A method for testing electrical signals of gaming equipment

Abstract

The present invention relates to the field of electrical performance testing technology, and in particular to a method for testing the electrical signal of a gaming device. The method comprises: obtaining the electrical signal of the gaming device, using a multi-level dynamic adaptive signal structure and reconstruction algorithm to perform intelligent preprocessing on the electrical signal of the gaming device, and obtaining the electrical signal of the gaming device after intelligent preprocessing; identifying and analyzing the pattern characteristics of the electrical signal of the gaming device after intelligent preprocessing, and obtaining a valid signal; using a multi-level iterative adaptive adjustment and deviation optimization calibration algorithm to calibrate and adjust the valid signal, and obtain a final calibration signal; performing anomaly detection on the final calibration signal, and obtaining a signal error; comparing the signal error with anomaly detection threshold, and obtaining a comparison result. The method solves the technical problems of inaccurate signal processing and inaccurate test results in the process of testing the electrical signal of the gaming device.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical performance testing, and in particular to a method for testing electrical signals of gaming equipment. Background Art

[0002] In the electrical signal testing of gaming devices, accurate signal acquisition and processing are crucial to the performance of gaming devices and user experience. The electrical signals inside gaming devices contain many types, and different signals have different frequencies and intensities. Mixing them together will produce complex interference and superposition effects. The real-time acquisition and accurate identification of these electrical signals place high demands on the test system, especially when multiple signal sources coexist, the environmental noise is complex, and the operating conditions of gaming devices are changeable. Traditional signal processing methods are difficult to meet the requirements of these conditions. Therefore, how to accurately collect and process multiple types of electrical signals of gaming devices to ensure the stability, accuracy, and anti-interference of the signals is an important technical challenge in the current electrical signal testing of gaming devices.

[0003] In summary, the existing gaming device electrical signal testing method has problems of inaccurate signal processing and inaccurate test results during the gaming device electrical signal testing process. Summary of the invention

[0004] The present invention provides a method for testing an electrical signal of a gaming device, so as to solve the technical problems of inaccurate signal processing and inaccurate test results during the testing of the electrical signal of the gaming device.

[0005] A method for testing electrical signals of a gaming device of the present invention specifically includes the following technical solutions:

[0006] A method for testing electrical signals of a gaming device comprises the following steps:

[0007] S1. Obtaining the electrical signal of the gaming device, using a multi-level dynamic adaptive signal structure and reconstruction algorithm to perform intelligent preprocessing on the electrical signal of the gaming device, and obtaining the electrical signal of the gaming device after intelligent preprocessing; identifying and analyzing the pattern characteristics of the electrical signal of the gaming device after intelligent preprocessing, and obtaining an effective signal;

[0008] S2. Use a multi-layer iterative adaptive adjustment and deviation optimization calibration algorithm to calibrate and adjust the effective signal to obtain a final calibration signal; perform anomaly detection on the final calibration signal to obtain a signal error; compare the signal error with the anomaly detection threshold to obtain a comparison result.

[0009] Preferably, the S1 specifically includes:

[0010] In the process of implementing the multi-level dynamic adaptive signal structure and reconstruction algorithm, the deconstruction formula is used to deconstruct the electrical signal of the gaming device into hierarchical signals with different frequencies and characteristics. The specific formula is:

[0011] ,

[0012] in, It is Layer signal, indicating the first Layered signals of layers; It is The amplitude of the layer signal; It is The fundamental frequency of the layer signal; is the frequency adjustment parameter; is a time variable; is the modulation factor; is the modulation frequency; is the time modulation term; is the amplitude correction coefficient of the low-frequency feedback signal; is the feedback frequency adjustment factor.

[0013] Preferably, the S1 specifically includes:

[0014] In the process of implementing the multi-level dynamic adaptive signal structure and reconstruction algorithm, the layered signal is denoised and enhanced to obtain the denoised signal. The specific formula is:

[0015] ,

[0016] in, It's in time After denoising Layer signal; is the denoising attenuation coefficient; is the signal dynamic adjustment factor; is the first The absolute amplitude of the layer signal is the absolute amplitude of the layer signal at a certain moment. The instantaneous intensity of .

[0017] Preferably, the S1 specifically includes:

[0018] In the process of realizing the multi-level dynamic adaptive signal structure and reconstruction algorithm, the denoised signal is adaptively reconstructed to obtain a reconstructed signal.

[0019] Preferably, the S1 specifically includes:

[0020] In the process of implementing the multi-level dynamic adaptive signal structure and reconstruction algorithm, after signal reconstruction, a feedback mechanism is introduced to optimize the reconstructed signal to obtain a feedback-optimized signal; the feedback-optimized signals are merged to obtain the electrical signal of the gaming device after intelligent preprocessing.

