Digital sound console sound tuning data intelligent processing method and system based on ARM processor

Abstract

The invention discloses a digital sound console sound tuning data intelligent processing method and system based on an ARM processor, and belongs to the technical field of data processing. The method and the device are used for solving the technical problems that different tuning data of the digital sound console cannot be supervised and analyzed in different aspects, and subsequent implementation of different tuning cannot be dynamically optimized and managed in different aspects in an existing scheme. Monitoring, counting and processing the whole process of different tuning request processing in the operation process of the digital sound console to obtain tuning single supervision sequences corresponding to different tuning processing, and processing and analyzing local tuning processing states and local tuning support states in different aspects on the tuning single supervision sequences obtained through processing; according to all tone tuning single supervision processing analysis sequences obtained by target tone tuning history processing, processing analysis of an overall tone tuning processing state is carried out, investigation and verification of influence factors are carried out on a processing analysis result, and optimization management is carried out on subsequent different aspects of target tone tuning.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an intelligent processing method for tuning data of a digital mixing console based on an ARM processor. Background Art

[0002] A digital mixing console is a professional audio device used in audio recording, live performances, broadcasting, film production and other occasions. It combines the functions of traditional analog mixing consoles with modern digital technology to provide more powerful and flexible audio processing capabilities. The mixing data of a digital mixing console contains information from multiple aspects, which together determine the processing method of the audio signal and the final mixing effect.

[0003] When implementing the existing digital mixing console tuning data processing scheme, it is impossible to perform data supervision and processing analysis on the different tuning processing processes of the digital mixing console, and it is impossible to process and analyze the tuning processing implementation status of different dimensions of different tuning processing. Therefore, it is impossible to adaptively perform targeted optimization management of different aspects of the different tuning processing of the digital mixing console according to the analysis results. There is a problem that different aspects of the digital mixing console's different tuning data cannot be supervised and analyzed, and different aspects of the subsequent implementation of different tunings cannot be dynamically optimized. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent processing method for tuning data of a digital mixing console based on an ARM processor, which is used to solve the technical problems in the existing scheme that different aspects of different tuning data of the digital mixing console cannot be supervised and analyzed, and different aspects of the subsequent implementation of different tunings cannot be dynamically optimized and managed.

[0005] The purpose of the present invention can be achieved through the following technical solutions: The intelligent processing method of tuning data of a digital mixer based on an ARM processor includes: Monitor, count and process the entire process of request processing for different tunings during the operation of the digital mixing console, obtain the tuning single supervision sequence corresponding to the different tuning processes, and perform different aspects of local tuning processing status and local tuning support status processing analysis on the obtained tuning single supervision sequence, and obtain the tuning single supervision processing analysis sequence corresponding to the different tuning processes; Among them, the requests for different tunings during the operation of the digital mixing console are monitored and counted, and the tunings processed by the request are marked as target tunings. The tuning single processing data corresponding to the target tunings are processed and calculated to obtain the corresponding tuning single processing validity; and, processing and calculating the tuning single support data of the processor corresponding to the target tuning process to obtain the corresponding tuning single support validity; Performing data analysis and digital processing combination on the tuning single supervision sequence obtained by tuning single processing validity and tuning single support validity processing, and obtaining the tuning single supervision processing analysis sequence corresponding to the target tuning; According to all tuning single supervision processing analysis sequences obtained by the target tuning corresponding processing, the overall tuning processing status is processed and analyzed, and the influencing factors of the processing and analysis results are checked and verified to obtain the target tuning processing abnormal supervision set corresponding to the target tuning; Dynamically optimize and manage the tuning processing of the target tuning and the tuning support of the processor according to the target tuning processing exception supervision set.

[0006] Preferably, monitoring and counting the requests for different tunings during the operation of the digital mixing console, marking the tunings processed by the request as target tunings, and obtaining the request timestamp corresponding to the target tunings; Monitor and count the entire process of processing the target tuning, obtain the available resources of the corresponding processor when the target tuning starts processing, and obtain the completion timestamp corresponding to the completion of the target tuning processing; Calculate the processing time difference TC between the completion timestamp of the target tuning and the request timestamp, and use the formula Calculate the tuning single-time processing validity DX corresponding to the target tuning; where, The standard processing time difference corresponding to the target tuning; is the rounding function, which means no more than a real number The largest integer is called The integer part of .

