Synchronous acquisition error detection method and system of multi-channel dynamic data acquisition system

Abstract

The invention relates to a synchronous acquisition error detection method and system for a multi-channel dynamic data acquisition system. The method comprises: a) generating a sinusoidal input signal by a signal generator; b) inputting the sine input signal into all channels of a multi-channel dynamic data acquisition system; c) acquiring and recording an output signal of each channel by a multi-channel dynamic data acquisition system; d) taking a first channel of the multi-channel dynamic data acquisition system as a reference channel, and calculating a cross-power spectral density function between an output signal of each of other channels except the first channel and an output signal of the first channel; e) for each of the cross-power spectral density functions, extracting a phase angle at the frequency of the sinusoidal input signal; f) calculating a delay value with respect to the first channel for each of the remaining channels other than the first channel based on each of the phase angles; and g) determining a synchronous acquisition error based on the delay value.

Description

Technical Field

[0001] The present disclosure relates to the field of aeroengines, and in particular to a method for detecting synchronous acquisition errors of a multi-channel dynamic data acquisition system. Background Art

[0002] During the engine test, a dynamic data acquisition system is required to collect dynamic signals such as vibration, dynamic strain, dynamic pressure, and rotation speed of the aircraft engine. For large aircraft engines, the test often requires hundreds of dynamic channels to synchronously collect the above signals at a sampling rate of more than 50kHz. Multi-channel (for example, 256 channels) dynamic data acquisition systems are often composed of multiple data acquisition modules in series, or require additional synchronization controllers to achieve synchronous acquisition control between multiple data acquisition modules. At high sampling rates (for example, above 50kHz), the stability of the multi-channel data acquisition system decreases with the increase of data acquisition modules, and the synchronous acquisition error between different channels will increase accordingly.

[0003] The present disclosure has been improved with respect to but not limited to the above-mentioned factors. Summary of the invention

[0004] To this end, the present disclosure provides a synchronous acquisition error detection method and system for a multi-channel dynamic data acquisition system, which is used to accurately evaluate the synchronous acquisition error between the channels of the multi-channel dynamic data acquisition system, so that it can be determined whether the constructed dynamic data acquisition system meets the dynamic test requirements before the aircraft engine test, and the reliability of the test data is guaranteed. The synchronous acquisition error detection method and system for a multi-channel dynamic data acquisition system disclosed in the present disclosure can calculate the time difference of homologous deterministic signals collected on different channels. Preferably, the synchronous acquisition error detection method and system for a multi-channel dynamic data acquisition system disclosed in the present disclosure can eliminate random errors through multiple tests, thereby obtaining the statistical characteristics of the synchronous acquisition errors of each channel.

[0005] Therefore, the present invention proposes a sinusoidal signal phase difference estimation method based on the signal cross-power spectral density function, and converts the phase difference into a synchronization time error, thereby extracting the synchronization acquisition time error between data acquisition channels; proposes applying the statistical error evaluation method of the Gaussian statistical model to the synchronization error evaluation of the data acquisition system, thereby comprehensively evaluating the synchronization acquisition error of the data acquisition system and reducing the uncertainty of the test evaluation; establishes a set of synchronization error verification methods and systems for dynamic data acquisition systems, which covers the use of test equipment, the calculation of synchronization errors between channels and the evaluation of the overall error of the data acquisition system.

[0006] According to a first aspect of the present disclosure, a synchronous acquisition error detection method for a multi-channel dynamic data acquisition system is provided, the method comprising: a) generating a sinusoidal input signal by a signal generator; b) inputting the sinusoidal input signal into all channels of the multi-channel dynamic data acquisition system; c) acquiring and recording the output signal of each channel by the multi-channel dynamic data acquisition system; d) taking the first channel of the multi-channel dynamic data acquisition system as a reference channel, and calculating the cross-power spectral density function between the output signal of each of the remaining channels except the first channel and the output signal of the first channel; e) for each of the cross-power spectral density functions, extracting the phase angle at the frequency of the sinusoidal input signal; f) calculating the delay value of each of the remaining channels except the first channel relative to the first channel based on each of the phase angles; and g) determining the synchronous acquisition error based on the delay value.

[0007] According to an embodiment, the frequency of the sinusoidal input signal is a single frequency and is less than half of the sampling frequency of the multi-channel dynamic data acquisition system.

