阅读说明：本技术 一种加速度传感器故障诊断方法及系统 (Acceleration sensor fault diagnosis method and system ) 是由 尚敬 侯招文 郭维 徐绍龙 甘韦韦 陈启会 刘良杰 许义景 王文韬 陈科 易笛 于 2020-06-30 设计创作，主要内容包括：本发明公开揭示了一种加速度传感器故障诊断方法和系统,应用于悬浮系统,所述方法包括：采集加速度信号和间隙信号；在特定频段对所述加速度信号和所述间隙信号进行处理,获得偏差值；根据所述偏差值与阈值比较,获得加速度传感器故障信息；当检测到所述加速度传感器发生故障,进一步判断悬浮系统中其他加速度传感器是否发生故障,若所述其他加速度传感器无故障,采用所述其他加速度传感器采集的信号继续用于所述悬浮系统的控制,若所述其他加速度传感器发生故障,切换至不使用所述加速度传感器的控制。本发明可以在不增加任何硬件成本情况下有效诊断出加速度传感器故障。(The invention discloses a fault diagnosis method and a fault diagnosis system for an acceleration sensor, which are applied to a suspension system, wherein the method comprises the following steps: collecting an acceleration signal and a gap signal; processing the acceleration signal and the gap signal in a specific frequency band to obtain a deviation value; comparing the deviation value with a threshold value to obtain fault information of the acceleration sensor; when the acceleration sensor is detected to be in fault, further judging whether other acceleration sensors in the suspension system are in fault, if the other acceleration sensors are not in fault, adopting signals acquired by the other acceleration sensors to continue to be used for controlling the suspension system, and if the other acceleration sensors are in fault, switching to control without using the acceleration sensors. The method can effectively diagnose the faults of the acceleration sensor without increasing any hardware cost.)

1. An acceleration sensor fault diagnosis method is applied to a suspension system, and is characterized by comprising the following steps:

acquiring an acceleration signal and a gap signal;

step two, processing the acceleration signal and the gap signal at a specific frequency band to obtain a deviation value;

step three, obtaining fault information of the acceleration sensor according to the comparison between the deviation value and a threshold value;

and step four, when the acceleration sensor is detected to be in fault, further judging whether other acceleration sensors in the suspension system are in fault, if the other acceleration sensors are not in fault, adopting signals acquired by the other acceleration sensors to continue to be used for controlling the suspension system, and if the other acceleration sensors are in fault, switching to control without using the acceleration sensors.

2. The acceleration sensor fault diagnosis method according to claim 1, characterized in that the second step further comprises:

low pass filtering the acceleration signal and the gap signal;

high-pass filtering the low-pass filtered acceleration signal and the gap signal;

integrating the high-pass filtered acceleration signal, and differentiating the high-pass filtered gap signal;

the deviation value is an absolute value of a difference between the integrated acceleration signal and the differentiated gap signal.

3. The acceleration sensor malfunction diagnosis method according to claim 2,

the specific frequency band is a frequency band between the turning frequency ranges of the low-pass filter and the high-pass filter.

4. The acceleration sensor malfunction diagnosis method according to claim 3,

the turning frequency of the low-pass filter is 100-900 Hz, and the turning frequency of the high-pass filter is 0.5-20 Hz.

5. The acceleration sensor malfunction diagnosis method according to claim 4,

in step three, when the deviation value is smaller than the threshold value, the acceleration sensor has no fault;

and when the deviation value is larger than the threshold value, the acceleration sensor is in failure.

6. The acceleration sensor malfunction diagnosis method according to claim 5,

carrying out low-pass filtering on the acceleration signal and the gap signal by adopting the same low-pass filter;

and carrying out high-pass filtering on the acceleration signal and the gap signal after low-pass filtering by adopting the same high-pass filter.

7. An acceleration sensor fault diagnosis system characterized by comprising:

the signal acquisition module is used for acquiring an acceleration signal and a gap signal of an acceleration sensor in the suspension system;

the signal processing module is used for processing the acceleration signal and the gap signal at a specific frequency band to obtain a deviation value;

the diagnosis and judgment module is used for comparing the deviation value with a threshold value and judging whether the acceleration sensor has a fault according to a comparison result;

and the fault adjusting module is used for further judging whether other acceleration sensors in the suspension system have faults or not when detecting that the acceleration sensor has faults, adopting signals acquired by the other acceleration sensors to continue to be used for controlling the suspension system if the other acceleration sensors have no faults, and switching to control without using the acceleration sensors if the other acceleration sensors have faults.

