Method for testing a flexray bus for faults

Abstract

The application belongs to the technical field of electric digital data processing, and discloses a fault test method of a Flexray bus, which comprises the following steps: in a non-data transmission state of a bus network, injecting, by an excitation node, a sub-threshold electric excitation pulse which appears as noise to a communication controller; measuring, by the excitation node itself, a local echo of the pulse to obtain a real-time probe fingerprint, and meanwhile, measuring, by a listening node, a far-end response signal of the pulse; finally, performing normalization processing on the far-end response signal by using the real-time probe fingerprint, and comparing the normalized far-end response signal with a reference feature to determine whether the bus has a potential fault, wherein the application establishes a dynamic self-calibration measurement reference, solves the diagnostic confusion problem caused by state fluctuation of an excitation source itself, changes the nature of fault test from relative comparison to quasi-absolute measurement which can resist signal source drift, and improves the confidence and reliability of online diagnosis of unattended transaction equipment.

Description

TECHNICAL FIELD

[0001] The application relates to a fault test method of a Flexray bus and belongs to the technical field of electric digital data processing. BACKGROUND

[0002] At present, in a data processing system, the Flexray bus has become a technical basis for data exchange between nodes in the fields of automobile electronic industry automation and the like due to high bandwidth, deterministic timing and fault tolerance characteristics, and the Flexray bus guarantees reliable transmission of data at a logical level through a set of communication protocols and error processing mechanisms; when the technology is applied to an unattended transaction system with strict requirements for long-term uninterrupted operation and extremely low field maintenance, a technical requirement for reliability of the system in a whole life cycle is generated, that is, the existing technical system has a deficiency in predicting a progressive degradation process of a communication physical layer; at present, evaluation of a bus physical layer state mainly depends on two technical paths: one is that after a device is shut down, external measuring instruments are used to comprehensively analyze electrical characteristics; and the other is that a communication controller built-in error counter is relied on to passively record a communication error that has occurred; the two ways have a common point that a diagnosis object is a logical layer communication error that has occurred or appeared, rather than a root problem such as a physical connection problem or impedance mismatch that causes the error to be in an early degradation stage; for slow evolution of the physical layer state before failure without producing any logical error, the existing monitoring method cannot effectively perceive in principle; in order to solve the problem, a direct idea is to integrate special online monitoring hardware for network nodes, but this will increase hardware cost and system complexity of large-scale deployed unattended devices, and does not meet the cost control requirement in the field.

[0003] Moreover, the prior art has limitations in the idea of active fault injection testing. It often focuses on verifying the response of the node under specific logic errors, while ignoring the fundamental influence of the state fluctuation of the test excitation source itself on the diagnosis results. For example, the Chinese invention patent with the authorization announcement number CN119396641A discloses a fault simulation method, a test method, an equipment and a system of Flexray bus. The core of the scheme is to determine the bus time information such as period and time slot by listening to the bus, and on this basis, to inject fault simulation messages or interference signals that violate the protocol specification in the specified time slot to test the response of the measured piece. However, such a method is essentially an external idealized fault scenario reproduction, and its purpose is to verify the fault tolerance capability of the measured piece at the logic level, rather than to diagnose the health status of the bus physical layer itself. More importantly, it does not consider the performance fluctuation of the excitation source (i.e. the fault injection equipment) itself due to factors such as temperature drift and aging. This fluctuation will directly couple into the test results, causing diagnosis confusion, so that it cannot distinguish whether the bus channel is truly degraded or only the test signal source is drifting, which leads to its inability to meet the stringent requirements of high confidence, repeatable and online predictive diagnosis for unattended equipment.

[0004] The prior art has a set of mutually restrictive technical conditions in application: on the one hand, to ensure the high availability of unattended transaction systems, a predictive diagnosis capability is needed to monitor the evolution process of the health of the bus physical layer; on the other hand, due to the limitations of cost complexity and in-service operation, additional dedicated measurement hardware cannot be introduced or any test process that may interfere with normal data communication cannot be adopted. Under this restriction, the prior art mainly has the following deficiencies: 1. The diagnosis methods all act on the logic communication level, and there is a lack of effective sensing method for the progressive deterioration precursors of the physical layer connector such as small looseness terminal resistance thermal aging drift that have not yet caused communication errors; 2. Deep physical layer diagnosis relies on system downtime and the intervention of external professional instruments, which cannot meet the uninterrupted service operation requirements of unattended equipment, causing a conflict between the diagnosis behavior and the operation and maintenance goal. Therefore, how to use the existing hardware of the system to establish a test method that can actively obtain the health status characteristics of the bus physical layer and early warn potential faults on this basis without affecting the normal data transmission of the bus has become a technical problem to be solved by the present application. SUMMARY

[0005] The present application provides a fault test method for Flexray bus, which mainly aims to solve the problem that the prior art cannot use the existing hardware of the system to effectively predict the progressive state degradation of the bus physical layer without interrupting normal communication.

[0006] To achieve the above object, the application provides a fault testing method of a Flexray bus, which is applied to a Flexray bus network, and comprises the following steps:

[0007] Step a: when the Flexray bus network is in a preset non-data frame transmission state, injecting, by a stimulating node in the network, a sub-threshold electrical stimulation pulse with a voltage amplitude lower than a valid data logic level threshold into a bus channel through a control of a communication transceiver of the stimulating node, wherein the sub-threshold electrical stimulation pulse cannot be recognized as a valid data frame by a Flexray communication controller of any node in the Flexray bus network, and only appears as network noise;

[0008] Step b: measuring and acquiring, by at least one listening node in the network, one or more first electrical characteristics of a response signal formed after the sub-threshold electrical stimulation pulse propagates through the bus channel within a time window of an expected arrival of the sub-threshold electrical stimulation pulse;

[0009] Step c: in the middle or after the injection of the sub-threshold electrical stimulation pulse in step a, measuring, by the stimulating node itself, a local echo signal generated by the sub-threshold electrical stimulation pulse injected into the bus channel by a receiving pin of the communication transceiver of the stimulating node to acquire one or more second electrical parameters representing actual parameters of the injected pulse, and defining the one or more second electrical parameters as a real-time probe fingerprint;

[0010] Step d: performing, by the listening node, a normalization operation, wherein the input of the normalization operation is the first electrical characteristics and the real-time probe fingerprint, and the output of the normalization operation is a normalized response fingerprint;

[0011] Step e: comparing the normalized response fingerprint with a reference electrical characteristic, and judging whether there is a potential fault indicating a physical layer state deterioration in the bus channel based on a comparison result.