[0008] According to another embodiment, the frequency of the sinusoidal input signal includes a plurality of frequencies, and each of the plurality of frequencies is less than half of a sampling frequency of the multi-channel dynamic data acquisition system.

[0009] According to yet another embodiment, extracting the phase angle at a frequency of the sinusoidal input signal comprises extracting the phase angle at each frequency of the plurality of frequencies of the sinusoidal input signal.

[0010] According to yet another embodiment, before step g), steps a)-f) are repeated multiple times.

[0011] According to yet another embodiment, the synchronization acquisition error includes a maximum value among the delay values, a mean value and a standard deviation of the delay values, and a 95% confidence interval of the delay values.

[0012] According to yet another embodiment, the 95% confidence interval of the delay value is obtained assuming that the data is normally distributed.

[0013] According to yet another embodiment, the method further comprises issuing an alarm if the synchronization acquisition error exceeds a predetermined range.

[0014] According to a second aspect of the present disclosure, a synchronous acquisition error detection system for a multi-channel dynamic data acquisition system is provided, the system comprising: a signal generator, the signal generator being arranged to: generate a sinusoidal input signal; and input the sinusoidal input signal into all channels of the multi-channel dynamic data acquisition system; and a detector, the detector being arranged to: receive an output signal of each channel of the multi-channel dynamic data acquisition system from the multi-channel dynamic data acquisition system; use a first channel of the multi-channel dynamic data acquisition system as a reference channel, and calculate a cross-power spectral density function between an output signal of each of the remaining channels except the first channel and an output signal of the first channel; for each of the cross-power spectral density functions, extract a phase angle at the frequency of the sinusoidal input signal; calculate a delay value of each of the remaining channels except the first channel relative to the first channel based on each of the phase angles; and determine the synchronous acquisition error based on the delay value.

[0015] According to an embodiment, the frequency of the sinusoidal input signal is a single frequency and is less than half of the sampling frequency of the multi-channel dynamic data acquisition system.

[0016] According to another embodiment, the frequency of the sinusoidal input signal includes a plurality of frequencies, and each of the plurality of frequencies is less than half of a sampling frequency of the multi-channel dynamic data acquisition system.

[0017] According to yet another embodiment, extracting the phase angle at a frequency of the sinusoidal input signal comprises extracting the phase angle at each frequency of the plurality of frequencies of the sinusoidal input signal.

[0018] According to yet another embodiment, the synchronization acquisition error includes a maximum value among the delay values, a mean value and a standard deviation of the delay values, and a 95% confidence interval of the delay values.

[0019] According to yet another embodiment, the 95% confidence interval of the delay value is obtained assuming that the data is normally distributed.

[0020] According to yet another embodiment, the detector is further arranged to issue an alarm if the synchronization acquisition error exceeds a predetermined range.

[0021] Aspects generally include methods, apparatus, systems, computer program products, and processing systems substantially as described herein with reference to and as illustrated by the accompanying figures.

[0022] The foregoing has broadly outlined the features and technical advantages of examples according to the present disclosure so that the following detailed description can be better understood. Additional features and advantages will be described hereinafter. The disclosed concepts and specific examples can be easily used as the basis for modifying or designing other structures for implementing the same purpose as the present disclosure. Such equivalent constructions do not depart from the scope of the appended claims. The characteristics of the concepts disclosed herein, both in terms of their organization and method of operation, and the associated advantages will be better understood by considering the following description in conjunction with the accompanying drawings. Each of the accompanying drawings is provided for illustration and description purposes and does not define limitations on the claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to understand in detail the manner in which the above-stated features of the present disclosure are used, the above briefly summarized content may be described in more detail with reference to various aspects, some of which are illustrated in the accompanying drawings. However, it should be noted that the accompanying drawings illustrate only certain typical aspects of the present disclosure and should not be considered to limit its scope, as the description may allow for other equally effective aspects. The same reference numerals in different drawings may identify the same or similar elements.