[0007] Preferably, the available resources of the corresponding processor when the target tuning process starts are calculated by the formula Calculate and obtain the tuning single support validity ZX of the processor corresponding to the target tuning process; where ZY is the available resources of the corresponding processor when the target tuning process starts; ZY1 and ZY2 are the minimum available resources and maximum available resources of the processor when the target tuning process is performed; min() means obtaining the minimum value of two real numbers; The tuning single processing validity and tuning single support validity calculated from different aspects of the target tuning are sorted and combined to obtain the tuning single supervision sequence corresponding to the target tuning.

[0008] Preferably, data analysis is performed on the tuning single supervision sequence to determine the local tuning implementation status of different aspects corresponding to the target tuning; If the tuning single supervision sequence is [0, 1], a first tuning tag is generated and the local tuning processing state of the target tuning is normal and the local tuning support state of the processor is normal, and the local tuning processing abnormality corresponding to the target tuning and the local tuning support abnormality value processed by the corresponding processor are set to 0; If the tuning single supervision sequence is [1, 1], a second tuning tag is generated and it is indicated that the local tuning processing state of the target tuning is abnormal and the local tuning support state of the processor is normal; If the tuning single supervision sequence is [1, 0], a third tuning tag is generated and it is prompted that the local tuning processing state of the target tuning is abnormal and the local tuning support state of the processor is abnormal.

[0009] Preferably, according to the second tuning tag, the formula Calculate and obtain the local tuning processing abnormality DY corresponding to the target tuning; And according to the third tuning tag, the local tuning support abnormal value JY processed by the processor corresponding to the target tuning is calculated by the formula JY=ZY1-ZY; The obtained local tuning processing abnormality and local tuning support abnormality are sorted and combined to obtain a tuning single supervision processing analysis sequence corresponding to the target tuning.

[0010] Preferably, all tuning single supervision processing analysis sequences obtained by the target tuning corresponding processing are obtained, and the total number of first local tuning processing NC1 with a statistical value of 0, the total number of second local tuning processing NC2 with a non-zero value, the total number of first local tuning support NZ1 with a statistical value of 0, and the total number of second local tuning support NZ2 with a non-zero value are respectively traversed; The total number of the first local tuning process and the total number of the second local tuning process are calculated by the formula Calculate and obtain the overall tuning processing value ZC corresponding to the target tuning; where DY´ is the value obtained by summing the local tuning processing abnormalities with different non-zero values; CB is the overall tuning processing standard value corresponding to the target tuning; It is an exponential function with the natural constant e as its base.

[0011] Preferably, if the overall tuning processing value is greater than or equal to 1, an overall tuning processing normal label is generated, and the corresponding target tuning is associated with the overall tuning processing normal state; If the overall tuning processing value is less than 1, an overall tuning processing verification tag is generated, and the total number of first local tuning supports and the total number of second local tuning supports are calculated by the formula Calculate and obtain the overall tuning support abnormal value ZZ processed by the corresponding processor of the target tuning; where, It is the value obtained by summing up the local tuning support exception values ​​with different non-zero values; ZB is the overall tuning support exception standard value corresponding to the target tuning request processed by the processor.

[0012] Preferably, if the overall tuning support exception value is less than 0, an overall tuning processing verification active exception label is generated, and the target tuning is associated with the overall tuning processing active exception state; If the overall tuning support exception value is greater than or equal to 0, the overall tuning processing verification passive exception label is generated, and the target tuning is associated with the overall tuning processing passive exception state; The overall tuning processing value, the overall tuning support abnormal value obtained by the target tuning corresponding processing, and the overall tuning processing normal state, the overall tuning processing active abnormal state or the overall tuning processing passive abnormal state obtained by the corresponding analysis are sorted and combined to obtain the target tuning processing abnormal supervision set.

[0013] Preferably, when dynamically optimizing and managing different aspects of the target tuning according to the target tuning processing exception supervision set, optimization management prompts are provided for the operation of the target tuning according to the associated overall tuning processing active exception status, and optimization management prompts are provided for the resource support of the target tuning according to the associated overall tuning processing passive exception status.