[0012] Preferably, the reference electrical characteristic is acquired and stored by performing the same operations as steps a to d under the premise that the Flexray bus network is in a healthy state.

[0013] Preferably, the preset non-data frame transmission state is a network idle time defined by the Flexray protocol.

[0014] Preferably, the method further comprises that the listening node stores a reference electrical characteristic set representing a recent healthy state of the bus channel acquired by a plurality of historical measurements; the comparison in step e comprises a statistical comparison of the normalized response fingerprint with the reference electrical characteristic set to distinguish whether a real-time state change of the bus channel is caused by a sudden potential fault or a gradual system aging; and the comparison in step e is satisfied only when the statistical comparison result is statistically significant. at the time, the state change is determined to be a one-time health probe, and the reference electrical characteristic set is updated using the normalized response fingerprint; wherein is the current acquired normalized response fingerprint, is the most recent historical fingerprint in time in the reference electrical characteristic set, is a sudden change threshold determined based on a statistical distribution of historical response data of the bus network in a healthy state, and used to determine a sudden change.

[0015] Preferably, steps a to e are repeatedly performed multiple times sequentially, and in each repeated performance, a different node in the Flexray bus network is selected as the stimulus node; the method further comprises: performing a correlation analysis on the multiple determination results obtained in the multiple repeated performances to construct a channel response deviation matrix, wherein an element in the channel response deviation matrix represents the health status of the bus channel from the node to the node ; and based on the response pattern in the channel response deviation matrix, the topology location and root cause type of the potential fault are located.

[0016] Preferably, locating the topology location and root cause type of the potential fault comprises: when the mth row elements of the channel response deviation matrix all indicate the presence of a potential fault, judging the root cause type of the potential fault to be a transmission capability fault of the node m; and when the mth column elements of the channel response deviation matrix all indicate the presence of a potential fault, judging the root cause type of the potential fault to be a reception capability or access point fault of the node m.

[0017] Preferably, before the sub-threshold electrical stimulus pulse in step a, the method further comprises: measuring, by the listening node, a background noise level on the bus channel to obtain a channel disturbance indicator; sending, by the stimulus node, a probe query to the listening node; comparing, by the listening node, the channel disturbance indicator with a preset quiet threshold, and only when the channel disturbance indicator is lower than the quiet threshold, replying, by the listening node, a probe permission signaling to the stimulus node; and the execution of step a is subject to the condition that the stimulus node receives the probe permission signaling.

[0018] Preferably, the method further comprises: when the Flexray bus network is in a data frame transmission state, measuring, by one or more nodes in the network, a direct current baseline level of a data frame signal sent by a preset sending node within a time window in which the preset sending node is known to be sending a data frame, according to a deterministic scheduling table of the Flexray protocol, to obtain a measured baseline level value; comparing the measured baseline level value with a reference baseline level value representing the preset sending node in a healthy state, which is stored in advance, and based on the comparison result, determining whether the preset sending node has a potential hardware fault.

[0019] Preferably, during the time period when the Flexray bus network is in the preset non-data frame transmission state and step a is not performed, further comprising: by at least one node in the network, using a comparator inside its microcontroller, monitoring whether the level of the bus channel accidentally crosses one or more preset asymmetric voltage thresholds, wherein the asymmetric voltage thresholds include an upper threshold higher than the voltage of the normal bus recessive level and a lower threshold lower than the voltage of the normal bus recessive level; and based on the frequency of occurrence of events in which the level of the bus channel crosses the asymmetric voltage thresholds within a unit of time, determining whether there is a parasitic wake-up fault caused by external interference in the bus channel.

[0020] Preferably, the comparison in step e is specifically calculating the Euclidean distance or correlation coefficient between the normalized response fingerprint and the reference electrical characteristic to obtain a deviation value, and the determination is specifically comparing the deviation value with a preset degradation threshold, and generating a pre-warning signal indicating a potential fault when the deviation value continuously exceeds the degradation threshold.

[0021] Compared with the prior art, the present application has the following beneficial effects:

[0022] 1. By synchronously measuring the real-time electrical parameters of the injected pulse by the excitation node itself in the step of injecting the excitation pulse by the excitation node, and using the parameters for normalizing the response signal obtained by the listening node, the combination of these technical features makes the final determination of the state of the bus channel logically independent of the performance fluctuations of the communication transceiver of the excitation node itself due to aging or changes in working conditions, and the method establishes a dynamic self-calibrating measurement reference, so that the results of each fault test are consistent and traceable, avoiding diagnostic confusion caused by the uncertain state of the measurement source itself.

[0023] 2. By storing the reference electrical characteristic set composed of multiple historical measurements in the listening node, and statistically comparing the real-time obtained electrical characteristic with the set, the system can distinguish two physical processes of completely different natures; for a persistent and small one-way deviation between the real-time characteristic and the statistical center of the historical set, the system identifies it as the gradual aging of the bus system and updates the reference set, and for a sudden and large difference between the real-time characteristic and the recent historical record, it is judged as a sudden potential fault; this mechanism enables the system to recognize the evolution process of the bus physical state, avoids false alarms caused by normal aging of the system, and improves the effectiveness of the pre-warning signal.