8. The acceleration sensor malfunction diagnosis system according to claim 7,

the signal processing module further comprises:

a low-pass filter that low-pass filters the acceleration signal and the gap signal;

a high-pass filter for high-pass filtering the acceleration signal and the gap signal after low-pass filtering;

the integration and differentiation processing unit is used for integrating the acceleration signal subjected to high-pass filtering and differentiating the gap signal subjected to high-pass filtering;

a subtraction unit that subtracts the difference between the integrated acceleration signal and the differentiated gap signal from the integrated acceleration signal.

9. The acceleration sensor malfunction diagnosis system according to claim 8,

the specific frequency band is a frequency band between a range of turning frequencies of the low-pass filter and the high-pass filter.

10. The acceleration sensor malfunction diagnosis system according to claim 9,

the turning frequency of the low-pass filter is 100-900 Hz, and the turning frequency of the high-pass filter is 0.5-20 Hz.

11. The acceleration sensor malfunction diagnosis system according to claim 10,

when the diagnosis judgment module carries out comparison, when the deviation value is smaller than the threshold value, the acceleration sensor has no fault;

and when the deviation value is larger than the threshold value, the acceleration sensor is in failure.

12. The acceleration sensor malfunction diagnosis system according to claim 11,

carrying out low-pass filtering on the acceleration signal and the gap signal by adopting the same low-pass filter;

and carrying out high-pass filtering on the acceleration signal and the gap signal after low-pass filtering by adopting the same high-pass filter.

Technical Field

The invention relates to the field of levitation control of a maglev train, in particular to a fault diagnosis method and system for an acceleration sensor.

Background

As one of the key technologies of a magnetic levitation train, a levitation control technology is a foundation stone for realizing stable operation of the train. If the stable running of the train can not be realized, all the advantages of the magnetic-levitation train become the talk. The criticality of the levitation control technology is self-evident, and the performance of the levitation guidance control system directly affects the stability, safety and comfort of the levitation train.

For an electromagnetic levitation (EMS) type magnetic levitation system, the system is an unstable system, and feedback must be introduced to achieve stable levitation. The feedback signals commonly used in the existing magnetic suspension system are mainly gap signals, gap differential signals and current signals, and the suspension of the train is realized through a PID algorithm. The reasonable arrangement of the gap differential terms is the key for realizing the high-performance control of the suspension system.

Direct differentiation using the gap signal introduces significant noise into the system due to gap signal measurement accuracy and noise issues. For this purpose, the differential of the gap signal is usually obtained by means of acceleration integration. Because the acceleration sensor is installed on the electromagnet, the running environment is poor, and the impact and the vibration which need to be born are large, so that the acceleration sensor has certain probability of failure. The commercial operation experience of the existing magnetic suspension line also shows that the failure rate of the acceleration sensor in the suspension system is higher. If no effective measures are taken after the failure of the acceleration sensor, the control may be failed. For this reason, an acceleration sensor failure diagnosis is required.

Currently, the basic method for diagnosing the fault of the acceleration sensor is to judge through the relationship between the acceleration signal and the gap signal. Theoretically, when operating on a straight track, the integral signal of the acceleration sensor and the differential signal of the gap signal are identical. However, the following problems should be noted during the actual operation:

firstly, the acceleration signal contains the gravity effect, and inevitable direct current offset also occurs in the sampling process, so that real integral cannot be realized, and parameter selection during blocking integral is a difficult problem;

secondly, when the gap signal is subjected to differential operation, great high-frequency noise exists, so that high-frequency filtering is required;

third, there is a range of frequency response for the acceleration sensor and the gap sensor themselves.

Therefore, the conventional method of regarding the acceleration sensor and the gap signal sensor as ideal sensors and performing the acceleration sensor diagnosis based on the ideal sensors has certain misjudgment and missed judgment.

Disclosure of Invention

It is to be understood that both the foregoing general description and the following detailed description of the present disclosure are exemplary and explanatory and are intended to provide further explanation of the disclosure as claimed.