[0014] The digital mixer tuning data intelligent processing system based on ARM processor includes: The digital mixer different tuning processing supervision module is used to monitor, count and process the whole process of different tuning request processing during the operation of the digital mixer, obtain the tuning single supervision sequence corresponding to the different tuning processing, and perform different aspects of local tuning processing status and local tuning support status processing analysis on the obtained tuning single supervision sequence, and obtain the tuning single supervision processing analysis sequence corresponding to the different tuning processing; The multi-dimensional analysis and verification module for single tuning processing is used to analyze the overall tuning processing status according to all tuning single supervision processing analysis sequences obtained from the target tuning corresponding processing, and to check and verify the influencing factors of the processing analysis results to obtain the target tuning processing abnormal supervision set corresponding to the target tuning; The multi-dimensional optimization management module for single-item tuning processing is used to dynamically optimize the tuning processing of the target tuning and the tuning support of the processor according to the target tuning processing exception supervision set.

[0015] Compared with the existing solutions, the present invention achieves the following beneficial effects: The present invention obtains tuning single supervision sequences corresponding to different tuning processes by monitoring, counting and processing the entire process of request processing for different tunings during the operation of a digital mixing console, and performs local tuning processing status and local tuning support status processing analysis in different aspects on the obtained tuning single supervision sequences, thereby realizing the processing and digital representation of local tuning supervision states in different aspects for single request processing processes for different target tunings, and can provide reliable local tuning supervision data support for subsequent optimization management of different aspects corresponding to different target tunings.

[0016] The present invention processes and analyzes the overall tuning processing status of all tuning single supervision processing and analysis sequences obtained from the target tuning history processing, and checks and verifies the influencing factors of the processing and analysis results, thereby realizing the expanded integrated utilization of all tuning single supervision processing and analysis sequences in the target tuning history, and verifying and classifying the abnormal results obtained from the analysis, which can provide reliable supervision processing data support for the subsequent optimization management of different aspects of the target tuning, and improve the multi-dimensional local processing expansion effect and the overall verification and analysis effect of the digital mixing console tuning data processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention will be further described below in conjunction with the accompanying drawings.

[0018] Figure 1 The present invention is a flowchart of the steps of implementing the method for intelligently processing tuning data of a digital mixing console based on an ARM processor.

[0019] Figure 2 It is a flowchart of the data analysis of the tuning single supervision sequence in the present invention.

[0020] Figure 3 It is a flowchart of analyzing the overall tuning support abnormal value processed by the target tuning corresponding processor in the present invention.

[0021] Figure 4 The present invention is a module block diagram of the digital mixer tuning data intelligent processing system based on the ARM processor. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of 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.

