amplitude content item by item along the continuous sampling period to see if it is within the amplitude fluctuation tolerance range, write the sampling period within the amplitude fluctuation tolerance range into the extended arrangement position, and set the sampling period exceeding the amplitude fluctuation tolerance range as the stage breakpoint to establish a stable operation cycle; The segment aggregation submodule reads the starting sampling period position and the stage breakpoint sampling period position for each stable operating cycle, continues the corresponding interval records of the same stable operating cycle in the order of sampling time, writes multiple stable operating cycles into the time sequence arrangement position in sequence, arranges the interval content of the previous stable operating cycle and the interval content of the next stable operating cycle in sequence, and organizes the distribution content of each stable operating cycle interval along the sampling time sequence to establish a set of stable operating segments.

[0012] As a further aspect of the present invention, the lifetime reliability assessment module includes a segment timing submodule, a threshold alignment submodule, a stage boundary submodule, and a timing arrangement submodule: The segment timing submodule reads the start and end sampling positions of each stable operating segment in the set of stable operating segments based on the set of stable operating segments. It then continues the content of the previous and subsequent stable operating segments in the order of time segments, organizes the corresponding start and end ranges of each stable operating segment, verifies the continuity status of each stable operating segment for the start and end ranges of each stable operating segment, and writes the continuity content of each stable operating segment into the time sequence arrangement position to obtain the segment continuity period. Off-threshold alignment submodule: Based on the duration of the segment, it calls the accumulated deviation content of the same time segment in the deviation drift accumulation trajectory, retrieves the drift judgment threshold content of the same sampling period in the adaptive drift judgment threshold sequence, writes the accumulated deviation content and drift judgment threshold content into the corresponding sampling position according to the time segment order, and continuously arranges the corresponding records of each sampling period along the time sequence of each stable operating segment to obtain the time period corresponding column; Phase Boundary Submodule: Based on the corresponding column of the time period, read the cumulative deviation content within the continuous period of each stable segment and the drift judgment threshold content of the same sampling period, verify the cumulative deviation in the range below the drift judgment threshold and the state above the drift judgment threshold along the time segment, write the sampling period with the cumulative deviation below the drift judgment threshold into the stable operation phase arrangement position, and write the sampling period with the cumulative deviation above the drift judgment threshold into the performance degradation phase arrangement position to establish a phase distribution column; The timing arrangement submodule reads the starting record content in the stable operation stage arrangement position and the subsequent record content in the performance degradation stage arrangement position for the stage distribution column. It connects the previous stage record content and the subsequent stage record content in chronological order, writes the stage records in the same stable operation segment into the timing arrangement position in sequence, and arranges the distribution content of each stage continuously along the stable operation segment to establish the sensor lifespan stage division result.

[0013] As a further aspect of the present invention, in the noise verification submodule, when verifying the amplitude-scaled voltage difference records against the preset noise voltage range item by item, a sliding window statistical discrimination method is adopted.

[0014] As a further embodiment of the present invention, in the tolerance mapping submodule, when converting the drift judgment threshold of each sampling period into the corresponding amplitude fluctuation tolerance range according to the sampling time sequence, a hierarchical tolerance mapping method is adopted.

[0015] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, by using precise sampling and voltage difference analysis, invalid data can be removed while retaining valid information related to sensor operation, thus improving data quality. It can also accurately track sensor status and identify performance drift trends, providing a dynamic basis for subsequent adjustments. Through an adaptive adjustment mechanism, it can cope with sensor performance fluctuations, improving overall reliability. Furthermore, by using precise division of stable operating cycles, the reliability assessment of the sensor becomes more detailed, enabling timely identification of performance degradation stages and providing support for early warning and maintenance. This achieves a scientific and accurate assessment throughout the entire lifecycle. Attached Figure Description

[0016] Figure 1 This is a system flowchart of the present invention; Figure 2 This is a flowchart illustrating the acquisition process of the signal acquisition module in this invention. Figure 3 This is a flowchart illustrating the process of obtaining the deviation accumulation construction module of the present invention; Figure 4 This is a flowchart illustrating the acquisition process of the threshold self-sensing calibration module of the present invention. Figure 5 This is a flowchart illustrating the acquisition process of the fluctuation segment identification module of the present invention. Figure 6 This is a flowchart illustrating the acquisition process of the lifetime reliability assessment module of this invention. Detailed Implementation