[0024] 3. The Flexray protocol determines the timing of the data frame transmission state, one or more nodes measure the DC baseline level of the data frame signal sent by the preset sending node, and compare it with the reference parameter representing the health status of the preset sending node; this step is combined with the step of injecting sub-threshold pulses for channel detection in the non-data frame transmission state, forming a diagnostic system covering both dynamic and static working modes; the former monitors the active signal characteristics strongly related to the hardware working condition of the sending node when the system is fully loaded, and the latter detects the passive response characteristics of the bus physical medium when the system is idle; the two work together to enable the system to attribute the root cause of the fault, i.e., to distinguish whether the fault is caused by the transmission channel itself or by the hardware degradation of a specific node.

[0025] 4. The steps of injection, measurement, comparison and judgment are repeated sequentially and repeatedly multiple times, and different nodes are selected as excitation nodes in each repeated execution, and finally the correlation analysis of the obtained multiple judgment results is performed; this method changes the diagnosis of the bus network from a series of independent linear path evaluations to an analysis of the associated response patterns between the nodes of the entire network topology; when the analysis result shows that all paths starting from a certain node are degraded, the system can locate the potential fault to the sending function of the node, otherwise, if all paths ending at the node are degraded, the fault can be located to the receiving function or access point, realizing the synchronous judgment of the fault topology location and root cause type. BRIEF DESCRIPTION OF DRAWINGS

[0026] Fig. 1 Self-calibration data processing flowchart for fault test of the present application;

[0027] Fig. 2 Deviation evolution curve graph in the progressive fault monitoring of the present application;

[0028] Fig. 3 Distributed diagnostic system architecture based on Flexray bus of the present application. DETAILED DESCRIPTION

[0029] To make the objectives, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described in detail below. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0030] The application relates to a Flexray bus fault testing method, which is applied to a Flexray bus network composed of multiple electronic control unit nodes, the network serving as a technical basis of a data processing system and being applied to unattended transaction equipment with strict requirements for long-term uninterrupted operation. The method uses the existing communication transceiver and microcontroller of the nodes in the system to quantitatively evaluate and give a fault warning to the health state of the bus physical channel without affecting the normal data transmission of the bus. The core operation process includes a series of data processing steps such as excitation injection and self-calibration, response capture and normalization, and state comparison and fault judgment. In a specific application scenario, for example, a high-end unmanned retail terminal deployed in a city traffic hub, the Flexray bus network for controlling a precise mechanical arm, coordinating a payment module and managing a material sensor in the terminal needs a testing capability capable of foreseeing and diagnosing the progressive deterioration precursors such as slight loosening of a physical layer connector or terminal resistance thermal aging drift, so as to guarantee the system availability of uninterrupted service. Therefore, the system uses the method as claimed in the application to perform online evaluation of the health degree of the bus physical channel without interrupting the normal transaction process. The execution subject of the method is any designated node in the network with a standard Flexray communication transceiver and a microcontroller integrated with an analog-to-digital converter (ADC). The initial state definition procedure of the method includes the following steps: after the system is powered on for the first time or is maintained, it is confirmed that the entire Flexray bus network is in a healthy state with perfect physical connection and error-free communication. At this time, one designated node serves as an excitation node, and one or more nodes serve as listening nodes, and the following test process is completely executed once, and the finally obtained response signal electrical characteristics after normalization are stored in the nonvolatile memory of each listening node as the reference electrical characteristics representing the path health state of the node to the excitation node. For example, in a network composed of nodes A, B and C, A is designated as the excitation node, and B and C are the listening nodes. After the test is executed, node B stores a reference value , and node C stores a reference value .

[0031] The test flow of the method, i.e. steps a to e, is periodically and automatically executed, for example every 10 minutes, in the following way: step a, the injection of the sub-threshold electrical excitation pulse is performed by the excitation node A, in a Flexray communication cycle, there is a network idle time (NIT) defined by the protocol in which all nodes do not send data frames, the microcontroller of the excitation node A, with precise synchronization to the protocol timing, generates a single short level pulse in the NIT window by directly controlling the level state of the TXD transmit data pin of its communication transceiver, instead of sending a standard data frame through the communication controller; the voltage amplitude of the pulse is set in a specific sub-threshold interval, the upper limit of which is lower than the minimum level threshold that the Flexray communication controller can recognize as valid data logic, and the lower limit is higher than the average amplitude of the bus background noise, a specific numerical example is that if the bus operating voltage is 5V, the valid logic level threshold is 1.5V, and the peak-to-peak value of the background noise is 50mV, the amplitude of the sub-threshold pulse can be set to 300mV, and the pulse width can be set to 100ns; the pulse configured in this way will not be misinterpreted as the start or content of a data frame by any node, because its amplitude does not reach the logic decision threshold of the communication controller, thus completing the injection without interrupting the normal data communication on the bus; step c, during or after the injection of the sub-threshold electrical excitation pulse by the excitation node A, the microcontroller of the excitation node A simultaneously samples the level of the RXD receive pin of its communication transceiver using its own analog-to-digital converter, to capture the local echo signal generated by the injection pulse at the injection point. The electrical characteristics of the echo signal, such as the peak voltage, directly represent the actual strength and morphology of the injection pulse, and are therefore defined as the real-time probe fingerprint; continuing the previous example, if the injected 300mV pulse is actually output as 290mV due to temperature drift of the excitation node's own drive circuit, the peak value of its local echo signal may be measured as 285mV, then the numerical value 285mV becomes the real-time probe fingerprint of this test, this step provides a dynamic self-calibration measurement reference for subsequent normalization processing by real-time parameter calibration of the excitation source, solving the diagnostic confusion problem caused by fluctuations in the state of the excitation source.