[0021] Preferably, the S2 specifically includes:

[0022] During the implementation of the multi-layer iterative adaptive adjustment and deviation optimization calibration algorithm, environmental parameters and operating parameters of the gaming device are collected and quantified to obtain comprehensive quantized values ​​of the environmental parameters and comprehensive quantized values ​​of the gaming device operating status parameters; the preliminary deviation of the effective signal is calculated based on the comprehensive quantized values ​​of the environmental parameters and comprehensive quantized values ​​of the gaming device operating status parameters.

[0023] Preferably, the S2 specifically includes:

[0024] In the process of implementing the multi-layer iterative adaptive adjustment and deviation optimization calibration algorithm, based on the preliminary deviation of the effective signal, an adaptive coefficient matrix is ​​introduced to perform multi-layer adaptive deviation adjustment processing. In each level of adaptive deviation adjustment, the elements of the adaptive coefficient matrix are used to recursively adjust the preliminary deviation of the effective signal.

[0025] Preferably, the S2 specifically includes:

[0026] After the multi-level adaptive adjustment is completed, high-order adjustment optimization is performed to obtain the final calibration signal after high-order adjustment. The specific formula is:

[0027] ,

[0028] in, is the final calibration signal after high-order adjustment; Indicates a valid signal; It is an adaptive adjustment parameter in high-order adjustment, which is used to balance the attenuation of deviation during signal calibration; is a regulation parameter that controls the intensity of periodic influence in the high-order regulation process; is the signal frequency factor; is the signal smoothing factor; It is Signal deviation value after the adjustment; is an element in the adaptive coefficient matrix, indicating the Environmental parameters and The game device running status parameters are in Adaptive adjustment coefficient in hierarchical adjustment.

[0029] The beneficial effects of the technical solution of the present invention are:

[0030] 1. A multi-level dynamic adaptive structure is used to denoise and enhance the layered signal. The denoising attenuation coefficient and dynamic adjustment factor are used to suppress noise, which can effectively remove environmental noise and improve signal clarity. Even in an environment with large interference, the accurate acquisition of the signal can be guaranteed. Signal reconstruction is achieved through multi-level integration and adaptive adjustment of harmonic components, so that the signal has a high degree of restoration in terms of frequency, amplitude and phase. This method corrects the signal from multiple angles to ensure that the output signal has higher authenticity and consistency.

[0031] 2. Use multi-layer iterative adaptive adjustment to make effective signal calibration and adjustment highly adaptive under the joint influence of multi-dimensional environmental parameters and game device operating status parameters, reduce the complexity of signal calibration, improve the real-time performance of signal adjustment, and introduce the multi-dimensional structure and nonlinear adjustment relationship of the adaptive coefficient matrix, which gives the multi-layer iterative adaptive adjustment and deviation optimization calibration algorithm flexibility and adaptability in complex environments, and can effectively respond to changes in different environments and game device states, making the final calibration result more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a flow chart of a method for testing electrical signals of gaming equipment according to the present invention. DETAILED DESCRIPTION

[0033] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0035] The specific scheme of the method for testing the electrical signal of a gaming device provided by the present invention is described in detail below with reference to the accompanying drawings.

[0036] See attached Figure 1 , which shows a flow chart of a method for testing an electrical signal of a gaming device provided by an embodiment of the present invention, the method comprising the following steps:

[0037] S1. Obtaining the electrical signal of the gaming device, using a multi-level dynamic adaptive signal structure and reconstruction algorithm to perform intelligent preprocessing on the electrical signal of the gaming device, and obtaining the electrical signal of the gaming device after intelligent preprocessing; identifying and analyzing the pattern characteristics of the electrical signal of the gaming device after intelligent preprocessing, and obtaining an effective signal;

[0038] Professional technicians set the sampling frequency, sampling duration and signal amplification parameters according to the type of game equipment and experience, so as to accurately collect the signal data of each signal source inside the game equipment and obtain the electrical signal of the game equipment, including control signals, communication signals and feedback signals; the electrical signal of the game equipment is intelligently preprocessed using a multi-level dynamic adaptive signal structure and reconstruction algorithm, and the multi-level dynamic adaptive signal structure and reconstruction algorithm deconstructs, reconstructs and feedback-adjusts the electrical signal of the game equipment through a multi-level structure to ensure the high quality of the obtained electrical signal of the game equipment in a complex environment. The specific implementation process is as follows:

[0039] The obtained electrical signal of the gaming device, that is, the original mixed signal data, is deconstructed and separated. The original mixed signal data contains signals of multiple different frequency components, such as high-frequency control signals, medium-frequency communication signals, low-frequency feedback signals, etc. The original mixed signal is deconstructed into layered signals of different frequencies and different characteristics using a deconstruction formula. The deconstruction formula is as follows:

[0040] ,

[0041] in, It is Layer signal, indicating the first Layered signal of the layer, over time changes with the changes in It is The amplitude of the layer signal indicates the strength or amplitude of the signal, reflecting the energy proportion of the layer signal in the total signal; It is The fundamental frequency of the layer signal represents the frequency characteristics of the layer signal and is used to distinguish different types of signals, such as control signals, communication signals, etc. It is a frequency adjustment parameter that controls the time dependence of the signal frequency and is used to process the characteristics of the signal frequency changing with time; is a time variable, indicating the time point at which the electrical signal of the gaming device is collected; It is a modulation factor, which is used exclusively for the amplitude adjustment of the intermediate frequency communication signal and reflects the characteristic strength of the signal at this layer; It is the modulation frequency, which determines the oscillation frequency or period of the intermediate frequency communication signal and is used to characterize the changing characteristics of the signal at this layer; is the time modulation term, Logarithmic scaling is performed to make the intermediate frequency communication signal show a more moderate change trend in time; It is the amplitude correction coefficient of the low-frequency feedback signal, which indicates the amplitude of the low-frequency part of the signal in this layer; It is the feedback frequency adjustment factor, which controls the time response speed of the low-frequency feedback signal.

[0042] After deconstruction, each signal has environmental noise and mutual interference. Each layered signal is denoised and enhanced to ensure the purity of the layered signal. The specific denoising formula is as follows:

[0043] ,

[0044] in, It's in time After denoising Layer signal, which means the signal after noise suppression; is the denoising attenuation coefficient, which controls the rate at which noise is attenuated; It is the signal dynamic adjustment factor, which controls the adaptive adjustment of the frequency; is the first The absolute amplitude of the layer signal is the absolute amplitude of the layer signal at a certain moment. The instantaneous intensity of .

[0045] The denoised signal still has small fluctuations. In order to improve the accuracy and consistency of the signal, the denoised signal is adaptively reconstructed. The reconstruction formula is as follows:

[0046] ,

[0047] in, It is Layer signal at time Reconstructed signal after denoising and adaptive adjustment; It is at the moment After denoising Layer signal; It is The adaptive gain coefficient of the layer signal is used to adjust the amplitude of the reconstructed signal; It is The phase adjustment factor of the layer signal is used to ensure that the phase characteristics of the reconstructed signal are consistent with the denoised signal; is the reference value adjustment coefficient, which corrects the reference value of the reconstructed signal to ensure the stability of the output signal; is the smoothing factor, which is used to smooth the output of the signal to ensure that the signal does not have unnecessary fluctuations after reconstruction; is the time integral variable, which represents the intermediate variable for accumulating time and is the time step variable used for the integration operation; is the number of harmonic components, which indicates the number of harmonic components used to enhance signal details during the reconstruction process; It is The amplitude adjustment coefficient of each harmonic is used to adjust the intensity of the harmonic component in the reconstructed signal; It is A frequency adjustment factor of a harmonic, used to adjust the frequency of the harmonic component in the reconstructed signal; It is The feedback noise adjustment parameter of each harmonic is used to control the feedback attenuation rate of the harmonic component to reduce the impact of noise on the reconstructed signal.

[0048] After signal reconstruction, there is still a slight signal deviation, so a feedback mechanism is introduced for feedback optimization. The purpose of feedback optimization is to monitor and adjust the signal error in real time so that the output signal can be maintained within a stable range. The feedback optimization formula is as follows:

[0049] ,

[0050] in, It is Layer signal at time The signal after feedback optimization represents the The final output signal of the layer signal after deconstruction, denoising, reconstruction and feedback optimization; is the feedback gain coefficient, which adjusts the influence of the cumulative value on the final output signal during the feedback optimization process; is the time decay coefficient of the feedback, which controls the decay rate of the historical influence of the feedback optimization over time; It is the feedback adjustment frequency, which is used to adjust the oscillation frequency of the feedback signal so that the feedback signal is more consistent with the natural characteristics of the signal in terms of timing; It is Layer signal at time Reconstructed signal after denoising and adaptive adjustment; It is a dynamic gain control factor, which is used to adjust the impact of the feedback accumulation value on the current signal; is the noise suppression coefficient.

[0051] Finally, the optimized signal is fed back Merge and obtain the electrical signal of the gaming device after intelligent preprocessing .