[0017] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0018] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0019] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0020] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0021] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0022] Example 1 Please see Figure 1 This embodiment provides a technical solution: a self-sensing road surface sensor full life cycle reliability assessment system, the system comprising: The signal acquisition module receives the voltage value output by the piezoelectric sensor on the road surface, forms an original voltage change sequence with the continuous sampling period as the time reference, forms a corresponding voltage difference sequence between adjacent sampling periods, and performs absolute value conversion on each amplitude of the voltage difference sequence and compares it with the preset noise voltage range. The sampling period that exceeds the noise voltage range enters the effective sequence range, while the sampling period that is within the noise voltage range leaves the sequence range. The voltage amplitudes within the effective range are retained in time sequence and arranged continuously, thus forming the effective operating amplitude sequence of the sensor. Deviation accumulation construction module: Based on the effective operating amplitude sequence of the sensor, the amplitude of each sampling period forms a corresponding deviation with the preset calibration reference voltage. The deviation increases or decreases between adjacent sampling periods. The direction of deviation change distinguishes between positive and negative drift trends. The deviation change continues to expand along the sampling time sequence, so that each sampling period forms a continuous and progressive deviation accumulation state, forming a deviation drift accumulation trajectory. Threshold self-sensing calibration module: Based on the cumulative deviation trajectory, the module establishes a correspondence between the cumulative deviation of each sampling period and the preset initial deviation threshold. As the cumulative deviation gradually expands towards the preset threshold trigger range along the time sequence, the direction of the deviation increment shows a drift trend. When the drift trend shows a positive expansion, the drift judgment threshold of the corresponding sampling period is increased. When the drift trend shows a reverse decline, the drift judgment threshold of the corresponding sampling period is decreased. This ensures that the drift judgment thresholds corresponding to each sampling period are continuously updated and arranged sequentially along the sampling time order, forming an adaptive drift judgment threshold sequence. Fluctuation Segment Identification Module: Based on the effective operating amplitude sequence of the sensor, a continuous amplitude change relationship is formed between the amplitudes of adjacent sampling periods, and the amplitude change presents an instantaneous fluctuation state. At the same time, the drift judgment threshold of each sampling period in the adaptive drift judgment threshold sequence is converted into the corresponding amplitude fluctuation tolerance range. Under the same sampling period, the instantaneous fluctuation amplitude is compared with the amplitude fluctuation tolerance range. When the instantaneous fluctuation amplitude in the continuous sampling period is within the amplitude fluctuation tolerance range, it enters the stable extension stage. When the instantaneous fluctuation amplitude exceeds the amplitude fluctuation tolerance range, the stable extension stage ends. According to the sampling time sequence, the corresponding stable operating period is formed from the start position to the end position of the stable extension stage. Multiple stable operating periods are continuously distributed along the time sequence to form a set of stable operating segments. Lifetime reliability assessment module: Using a set of stable operating segments as the basis for time segments, each stable segment corresponds to a segment duration period. Within the same time segment, the cumulative deviation in the deviation drift accumulation trajectory is correlated with the drift judgment threshold of the same sampling period in the adaptive drift judgment threshold sequence. Within the duration period of a stable segment, a stable operating phase is formed when the cumulative deviation is below the drift judgment threshold, and a performance degradation phase is formed when the cumulative deviation exceeds the drift judgment threshold. The stable operating phase and the performance degradation phase are continuously connected and arranged in chronological order to form the sensor lifetime stage division result.

[0023] Please see Figure 2 This embodiment also provides an implementation method for the running signal acquisition module. Specifically, the running signal acquisition module includes a voltage receiving submodule, a differential noise detection submodule, and an amplitude arrangement submodule. Voltage receiving submodule: Receives the output voltage value of the piezoelectric sensor on the road surface, reads the time identifier corresponding to the continuous sampling period and records the voltage value of each sampling period in time stamp order, arranges the voltage value of each sampling period with the corresponding sampling time identifier, and writes it continuously into the sequence unit according to the sampling order to form a voltage arrangement state unfolded according to the sampling period, and obtains the original voltage change sequence. Specifically, it receives the output voltage value from the piezoelectric sensor on the road surface, calls the built-in high-speed analog-to-digital converter to capture the analog signal transmitted by the sensor at equal intervals, and sets the sampling period. It is 0.01s, according to The timeline sequence timestamps each voltage data point. The voltage value is constantly read as 1.25V. The voltage value is constantly read as 1.28V. The system continuously reads a voltage value of 1.26V. It then pairs and binds the read values ​​of 1.25V, 1.28V, and 1.26V with their corresponding time markers of 0.01s, 0.02s, and 0.03s. The paired data groups are then sequentially written into the system's FIFO circular memory unit, ensuring data flows smoothly within the storage space. The order of the data is arranged in a linear linked list, and a continuous voltage data stream reflecting the real-time pressure state of the road surface is constructed in the memory to obtain the original voltage change sequence.

[0024] Noise verification submodule: Based on the original voltage change sequence, read the voltage records arranged before and after adjacent sampling periods, organize them into voltage difference records between consecutive sampling periods, perform amplitude-based processing on each voltage difference record, verify each amplitude-based voltage difference record against the preset noise voltage range, retain the voltage difference records corresponding to the sampling periods that exceed the preset noise voltage range, and remove the voltage difference records corresponding to the sampling periods that fall within the preset noise voltage range to obtain the effective period range; When verifying each voltage difference record after amplitudeization against the preset noise voltage range, a sliding window statistical discrimination method is adopted. Based on the original voltage change sequence, extract and The voltage records of two adjacent nodes are used as follows: , Perform a subtraction operation and take the absolute value of the result; For example when It is 1.25V and When the voltage is 1.28V, the calculated voltage difference amplitude is 0.03V. The preset noise voltage range parameter is then applied to this amplitude. ,Should The settings are based on the environmental reference voltage fluctuations under no-load conditions, and the specific calculations refer to the standard deviation of 100 cycles under no-load conditions. 3 times, set The voltage is 0.05V. During the verification process, a sliding window statistical discrimination method with a length of 5 sampling periods is used to compare the average voltage difference amplitude within the window with... A numerical comparison is performed. If the mean value is greater than 0.05V, the sampling period corresponding to that interval is determined to be a valid trigger caused by vehicle running over it, and the voltage records corresponding to all sampling periods within that interval are retained. If the mean value within the window is less than or equal to 0.05V, it is determined to be environmental noise or electromagnetic interference, and the voltage difference data within that interval is removed from the sequence records. This step-by-step sliding comparison is used to... arrive The trigger paragraphs that meet the criteria are filtered out to obtain the effective period range.

[0025] Amplitude Arrangement Submodule: Based on the effective period range, retrieve the voltage amplitude corresponding to each sampling period within the effective period range, write it sequentially into the amplitude arrangement unit according to the sampling time order, connect the reserved voltage amplitude records along the time sequence, and perform sequential connection for missing positions to establish the effective operating amplitude sequence of the sensor; Based on the valid period range, retrieve and call the time stamps of each sampling period marked as "valid" during the noise verification phase, and extract the voltage amplitude data under the corresponding time stamp from the original storage unit, such as extracting the valid time period. to The 26 voltage amplitude points within are arranged according to... The original time logic order is rewritten into the new amplitude arrangement unit, and the write process is detected. and Temporal breakpoints caused by noise removal are directly... The starting address is logically connected to the ending address of the previous valid segment. The physical addresses of all the storage gaps left by invalid data are sequentially connected. The vehicle load signal, which was originally discretely distributed in the original sequence, is compressed into a denoised continuous data cluster, and the effective operating amplitude sequence of the sensor is established.