[0024] Figure 1 is a flow chart of a synchronous acquisition error detection method of a multi-channel dynamic data acquisition system according to an exemplary embodiment of the present disclosure;

[0025] Figure 2 is a schematic block diagram of a synchronous acquisition error detection system of a multi-channel dynamic data acquisition system according to an exemplary embodiment of the present disclosure;

[0026] Figure 3 is a schematic diagram of an output signal collected according to an example implementation of the present disclosure;

[0027] Figure 4 is a schematic diagram of a cross-spectral power spectral density function obtained by plotting it in a Bode diagram according to an example implementation of the present disclosure; and

[0028] Figure 5 is a schematic diagram of a time synchronization error estimation value according to an example implementation of the present disclosure. DETAILED DESCRIPTION

[0029] Terminology explanation:

[0030] Multi-channel dynamic data acquisition system: In dynamic testing, multiple channels synchronously collect electrical signals generated by sensors such as speed, vibration, dynamic strain, and pulsating pressure, and convert analog signals into digital signals, and then transmit and store the digital signals.

[0031] Synchronous acquisition error: refers to the synchronization error between signals acquired by different channels when the dynamic data acquisition system samples multiple channel analog voltages at the set sampling rate at the same time;

[0032] Cross-power spectral density function: Fourier transform of the cross-correlation function, which describes the change of power between signals in a unit frequency band with frequency, that is, the distribution of power of two signals in the frequency domain;

[0033] Normal distribution: The random variable x obeys a probability distribution with location parameter μ and scale parameter σ, and its probability density function is:

[0034]

[0035] Confidence interval: An interval consisting of the upper and lower confidence limits of a statistic, respectively, and the interval satisfies a given confidence level.

[0036] The inventors recognize that during the engine test, dynamic signals such as vibration, dynamic strain, dynamic pressure, and rotation speed of the aircraft engine need to be collected through a dynamic data acquisition system. For large aircraft engines, the test often requires hundreds of dynamic channels to synchronously collect the above signals at a sampling rate of more than 50kHz. Multi-channel (e.g., 256 channels) dynamic data acquisition systems are often composed of multiple data acquisition modules in series, or require additional synchronization controllers to achieve synchronous acquisition control between multiple data acquisition modules. At high sampling rates (e.g., more than 50kHz), the stability of the multi-channel data acquisition system decreases as the number of data acquisition modules increases, and the synchronous acquisition error between different channels will increase accordingly.

[0037] The inventors also realized that, on the one hand, it is necessary to evaluate the synchronous acquisition error between data acquisition channels at the beginning of building a data acquisition system, and then determine whether the construction method meets the acquisition requirements. On the other hand, as the data acquisition equipment is used for a long time, the stability of synchronous acquisition will also decrease, and there will be failure phenomena such as delayed sampling. Therefore, it is very necessary to evaluate the synchronous acquisition error between channels of a multi-channel dynamic data acquisition system.

[0038] To this end, the present disclosure provides a method and system for detecting synchronous acquisition errors of a multi-channel dynamic data acquisition system, which are used to accurately evaluate the synchronous acquisition errors between channels of the multi-channel dynamic data acquisition system, so that before the aircraft engine test, it can be determined whether the constructed dynamic data acquisition system meets the dynamic test requirements and ensure the reliability of the test data.

[0039] The synchronous acquisition error detection method and system of the multi-channel dynamic data acquisition system disclosed in the present invention can calculate the time difference of homologous deterministic signals collected on different channels. Preferably, the synchronous acquisition error detection method and system of the multi-channel dynamic data acquisition system disclosed in the present invention can eliminate random errors through multiple tests, thereby obtaining the statistical characteristics of the synchronous acquisition errors of each channel.

[0040] In the synchronous acquisition error detection method and system of the multi-channel dynamic data acquisition system disclosed in the present invention, firstly, the homologous deterministic signal is synchronously acquired through each channel to determine the synchronization error between two of these channels. Preferably, the test signal can be a single-frequency sinusoidal signal, and the frequency of the sinusoidal signal is denoted as f sin , the test signal can be used as a signal source to be synchronously collected by two data acquisition channels, and the phase difference between the collected signals is calculated by the cross power spectrum density function. If there is no difference, the phase corresponding to the peak of the cross power spectrum density function is 0°, that is, the signals collected by the two data acquisition channels are consistent. If the phase difference of the cross power spectrum density function is θ°, then the synchronous sampling time difference between the two data acquisition channels is θ / (180×f sin ). Then, the overall synchronization error of the data acquisition system is evaluated by statistics. After acquiring the synchronization error data of different channels (preferably after multiple tests), the data is modeled with a Gaussian random variable model to calculate the mean, variance, maximum value and 95% confidence interval of the error. The synchronization acquisition error value of the data acquisition system is determined based on the 95% confidence interval of the data model.