[0032] Step b, by the listening node B in the network, according to the global clock synchronization mechanism of the Flexray protocol, within the expected arrival time window of the sub-threshold electrical excitation pulse, using its microcontroller integrated analog-to-digital converter, high-speed sampling on the RXD receiving pin of its communication transceiver, measuring and acquiring the far-end response signal formed after the pulse propagates through the bus channel, and extracting one or more first electrical characteristics, such as the peak voltage of the response signal, from the sampling data; for example, the peak voltage of the pulse emitted by node A and propagated through the bus to node B is measured by node B as 140 mV due to channel attenuation; step d, by the listening node B, performing a normalization operation, the input of which is the first electrical characteristic (140 mV) acquired in step b and the real-time probe fingerprint (285 mV) informed by the excitation node A through the conventional data frame, and the output of which is a normalized response fingerprint; the normalization operation can be a division operation, i.e. normalized response fingerprint = first electrical characteristic / real-time probe fingerprint = 140 mV / 285 mV ≈ 0.491, which is a dimensionless value reflecting the transfer function characteristics of the bus channel from the excitation node to the listening node, excluding the influence of the excitation source itself; step e, the listening node B compares the normalized response fingerprint (0.491) calculated in step d with the pre-stored reference electrical characteristic (for example, the initial calibration healthy reference value is 0.520) to determine whether there is a potential fault in the bus channel; the comparison can be specifically to calculate the deviation between the two, deviation = |current fingerprint - reference fingerprint| / reference fingerprint = |0.491 - 0.520| / 0.520 ≈ 5.6%, and then compare the deviation value with a preset degradation threshold (for example, 5%), if the deviation (for example, continuously for 3 times) exceeds the degradation threshold, a potential fault warning signal indicating the degradation of the physical layer state is generated.

[0033] The first electrical characteristic and the second electrical parameter are a specific set of indicators for quantifying the captured pulse signal waveform, in addition to the signal peak voltage mentioned in the embodiment, the set can also include: the pulse energy obtained by time integration of the voltage signal in the sampling window, which reflects the overall intensity of the signal and is not sensitive to single noise spikes; the rise time required for the signal amplitude to rise from 10% to 90%, which is directly responsive to impedance mismatch and capacitive load changes of the bus network; and the duration of the signal amplitude exceeding the 50% threshold, i.e. the pulse width, which characterizes the broadening effect of the signal during channel transmission; when making fault judgment, these electrical characteristics can be constructed into a multi-dimensional feature vector, at this time, the comparison operation in step e is to calculate the Euclidean distance between the feature vector obtained by the current measurement and the pre-stored reference feature vector, so as to obtain a deviation value which more comprehensively characterizes the health status of the bus channel; a key point is that in order to enable the analog-to-digital converter ADC inside the microcontroller to reliably capture the waveform of the sub-threshold electrical excitation pulse, the width of the injected pulse is directly related to the sampling rate of the ADC itself, and the value of the sampling period should be set to several times the sampling period in engineering debugging, , and specifically can be , wherein is a coefficient to ensure that multiple sampling points can be obtained within a pulse, and the value range is usually between 5 and 10, for example, if the ADC sampling rate of a node is 10MSPS, i.e. equals 100ns, then the injected pulse width can be set in the range of 500ns to 1000ns; both the listening node and the excitation node continuously collect a set of discrete voltage sample points within the expected time window using the ADC, and then extract the peak voltage from the set of sample points as the electrical characteristic of this time through a sliding window maximum search algorithm. This method uses the existing processor and is not sensitive to the inherent asynchrony between the sampling clock and the pulse peak.

[0034] In a preferred embodiment, in order to distinguish whether the real-time state change of the bus channel is caused by a sudden potential fault or by gradual system aging, the listening node also stores a set of reference electrical characteristics representing the recent health status of the bus channel obtained by multiple historical measurements, for example, a queue containing the results of the last 100 measurements; the comparison in step e further includes comparing the normalized response fingerprint obtained at present with the most recent historical fingerprint in the reference electrical characteristic set, and only when the condition is met, it is determined that the state change is a health detection, and the use updating the reference set of electrical characteristics, wherein, a sudden change threshold determined from the statistical distribution of historical response data (e.g. 3 standard deviations) of the bus network in a healthy state, which mechanism enables the diagnostic reference to dynamically adapt to the normal aging process of the system, avoiding false positives due to normal aging; in another preferred embodiment, for locating the topology position and source of potential faults, steps a to e are sequentially repeated multiple times, and in each repeated execution, a different node in the network is selected as the stimulus node, for example, in a network of three nodes A, B, C, A, B, C take turns to act as the stimulus node, thereby obtaining a channel response deviation matrix wherein the element represents the health of the bus channel from node to node ; by analyzing the response pattern in the matrix, the fault can be located, for example, when the mth row element of the matrix, i.e. the path from node m to all other nodes, indicates the presence of potential faults, then the fault source is judged to be the transmission capability fault of node m; conversely, when the mth column element of the matrix, i.e. the path from all other nodes to node m, indicates the presence of faults, then the fault source is judged to be the receiving capability or access point of node m.

[0035] To improve the test reliability in a complex electromagnetic environment, a synchronization mechanism of a detection window can be further included before injecting the sub-threshold electrical excitation pulse in step a: the listening node first measures the background noise level on the bus channel to obtain a channel disturbance index; the excitation node sends a detection inquiry to the listening node, the listening node compares the channel disturbance index with a preset quiet threshold, for example, the noise peak-to-peak value is lower than 10% of the excitation pulse amplitude, and only when the threshold is lower than the threshold, the excitation node replies to the excitation node with detection permission signaling, and the excitation node performs the injection operation in step a after receiving the permission signaling, the inquiry and permission process before ensures that the detection is always performed in a window where the channel is quiet enough, avoiding measurement errors caused by external strong interference; in addition, the method claimed in the present application can also work with other diagnostic methods to build a diagnostic system covering both static and dynamic working modes, for example, when the Flexray bus network is in the data frame transmission state, one or more nodes in the network can measure the DC baseline level of the data frame signal sent by the preset sending node (for example, node X) within the time window when the Flexray protocol determines the scheduling table, and compare the measured baseline level with a pre-stored baseline level representing the healthy state of node X, if the level deviates from the reference, it can be judged that the preset sending node has potential hardware failure, for example, its power supply system appears early degradation; at the same time, during the period when the Flexray bus network is in a non-data frame transmission state and no active detection is performed, at least one node in the network can use a comparator inside its microcontroller to continuously monitor whether the bus channel level accidentally crosses one or more preset asymmetric voltage thresholds, wherein the asymmetric voltage threshold includes an upper threshold higher than the normal bus implicit level and a lower threshold lower than the normal bus implicit level, by counting the frequency of threshold crossing events per unit time, it can be judged whether there is a parasitic wake-up fault caused by external electromagnetic interference on the bus channel, thereby providing early warning for the deterioration of the external electromagnetic environment of the bus.