[0026] Example 2 Please see Figure 3 This embodiment uses effective voltage amplitude sequences and deviation analysis to construct the sensor's deviation accumulation trajectory, helping to assess whether the sensor has a drift problem. Specifically, the deviation accumulation construction module includes a deviation correspondence submodule, a trend identification submodule, and an accumulation extension submodule. Deviation Correspondence Submodule: Based on the effective operating amplitude sequence of the sensor, the voltage amplitude of each sampling period is called and expanded in the order of sampling time. The preset calibration reference voltage is retrieved and matched with the voltage amplitude of each sampling period item by item. The voltage amplitude position and the reference voltage position under the same sampling period are written into the corresponding mark unit. The corresponding contents in each mark unit are arranged in sequence along the sampling order to form the deviation correspondence quantity. Based on the effective operating amplitude sequence of the sensor, call to Voltage amplitude during the sampling period to ,exist The specific value retrieved at any given time is 1.35V. The specific value retrieved at all times is 1.38V, and the preset calibration reference voltage is retrieved simultaneously. ,Should The settings are based on the average calibrated output value of the sensor under factory conditions at a constant temperature of 20°C and a standard static pressure load of 10kN. The voltage is 1.40V. At time 1.35V and 1.40V, corresponding position matching is performed, and... At time 1.38V and 1.40V, a corresponding position matching is performed, and each matching relationship is written into the corresponding marker cell indexed by the memory address pointer. Stored in the corresponding tag unit The pairing data, in Stored in the corresponding tag unit The paired data is used to perform a linear connection of the logical addresses of the marker units loaded with the paired data along the sampling time axis, so that the voltage observation value of each sampling period can be aligned with its static reference value at the same timestamp, forming a deviation correspondence.

[0027] Trend identification submodule: Based on the corresponding deviation, read the corresponding deviation values ​​arranged before and after adjacent sampling periods, verify the direction of change of each corresponding deviation value along the sampling time sequence, classify the upward extension records into the positive drift mark area, classify the downward fall records into the reverse drift mark area, and arrange each drift mark area continuously according to the sampling time sequence to obtain the drift direction sequence. Based on the deviation correspondence, adjacent sampling periods are extracted. and The voltage observations and corresponding calibration reference voltages are obtained using: , Perform subtraction to obtain the real-time deviation value; For example in The deviation calculated at time is ; exist The deviation calculated at time is ; By executing: , Perform a second subtraction operation to verify the change direction; When the calculation result When 0.03V > 0V, the direction of change is determined to be an upward increase in value. This moment is marked as a positive drift direction and stored in the positive drift marker area. At that moment, the voltage dropped to 1.30V, causing the deviation to become -0.10V. for If 0.08V < 0V, then the direction of change is determined to be a downward decrease in value. This moment is marked as the reverse drift direction and stored in the reverse drift marker area. The value is then determined to be within... The interval is marked as zero-direction stable, and the obtained For positive The reverse and other marker information is written into the shift register in the order of sampling time to establish a dynamic indicator stream that reflects the overall migration trend of the sensor output level, thus obtaining the drift pointing sequence.

[0028] Cumulative Extension Submodule: Based on the drift pointing sequence, it calls the drift marker corresponding to the same sampling period and retrieves the corresponding amount of deviation in the previous sampling period. Combined with the drift marker corresponding to the current sampling period, it determines the deviation change content of each sampling period. It continues the deviation change content of each sampling period in the order of sampling time, and merges the deviation change content of subsequent sampling periods into the corresponding arrangement position of the previous sampling period in turn. It then arranges the deviation content of each sampling period continuously according to the sampling order to establish the deviation drift accumulation trajectory. Based on the drift pointing sequence, call The positive drift marker of the moment is used to synchronously retrieve the previous one. Extract the corresponding quantitative data of the deviation at time. The deviation value that has already occurred at this moment is -0.05V, which will be the current value. Instantaneous deviation increment at time: , Perform numerical calculations; The increment is obtained as ; Through the formula: , Perform cumulative operations; in This represents the cumulative deviation value for the current period. This is the cumulative deviation value from the previous period. This represents the amplitude of the current cycle. This is the amplitude of the previous cycle; exist At each step, the -0.05V from the previous moment is added to the current 0.03V to obtain -0.02V, and this result is used as... The cumulative deviation over time, when entering At time 1, the reverse drift marker is read, and the previous bit is retrieved. The accumulated value of -0.02V is combined with the increment of -0.08V generated at that moment and the result is obtained. The cumulative result at each moment is -0.10V. The values ​​calculated at each moment are then processed sequentially along the sampling time. The results are written sequentially to consecutive physical storage sectors. The dynamic deviation values ​​of subsequent sampling periods are then appended to the end of the historical offset records. By continuously superimposing the values ​​over time, the wandering path of the sensor output center value is simulated, and the deviation drift accumulation trajectory is established.