[0041] Therefore, the present invention proposes a sinusoidal signal phase difference estimation method based on the signal cross-power spectral density function, and converts the phase difference into a synchronization time error, thereby extracting the synchronization acquisition time error between data acquisition channels; proposes applying the statistical error evaluation method of the Gaussian statistical model to the synchronization error evaluation of the data acquisition system, thereby comprehensively evaluating the synchronization acquisition error of the data acquisition system and reducing the uncertainty of the test evaluation; establishes a set of synchronization error verification methods and systems for dynamic data acquisition systems, which covers the use of test equipment, the calculation of synchronization errors between channels and the evaluation of the overall error of the data acquisition system.

[0042] The method and system disclosed in the present invention can realize the evaluation of the synchronous acquisition error of the dynamic data acquisition system, with accurate calculation, simple implementation and low cost. The synchronous acquisition performance of the dynamic data acquisition system can be evaluated before the engine test or during the annual dynamic data acquisition measurement process, and the synchronous acquisition problems existing in the dynamic data acquisition system can be discovered in time to ensure the validity of the test data.

[0043] The detailed description set forth below in conjunction with the accompanying drawings is intended as a description of various configurations and is not intended to represent the only configurations in which the concepts described herein may be practiced. This detailed description includes specific details to provide a thorough understanding of the various concepts. However, it will be apparent to those skilled in the art that these concepts may be practiced without these specific details.

[0044] Reference below Figure 1 , which shows a flowchart of a synchronous acquisition error detection method 100 of a multi-channel dynamic data acquisition system according to an example embodiment of the present disclosure.

[0045] like Figure 1 As shown, the method 100 may include generating a sinusoidal input signal by a signal generator at block 110. It will be appreciated that the sinusoidal input signal is generated for the purpose of testing convenience because it is the simplest test signal. Of course, a cosine input signal or any other suitable test signal may also be generated, which will not be described in detail herein.

[0046] In one embodiment of the present disclosure, the frequency of the sinusoidal input signal can be a single frequency. That is, a single-frequency sinusoidal signal can be generated for testing. According to the Nyquist sampling theorem, the frequency of the sinusoidal input signal needs to be less than half of the sampling frequency of the multi-channel dynamic data acquisition system. It will be understood that the term "sampling frequency of the multi-channel dynamic data acquisition system" refers to the sampling frequency of all channels of the multi-channel dynamic data acquisition system. In other words, in this embodiment, the sampling frequencies of all channels of the multi-channel dynamic data acquisition system are the same.

[0047] In another embodiment of the present disclosure, the sampling frequencies of all channels of the multi-channel dynamic data acquisition system are not the same. Thus, in this embodiment, the frequency of the sinusoidal input signal needs to be less than half of the minimum of the sampling frequencies of all channels of the multi-channel dynamic data acquisition system to satisfy the Nyquist sampling theorem.

[0048] In another preferred embodiment of the present disclosure, the frequency of the sinusoidal input signal may include multiple frequencies. Thus, in this embodiment, it is possible to avoid the situation where the phase difference exceeds 180 degrees or 360 degrees when the synchronous acquisition error is subsequently determined by the phase difference of the output signal. For example, the sinusoidal input signal may be a superposition signal of sinusoidal signals of two, three, four or more frequencies. In this embodiment, each of the multiple frequencies is less than half of the sampling frequency of the multi-channel dynamic data acquisition system.

[0049] For simplicity and without loss of generality, the following assumes that the frequency of the sinusoidal input signal is a single frequency, denoted by f sin .

[0050] Continue to refer Figure 1, the method 100 may include inputting the sinusoidal input signal into all channels of the multi-channel dynamic data acquisition system at block 120. For example, the sinusoidal input signal may be input into all channels of the multi-channel dynamic data acquisition system by a signal generator or a signal distributor connected to the signal generator. It will be appreciated that the sinusoidal input signal is input into all channels of the multi-channel dynamic data acquisition system synchronously.

[0051] At block 130, the method 100 may include collecting and recording the output signal of each channel by the multi-channel dynamic data acquisition system, and at block 140, taking the first channel of the multi-channel dynamic data acquisition system as a reference channel, and calculating the cross-power spectral density function between the output signal of each of the remaining channels except the first channel and the output signal of the first channel. It will be understood that the first channel of the multi-channel dynamic data acquisition system as a reference channel may be any channel of the multi-channel dynamic data acquisition system. For example, if the multi-channel dynamic data acquisition system includes n+1 channels (where n is an integer greater than or equal to 1), the n cross-power spectral density functions that can be calculated at block 140 may be recorded as P 1,0 (ω),P 2,0 (ω),P 3,0 (ω),…,P n,0 (ω), where ω=2πf sin .