[0052] Furthermore, the electrical signals of the gaming devices after intelligent preprocessing Apply pattern matching algorithms (such as DTW algorithm and template matching algorithm) to identify the pattern characteristics of the signal, classify the signals that meet the expected characteristics as preliminary effective signals, use the existing convolutional neural network model to perform multi-layer feature extraction on the preliminary effective signals, gradually deepen the recognition and analysis of the pattern characteristics of the signal, and obtain effective signals. .

[0053] In the identification and classification process using the pattern matching algorithm, based on the requirements of different electrical signal types in gaming devices, professional technicians establish feature libraries for control signals, communication signals, feedback signals, etc.

[0054] S2. Use a multi-layer iterative adaptive adjustment and deviation optimization calibration algorithm to calibrate and adjust the effective signal to obtain a final calibration signal; perform anomaly detection on the final calibration signal to obtain a signal error; compare the signal error with the anomaly detection threshold to obtain a comparison result.

[0055] In order to achieve accurate testing of the electrical signals of gaming devices, a multi-layer iterative adaptive adjustment and deviation optimization calibration algorithm is introduced. The effective signal is calibrated and adjusted according to the current environment and the operating status of the gaming device to obtain the final calibration signal. The final calibration signal is subjected to abnormality detection to obtain the signal error. The signal error is compared with the abnormality detection threshold set according to the expert experience method to obtain the comparison result and realize the electrical signal test of gaming devices. The multi-layer iterative adaptive adjustment and deviation optimization calibration algorithm aims to improve the accuracy and dynamic adjustment capability of signal calibration, realize adaptive adjustment of multi-level signal calibration, and dynamically optimize the stability of the final signal data under fluctuating environment. The specific implementation process is as follows:

[0056] First, in the initialization phase, the current environment and operating parameters of the gaming device are collected, which provide a data basis for subsequent adaptive adjustment and signal calibration. , including temperature ,humidity , noise interference intensity , and quantify the environmental parameters according to the expert experience method to obtain the comprehensive quantitative value of the environmental parameters ;Game device operation status parameters , respectively represent the operating frequency of the gaming device ,load , Power consumption , and quantify the game equipment operation status parameters according to the expert experience method to obtain the comprehensive quantified value of the game equipment operation status parameters Environmental parameters and game device operating status parameters are both dimensionless parameters.

[0057] After the initial conditions are set, the effective signal is calculated The initial deviation of the current signal and the standard signal The difference between the current signal and the standard signal The deviation between them is preliminarily estimated, and the specific implementation formula is as follows:

[0058] ,

[0059] Among them, is the deviation between the current signal and the standard signal, i.e. the preliminary deviation of the effective signal; Used to introduce noise coefficient so that the greater the noise, the greater the signal fluctuation; Represents the periodic effect of the simulated frequency on the deviation.

[0060] After obtaining the preliminary deviation, enter the multi-layer adaptive deviation adjustment stage to reduce the deviation caused by the environment and the operating status of the game device. Define the adaptive coefficient matrix , used to control the weight of different factors on deviation adjustment:

[0061] ,

[0062] Any of these elements can be used It indicates that it changes with the environmental parameters and the operating status parameters of the gaming device; is the number of environmental parameters; is the number of game device running status parameters;

[0063] ,

[0064] in, For the Environmental parameters and The game device running status parameters are in Adaptive adjustment coefficient in hierarchical adjustment; It is Adaptive weight coefficients of environmental parameters; It is Adaptive weight coefficients of game device operating status parameters; It is Environmental parameters; It is Game device operation status parameters; is the smoothing coefficient; It is The signal deviation value calculated in the layer iteration is used to reflect the difference between the current signal and the standard signal. The adaptive coefficient matrix represents the weight adjustment of the signal under the influence of different environments and game device operating states. Through multiple iterations, each layer adjusts the deviation according to the environmental parameters and game device status parameters to make the effective signal approach the standard signal.

[0065] At every level In the adjustment of , the initial deviation is recursively adjusted using the adaptive coefficient matrix elements to obtain the deviation of the next level :

[0066] ,

[0067] in, It is Signal deviation value after the adjustment; It is The partial derivative of the signal deviation value of the level with respect to the environmental factor indicates the influence of the environmental factor on the deviation; It is The partial derivative of the signal deviation value of the level with respect to the operating state of the game device represents the influence of the operating state of the game device on the deviation.