[0029] Example 3 Please see Figure 4 This embodiment describes the working principle of the threshold self-sensing calibration module. It dynamically adjusts the judgment threshold based on sensor drift, enabling the system to perform adaptive calibration according to the sensor's operating state. Specifically, the threshold self-sensing calibration module includes a threshold correspondence submodule, a direction threshold adjustment submodule, and a sequence update submodule. Threshold correspondence submodule: Based on the cumulative deviation trajectory, read the cumulative deviation content of each sampling period, retrieve the preset initial deviation threshold, match the cumulative deviation content of each sampling period with the preset initial deviation threshold item by item according to the sampling time sequence and write it into the threshold mark position, and arrange the sampling period threshold records written into the threshold mark positions in sequence along the sampling time to form the drift judgment threshold column. Extracting from the accumulated trajectory of deviation drift to Cumulative deviation value within the sampling period to ,exist The specific accumulated value is read as -0.05V at all times. The system continuously reads the accumulated value as -0.02V and simultaneously retrieves the preset initial deviation threshold from the system configuration register. ,Should The numerical setting is based on 15% of the allowable deviation range of the sensor's linearity, calculated in conjunction with the full-scale voltage of the piezoelectric sensor (5V). The voltage is 0.75V, so t 20 The cumulative deviation at each moment is recorded, and the time stamps of -0.05V and 0.75V are bound together and stored at address Addr. 20 The threshold marker position, t 21 The cumulative deviation at each moment is recorded. The time stamps for -0.02V and 0.75V are bound and stored at address Addr. 21 The threshold marker positions are stored in Addr in chronological order of sampling time. 20 To Addr 45 The 0.75V threshold parameters in each unit are linearly linked. By attaching the deviation data of each independent sampling period to a fixed initial judgment benchmark value, the subsequent threshold adjustment logic can retrieve the corresponding threshold records at each time point, forming a drift judgment threshold column.

[0030] Directional threshold adjustment submodule: Based on the drift judgment threshold column, it reads the cumulative deviation content arranged before and after each sampling period, verifies the direction of the deviation increment along the time series, classifies the records extending towards the preset threshold trigger range into the positive drift zone, and classifies the records in the falling direction into the negative drift zone. For the current drift judgment threshold corresponding to the sampling period in the positive drift zone, it performs upward adjustment, and for the current drift judgment threshold corresponding to the sampling period in the negative drift zone, it performs downward adjustment, and obtains the threshold adjustment result column; Specifically, based on the drift determination threshold column, extract... Cumulative deviation at time ; Cumulative deviation at time ; Perform subtraction: , The deviation increment was found to be 0.03V; Retrieve preset threshold trigger range Verify via comparison instructions The direction of the value is determined, and 0.03V is considered to be extending towards the positive threshold boundary of 0.75V. This record is then marked as a positive drift region. Time calculation If the value is -0.05V and falls in the direction of falling back towards the 0V central axis, then the record is marked as a reverse drift region. For records in the forward drift region... At any given time, the current threshold of 0.75V is invoked and the adjustment step size is incremented. The step size Based on the sensor's zero-point drift rate set to 0.01V, execute... The addition operation yields an increased V of 0.76, which is suitable for the region in the reverse drift region. At any time, execute The subtraction operation yields a reduced V of 0.74V, which is then verified by the numerical value. Is it within a reasonable threshold range? Within this process, the calculated new values ​​such as 0.76V and 0.74V are mapped to the corresponding sampling time nodes to obtain the threshold adjustment result column.

[0031] Sequence Update Submodule: Based on the threshold adjustment result column, read the drift judgment threshold content corresponding to each sampling period, write it into the corresponding period arrangement position in the order of sampling time, continue the drift judgment threshold content of the previous sampling period and the drift judgment threshold content of the next sampling period, continuously update the drift judgment threshold records of each sampling period along the sampling time sequence, and sequentially arrange the drift judgment threshold content of each sampling period to establish an adaptive drift judgment threshold sequence. Read from the register based on the threshold adjustment result column. The corresponding 0.75V, The corresponding 0.76V and The corresponding drift detection thresholds, such as 0.74V, are determined according to... The clock trigger sequence writes these values ​​sequentially into the corresponding physical address space of the adaptive sequence memory, and the pointer accesses them. The data content of the address bits is extracted and its terminal logical chain is obtained. The 0.76V content of the address bit is attached to the beginning of this logic chain, so that the threshold value of the previous sampling period and the updated value of the subsequent sampling period are sequentially connected in memory without gaps. During the 0.01s to 0.45s sampling period of the sensor operation, the originally static 0.75V fixed threshold is replaced bit by bit based on the real-time drift amount, and the value fluctuation is determined to be within the range of... During the interval, the value of the previous moment remains unchanged. The voltage judgment thresholds of each sampling period after dynamic correction are serialized and arranged in chronological order of sampling time to establish an adaptive drift judgment threshold sequence.

[0032] Example 4 Please see Figure 5 This embodiment identifies fluctuation segments based on the voltage amplitude sequence of the sensor and an adaptive drift determination threshold sequence, and determines their stability. Specifically, the fluctuation segment identification module includes a fluctuation formation submodule, a tolerance mapping submodule, a stage discrimination submodule, and a segment consolidation submodule. The fluctuation formation submodule reads the voltage amplitude content arranged before and after adjacent sampling periods based on the effective operating amplitude sequence of the sensor, connects the voltage amplitude content of the previous position and the voltage amplitude content of the next position according to the sampling time sequence, organizes the relationship of continuous voltage amplitude change, verifies the fluctuation direction for the voltage amplitude change status before and after each sampling period, and writes the voltage amplitude change content corresponding to each sampling period into the time sequence arrangement position in sequence to obtain the instantaneous fluctuation sequence. Extract from the effective operating amplitude sequence of the sensor to The voltage amplitude records stored during the sampling period, The amplitude is constantly adjusted to 1.35V. The amplitude is 1.38V at any given time, and this is achieved by reading two adjacent sampling periods. and The stored value is then subtracted: , Obtain the values ​​of each change, in The change in voltage was calculated to be 0.03V at any given time. Record the obtained 0.03V change with its corresponding sampling time identifier. Perform logical encapsulation, and arrange them according to the step sequence of the timeline. amplitude content and The amplitude content is associated with the physical address, and the difference trajectory between each node is extracted by traversing the entire valid sequence to verify it. The sign of the fluctuation is used to determine the direction of the fluctuation. A value greater than 0V is marked as an upward fluctuation. A value less than 0V is marked as a downward fluctuation, for example, in If the amplitude is read as 1.30V and the fluctuation is calculated to be -0.08V, it is classified as a decreasing fluctuation. The absolute value of the instantaneous change calculated for each sampling period is then recorded. The data and its pointer are sequentially written into a preset fluctuation data buffer, and then stored in the buffer according to... A differential data chain corresponding to the dynamic load of vehicles on the road surface is established in sequence to obtain the instantaneous fluctuation sequence.