[0052] In one embodiment of the present disclosure, for the convenience and accuracy of subsequent calculations, the duration of the output signal of each channel recorded by the multi-channel dynamic data acquisition system has a sufficient number of cycles of the sinusoidal input signal, such as 100 cycles, 10,000 cycles, etc. For example, when the sampling rate of the data acquisition system is set to 50 kHz and the signal generator generates a sinusoidal input signal with a frequency of 10 kHz, the recording duration can be 10 to 20 seconds.

[0053] Next, at block 150, for each of the cross power spectral density functions, the phase angle at the frequency of the sinusoidal input signal is extracted. Continuing with the above example, if the multi-channel dynamic data acquisition system includes n+1 channels (where n is an integer greater than or equal to 1), then at block 150, the phase angle of the sinusoidal input signal can be extracted by using the n cross power spectral density functions P 1,0 (ω),P 2,0 (ω),P 3,0 (ω),…,P n,0 (ω) to get n phase angles, denoted as θ 1,0 ,θ 2,0 ,θ 3,0 ,…,θ n,0 .

[0054] It will be appreciated that where the sinusoidal input signal comprises a plurality of frequencies, extracting the phase angle at the frequency of the sinusoidal input signal comprises extracting the phase angle at each of the plurality of frequencies of the sinusoidal input signal.

[0055] Continue to refer Figure 1 , at block 160, the method 100 may include calculating a delay value of each of the remaining channels except the first channel relative to the first channel based on each of the phase angles. For example, continuing the above example, the delay value may be calculated as follows:

[0056]

[0057] where τ i is the delay value of the i-th channel relative to the reference channel, θ i，0 is the phase difference of the output signal of the i-th channel relative to the output signal of the reference channel, f sin is the frequency of the sinusoidal input signal, and n is the number of channels of the multi-channel dynamic data acquisition system excluding the reference channel. In other words, the total number of channels of the multi-channel dynamic data acquisition system is n+1.

[0058] Next, at block 170, method 100 may include determining a synchronization acquisition error based on the delay values. In an embodiment of the present disclosure, the synchronization acquisition error may include a maximum value among the delay values, a mean and standard deviation of the delay values, and a 95% confidence interval of the delay values.

[0059] For example, continuing the above example, we can find τ i The maximum delay value τ max Alternatively, the average of the delay values ​​can be calculated as follows And standard deviation s:

[0060]

[0061]

[0062] where τ i is the delay value of the i-th channel relative to the reference channel, and n is the number of channels of the multi-channel dynamic data acquisition system excluding the reference channel. In other words, the total number of channels of the multi-channel dynamic data acquisition system is n+1.

[0063] Furthermore, the 95% confidence interval for the delay value can be calculated as follows (assuming a normal distribution):

[0064]

[0065] in,

[0066] Because we need to take a 95% confidence interval, α is taken as 0.05; tα / 2 (n-1) is the critical value of the confidence interval with a confidence level of 1-α (this can be obtained by looking up the T distribution table); is the average value of the delay value and s is the standard deviation of the delay value, and n is the number of channels of the multi-channel dynamic data acquisition system excluding the reference channel (n is an integer greater than or equal to 1). In other words, the total number of channels of the multi-channel dynamic data acquisition system is n+1.

[0067] This can comprehensively evaluate the synchronous acquisition error level of the multi-channel dynamic data acquisition system:

[0068] The maximum synchronization error is τ max ;

[0069] The average synchronization error is

[0070] The 95% confidence interval for the synchronization error is

[0071] In a preferred embodiment of the present disclosure, before the synchronous acquisition error is determined at block 170, the operations in blocks 110 to 160 may be repeated multiple times to eliminate interference from random errors, noise, etc. For example, the operations in blocks 110 to 160 may be repeated three times, thereby obtaining 3n phase differences (and delay values). In this example, in the above calculation formulas for the mean value and standard deviation of the delay value, n may be changed to 3n accordingly. In other words, the above formulas may be rewritten more generally as:

[0072]

[0073]

[0074]

[0075]

[0076] Where a is the number of repetitions.