[0036] Example 1: In an unattended coffee vending terminal deployed in a high-traffic transportation hub, multiple electronic control unit nodes responsible for coordinating payment, inventory management, and precise movements of a robotic arm, exchange data via a Flexray bus network. After six months of continuous fault-free operation, the terminal's operational backend consistently shows zero communication error logs, and all data frames have correct cyclic redundancy checks. The system appears to be in perfect health at the logical communication level. However, due to the daily opening and closing of the equipment hatch, which causes hundreds of vibrations, and the periodic changes in temperature and humidity in the station environment, the crimped terminals inside the bus connector of a node connected to the end effector of the robotic arm gradually loosen by microns. This loosening introduces a small contact resistance that is not enough to disrupt any data frame transmission, but the signal integrity margin of the bus physical channel has started to decline. During this period, the operational system cannot effectively perceive this physical state evolution that does not produce logical errors, relying on the monitoring of the built-in error counters of the communication controllers. The control system of the terminal, according to the above method, automatically performs a bus physical channel health assessment once every two user transactions during network idle time. The main board node acts as the excitation node, injecting a preset sub-threshold electrical excitation pulse into the bus. At the same time, due to the 15 increase in ambient temperature from the initial calibration, the communication transceiver driving capability of the excitation node itself has a slight drift, and the actual strength of the pulse it emits is slightly lower than the nominal value. The excitation node captures the local echo signal of this pulse through its receiving pin, generating a real-time probe fingerprint that accurately reflects the strength of this excitation.

[0037] The node of the end effector of the mechanical arm acts as a listening node, and captures a response signal that has occurred additional attenuation after propagating through a channel containing a micro contact resistance within an expected time window of the listening node, and extracts a first electrical characteristic thereof. If a judgment is made solely based on the electrical characteristic, the value thereof has exceeded a set degradation threshold, but the judgment cannot rule out the possibility of drift of the excitation source itself. Further, after the listening node receives a real-time probe fingerprint sent by the excitation node, a normalization operation is performed, and the operation dynamically calibrates the first electrical characteristic by using the real-time probe fingerprint. The output normalized response fingerprint eliminates the influence of the excitation source drift and purely represents the actual transmission characteristics of the bus channel. After comparing the normalized response fingerprint with a reference electrical characteristic stored locally, a deviation degree of 8.2% is calculated, which stably exceeds the degradation threshold of 5%. The system generates a warning indicating degradation of the physical layer health degree instead of an urgent alarm of a communication interruption in one communication, and an operation and maintenance personnel performs preventive maintenance on the equipment in a predetermined off-peak period, so that the deviation degree in subsequent tests falls to 0.5% by tightening the loose connector, thereby avoiding a communication interruption that may occur due to depletion of signal margin under future power grid fluctuations or electromagnetic interference without affecting any user transaction.

[0038] Example 2: To objectively verify the effectiveness of the method claimed in the present application in diagnosing early progressive faults of the bus physical channel under the working condition of excitation source state fluctuation, and to demonstrate the necessity of the excitation pulse online self-calibration and response normalization mechanism, a hardware-in-the-loop test platform including three Flexray nodes is constructed in this embodiment. All nodes are commercial electronic control units integrated with 12-bit analog-to-digital converters, and the sampling rate of the analog-to-digital converter is set to 10 MSPS. The entire platform is placed in an environmental test chamber with a temperature control range of 20 to 60 to simulate the working state of unattended transaction equipment under different environmental temperatures. In the test, node A is designated as the excitation node, and node B is the listening node. An adjustable precision resistance box is connected in series at the access branch of node B to simulate the early contact resistance caused by poor contact of the bus connector. Two states are set in the test: a healthy state, in which the resistance value of the precision resistance box is set to 0 Ω; and a fault state, in which the resistance value is set to 5 Ω, which is insufficient to cause any communication error that can be recorded by the Flexray communication controller, but has affected the high-frequency response characteristics of the channel. The test is divided into the inventive group using the complete method claimed in the present application and the control group without performing steps c and d, i.e., lacking excitation pulse self-calibration and response normalization processing. Both groups are tested under the same working conditions. The test procedure first sets the temperature of the environmental test chamber to 25 at a stable ambient temperature, to obtain and store the baseline electrical characteristics (normalized) of the inventive sample group and the baseline electrical characteristics (non-normalized) of the control group, respectively, then set the bus to a fault condition of 5Ω and measure the electrical characteristics at 25 and 50 Two groups were tested at two ambient temperatures, respectively, in which the temperature change was mainly used to cause the thermal-induced performance drift of the transceiver driving circuit of the excitation node A, so as to change the actual strength of the sub-threshold electrical excitation pulse emitted thereby. The key data recorded during the test are shown in Table 1.

[0039] Table 1: Comparison table of test data under different working conditions.

[0040]

[0041] According to the data in Table 1, in the control group, when the ambient temperature rises from 25 to 50 , due to the decrease in the driving ability of the excitation node A caused by temperature drift, the amplitude of the local echo signal, i.e. the real-time probe fingerprint, decreases from about 299mV to about 275mV. At this time, the control group directly compares the far-end response signal, i.e. the first electrical characteristic, and the calculated deviation degree is affected by the excitation source fluctuation and channel fault, the value changes from about 8.4% to about 15.1%, and even in a certain measurement, due to random fluctuation, the value is 4.2%, which is lower than the degradation threshold of 5%, and the possibility of false negative is generated. In the inventive sample group, by introducing the real-time probe fingerprint for normalization processing, the normalized response fingerprint obtained at 25 and 50 is stable in the interval of 0.47 to 0.48, and the finally calculated deviation degree is also stable in the range of 8% to 9%, which reflects the fixed degradation degree of the channel introduced by the 5Ω resistor. The test data shows that in the absence of online self-calibration of excitation pulse and response normalization processing, the diagnosis result will be deviated due to the state fluctuation of the excitation source itself, resulting in the decrease of the reliability and consistency of the diagnosis. By using the complete method claimed in the present application, the uncertainty factors of the measurement system itself are effectively isolated by dynamically self-calibrating the measurement reference, so that the judgment of the health degree of the bus physical channel can be stably and repeatedly directed to the physical state change of the channel itself.