[0023] Embodiment 1, as Figure 1As shown, the present invention is an intelligent processing method for tuning data of a digital mixer based on an ARM processor, comprising: The whole process of request processing of different tunings during the operation of the digital mixing console is monitored, counted and processed to obtain the tuning single supervision sequence corresponding to the different tuning processing, and the obtained tuning single supervision sequence is processed and analyzed in different aspects of the local tuning processing state and the local tuning support state to obtain the tuning single supervision processing analysis sequence corresponding to the different tuning processing; the specific steps include: Monitor and count the requests for different tunings during the operation of the digital mixer, mark the tuning processed by the request as the target tuning, and obtain the request timestamp corresponding to the target tuning; The tuning request is obtained by the tuner's operation on the tuning item; the tuning of the digital mixing console includes but is not limited to gain adjustment, equalization, dynamic processing, reverberation and other effects, and sound and image positioning; In addition, the request timestamp corresponding to the target tuning is accurate to milliseconds and can be monitored and obtained by the high-precision clock source equipped inside the digital mixing console; Monitor and count the entire process of processing the target tuning, obtain the available resources of the corresponding processor when the target tuning starts processing, and obtain the completion timestamp corresponding to the completion of the target tuning; the completion timestamp is also accurate to milliseconds; The processor for processing the tuning data of the digital mixer in the embodiment of the present invention may specifically be an ARM processor. Some portable or low-cost mixers use ARM processors to process some audio tasks, especially in applications that do not require extremely high performance. In addition, the available resources of the processor, specifically the CPU cycles, can be evaluated by monitoring the CPU utilization (percentage) to evaluate the currently available CPU cycles; for example, if the CPU utilization is 50%, then 50% of the CPU cycles are available for other tasks; Calculate the processing time difference TC between the completion timestamp of the target tuning and the request timestamp, and use the formula Calculate the tuning single-time processing validity DX corresponding to the target tuning; where, The standard processing time difference corresponding to the target tuning is determined according to the operation design data corresponding to the target tuning, and can also be determined according to the preliminary test data of the target tuning; is the rounding function, which means no more than a real number The largest integer is called The integer part of ; And, the available resources of the corresponding processor when the target tuning starts processing are calculated by the formula Calculate and obtain the tuning single support validity ZX of the processor corresponding to the target tuning process; where ZY is the available resources of the corresponding processor when the target tuning process starts; ZY1 and ZY2 are the minimum available resources and maximum available resources of the processor when the target tuning process is performed, respectively, which are determined according to the operation design data corresponding to the target tuning, and can also be determined according to the early test data of the target tuning; Indicates obtaining the minimum value of two real numbers; The tuning single processing validity and tuning single support validity calculated and obtained from different aspects of the target tuning are sorted and combined to obtain the tuning single supervision sequence corresponding to the target tuning; It should be noted that by performing data processing and calculation on the tuning single processing aspect and the tuning single support aspect of the target tuning respectively, the tuning single processing state and the tuning single support state corresponding to different aspects are digitally represented; Conduct data analysis on the tuning single supervision sequence to determine the local tuning implementation status of different aspects corresponding to the target tuning; If the tuning single supervision sequence is [0, 1], a first tuning tag is generated and the local tuning processing state of the target tuning is normal and the local tuning support state of the processor is normal, and the local tuning processing abnormality corresponding to the target tuning and the local tuning support abnormality value processed by the corresponding processor are set to 0; like Figure 2 As shown, if the tuning single supervision sequence is [1, 1], a second tuning tag is generated and it is prompted that the local tuning processing state of the target tuning is abnormal and the local tuning support state of the processor is normal; If the tuning single supervision sequence is [1, 0], a third tuning tag is generated and it is indicated that the local tuning processing state of the target tuning is abnormal and the local tuning support state of the processor is abnormal; And, according to the second tuning label by the formula Calculate and obtain the local tuning processing abnormality DY corresponding to the target tuning; And according to the third tuning tag, the local tuning support abnormal value JY processed by the processor corresponding to the target tuning is calculated by the formula JY=ZY1-ZY; The obtained local tuning processing abnormality and local tuning support abnormality are sorted and combined to obtain a tuning single supervision processing analysis sequence corresponding to the target tuning; In an embodiment of the present invention, by monitoring, counting and processing the entire process of request processing for different tunings during the operation of a digital mixing console, a tuning single supervision sequence corresponding to different tuning processing is obtained, and the obtained tuning single supervision sequence is processed and analyzed for different aspects of local tuning processing status and local tuning support status, thereby realizing the processing and digital representation of different aspects of local tuning supervision status in the single request processing process for different target tunings, and providing reliable local tuning supervision data support for subsequent optimization management of different aspects corresponding to different target tunings.