The purpose of the invention is: the fault diagnosis method and the fault diagnosis system for the acceleration sensor are provided, and the acceleration sensor is rapidly processed after the fault of the acceleration sensor is diagnosed, so that the fault of the magnetic suspension train caused by system divergence is avoided, and the availability of the system is improved.

In order to achieve the above object, the present invention discloses an acceleration sensor fault diagnosis method applied to a levitation system, wherein the method comprises:

acquiring an acceleration signal and a gap signal;

step two, processing the acceleration signal and the gap signal at a specific frequency band to obtain a deviation value;

step three, obtaining fault information of the acceleration sensor according to the comparison between the deviation value and a threshold value;

and step four, when the acceleration sensor is detected to be in fault, further judging whether other acceleration sensors in the suspension system are in fault, if the other acceleration sensors are not in fault, adopting signals acquired by the other acceleration sensors to continue to be used for controlling the suspension system, and if the other acceleration sensors are in fault, switching to control without using the acceleration sensors.

Preferably, the invention further discloses an acceleration sensor fault diagnosis method, which is characterized in that the second step further comprises:

low pass filtering the acceleration signal and the gap signal;

high-pass filtering the low-pass filtered acceleration signal and the gap signal;

integrating the high-pass filtered acceleration signal, and differentiating the high-pass filtered gap signal;

the deviation value is an absolute value of a difference between the integrated acceleration signal and the differentiated gap signal.

Preferably, the present invention further discloses a method for diagnosing a failure of an acceleration sensor, wherein the specific frequency band is a frequency band between the turning frequency ranges of the low-pass filter and the high-pass filter.

Preferably, the invention further discloses an acceleration sensor fault diagnosis method, which is characterized in that the turning frequency of the low-pass filter is 100-900 Hz, and the turning frequency of the high-pass filter is 0.5-20 Hz.

Preferably, the invention further discloses a method for diagnosing faults of the acceleration sensor, which is characterized in that in the third step, when the deviation value is smaller than the threshold value, faults do not exist in the acceleration sensor;

and when the deviation value is larger than the threshold value, the acceleration sensor is in failure.

Preferably, the invention further discloses an acceleration sensor fault diagnosis method, which is characterized in that the same low-pass filter is adopted to carry out low-pass filtering on the acceleration signal and the gap signal;

and carrying out high-pass filtering on the acceleration signal and the gap signal after low-pass filtering by adopting the same high-pass filter.

The invention also discloses an acceleration sensor fault diagnosis system, which is characterized by comprising the following components:

the signal acquisition module is used for acquiring an acceleration signal and a gap signal of an acceleration sensor in the suspension system;

the signal processing module is used for processing the acceleration signal and the gap signal at a specific frequency band to obtain a deviation value;

the diagnosis and judgment module is used for comparing the deviation value with a threshold value and judging whether the acceleration sensor has a fault according to a comparison result;

and the fault adjusting module is used for further judging whether other acceleration sensors in the suspension system have faults or not when detecting that the acceleration sensor has faults, adopting signals acquired by the other acceleration sensors to continue to be used for controlling the suspension system if the other acceleration sensors have no faults, and switching to control without using the acceleration sensors if the other acceleration sensors have faults.

Preferably, the invention further discloses and discloses a fault diagnosis system of the acceleration sensor, which is characterized in that,

the signal processing module further comprises:

a low-pass filter that low-pass filters the acceleration signal and the gap signal;

a high-pass filter for high-pass filtering the acceleration signal and the gap signal after low-pass filtering;

the integration and differentiation processing unit is used for integrating the acceleration signal subjected to high-pass filtering and differentiating the gap signal subjected to high-pass filtering;

a subtraction unit that subtracts the difference between the integrated acceleration signal and the differentiated gap signal from the integrated acceleration signal.

Preferably, the invention further discloses and discloses a fault diagnosis system of the acceleration sensor, which is characterized in that,

the specific frequency band is a frequency band between a range of turning frequencies of the low-pass filter and the high-pass filter.

Preferably, the invention further discloses and discloses a fault diagnosis system of the acceleration sensor, which is characterized in that,

the turning frequency of the low-pass filter is 100-900 Hz, and the turning frequency of the high-pass filter is 0.5-20 Hz.

Preferably, the invention further discloses and discloses a fault diagnosis system of the acceleration sensor, which is characterized in that,

when the diagnosis judgment module carries out comparison, when the deviation value is smaller than the threshold value, the acceleration sensor has no fault;

and when the deviation value is larger than the threshold value, the acceleration sensor is in failure.