[0042] To further verify the technical necessity of the online self-calibration and response normalization mechanism of the excitation pulse, the present application provides the following Comparative Example 1.

[0043] Comparative Example 1: To verify the necessity of the combination of the technical features that the excitation node itself measures the local echo and normalizes the far-end response in the method claimed in the present application, a comparative technical solution is constructed, which is completely consistent with Example 2 in all test conditions, hardware platforms, and basic processes, and the only difference is that this solution deliberately omits steps c (measuring the local echo by the excitation node itself to obtain the real-time probe fingerprint) and d (performing normalization operation) in Example 2, but instead adopts a more direct technical path that can be easily thought of by those skilled in the art, that is, directly comparing the far-end response signal (first electrical characteristic) measured by the listening node with a healthy state response signal obtained under the reference working condition, and judging the bus state accordingly; the test process of this comparative example is as follows, and the test platform is exactly the same as Example 2, that is, node A is set as the excitation node, node B as the listening node, and a precision resistance box is connected in series at the access branch of node B to simulate the progressive contact fault.

[0044] First, the temperature of the environmental test chamber is maintained at 25 The resistance value of the precision resistance box is set to 0Ω to simulate the healthy state of the bus, at this time, node A injects sub-threshold electrical excitation pulses into the bus, and node B measures the peak voltage of the far-end response signal, which is recorded as 155.4mV and stored locally in node B as the reference electrical characteristic for subsequent state comparison; then, to simulate an early physical layer fault that does not yet produce logic communication errors, the resistance value of the precision resistance box is set to 5Ω, and the environmental temperature is maintained at 25 The test process of step 2 is repeated; to verify the reliability of this comparative technical solution under real working conditions with excitation source state fluctuations, the temperature of the environmental test chamber is raised to 50 This temperature change is intended to simulate the real thermal-induced performance drift of the internal communication transceiver driver circuit of the unattended device due to its own power consumption and external environmental warming during typical daytime work, under this working condition, the test process of step 2 is repeated again, and the key data recorded during the test process is shown in Table 2.

[0045] Table 2: Test data table of the comparative technical solution under different working conditions.

[0046]

[0047] Test result analysis, according to the data in Table 2, in test 1 (25 ), this comparative technical solution can detect the channel degradation introduced by the 5Ω resistance and calculate a deviation of 8.4%, indicating a potential fault; however, in test 2 (50 Although the physical fault (5Ω resistance) of the bus channel remained unchanged, the pulse transmission intensity of excitation node A naturally weakened due to temperature drift in its internal circuitry caused by the increased ambient temperature. This resulted in a drop in the peak voltage of the response signal measured by listening node B to 131.9mV, causing the system-calculated deviation to surge from 8.4% to 15.1%. This experimental result demonstrates that without a mechanism for real-time status calibration of the excitation source and normalization of the response signal, the diagnostic system is completely unable to distinguish between the degradation of the bus channel itself and the state fluctuations of the excitation source—two entirely different physical processes. The calculated deviation is a confused result of the combined effect of these two variables, making it impossible for maintenance personnel to accurately classify the severity of the fault based on this value. For example, a deviation of 15.1% could simply be due to the 5Ω fault combined with the temperature drift effect, but it could also be due to a deviation at 25°C. The failure has deteriorated to approximately 12Ω, and this diagnostic uncertainty makes it impossible to set a stable and reliable degradation threshold for the system throughout its entire life cycle (especially when experiencing different seasonal temperature changes). Therefore, this comparative technical solution is not practical for unattended applications requiring high reliability.

[0048] Example 3: This example combines Figs. 1 to 3 This describes a fault testing method for a Flexray bus, such as... Fig. 1 As shown, a subthreshold electrical excitation pulse is injected into the bus by the excitation node. In the excitation and response capture stage, the excitation node measures the local echo signal generated by this pulse to obtain a real-time probe fingerprint. At the same time, the listening node measures the far-end response signal of the pulse to obtain the first electrical feature. The subsequent data normalization processing stage uses the real-time probe fingerprint to process the first electrical feature to output a normalized response fingerprint. In the fault status judgment stage, the normalized response fingerprint is compared with the reference electrical feature retrieved from the A1 reference feature storage. The comparison result can be used to generate updated reference features and form a single deviation result. If the result indicates an anomaly, a potential fault warning is sent to the remote operation and maintenance center. At the same time, the single deviation result is stored in the A2 deviation matrix and read and analyzed by the advanced diagnostic analysis stage to determine the fault location and root cause and report it to the remote operation and maintenance center.

[0049] like Fig. 2 As shown, the horizontal axis represents the number of measurements, and the vertical axis represents the deviation percentage. The dashed line indicates the preset degradation threshold, which is 2.4% in this example. The solid line represents the deviation values ​​obtained from each measurement. In the initial stage, the deviation fluctuates steadily below the degradation threshold, indicating that the bus physical layer is in a healthy state. However, as the number of measurements increases, the deviation shows a continuous upward trend and eventually crosses the degradation threshold.Fig. 3 As shown, the system is based on a Flexray physical bus, connecting multiple units including a master board node as a diagnostic scheduler, a payment module node, and a mechanical arm control node, wherein the master board node integrates a diagnostic analysis and scheduling module, and other nodes can perform excitation injection and response capture according to the schedule, and perform calculation according to a local reference feature library, and finally a warning generation and reporting module sends the diagnostic results and warning information to a remote operation and maintenance center through a remote communication link.