[0024] According to all tuning single supervision processing analysis sequences obtained by the target tuning corresponding processing, the overall tuning processing status is processed and analyzed, and the influencing factors of the processing and analysis results are checked and verified to obtain the target tuning processing abnormal supervision set corresponding to the target tuning; the specific steps include: Obtain all tuning single supervision processing analysis sequences obtained by the target tuning corresponding processing, and respectively traverse the total number of first local tuning processing NC1 with a statistical value of 0, the total number of second local tuning processing NC2 with a non-zero value, the total number of first local tuning supports NZ1 with a statistical value of 0, and the total number of second local tuning supports NZ2 with a non-zero value; The total number of the first local tuning process and the total number of the second local tuning process are calculated by the formula Calculate and obtain the overall tuning processing value ZC corresponding to the target tuning; where: is the value obtained by summing up the abnormality of the local tuning processing with different non-zero values; CB is the standard value of the overall tuning processing corresponding to the target tuning, which is determined according to the operation processing design data corresponding to the target tuning, and can also be determined according to the preliminary test data of the target tuning; It is an exponential function with the natural constant e as the base; It should be noted that the overall tuning processing value is used to integrate and calculate all the single tuning processing data corresponding to the target tuning to digitally represent the corresponding overall tuning processing state; If the overall tuning processing value is greater than or equal to 1, an overall tuning processing normal label is generated, and the corresponding target tuning is associated with the overall tuning processing normal state; It should be noted that when the overall tuning processing value is less than 1, there are two situations: one is that the target tuning's own operations are abnormal, and the other is that the target tuning's external processing resources are abnormal. Further investigation, verification and analysis are required to improve the regulatory analysis effects of different aspects of the target tuning and the subsequent optimization management effects; If the overall tuning processing value is less than 1, an overall tuning processing verification tag is generated, and the total number of first local tuning supports and the total number of second local tuning supports are calculated by the formula Calculate and obtain the overall tuning support abnormal value ZZ processed by the corresponding processor of the target tuning; where, is the value obtained by summing up the local tuning support exception values ​​with different non-zero values; ZB is the overall tuning support exception standard value corresponding to the processor processing the target tuning request, which is determined according to the operating resource support design data corresponding to the target tuning, and can also be determined according to the preliminary test data of the target tuning; It should be noted that the overall tuning support abnormal value is used to integrate and calculate all single tuning support data supported by the corresponding processor of the target tuning process to digitally represent the corresponding overall tuning support state; like Figure 3 As shown, if the overall tuning support exception value is less than 0, an overall tuning processing verification active exception label is generated, and the target tuning is associated with the overall tuning processing active exception state, and the overall tuning processing active exception state indicates that the target tuning has an abnormal operation corresponding to itself; If the overall tuning support exception value is greater than or equal to 0, an overall tuning processing verification passive exception label is generated, and the target tuning is associated with the overall tuning processing passive exception state. The overall tuning processing passive exception state indicates that the processing resources corresponding to the target tuning are abnormal. The normal state of the overall tuning processing, the active abnormal state of the overall tuning processing, or the passive abnormal state of the overall tuning processing obtained by the corresponding processing of different target tunings are sorted and combined respectively to obtain a target tuning processing abnormal supervision set; In the embodiment of the present invention, the overall tuning processing status is processed and analyzed based on all tuning single supervision processing analysis sequences obtained from the target tuning history processing, and the influencing factors of the processing and analysis results are checked and verified, thereby realizing the expanded integrated utilization of all tuning single supervision processing analysis sequences in the target tuning history, and verifying and classifying the abnormal results obtained from the analysis, which can provide reliable supervision processing data support for the subsequent optimization management of different aspects of the target tuning, and improve the multi-dimensional local processing expansion effect and the overall verification and analysis effect of the digital mixing console tuning data processing.

[0025] Dynamically optimize and manage the tuning processing of the target tuning and the tuning support of the processor according to the target tuning processing exception supervision set; the specific steps include: When dynamically optimizing different aspects of target tuning according to the target tuning processing exception supervision set, optimizing management prompts for the operation of the target tuning according to the associated overall tuning processing active exception state, and optimizing management prompts for the resource support of the target tuning according to the associated overall tuning processing passive exception state; Among them, optimization management tips for operations can provide targeted optimization training tips for tuners' subsequent tuning operations; Providing optimized management tips for resource support, and providing targeted resource processing and allocation optimization optimization tips to the operation and maintenance personnel of the digital mixing console.

[0026] In the embodiment of the present invention, the tuning processing of the target tuning and the tuning support of the processor are dynamically optimized and managed according to the target tuning processing exception supervision set, thereby realizing targeted optimization management of different aspects of different target tuning targets in the digital mixing console, and improving the diversity and reliability of the expansion and optimization management of the digital mixing console's tuning data.

[0027] Embodiment 2, as Figure 4 As shown, the digital mixer tuning data intelligent processing system based on ARM processor includes: The digital mixer different tuning processing supervision module is used to monitor, count and process the whole process of different tuning request processing during the operation of the digital mixer, obtain the tuning single supervision sequence corresponding to the different tuning processing, and perform different aspects of local tuning processing status and local tuning support status processing analysis on the obtained tuning single supervision sequence, and obtain the tuning single supervision processing analysis sequence corresponding to the different tuning processing; The multi-dimensional analysis and verification module for single tuning processing is used to analyze the overall tuning processing status according to all tuning single supervision processing analysis sequences obtained from the target tuning corresponding processing, and to check and verify the influencing factors of the processing analysis results to obtain the target tuning processing abnormal supervision set corresponding to the target tuning; The multi-dimensional optimization management module for single-item tuning processing is used to dynamically optimize the tuning processing of the target tuning and the tuning support of the processor according to the target tuning processing exception supervision set.