[0068] Through multi-level adaptive adjustment, the deviation gradually decreases and eventually converges to the allowable range preset according to expert experience or reaches the preset number of levels. After the multi-level adaptive adjustment is completed, in order to further optimize the signal, high-order adjustment optimization is performed to eliminate small fluctuations and ensure high accuracy. High-order adjustment introduces the following compound adjustment formula:

[0069] ,

[0070] in, is the final calibration signal after high-order adjustment; It is an adaptive adjustment parameter in high-order adjustment, which is used to balance the attenuation of deviation during signal calibration; is a tuning parameter used to control the intensity of periodic influences in the higher-order tuning process; Used to represent the periodic components of a signal that vary over time; is the signal frequency factor; is the signal smoothing factor, which controls the degree of exponential smoothing of the deviation.

[0071] get Then, the signal error is calculated by the anomaly detection formula ,based on Compare the anomaly detection threshold to determine the signal state. The anomaly detection formula is:

[0072] ,

[0073] The above formula represents the Euclidean distance between the standard signal and the final calibration signal. , then the signal is abnormal, if , the signal is normal; It is an anomaly detection threshold preset based on expert experience. By comparing the signal error with the anomaly detection threshold, the automation of signal testing and anomaly detection is achieved.

[0074] In summary, a method for testing electrical signals of gaming equipment is completed.

[0075] The order of the embodiments of the invention is for description only and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0076] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0077] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A method for testing electrical signals of a gaming device, characterized in that: The following steps are involved: S1. Obtain the electrical signal of the gaming device, and use a multi-level dynamic adaptive signal structure and reconstruction algorithm to perform intelligent preprocessing on the electrical signal of the gaming device. In the process of implementing the multi-level dynamic adaptive signal structure and reconstruction algorithm, use a deconstruction formula to deconstruct the electrical signal of the gaming device into hierarchical signals with different frequencies and characteristics. The specific formula is: ， in, It is Layer signal, indicating the first Layered signals of layers; It is The amplitude of the layer signal; It is The fundamental frequency of the layer signal; is the frequency adjustment parameter; is a time variable; is the modulation factor; is the modulation frequency; is the time modulation term; is the amplitude correction coefficient of the low-frequency feedback signal; is the feedback frequency adjustment factor; The layered signal is subjected to denoising and signal enhancement processing to obtain the denoised signal. The specific formula is: ， in, It's in time After denoising Layer signal; is the denoising attenuation coefficient; is the signal dynamic adjustment factor; is the first The absolute amplitude of the layer signal is the absolute amplitude of the layer signal at a certain moment. The instantaneous intensity of Perform feature adaptive reconstruction on the denoised signal to obtain a reconstructed signal; After signal reconstruction, a feedback mechanism is introduced to optimize the reconstructed signal to obtain a feedback-optimized signal; the feedback-optimized signal is merged to obtain an intelligently preprocessed electrical signal of the gaming device; and the pattern characteristics of the intelligently preprocessed electrical signal of the gaming device are identified and analyzed to obtain an effective signal; S2. Use multi-layer iterative adaptive adjustment and deviation optimization calibration algorithm to calibrate and adjust the effective signal. After the multi-level adaptive adjustment is completed, high-order adjustment optimization is performed to obtain the final calibration signal after high-order adjustment. The specific formula is: ， in, is the final calibration signal after high-order adjustment; Indicates a valid signal; It is the adaptive adjustment parameter in high-order regulation; is the adjustment parameter; is the signal frequency factor; is the signal smoothing factor; It is Signal deviation value after adjustment; is an element in the adaptive coefficient matrix, indicating the Environmental parameters and The game device running status parameters are in Adaptive adjustment coefficient in hierarchical adjustment; Anomaly detection is performed on the final calibration signal to obtain a signal error; the signal error is compared with an anomaly detection threshold to obtain a comparison result.

2. A method for testing electrical signals of gaming devices according to claim 1, characterized in that: The S2 specifically includes: During the implementation of the multi-layer iterative adaptive adjustment and deviation optimization calibration algorithm, environmental parameters and operating parameters of the gaming device are collected and quantified to obtain comprehensive quantized values ​​of the environmental parameters and comprehensive quantized values ​​of the gaming device operating status parameters; the preliminary deviation of the effective signal is calculated based on the comprehensive quantized values ​​of the environmental parameters and comprehensive quantized values ​​of the gaming device operating status parameters.

3. A method for testing electrical signals of gaming devices according to claim 2, characterized in that: The S2 specifically includes: In the process of implementing the multi-layer iterative adaptive adjustment and deviation optimization calibration algorithm, based on the preliminary deviation of the effective signal, an adaptive coefficient matrix is ​​introduced to perform multi-layer adaptive deviation adjustment processing. In each level of adaptive deviation adjustment, the elements of the adaptive coefficient matrix are used to recursively adjust the preliminary deviation of the effective signal.

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