[0077] It will be appreciated that in the case where the sinusoidal input signal includes multiple frequencies, the above calculations will be performed for each frequency separately, including the operations in blocks 140 , 150 , 160 , and 170 , which will not be described in detail herein.

[0078] In another embodiment of the present disclosure, method 100 may optionally include issuing an alarm when the synchronous acquisition error exceeds a predetermined range. For example, if the maximum value of the delay value exceeds a predetermined range (e.g., 1 ms), an alarm may be issued in various ways, such as an alarm in the form of sound, light, vibration, etc., to notify relevant personnel that the synchronous acquisition error of the multi-channel dynamic data acquisition system will not be suitable for use.

[0079] Reference below Figure 2 , which shows a schematic block diagram of a synchronous acquisition error detection system 200 of a multi-channel dynamic data acquisition system according to an example embodiment of the present disclosure.

[0080] like Figure 2 As shown, the system 200 may include a signal generator 201 and a detector 203. In one embodiment, the signal generator 201 may be arranged to: generate a sinusoidal input signal; and input the sinusoidal input signal into all channels of the multi-channel dynamic data acquisition system. In this embodiment, the detector 203 may be arranged to receive an output signal of each channel of the multi-channel dynamic data acquisition system from the multi-channel dynamic data acquisition system; take the first channel of the multi-channel dynamic data acquisition system as a reference channel, and calculate the cross-power spectral density function between the output signal of each of the remaining channels except the first channel and the output signal of the first channel; for each of the cross-power spectral density functions, extract the phase angle at the frequency of the sinusoidal input signal; calculate the delay value of each of the remaining channels except the first channel relative to the first channel based on each of the phase angles; and determine the synchronous acquisition error based on the delay value.

[0081] It will be understood that the sine input signal is generated for the purpose of testing convenience, because this is the simplest test signal. Of course, a cosine input signal or any other suitable test signal may also be generated, which will not be described in detail here.

[0082] In one embodiment of the present disclosure, the frequency of the sinusoidal input signal can be a single frequency. That is, a single-frequency sinusoidal signal can be generated for testing. According to the Nyquist sampling theorem, the frequency of the sinusoidal input signal needs to be less than half of the sampling frequency of the multi-channel dynamic data acquisition system. It will be understood that the term "sampling frequency of the multi-channel dynamic data acquisition system" refers to the sampling frequency of all channels of the multi-channel dynamic data acquisition system. In other words, in this embodiment, the sampling frequencies of all channels of the multi-channel dynamic data acquisition system are the same.

[0083] In another embodiment of the present disclosure, the sampling frequencies of all channels of the multi-channel dynamic data acquisition system are not the same. Thus, in this embodiment, the frequency of the sinusoidal input signal needs to be less than half of the minimum of the sampling frequencies of all channels of the multi-channel dynamic data acquisition system to satisfy the Nyquist sampling theorem.

[0084] In another preferred embodiment of the present disclosure, the frequency of the sinusoidal input signal may include multiple frequencies. Thus, in this embodiment, it is possible to avoid the situation where the phase difference exceeds 180 degrees or 360 degrees when the synchronous acquisition error is subsequently determined by the phase difference of the output signal. For example, the sinusoidal input signal may be a superposition signal of sinusoidal signals of two, three, four or more frequencies. In this embodiment, each of the multiple frequencies is less than half of the sampling frequency of the multi-channel dynamic data acquisition system.

[0085] For simplicity and without loss of generality, the following assumes that the frequency of the sinusoidal input signal is a single frequency, denoted by f sin .

[0086] It will be understood that the first channel of the multi-channel dynamic data acquisition system as a reference channel can be any channel of the multi-channel dynamic data acquisition system. For example, if the multi-channel dynamic data acquisition system includes n+1 channels (where n is an integer greater than or equal to 1), the detector 203 can calculate the obtained n cross-power spectral density functions, which can be recorded as P 1,0 (ω),P 2,0 (ω),P 3,0 (ω),…,P n,0 (ω), where ω=2πf sin Further, the detector 203 can obtain n phase angles through the n cross power spectrum density functions, which can be recorded as θ 1,0 ,θ 2,0 ,θ 3,0 ,…,θ n,0 .