[0028] In addition, the formulas involved in the above are all dimensionless and numerical calculations. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and simulating it with simulation software.

[0029] In the several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described embodiments of the invention are only illustrative, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0030] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0031] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0032] It is obvious to a person skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the essential characteristics of the present invention.

[0033] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. An intelligent processing method for tuning data of a digital mixer based on an ARM processor, characterized in that: include: Monitor, count and process the entire process of request processing for different tunings during the operation of the digital mixing console, obtain the tuning single supervision sequence corresponding to the different tuning processes, and perform different aspects of local tuning processing status and local tuning support status processing analysis on the obtained tuning single supervision sequence, and obtain the tuning single supervision processing analysis sequence corresponding to the different tuning processes; Among them, the requests for different tunings during the operation of the digital mixing console are monitored and counted, and the tunings processed by the request are marked as target tunings. The tuning single processing data corresponding to the target tunings are processed and calculated to obtain the corresponding tuning single processing validity; and, processing and calculating the tuning single support data of the processor corresponding to the target tuning process to obtain the corresponding tuning single support validity; Performing data analysis and digital processing combination on the tuning single supervision sequence obtained by tuning single processing validity and tuning single support validity processing, and obtaining the tuning single supervision processing analysis sequence corresponding to the target tuning; According to all tuning single supervision processing analysis sequences obtained by the target tuning corresponding processing, the overall tuning processing status is processed and analyzed, and the influencing factors of the processing and analysis results are checked and verified to obtain the target tuning processing abnormal supervision set corresponding to the target tuning; Dynamically optimize and manage the tuning processing of the target tuning and the tuning support of the processor according to the target tuning processing exception supervision set.

2. The method for intelligently processing tuning data of a digital mixing console based on an ARM processor according to claim 1, characterized in that: Monitor and count the requests for different tunings during the operation of the digital mixer, mark the tuning processed by the request as the target tuning, and obtain the request timestamp corresponding to the target tuning; Monitor and count the entire process of processing the target tuning, obtain the available resources of the corresponding processor when the target tuning starts processing, and obtain the completion timestamp corresponding to the completion of the target tuning processing; Calculate the processing time difference TC between the completion timestamp of the target tuning and the request timestamp, and use the formula Calculate the tuning single-time processing validity DX corresponding to the target tuning; where, The standard processing time difference corresponding to the target tuning; is the rounding function, which means no more than a real number The largest integer is called The integer part of .

3. The intelligent processing method for tuning data of a digital mixing console based on an ARM processor according to claim 2 is characterized in that: The available resources of the corresponding processor when the target tuning starts processing are calculated by the formula Calculate and obtain the tuning single support validity ZX of the processor corresponding to the target tuning process; Wherein, ZY is the available resources of the corresponding processor when the target tuning starts processing; ZY1 and ZY2 are the minimum available resources and maximum available resources of the processor when the target tuning is processed; min() means getting the minimum value of two real numbers; The tuning single processing validity and tuning single support validity calculated from different aspects of the target tuning are sorted and combined to obtain the tuning single supervision sequence corresponding to the target tuning.

4. The method for intelligently processing tuning data of a digital mixer based on an ARM processor according to claim 3 is characterized in that: Conduct data analysis on the tuning single supervision sequence to determine the local tuning implementation status of different aspects corresponding to the target tuning; If the tuning single supervision sequence is [0, 1], a first tuning tag is generated and the local tuning processing state of the target tuning is normal and the local tuning support state of the processor is normal, and the local tuning processing abnormality corresponding to the target tuning and the local tuning support abnormality value processed by the corresponding processor are set to 0; If the tuning single supervision sequence is [1, 1], a second tuning tag is generated and it is indicated that the local tuning processing state of the target tuning is abnormal and the local tuning support state of the processor is normal; If the tuning single supervision sequence is [1, 0], a third tuning tag is generated and it is prompted that the local tuning processing state of the target tuning is abnormal and the local tuning support state of the processor is abnormal.