Preferably, the invention further discloses and discloses a fault diagnosis system of the acceleration sensor, which is characterized in that,

carrying out low-pass filtering on the acceleration signal and the gap signal by adopting the same low-pass filter;

and carrying out high-pass filtering on the acceleration signal and the gap signal after low-pass filtering by adopting the same high-pass filter.

By applying the scheme provided by the invention, the fault of the acceleration sensor can be effectively diagnosed, and meanwhile, the diagnosis method provided by the invention does not need to increase any hardware cost, is simple to realize and can be embedded into a control chip of a suspension control system.

Drawings

Embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. Reference will now be made in detail to the preferred embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts. Further, although the terms used in the present disclosure are selected from publicly known and used terms, some of the terms mentioned in the specification of the present disclosure may be selected by the applicant at his or her discretion, the detailed meanings of which are described in relevant parts of the description herein. Furthermore, it is required that the present disclosure is understood, not simply by the actual terms used but by the meaning of each term lying within.

The above and other objects, features and advantages of the present invention will become apparent to those skilled in the art from the following detailed description of the present invention with reference to the accompanying drawings.

Fig. 1 is a schematic flow chart of a fault diagnosis method for an acceleration sensor according to an embodiment of the present invention;

fig. 2 is a block diagram of components of an acceleration sensor fault diagnosis system according to an embodiment of the present application.

Reference numerals

21-signal acquisition module

22-signal processing module

221-low pass filter

222-high pass filter

223-integration and differentiation processing unit

224-subtraction unit

23-diagnostic judgment Module

24-fault elimination module

Detailed Description

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings used in the description of the embodiments will be briefly introduced below. It is obvious that the drawings in the following description are only examples or embodiments of the application, from which the application can also be applied to other similar scenarios without inventive effort for a person skilled in the art. Unless otherwise apparent from the context, or otherwise indicated, like reference numbers in the figures refer to the same structure or operation.

As used in this application and the appended claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.

The relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present application unless specifically stated otherwise. Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description. Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate. In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.

In the description of the present application, it is to be understood that the orientation or positional relationship indicated by the directional terms such as "front, rear, upper, lower, left, right", "lateral, vertical, horizontal" and "top, bottom", etc., are generally based on the orientation or positional relationship shown in the drawings, and are used for convenience of description and simplicity of description only, and in the case of not making a reverse description, these directional terms do not indicate and imply that the device or element being referred to must have a particular orientation or be constructed and operated in a particular orientation, and therefore, should not be considered as limiting the scope of the present application; the terms "inner and outer" refer to the inner and outer relative to the profile of the respective component itself.

Spatially relative terms, such as "above … …," "above … …," "above … …," "above," and the like, may be used herein for ease of description to describe one device or feature's spatial relationship to another device or feature as illustrated in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures. For example, if a device in the figures is turned over, devices described as "above" or "on" other devices or configurations would then be oriented "below" or "under" the other devices or configurations. Thus, the exemplary term "above … …" can include both an orientation of "above … …" and "below … …". The device may be otherwise variously oriented (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.

It should be noted that the terms "first", "second", and the like are used to define the components, and are only used for convenience of distinguishing the corresponding components, and the terms have no special meanings unless otherwise stated, and therefore, the scope of protection of the present application is not to be construed as being limited. Further, although the terms used in the present application are selected from publicly known and used terms, some of the terms mentioned in the specification of the present application may be selected by the applicant at his or her discretion, the detailed meanings of which are described in relevant parts of the description herein. Further, it is required that the present application is understood not only by the actual terms used but also by the meaning of each term lying within.

Flow charts are used herein to illustrate operations performed by systems according to embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, various steps may be processed in reverse order or simultaneously. Meanwhile, other operations are added to or removed from these processes.

According to the introduction of the background art, in the fault diagnosis of the acceleration sensor, an acceleration signal collected by the acceleration sensor is set to be a (t), and a gap signal collected is set to be g (t).

If the gravity component in the acceleration signal a (t) is removed, the acceleration signal a after the gravity component is removed is recorded₁(t) is:

a₁(t)＝a(t)-g₀ (1)

wherein g is₀Is a gravity-related component.