[0050] In order to ensure that the diagnostic results of the foregoing fault test method have high confidence and traceability, the initial health status of the specific network needs to be quantitatively calibrated before the Flexray bus network of a newly deployed unattended transaction device is put into long-term operation, and a series of key judgment parameters are set accordingly. This process aims to eliminate the measurement uncertainty introduced by different bus topologies, cable lengths and individual differences of node hardware. This embodiment describes a standardized parameter calibration procedure for determining reference electrical characteristics, degradation threshold and mutation threshold. The initial state is defined as the device has completed final assembly, the Flexray bus network has no logic errors confirmed by standard communication tests, and the device is placed in an electromagnetically shielded test environment with an ambient temperature of 25 The system is set to a dedicated offline calibration mode, in which the system performs a complete test process including sub-threshold electrical excitation pulse injection, real-time probe fingerprint acquisition, remote response signal measurement and normalization operation 1000 times continuously with a period of 100ms. In the 1000 continuous tests, the system records all 1000 normalized response fingerprint values from a specific excitation node to a specific listening node to form a sample set First, the system performs statistical analysis on the sample set to calculate the arithmetic mean and standard deviation , and the arithmetic mean μ is defined as the reference electrical characteristic of the path. In a specific numerical example, if μ = 0.521 is calculated, then 0.521 is stored as the health status reference of the path. Second, the setting of the degradation threshold, which balances the sensitivity to gradual slow degradation and the false alarm rate under normal measurement fluctuations. To statistically distinguish the persistent small deviation caused by physical degradation, the degradation threshold is set to , i.e. six times the standard deviation. If = 0.004 is calculated, then the degradation threshold is determined to be 6x0.004 = 0.024, i.e. when the deviation exceeds 2.4%, the system will consider that there may be gradual degradation.

[0051] Further, to determine the mutation threshold value for distinguishing progressive system aging from sudden potential failure , the system calculates the absolute value of the difference between two adjacent measurements based on the same sample set , forming a new sample set containing 999 difference values , i.e. , this set characterizes the normal jitter range of measurement results under healthy state; the system then calculates the mean value and standard deviation of this difference set , and sets the mutation threshold value as , i.e. the normal jitter mean value plus ten times the standard deviation, which aims to capture the response mutation caused by physical events such as instantaneous poor contact of the connector, which is a small probability event in statistical distribution; in a specific numerical example, if the calculation results are , , then is determined as 0.001+10x0.0005=0.006; by performing this parameter calibration procedure, each key threshold value in the system is uniquely determined by its own statistical characteristics under healthy state, rather than relying on pre-set fixed values; thereafter, the system exits the calibration mode and enters normal operation, and its fault diagnosis logic is based on this set of parameters tailored to its own physical characteristics with clear statistical basis.

[0052] Embodiment 5: In a complex Flexray bus network with high-density wiring and multi-branch topology of unattended transaction equipment, to realize the topological location tracing and root type judgment of potential failure, the system performs the rotating tomographic method of distributed channel response, which is completed through a preset detection sequence in which all nodes in the network take turns as excitation nodes; in a star topology network containing nodes A, B, C, and D, node A as the initial diagnostic scheduler is responsible for arranging and starting the detection sequence; in the first stage of the sequence, the diagnostic scheduler A sends a data frame containing specific instructions to command itself as the excitation node and the remaining all nodes B, C, and D as the listening nodes to perform a complete fault test process; after completing the measurement and comparison, each listening node reports the calculated deviation value to the scheduler A through a regular data frame; after completing the first stage, the scheduler A issues a second instruction to pass the role of excitation node to node B while itself turns into a listening node, and then node B as the excitation node repeats the above detection process and reports the obtained deviation value Report to the dispatcher A; this role rotation process in turn, until all nodes have served once the incentive node, finally, the dispatcher A in the local construction of a complete channel response deviation matrix.

[0053] In the detection sequence execution process, if the analysis result of the matrix shows that only the third column element, i.e. The numerical value continuously exceeds the degradation threshold, while other elements in the matrix are within the normal range, the system judges that the potential fault is highly localized to the receiving ability of node C or the physical connection point of its access bus; otherwise, if the analysis result shows that only the second row element, i.e. The numerical value continuously exceeds the degradation threshold, the system judges that the root cause of the potential fault is that the sending ability of node B has degraded. This matrix pattern-based correlation analysis changes the diagnosis from single-path evaluation to systematic analysis of the overall network topology health.

[0054] Example 6: In an outdoor self-service ticketing terminal deployed near the urban rail transit line, the internal Flexray bus network is continuously subjected to high-intensity, transient electromagnetic interference generated by passing trains, resulting in a harsh operating environment. In this scenario, to ensure the reliability of diagnostic data and expand the diagnostic dimension, the system cooperatively uses three methods: opportunistic window detection, parasitic wake-up monitoring, and DC baseline level analysis. First, the system uses the method for monitoring parasitic wake-up faults as described in the detailed description. All nodes in the network continuously monitor whether the bus level accidentally crosses the preset asymmetric voltage threshold when the bus is idle. The system background statistics show that the parasitic wake-up count rate increases by more than two orders of magnitude compared with the background value on weekdays within a 15-second time window of the passing rail train. This data objectively quantifies the severity of the electromagnetic environment in which the bus is located and is reported to the operation and maintenance system as a high-priority state flag. In view of the existence of such high-intensity external interference, the system executes the opportunistic window synchronization mechanism of the detection opportunity as described in the detailed description. Before initiating each sub-threshold electrical excitation pulse injection, the designated listening node first measures the current channel background noise level to obtain the channel disturbance index, which is compared with a quiet threshold determined based on a calibration procedure. During the passing of the rail train, the measured channel disturbance index continuously exceeds the quiet threshold, so the excitation node does not receive the detection permission signal and automatically gives up multiple active detection attempts within the window.