[0033] Tolerance Mapping Submodule: Based on the instantaneous fluctuation sequence, it calls the drift judgment threshold content of each sampling period in the adaptive drift judgment threshold sequence, converts the drift judgment threshold of each sampling period into the corresponding amplitude fluctuation tolerance range according to the sampling time order, writes the amplitude fluctuation tolerance range of each sampling period into the corresponding time sequence position, and arranges the amplitude fluctuation tolerance range of each sampling period in sequence along the sampling order to obtain the tolerance interval column; When converting the drift judgment threshold of each sampling period into the corresponding amplitude fluctuation tolerance range according to the sampling time sequence, a hierarchical tolerance mapping method is adopted; Based on the instantaneous fluctuation sequence, retrieve from the adaptive drift determination threshold sequence to Dynamic thresholds for each sampling period ,exist The update threshold of 0.76V calculated above is retrieved at all times. The reduced threshold of 0.74V is retrieved at all times, and this voltage offset threshold is converted into a dynamic fluctuation tolerance boundary through a mapping operation. Set the conversion ratio coefficient It is 0.5. The value is preset based on the ratio of the dynamic response sensitivity to the static drift rate of the piezoelectric ceramic sensor, by utilizing: , Perform multiplication to calculate the tolerance range; exist Time calculation ; exist Time calculation ; The calculated values ​​of 0.38V and 0.37V are used as the amplitude fluctuation tolerance limits for the corresponding period. These tolerance values ​​and their corresponding values ​​are then used to determine the tolerance range limits. The interval range is written into the system memory's tolerance-addressed space in the order of sampling time, so that the instantaneous fluctuation at each timestamp is associated with a judgment benchmark that is dynamically adjusted according to the sensor's zero-point drift state. The interval range is then written into the system memory's tolerance-addressed space in the order of sampling. The values ​​are arrayed to obtain the tolerance range column.

[0034] Stage discrimination submodule: Based on the tolerance interval column, read the amplitude fluctuation tolerance range content and the corresponding instantaneous fluctuation amplitude content in the instantaneous fluctuation sequence under the same sampling period, and verify whether the instantaneous fluctuation amplitude content is within the amplitude fluctuation tolerance range item by item along the continuous sampling period. The sampling period within the amplitude fluctuation tolerance range is continuously written into the extended arrangement position, and the sampling period exceeding the amplitude fluctuation tolerance range is set as the stage breakpoint to establish a stable operation cycle; Extract from the tolerance interval column The amplitude fluctuation tolerance range at any given time is 0.38V, and the instantaneous fluctuation sequence is retrieved synchronously. The instantaneous fluctuation amplitude at any given time is 0.03V, verified by comparison command. Is it in Within the given range, 0.03V < 0.38V is considered within the acceptable range. The sampling period is written to the extended arrangement position and marked as a stable state. When a stable state is detected... When the instantaneous fluctuation amplitude is 0.45V and the corresponding tolerance range is 0.37V, a numerical comparison determines that 0.45V > 0.37V, indicating an out-of-range condition. The sampling period is determined as a stage breakpoint, terminating the current stable sequence expansion. By performing this point-by-point logical determination, the set of continuously satisfying tolerance requirements is defined as a running segment with temporal continuity. For those segments that meet the determination conditions... to The interval segments are encapsulated, the start and end timestamps of the segment are determined, and all points that meet the conditions are clustered and combined in chronological order to establish a stable operating cycle.

[0035] The segment aggregation submodule reads the starting sampling period position and the stage breakpoint sampling period position for each stable operating cycle, and continues the corresponding interval records of the same stable operating cycle in the order of sampling time. Multiple stable operating cycles are written into the time sequence arrangement position in sequence, and the interval content of the previous stable operating cycle and the interval content of the next stable operating cycle are arranged continuously. The distribution content of each stable operating cycle interval is organized along the sampling time sequence to establish a set of stable operating segments. For stable operating cycles, extract the starting position identifier of the first set of stable operating cycles. and stage breakpoint location identifier The duration of this segment is calculated to be... Each sampling interval, the The closed interval record is written to the first record cell of the segment memory, and then the next starting position is retrieved. To the breakpoint The interval information is processed by appending the start and end markers of the next stable operating cycle to the first segment record according to the sampling time sequence, and then storing the information in memory. to as well as to Multiple non-continuous time clusters are connected by a logical linked list. By reading the distribution span of each interval on the time axis, the time intervals that belong to normal vehicle passage and sensor output in a dynamic equilibrium state are summarized. Instable data between breakpoints are excluded. The data are organized into a sensor health condition distribution map composed of multiple discrete time periods, and a set of stable operating segments is established.