If the influence of factors such as the slope and the track irregularity is not considered, the acceleration signal a after the gravity component is removed can be considered₁There is a relationship of two differentiations between (t) and the acquired gap signal g (t), namely:

thus can be obtained by: a is₁Integral of (t) and derivative of g (t)The relationship between them determines whether there is an acceleration sensor failure.

However, in practical applications, the acceleration signal a (t) acquired by the acceleration sensor also contains a component of gravity, which is affected by the geographical position, the track state (curve, ramp), and the like, and meanwhile, a certain dc offset cannot be avoided in the acquisition process of the sensor signal, so that a real integral cannot be realized. Secondly, there is noise in the gap signal g (t), so that directly performing the differential operation introduces a lot of noise.

Furthermore, the acceleration sensor and the gap sensor themselves have a certain frequency response range. Therefore, it is easy to make an erroneous determination by directly comparing the integral signal of the acceleration signal a (t) and the differential signal of the gap signal g (t).

In order to achieve normal operation control, the acceleration signal a (t) and the clearance signal g (t) are accurate in a certain frequency range, and the influence of the track gradient can be eliminated.

Therefore, the invention proposes that the information of the acceleration signal a (t) and the gap signal g (t) in a specific frequency band can be used for fault diagnosis of the acceleration sensor, which is the innovative point of the invention.

The specific scheme mentioned below should be regarded as a specific implementation, and in practical application, those skilled in the art can easily think of other real-time modes, such as applying filters of different orders when performing low-frequency filtering, or combining a low-pass filter and a high-pass filter into a band-pass filter instead.

The following specifically describes the flow of fault diagnosis according to the present invention with reference to a flow diagram of a fault diagnosis method for an acceleration sensor according to an embodiment shown in fig. 1.

It should be noted that the following embodiments are merely preferred embodiments, and other embodiments utilizing the concepts of the present application should also fall within the scope of the present patent.

Acquiring an acceleration signal and a gap signal;

the method comprises the steps of acquiring an acceleration signal and a gap signal by utilizing an existing sensor in a suspension system, recording the acquired acceleration signal as a (t), and recording the acquired gap signal as g (t).

Step two, signal processing and difference value calculation are carried out, and the specific processing mode comprises the following steps:

step 21, performing low-pass filtering processing on the acquired gap signals g (t) and the acquired acceleration signals a (t);

and (3) carrying out low-pass filtering processing on the gap signals g (t) and the acceleration signals a (t), wherein the turning frequency of the low-pass filter can be selected according to actual needs and is generally 100-900 Hz.

Typical low pass filters are:

wherein, ω is₁For corner frequency, ω is₁Can be selected according to the actual situation, and is generally 2 π × 100 to 2 π × 900.

It should be noted that the transfer function H of the low-pass filter₁The(s) can be varied, and the selection of them is different without affecting the innovation point of the present invention, but the low-pass filters for processing the gap signal and the acceleration signal should be the same, that is, only the same low-pass filter is used for processing to ensure the same following difference, otherwise, the misjudgment may be caused. Recording the processed acceleration signal as a_m(t) the processed gap signal is g_m(t)。

Step 22, the gap signal g after the low-pass filtering processing is processed_m(t) and acceleration signal a_m(t) performing high-pass filtering;

typical high-pass filters are:

wherein the content of the first and second substances,

ω₂＝2πf₂ (5)

wherein f is₂The turning frequency is generally selected to be 0.5-20 Hz, so as to derive the turning frequency parameter.

The turning frequency of the high-pass filter can be selected according to actual needs, and the transfer function H of the high-pass filter₂(s) can vary widely.

The difference between the two methods does not affect the innovation point of the invention, but the acceleration signal a is processed_m(t) and gap signal g_m(t) the high-pass filter should be identical, i.e. only the same high-pass filter is used to ensure the same subsequent difference, otherwiseErroneous judgment can be caused.