[0055] As a supplementary diagnostic means during active probing obstruction, the system performs the direct current baseline level analysis method as the specific embodiment, when the device performs the ticket printing operation, that is, the high frequency data frame of the driving printing motor node is carried on the Flexray bus, an idle node in the network as a monitoring unit, according to the deterministic scheduling table, in the time window when the printing motor node is sending data, the direct current baseline level of the data frame signal sent by it is sampled, the analysis result shows that only when the specific node sends data, the measured direct current baseline level has a negative offset of-80mV compared with the reference baseline level value in the healthy state, and the baseline level is normal when other nodes in the network send data, and this result points to the power supply unit of the printing motor node itself as the potential hardware failure source, rather than the bus channel itself.

[0056] It is obvious for those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application.

[0057] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not limiting, and although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A method for testing a Flexray bus for faults, applied to a Flexray bus network, characterized in that, The method comprises the following steps: Step a, by an excitation node in the Flexray bus network, injecting a sub-threshold electrical excitation pulse with a voltage amplitude lower than the effective data logic level threshold to a bus channel through controlling its communication transceiver when the Flexray bus network is in a preset non-data frame transmission state, wherein the signal characteristics of the sub-threshold electrical excitation pulse cannot be recognized as effective data frames by the Flexray communication controller of any node in the Flexray bus network, and only appear as network noise; Step b, by at least one listening node in the Flexray bus network, measuring and obtaining one or more first electrical characteristics of the response signal formed after the sub-threshold electrical excitation pulse propagates through the bus channel within the expected arrival time window of the pulse; Step c, by the excitation node itself, measuring the local echo signal of the sub-threshold electrical excitation pulse injected by itself to the bus channel through the receiving pin of its communication transceiver to obtain one or more second electrical parameters characterizing the actual parameters of the injected pulse itself, and defining the real-time probe fingerprint, during or after the injection of the sub-threshold electrical excitation pulse in step a; Step d, performing a normalization operation by the listening node, the input of the normalization operation being the first electrical characteristics and the real-time probe fingerprint, and the output being a normalized response fingerprint; Step e, comparing the normalized response fingerprint with a reference electrical characteristic, and judging whether there is a potential fault indicating physical layer state degradation in the bus channel based on the comparison result.

2. The method of claim 1, wherein, The reference electrical characteristic is obtained and stored by performing the same operations as steps a to d under the premise that the Flexray bus network is in a healthy state.

3. The method of claim 1, wherein, The preset non-data frame transmission state is the network idle time defined by the Flexray protocol.

4. The method of claim 1, wherein, The method further comprises: the listening node storing a set of baseline electrical signatures representing recent health status of the bus channel acquired from multiple historical measurements; the comparison of step e. comprises a statistical comparison of the normalized response fingerprint against the set of baseline electrical signatures to distinguish whether the real-time status change of the bus channel is due to a sudden potential fault or to a gradual system aging; and the status change is determined to be a health probe only when and if the condition is met, and the set of baseline electrical signatures is updated using the normalized response fingerprint; wherein, is the normalized response fingerprint currently acquired, is the most recent historical fingerprint in time from the set of baseline electrical signatures, is a sudden change threshold determined based on a statistical distribution of historical response data of the bus network in healthy status to discriminate sudden faults.

5. The method of claim 1, wherein, Steps a to e are repeatedly performed sequentially a plurality of times, and in each repeated performance, one of the different nodes in the Flexray bus network is selected as the stimulus node; the method further comprises: performing a correlation analysis on the plurality of judgment results obtained in the plurality of repeated performances, to construct a channel response deviation matrix, wherein the elements in the channel response deviation matrix represent the health status of the bus channel from the node to the node ; and according to the response pattern in the channel response deviation matrix, the topology location and root cause type of the potential fault are located.

6. The method of claim 5, wherein the FlexRay bus is a FlexRay bus having a communication cycle of 10 milliseconds. The topology location and root cause type of the potential fault are located, including: when the elements of the mth row of the channel response deviation matrix all indicate the existence of a potential fault, the root cause type of the potential fault is judged as a transmission capability fault of node m; when the elements of the mth column of the channel response deviation matrix all indicate the existence of a potential fault, the root cause type of the potential fault is judged as a receiving capability or access point fault of node m.

7. The method of claim 1, wherein, Before injecting the sub-threshold electrical excitation pulse in step a, it further comprises: measuring the background noise level on the bus channel by the listening node to obtain a channel disturbance index; sending a detection inquiry by the excitation node to the listening node; comparing the channel disturbance index with a preset quiet threshold by the listening node, and only when the channel disturbance index is lower than the quiet threshold, replying a detection permission signaling to the excitation node; and the execution of step a is subject to the precondition that the excitation node receives the detection permission signaling.

8. The method of claim 1, wherein, The method further comprises: when the Flexray bus network is in the data frame transmission state, measuring, by one or more nodes in the network, a direct current baseline level of a data frame signal sent by a preset sending node within a time window when the preset sending node is sending the data frame according to a deterministic schedule table of the Flexray protocol, to obtain a measured baseline level value; comparing the measured baseline level value with a baseline level value representing a healthy state of the preset sending node stored in advance, and judging whether the preset sending node has a potential hardware fault based on a comparison result.

9. The method of claim 1, wherein, When the Flexray bus network is in the preset non-data frame transmission state and a time period in which step a is not performed, the method further comprises: monitoring, by at least one node in the network, whether a level of the bus channel unexpectedly crosses one or more preset asymmetric voltage thresholds by using a comparator in a microcontroller of the node, wherein the asymmetric voltage thresholds include an upper threshold higher than a voltage of a normal bus idle level and a lower threshold lower than the voltage of the normal bus idle level; and judging whether the bus channel has a parasitic wake-up fault caused by external interference based on a frequency of events in which the level of the bus channel crosses the asymmetric voltage thresholds per unit time.

10. The method of claim 1, wherein, The comparison in step e is specifically calculating an Euclidean distance or a correlation coefficient between the normalized response fingerprint and the reference electrical characteristic to obtain a deviation value, and the judging is specifically comparing the deviation value with a preset degradation threshold, and generating a pre-warning signal indicating a potential fault when the deviation value continuously exceeds the degradation threshold.

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