[0087] In one embodiment of the present disclosure, for the convenience and accuracy of subsequent calculations, the duration of the output signal of each channel recorded by the multi-channel dynamic data acquisition system has a sufficient number of cycles of the sinusoidal input signal, such as 100 cycles, 10,000 cycles, etc. For example, when the sampling rate of the data acquisition system is set to 50 kHz and the signal generator generates a sinusoidal input signal with a frequency of 10 kHz, the recording duration can be 10 to 20 seconds.

[0088] In an embodiment of the present disclosure, the synchronization acquisition error may include a maximum value of the delay values, a mean value and a standard deviation of the delay values, and a 95% confidence interval of the delay values.

[0089] In a preferred embodiment of the present disclosure, before determining the synchronous acquisition error, the signal generator 201 and the detector 203 may be arranged to repeat the operation for multiple times to eliminate interference from random errors, noise, and the like.

[0090] In another embodiment of the present disclosure, the detector 203 may optionally be arranged to issue an alarm when the synchronous acquisition error exceeds a predetermined range. For example, if the maximum value of the delay value exceeds a predetermined range (e.g., 1 ms), an alarm may be issued in various ways, such as an alarm in the form of sound, light, vibration, etc., to inform relevant personnel that the synchronous acquisition error of the multi-channel dynamic data acquisition system will not be suitable for use. Thus, the system 200 may also include any suitable alarm device ( Figure 2 not shown).

[0091] A specific implementation example of the method and system of the present disclosure is given below:

[0092] The example dynamic data acquisition system consists of 6 data acquisition modules, each module includes two channels, a total of 12 channels for data acquisition, and the sampling rate of data acquisition is set to 50kHz. The signal generator generates a sinusoidal input signal with a frequency of 10kHz and an amplitude of 1V. Thus, an example of the output signal collected can be seen in Figure 3 .

[0093] Select the first data acquisition channel as the reference channel, and use the output signal collected on this channel as the reference signal to calculate the cross power spectrum density function of the output signals of all other channels and the output signal of the reference channel. Take the calculation results of the second data acquisition channel and the reference channel as an example, and its Bode plot is as follows: Figure 4 shown. Figure 4 This example cross-spectrum power spectral density function is plotted in a Bode plot. It can be seen that the amplitude spectrum has a peak at 10kHz (the frequency of the sinusoidal input signal), and the corresponding phase angle at this peak is the phase difference of the output signals collected by the two channels.

[0094] The sampling time error value is calculated based on the obtained phase difference (for example, using the above formula). In this example, 33 sampling time error data can be obtained by repeating the acquisition three times. Figure 5 shown.

[0095] Therefore, the synchronous acquisition error of the dynamic data acquisition system can be evaluated:

[0096] Maximum value: 530.54ns

[0097] Average: 20.49ns

[0098] Standard deviation: 190.43ns

[0099] 95% confidence interval: [-368.36 409.34]ns.

[0100] It will be understood that the terms "time synchronization error", "synchronization error", "synchronization acquisition error" in this disclosure are used interchangeably.

[0101] The above detailed description includes references to the accompanying drawings, which form part of the detailed description. The accompanying drawings illustrate specific embodiments that can be practiced by way of illustration. These embodiments are also referred to herein as "examples". Such examples may include elements other than those shown or described. However, examples including the elements shown or described are also contemplated. In addition, examples using any combination or arrangement of those elements shown or described are also contemplated, or with reference to the specific examples (or one or more aspects thereof) shown or described herein, or with reference to other examples (or one or more aspects thereof) shown or described herein.

[0102] In the appended claims, the terms "including" and "comprising" are open ended, that is, systems, devices, articles, or processes having elements other than those elements listed after such terms in a claim are still deemed to fall within the scope of that claim. Furthermore, in the appended claims, the terms "first," "second," and "third," etc. are used merely as labels and are not intended to indicate a numerical order to their objects.

[0103] In addition, the order of each operation explained in this specification is exemplary. In alternative embodiments, each operation can be performed in a different order than that shown in the drawings, and each operation can be combined into a single operation or split into more operations.