Recording acceleration signal a_m(t) the signal after the high-pass filtering is a_n(t), gap signal g_m(t) the signal after the high-pass filtering is g_n(t)。

Step 23, integration and differentiation processing;

signal a after processing acceleration signal_n(t) performing an integration process using a transfer function of:

signal g after gap signal processing_n(t) performing a differential process using a transfer function of:

H_g3(s)＝s (7)

thereby, the acceleration signals a after the integral processing are respectively obtained_p(t) and gap signal g_p(t)。

Integrating the steps 21 to 23, unifying the steps into a signal processing link, which is summarized as a link for processing the acceleration signal:

the processing links of the gap signals are as follows:

H_g(s)＝sH₁(s)H₂(s) (9)

step 24, calculating a difference value;

recording the integrated acceleration signal a_p(t) and gap signal g_pThe absolute value of the difference between (t) is Δ:

Δ＝|a_p(t)-g_p(t)| (10)

thirdly, judging the fault according to the result;

the deviation value delta obtained by the previous step and a threshold value delta are calculated_thA comparison is made.

Note that the threshold value Δ_thCan be selected fromThe method is obtained according to experience or experimental tests, two aspects of accuracy and rapidity are mainly considered, and the method is related to parameters such as sensor characteristics, track states, signal sampling precision and the like, and the most important is the sensor characteristics.

If the threshold value is too small, misjudgment may exist, and if the threshold value is too large, failure post-processing is not facilitated, and system availability is not facilitated.

When the deviation value delta is less than or equal to delta_thWhen the acceleration sensor is detected to be in the fault state, the corresponding acceleration sensor is indicated to be in the fault state;

when the deviation value delta is greater than delta_thAnd if so, indicating that the corresponding acceleration sensor has a fault, and performing corresponding fault post-processing, namely entering the step four.

And step four, when a certain acceleration sensor is detected to be out of order, other signals are adopted to replace the signal of the acceleration sensor immediately. If a plurality of acceleration sensors exist in the system, whether other acceleration sensors have faults or not can be further judged, and if the other acceleration sensors do not have the faults, signals collected by the other acceleration sensors can be continuously used for controlling and judging the suspension system. Otherwise, the control system may be switched to a control method that does not use an acceleration sensor. In this case, although the performance of the system may be degraded, the conditional operation (e.g., speed limit) of the system can be maintained, thereby avoiding serious effects.

Fig. 2 is a block diagram showing the components of a fault post-processing system for an acceleration sensor according to the present invention.

The system comprises:

the signal acquisition module 21 acquires an acceleration signal and a clearance signal by using an existing sensor in the suspension system, and records the acquired acceleration signal as a (t) and the acquired clearance signal as g (t).

The signal processing module 22 sequentially performs low-pass filtering on the acceleration signal and the gap signal through a low-pass filter 221, performs high-pass filtering through a high-pass filter 222, performs integration and differentiation processing through an integration and differentiation processing unit 223, and obtains an absolute value of a difference between the acceleration signal and the gap signal as a deviation value through a subtraction unit 224;

the diagnosis and judgment module 23 compares the deviation value with a threshold value, and judges whether the acceleration sensor has a fault according to a comparison result;

and the fault adjusting module 24 is used for making adjustment for acquiring signals of other acceleration sensors or switching to control without using the acceleration sensors in combination with the fault conditions of the other acceleration sensors when detecting that the acceleration sensors have faults.

By applying the scheme provided by the invention, the fault of the acceleration sensor can be effectively diagnosed, and meanwhile, the diagnosis method provided by the invention does not need to increase any hardware cost, is simple to realize and can be embedded into a control chip of a suspension control system.

The invention provides a fault diagnosis method and a fault diagnosis system for an acceleration sensor, which have the core idea that the acceleration sensor is diagnosed by utilizing the relation between a gap signal and an acceleration signal in a specific frequency band, so that the problem of misdiagnosis in the conventional diagnosis method can be avoided.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing disclosure is by way of example only, and is not intended to limit the present application. Various modifications, improvements and adaptations to the present application may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present application and thus fall within the spirit and scope of the exemplary embodiments of the present application.

Also, this application uses specific language to describe embodiments of the application. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the present application is included in at least one embodiment of the present application. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the present application may be combined as appropriate.

Similarly, it should be noted that in the preceding description of embodiments of the application, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to require more features than are expressly recited in the claims. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the number allows a variation of ± 20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximations that may vary depending upon the desired properties of the individual embodiments. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.

Although the present application has been described with reference to the present specific embodiments, it will be recognized by those skilled in the art that the foregoing embodiments are merely illustrative of the present application and that various changes and substitutions of equivalents may be made without departing from the spirit of the application, and therefore, it is intended that all changes and modifications to the above-described embodiments that come within the spirit of the application fall within the scope of the claims of the application.