[0036] Example 5 Please see Figure 6 This embodiment is used for lifespan assessment to determine the reliability of a sensor throughout its entire lifespan and to divide the sensor into various lifespan stages. Specifically, the lifespan reliability assessment module includes a segment timing submodule, a threshold alignment submodule, a stage boundary submodule, and a timing orchestration submodule. The segment timing submodule reads the start and end sampling positions of each stable operating segment from the set of stable operating segments, continues the content of the previous and subsequent stable operating segments in the order of time segments, organizes the corresponding start and end ranges of each stable operating segment, verifies the continuity status of each stable operating segment for the start and end ranges of each stable operating segment, and writes the continuity content of each stable operating segment into the time sequence arrangement position to obtain the segment continuity period. Based on the set of stable operating segments, extract the starting position of the first segment stored in the register. and the end position ,use: , Perform subtraction; The number of sampling points spanned by this section is 20; Retrieve sampling period ; use: , Multiplication calculations yielded a duration of 0.2 seconds. Extract the starting position of the second segment in chronological order of time segments. and the end position ; implement: , The operation will The corresponding 0.2s recorded content and The corresponding 0.45s records are logically connected in ascending order of physical address, and the difference between the start timestamp of each segment and the end timestamp of the previous segment is verified. To determine the continuation status, a continuation determination benchmark value is set. It is 0.5s. The value is set with reference to the minimum safe headway for vehicles on the road, and is determined through execution. Then compare the value with 0.5s to determine if 0.15s is within the range. Within the specified range, this state is determined to be continuous operation under the same load event. The duration of each stable operating segment and the corresponding start and end marker points are sequentially written into the system's timing stack. This sequential arrangement of time period information is used to characterize the effective working span of the sensor at different time scales and obtain the segment duration period.

[0037] Off-threshold alignment submodule: Based on the segment duration period, it calls the accumulated deviation content of the same time segment in the deviation drift accumulation trajectory, retrieves the drift judgment threshold content of the same sampling period in the adaptive drift judgment threshold sequence, writes the accumulated deviation content and drift judgment threshold content into the corresponding sampling position according to the time segment order, and continuously arranges the corresponding records of each sampling period along the time sequence of each stable operation segment to obtain the corresponding column of the time period. Based on the segment duration period, retrieve the cumulative deviation drift trajectory in to as well as to Cumulative deviation value within the time interval ,exist The specific accumulated value is -0.05V, which is retrieved at all times. The specific accumulated value is retrieved at any given time as -0.02V, and the updated threshold corresponding to the same sampling period in the adaptive drift judgment threshold sequence is retrieved simultaneously. ,exist Constantly adjust to 0.75V, in At each interval, 0.76V is retrieved, and following the linear growth direction of the time interval, The addresses for storing -0.05V and 0.75V at any given time are: The alignment record unit will The addresses for storing -0.02V and 0.76V at time are: For each positional record unit, a multi-field joint write operation is performed, ensuring that each set of sampled data contains two key parameters in memory: the cumulative offset and its corresponding dynamic judgment threshold. to The time sequence of each stable operating segment is determined, and a one-to-one pairing association of "deviation-threshold" is performed for each valid time node. The data scattered in two independent sequences are physically aligned at the same timestamp by a pointer stepping method, and the sampling point information containing the paired records is continuously arranged in the storage sector to obtain the corresponding column of the time period.

[0038] Phase Boundary Submodule: Based on the corresponding column of time period, read the cumulative deviation content within the continuous period of each stable segment and the drift judgment threshold content of the same sampling period, verify the cumulative deviation in the range below the drift judgment threshold and the state above the drift judgment threshold along the time segment, write the sampling period with the cumulative deviation below the drift judgment threshold into the stable operation phase arrangement position, and write the sampling period with the cumulative deviation above the drift judgment threshold into the performance degradation phase arrangement position to establish the phase distribution column; Read according to the column corresponding to the time period The cumulative deviation value of -0.05V at any given time is compared with the corresponding drift judgment threshold of 0.75V after performing an absolute value calculation, and then compared using a logical judgment instruction. Based on the relationship with 0.75V, a value of 0.05V < 0.75V is determined to be below the drift threshold. The sampling period identifier is written into the preset stable operation phase storage area, and when it is read... When the cumulative deviation at any given time is 0.82V and the corresponding drift threshold is 0.78V, numerical subtraction is performed. And if the difference is greater than 0V, it is confirmed that the state exceeds the drift detection threshold, and then... The subsequent sampling points are marked as performance degradation stages and written into the corresponding degradation stage storage arrangement position. For each pair of data, the following is utilized along the time segment axis: , Perform symbolic function verification; If the result is positive, it is classified into the stable interval; if the result is negative, it is classified into the decay interval, and the numerical fluctuation is determined to be within the stable interval. During the critical interval, the original stage classification is maintained without switching. By labeling the attributes of the data throughout the entire time period, the sensor's operation process is separated into two physical processes with different properties, and a stage distribution column is established.

[0039] The timing arrangement submodule reads the starting record content in the stable operation stage arrangement position and the subsequent record content in the performance degradation stage arrangement position for the stage distribution column. It connects the previous stage record content and the subsequent stage record content in chronological order, writes the stage records in the same stable operation segment into the timing arrangement position in sequence, and arranges the distribution content of each stage continuously along the stable operation segment to establish the sensor lifespan stage division result. For the phase distribution column, read the starting record from the position of the stable operation phase. From the beginning to the end of the record before the boundary point, extract all sampling timestamps and voltage characteristics belonging to the stable state within this segment. Simultaneously read the subsequent record content generated immediately after the boundary point in the performance degradation stage arrangement, and follow... In the direction of increasing time, a hard link is executed between the tail address of the stable operation phase and the head address of the performance degradation phase. arrive Within the complete segment, to Stable data and to The attenuation data is serialized and assembled according to the order of timestamps. The records of each stage within the same stable operating segment are written into the final result sequence register in sequence. The stage division results of different working cycles are arranged continuously according to the distribution order of the stable operating segment. Through this sequential integration of time segments and their embedded state attributes, a complete timeline mapping result of the sensor from initial service to performance degradation is formed, and the sensor lifespan stage division result is established.