[0104] The above description is intended to be illustrative, not restrictive. For example, the examples described above (or one or more aspects thereof) may be used in conjunction with other embodiments. Other embodiments may be used, such as by a person of ordinary skill in the art, after reviewing the above description. The abstract allows the reader to quickly determine the nature of the present technology disclosure. The abstract is submitted, and it is understood that the abstract will not be used to interpret or limit the scope or meaning of the claims. In addition, in the above specific embodiments, various features may be grouped together to make the disclosure fluent. However, the claims may not state every feature disclosed herein, because the embodiments may characterize a subset of the features. In addition, the embodiments may include fewer features than those disclosed in a particular example. Therefore, the attached claims are thus incorporated into the specific embodiments, and a claim exists independently as a separate embodiment. The scope of the embodiments disclosed herein should be determined with reference to the attached claims and the full scope of equivalents to which such claims are entitled.

Claims

1. A synchronous acquisition error detection method for a multi-channel dynamic data acquisition system, the method include: a) Generate a sinusoidal input signal by a signal generator; b) inputting the sinusoidal input signal into all channels of the multi-channel dynamic data acquisition system; c) collecting and recording the output signal of each channel by the multi-channel dynamic data acquisition system; d) taking a first channel of the multi-channel dynamic data acquisition system as a reference channel, and calculating a cross-power spectral density function between an output signal of each of the remaining channels except the first channel and an output signal of the first channel; e) extracting, for each of the cross power spectral density functions, a phase angle at the frequency of the sinusoidal input signal; f) calculating a delay value of each of the remaining channels except the first channel relative to the first channel based on each of the phase angles; as well as g) determining the synchronization acquisition error based on the delay value.

2. The method according to claim 1, It is characterized in that The frequency of the sinusoidal input signal is a single frequency and is less than half of the sampling frequency of the multi-channel dynamic data acquisition system.

3. The method according to claim 1, It is characterized in that The frequency of the sinusoidal input signal includes a plurality of frequencies, and each of the plurality of frequencies is less than half of a sampling frequency of the multi-channel dynamic data acquisition system.

4. The method according to claim 3, It is characterized in that Extracting the phase angle at the frequency of the sinusoidal input signal includes extracting the phase angle at each of the plurality of frequencies of the sinusoidal input signal.

5. The method according to claim 1, It is characterized in that Prior to step g), steps a) to f) are repeated multiple times.

6. The method according to claim 1, It is characterized in that The synchronization acquisition error includes a maximum value of the delay values, a mean value and a standard deviation of the delay values, and a 95% confidence interval of the delay values.

7. The method according to claim 6, It is characterized in that The 95% confidence intervals for the delay values ​​were obtained assuming that the data were normally distributed.

8. The method according to claim 1, It is characterized in that It also includes issuing an alarm when the synchronization acquisition error exceeds a predetermined range.

9. A synchronous acquisition error detection system for a multi-channel dynamic data acquisition system, the system include: A signal generator, the signal generator being arranged to: Generate a sinusoidal input signal; as well as Inputting the sinusoidal input signal into all channels of the multi-channel dynamic data acquisition system; as well as A detector, the detector being arranged to: Receiving an output signal of each channel of the multi-channel dynamic data acquisition system from the multi-channel dynamic data acquisition system; Taking a first channel of the multi-channel dynamic data acquisition system as a reference channel, and calculating a cross-power spectral density function between an output signal of each of the remaining channels except the first channel and an output signal of the first channel; for each of the cross power spectral density functions, extracting a phase angle at a frequency of the sinusoidal input signal; calculating a delay value of each of the remaining channels except the first channel relative to the first channel based on each of the phase angles; as well as The synchronization acquisition error is determined based on the delay value.

10. The system according to claim 9, It is characterized in that The frequency of the sinusoidal input signal is a single frequency and is less than half of the sampling frequency of the multi-channel dynamic data acquisition system.

11. The system according to claim 9, It is characterized in that The frequency of the sinusoidal input signal includes a plurality of frequencies, and each of the plurality of frequencies is less than half of a sampling frequency of the multi-channel dynamic data acquisition system.

12. The system according to claim 11, It is characterized in that Extracting the phase angle at the frequency of the sinusoidal input signal includes extracting the phase angle at each of the plurality of frequencies of the sinusoidal input signal.

13. The system according to claim 9, It is characterized in that The synchronization acquisition error includes a maximum value of the delay values, a mean value and a standard deviation of the delay values, and a 95% confidence interval of the delay values.

14. The system according to claim 13, It is characterized in that The 95% confidence intervals for the delay values ​​were obtained assuming that the data were normally distributed.

15. The system according to claim 9, It is characterized in that The detector is further arranged to issue an alarm if the synchronization acquisition error exceeds a predetermined range.

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