5. The intelligent processing method for tuning data of a digital mixing console based on an ARM processor according to claim 4 is characterized in that: According to the second tuning label by formula Calculate and obtain the local tuning processing abnormality DY corresponding to the target tuning; And according to the third tuning tag, the local tuning support abnormal value JY processed by the processor corresponding to the target tuning is calculated by the formula JY=ZY1-ZY; The obtained local tuning processing abnormality and local tuning support abnormality are sorted and combined to obtain a tuning single supervision processing analysis sequence corresponding to the target tuning.

6. The method for intelligently processing tuning data of a digital mixing console based on an ARM processor according to claim 5, characterized in that: Obtain all tuning single supervision processing analysis sequences obtained by the target tuning corresponding processing, and respectively traverse the total number of first local tuning processing NC1 with a statistical value of 0, the total number of second local tuning processing NC2 with a non-zero value, the total number of first local tuning supports NZ1 with a statistical value of 0, and the total number of second local tuning supports NZ2 with a non-zero value; The total number of the first local tuning process and the total number of the second local tuning process are calculated by the formula Calculate and obtain the overall tuning processing value ZC corresponding to the target tuning; where DY´ is the value obtained by summing the local tuning processing abnormalities with different non-zero values; CB is the overall tuning processing standard value corresponding to the target tuning; exp() is an exponential function with the natural constant e as the base.

7. The method for intelligently processing tuning data of a digital mixing console based on an ARM processor according to claim 6, characterized in that: If the overall tuning processing value is greater than or equal to 1, an overall tuning processing normal label is generated, and the corresponding target tuning is associated with the overall tuning processing normal state; If the overall tuning processing value is less than 1, an overall tuning processing verification tag is generated, and the total number of first local tuning supports and the total number of second local tuning supports are calculated by the formula Calculate and obtain the overall tuning support abnormal value ZZ processed by the corresponding processor of the target tuning; where, It is the value obtained by summing up the local tuning support exception values ​​with different non-zero values; ZB is the overall tuning support exception standard value corresponding to the target tuning request processed by the processor.

8. The method for intelligently processing tuning data of a digital mixing console based on an ARM processor according to claim 7, characterized in that: If the overall tuning support exception value is less than 0, an overall tuning processing verification active exception label is generated, and the target tuning is associated with the overall tuning processing active exception state; If the overall tuning support exception value is greater than or equal to 0, the overall tuning processing verification passive exception label is generated, and the target tuning is associated with the overall tuning processing passive exception state; The overall tuning processing value, the overall tuning support abnormal value obtained by the target tuning corresponding processing, and the overall tuning processing normal state, the overall tuning processing active abnormal state or the overall tuning processing passive abnormal state obtained by the corresponding analysis are sorted and combined to obtain the target tuning processing abnormal supervision set.

9. The method for intelligently processing tuning data of a digital mixing console based on an ARM processor according to claim 8, characterized in that: When dynamically optimizing and managing different aspects of the target tuning according to the target tuning processing exception supervision set, optimizing and managing prompts are provided for the operation of the target tuning according to the associated overall tuning processing active abnormal state, and optimizing and managing prompts are provided for the resource support of the target tuning according to the associated overall tuning processing passive abnormal state.

10. The digital mixer tuning data intelligent processing system based on ARM processor is characterized by: include: The digital mixer different tuning processing supervision module is used to monitor, count and process the whole process of different tuning request processing during the operation of the digital mixer, obtain the tuning single supervision sequence corresponding to the different tuning processing, and perform different aspects of local tuning processing status and local tuning support status processing analysis on the obtained tuning single supervision sequence, and obtain the tuning single supervision processing analysis sequence corresponding to the different tuning processing; The multi-dimensional analysis and verification module for single tuning processing is used to analyze the overall tuning processing status according to all tuning single supervision processing analysis sequences obtained from the target tuning corresponding processing, and to check and verify the influencing factors of the processing analysis results to obtain the target tuning processing abnormal supervision set corresponding to the target tuning; The multi-dimensional optimization management module for single-item tuning processing is used to dynamically optimize the tuning processing of the target tuning and the tuning support of the processor according to the target tuning processing exception supervision set.

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