[0040] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A life-cycle reliability assessment system for a self-sensing road surface sensor, characterized in that, The system includes: The signal acquisition module receives sensor voltages, forms a sequence of adjacent voltage differences and converts them to absolute values, filters out invalid periods by comparing them with a preset noise voltage range, retains effective voltage amplitudes and arranges them continuously to form a sequence of effective operating amplitudes of the sensor. Deviation accumulation construction module: Based on the effective operating amplitude sequence of the sensor, the voltage amplitude is obtained and the deviation is generated by corresponding to the preset calibration reference voltage. The drift trend is distinguished by the increase or decrease of adjacent deviations, and the cumulative deviation change is expanded along the time sequence to form a deviation drift accumulation trajectory. Threshold self-sensing calibration module: Based on the cumulative trajectory of deviation drift, the cumulative deviation corresponds to the preset initial deviation threshold. It shows a drift trend according to the direction of deviation. When it expands in the positive direction, the drift judgment threshold is raised, and when it falls back in the reverse direction, the drift judgment threshold is lowered. It continuously updates the drift judgment threshold for each sampling period to form an adaptive drift judgment threshold sequence. Fluctuation segment identification module: It obtains the instantaneous fluctuation state from the effective operating amplitude sequence of the sensor, converts the drift judgment threshold into the corresponding amplitude fluctuation tolerance range, and generates a stable operating cycle by comparing and defining the start and end of the stable extension stage, thus forming a set of stable operating segments.

2. The self-sensing road surface sensor full life cycle reliability assessment system according to claim 1, characterized in that: The system also includes a life reliability assessment module, specifically: Lifetime reliability assessment module: The stable operating cycle is established by the set of stable operating segments, so that the cumulative deviation and the drift judgment threshold are correlated in time. Based on the conditions, the stable operating stage and the performance degradation stage are divided, and the stages are continuously connected to form the sensor lifetime stage division result.

3. The self-sensing road surface sensor full life cycle reliability assessment system according to claim 1, characterized in that, The operating signal acquisition module includes a voltage receiving submodule, a difference noise detection submodule, and an amplitude arrangement submodule. Voltage receiving submodule: Receives the output voltage value of the piezoelectric sensor on the road surface, reads the time identifier corresponding to the continuous sampling period and records the voltage value of each sampling period in time stamp order, arranges the voltage value of each sampling period with the corresponding sampling time identifier, and writes it continuously into the sequence unit according to the sampling order to form a voltage arrangement state unfolded according to the sampling period, and obtains the original voltage change sequence. Noise verification submodule: Based on the original voltage change sequence, read the voltage records arranged before and after adjacent sampling periods, organize them into voltage difference records between consecutive sampling periods, perform amplitude-based processing on each voltage difference record, verify each amplitude-based voltage difference record against the preset noise voltage range, retain the voltage difference records corresponding to the sampling periods that exceed the preset noise voltage range, and remove the voltage difference records corresponding to the sampling periods that fall within the preset noise voltage range to obtain the effective period range; Amplitude arrangement submodule: Based on the effective period range, retrieve the voltage amplitude corresponding to each sampling period within the effective period range, write it sequentially into the amplitude arrangement unit according to the sampling time order, connect each reserved voltage amplitude record along the time sequence, and perform sequential connection for the missing positions to establish the effective operating amplitude sequence of the sensor.

4. The self-sensing road surface sensor full life cycle reliability assessment system according to claim 1, characterized in that, The deviation accumulation construction module includes a deviation correspondence submodule, a trend identification submodule, and an accumulation extension submodule: Deviation Correspondence Submodule: Based on the effective operating amplitude sequence of the sensor, the voltage amplitude of each sampling period is called and expanded in the order of sampling time. The preset calibration reference voltage is retrieved and matched with the voltage amplitude of each sampling period item by item. The voltage amplitude position and the reference voltage position under the same sampling period are written into the corresponding mark unit. The corresponding contents in each mark unit are arranged in sequence along the sampling order to form the deviation correspondence quantity. Trend identification submodule: Based on the deviation corresponding amount, read the corresponding deviation amount arranged before and after adjacent sampling periods, verify the direction of change of each corresponding deviation amount before and after along the sampling time sequence, classify the upward extension record into the positive drift mark area, classify the downward fall record into the reverse drift mark area, and arrange each drift mark area continuously according to the sampling time sequence to obtain the drift direction sequence. The cumulative extension submodule: Based on the drift pointing sequence, it calls the drift marker corresponding to the same sampling period and retrieves the corresponding amount of deviation of the previous sampling period. Combined with the drift marker corresponding to the current sampling period, it determines the deviation change content of each sampling period. It continues the deviation change content of each sampling period in the order of sampling time, and merges the deviation change content of subsequent sampling periods into the corresponding arrangement position of the previous sampling period in sequence. It then arranges the deviation content of each sampling period continuously according to the sampling order to establish the deviation drift accumulation trajectory.

5. The self-sensing road surface sensor full life cycle reliability assessment system according to claim 1, characterized in that, The threshold self-sensing calibration module includes a threshold correspondence submodule, a direction threshold adjustment submodule, and a sequence update submodule. Threshold Correspondence Submodule: Based on the deviation drift accumulation trajectory, read the accumulated deviation content of each sampling period, retrieve the preset initial deviation threshold, and correspond the accumulated deviation content of each sampling period with the preset initial deviation threshold item by item according to the sampling time sequence and write it into the threshold mark position. Then, arrange the sampling period threshold records written into the threshold mark positions in sequence along the sampling time to form a drift judgment threshold column. Directional threshold adjustment submodule: Based on the drift judgment threshold column, read the cumulative deviation content arranged before and after each sampling period, verify the direction of the deviation increment along the time series, classify the records extending towards the preset threshold trigger range into the positive drift area, classify the records in the falling direction into the negative drift area, perform upward adjustment on the current drift judgment threshold corresponding to the sampling period of the positive drift area, and perform downward adjustment on the current drift judgment threshold corresponding to the sampling period of the negative drift area to obtain the threshold adjustment result column; Sequence Update Submodule: Based on the threshold adjustment result column, read the drift judgment threshold content corresponding to each sampling period, write it into the corresponding period arrangement position in the order of sampling time, continue the drift judgment threshold content of the previous sampling period and the drift judgment threshold content of the next sampling period, continuously update the drift judgment threshold records of each sampling period along the sampling time sequence, and sequentially arrange the drift judgment threshold content of each sampling period to establish an adaptive drift judgment threshold sequence.

6. The self-sensing road surface sensor full life cycle reliability assessment system according to claim 1, characterized in that, The fluctuation segment identification module includes a fluctuation formation submodule, a tolerance mapping submodule, a stage discrimination submodule, and a segment consolidation submodule. The fluctuation formation submodule reads the voltage amplitude content arranged before and after adjacent sampling periods based on the effective operating amplitude sequence of the sensor, connects the voltage amplitude content of the previous position and the voltage amplitude content of the next position according to the sampling time sequence, organizes the relationship of continuous voltage amplitude change, verifies the fluctuation direction for the voltage amplitude change state before and after each sampling period, and writes the voltage amplitude change content corresponding to each sampling period into the time sequence arrangement position in sequence to obtain the instantaneous fluctuation sequence. Tolerance mapping submodule: Based on the instantaneous fluctuation sequence, it calls the drift judgment threshold content of each sampling period in the adaptive drift judgment threshold sequence, converts the drift judgment threshold of each sampling period into the corresponding amplitude fluctuation tolerance range according to the sampling time order, writes the amplitude fluctuation tolerance range of each sampling period into the corresponding time sequence position, and arranges the amplitude fluctuation tolerance range of each sampling period in sequence along the sampling order to obtain the tolerance interval column; Stage discrimination submodule: Based on the tolerance interval column, read the amplitude fluctuation tolerance range content and the corresponding instantaneous fluctuation amplitude content in the instantaneous fluctuation sequence under the same sampling period, verify the instantaneous fluctuation amplitude content item by item along the continuous sampling period to see if it is within the amplitude fluctuation tolerance range, write the sampling period within the amplitude fluctuation tolerance range into the extended arrangement position, and set the sampling period exceeding the amplitude fluctuation tolerance range as the stage breakpoint to establish a stable operation cycle; The segment aggregation submodule reads the starting sampling period position and the stage breakpoint sampling period position for each stable operating cycle, continues the corresponding interval records of the same stable operating cycle in the order of sampling time, writes multiple stable operating cycles into the time sequence arrangement position in sequence, arranges the interval content of the previous stable operating cycle and the interval content of the next stable operating cycle in sequence, and organizes the distribution content of each stable operating cycle interval along the sampling time sequence to establish a set of stable operating segments.

7. The self-sensing road surface sensor full life cycle reliability assessment system according to claim 2, characterized in that, The lifetime reliability assessment module includes a segment timing submodule, a threshold alignment submodule, a stage boundary submodule, and a timing arrangement submodule. The segment timing submodule reads the start and end sampling positions of each stable operating segment in the set of stable operating segments based on the set of stable operating segments. It then continues the content of the previous and subsequent stable operating segments in the order of time segments, organizes the corresponding start and end ranges of each stable operating segment, verifies the continuity status of each stable operating segment for the start and end ranges of each stable operating segment, and writes the continuity content of each stable operating segment into the time sequence arrangement position to obtain the segment continuity period. Off-threshold alignment submodule: Based on the duration of the segment, it calls the accumulated deviation content of the same time segment in the deviation drift accumulation trajectory, retrieves the drift judgment threshold content of the same sampling period in the adaptive drift judgment threshold sequence, writes the accumulated deviation content and drift judgment threshold content into the corresponding sampling position according to the time segment order, and continuously arranges the corresponding records of each sampling period along the time sequence of each stable operating segment to obtain the time period corresponding column; Phase Boundary Submodule: Based on the corresponding column of the time period, read the cumulative deviation content within the continuous period of each stable segment and the drift judgment threshold content of the same sampling period, verify the cumulative deviation in the range below the drift judgment threshold and the state above the drift judgment threshold along the time segment, write the sampling period with the cumulative deviation below the drift judgment threshold into the stable operation phase arrangement position, and write the sampling period with the cumulative deviation above the drift judgment threshold into the performance degradation phase arrangement position to establish a phase distribution column; The timing arrangement submodule reads the starting record content in the stable operation stage arrangement position and the subsequent record content in the performance degradation stage arrangement position for the stage distribution column. It connects the previous stage record content and the subsequent stage record content in chronological order, writes the stage records in the same stable operation segment into the timing arrangement position in sequence, and arranges the distribution content of each stage continuously along the stable operation segment to establish the sensor lifespan stage division result.

8. The self-sensing road surface sensor full life cycle reliability assessment system according to claim 3, characterized in that, In the noise verification submodule, when verifying the amplitude-valued voltage difference records against the preset noise voltage range item by item, a sliding window statistical discrimination method is used.

9. The self-sensing road surface sensor full life cycle reliability assessment system according to claim 6, characterized in that, In the tolerance mapping submodule, a hierarchical tolerance mapping method is adopted when converting the drift judgment threshold of each sampling period into the corresponding amplitude fluctuation tolerance range according to the sampling time sequence.

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