A broadcast signal monitoring and analysis system

Abstract

The invention discloses a broadcast signal monitoring and analysis system, and relates to the technical field of audio signal processing. The broadcast signal monitoring and analysis system provided by the invention adopts root mean square error as a method for measuring signal strength, and determines whether an audio signal contains human voice through zero crossing rate analysis, thereby realizing real-time monitoring and analysis of broadcast signals; realizing automatic detection of broadcast quality and coverage effect, and at the same time being able to search for harmful radio wave interference and unauthorized illegal radio wave radiation sources in the broadcast frequency band, and discovering behaviors that seriously interfere with the order of air waves, such as unauthorized use of frequency, random setting of stations, and arbitrary increase of transmission power.

Description

Technical Field

[0001] The present invention relates to the technical field of audio signal processing, and in particular to a broadcast signal monitoring and analysis system. Background Art

[0002] In view of complex business needs, news broadcasting and television stations undertake many broadcast transmission tasks at different frequencies. Among them, not only do they need to generate signals through transmitters and transmit them through antennas, but sometimes they also need to effectively suppress the signals of risky radio stations that spread sensitive content to ensure the smooth and safe transmission of their own information.

[0003] In the existing technology, when suppressing the frequencies of risky radio stations, station staff will go to the suppression area in person and use a radio to manually test the suppression effect. If the suppression effect is not as expected, the staff must promptly notify their colleagues at the radio station to manually adjust the power of the transmitter. This operation process is not only inefficient and labor-intensive, but also may cause errors and delays in the test results due to human factors.

[0004] Therefore, in order to improve work efficiency and reduce labor costs, there is an urgent need for a device that can automatically detect and convey the transmitter suppression effect, and can monitor and analyze in real time whether there is risky broadcasting in the suppressed area, so as to assist radio station staff to make quick adjustments and ensure the efficiency and accuracy of broadcast transmission tasks. Summary of the invention

[0005] The purpose of the present invention is: to address the above-mentioned problems, the present invention provides a broadcast signal monitoring and analysis system, which uses root mean square error as a method to measure signal strength, and determines whether the audio signal contains human voice through zero crossing rate analysis, thereby realizing real-time monitoring and analysis of broadcast signals.

[0006] The technical solution adopted by the present invention is as follows:

[0007] A broadcast signal monitoring and analysis system includes an acquisition layer, a data layer, a service layer and an application layer; the service layer includes an energy characteristic analysis unit, a frequency component analysis unit and an audibility analysis unit, the frequency component analysis unit reflects the frequency characteristics of an audio signal by calculating a zero crossing rate, the energy characteristic analysis unit obtains the intensity level of the audio signal by calculating a root mean square error value, and the audibility analysis module divides the audio signal into an audible human voice segment and a background noise segment by analyzing the frequency characteristics and intensity level of the audio signal; the data layer includes a storage module, the acquisition layer includes a multi-channel receiving and measuring terminal for receiving broadcast signals, the data layer is signal-connected to the acquisition layer, the service layer and the application layer, the service layer is signal-connected to the application layer, the service layer is controlled by the application layer, and the application layer can retrieve, play and process the audible human voice segment.

[0008] Furthermore, the audibility analysis unit adjusts the root mean square error value according to the zero crossing rate, and performs audibility processing on the root mean square error value through the audibility analysis unit, obtains an audibility judgment value based on the audibility processing, judges the audibility of the audio signal based on the size of the audibility judgment value, discards audio signals less than the audibility threshold, and stores audio signals greater than the audibility threshold in the data layer.

[0009] Furthermore, the frequency component analysis unit stores the calculated zero crossing rate in a zero crossing rate buffer. When the storage capacity of the zero crossing rate buffer reaches the maximum storage value, the average value of the zero crossing rate in the zero crossing rate buffer is calculated, and then the difference between each zero crossing rate and the average value is calculated, and the difference is stored in the zero crossing rate buffer; the energy characteristic analysis unit normalizes the calculated root mean square error value to obtain a normalized root mean square error value, and stores the normalized root mean square error value in a root mean square error value buffer; the audibility analysis unit determines whether the difference exceeds a preset zero crossing rate threshold. If the difference exceeds the preset zero crossing rate threshold, the normalized root mean square error value is increased to obtain a normalized root mean square error adjustment value, and the normalized root mean square error adjustment value is used to perform over-value audibility processing; if the difference does not exceed the preset zero crossing rate threshold, the normalized root mean square error value is directly used to perform normal value audibility processing.

[0010] Further, the super-value audibility processing first performs super-value comparison judgment to judge whether the normalized root mean square error adjustment value exceeds the preset super-value root mean square adjustment value. If so, the normalized root mean square error adjustment value is reset to zero, and then processed as a processing value through the processing function and the last processing time is updated. If not, it is judged whether the last processing time exceeds the preset time threshold. If so, the root mean square error value is added to form a new normalized root mean square error adjustment value, and then processed as a processing value through the processing function and the last processing time is updated. If not, it is processed as a processing value through the processing function and the last processing time is updated. processing time; the normal value audibility processing first performs a normal value comparison judgment to judge whether the normalized root mean square error value exceeds the preset normal value root mean square adjustment value. If so, the normalized root mean square error value is reset to zero, and then processed as a processing value through the processing function and the last processing time is updated. If not, it is judged whether the last processing time exceeds the preset time threshold. If so, the root mean square error value is added to form a new normalized root mean square error value, and then processed as a processing value through the processing function and the last processing time is updated. If not, it is processed as a processing value through the processing function and the last processing time is updated.

[0011] Furthermore, the processed values ​​fed into the processing function constitute a root mean square error value array. When the length of the root mean square error value array is greater than 2, the average value of the root mean square error value array is calculated, and the average value is stored in the log as the audibility judgment value; at the same time, the average value is stored in a specified Redis key, and an expiration time is set.

[0012] Furthermore, the expiration time is 5-15s.

[0013] Furthermore, the preset time threshold is 1 second.

[0014] Furthermore, when the energy characteristic analysis unit performs normalization processing on the root mean square error value, the range is enlarged to 0-4; the over-value root mean square adjustment value is 3; and the normal value root mean square adjustment value is 1.

[0015] Furthermore, the maximum storage value of the zero-crossing rate buffer is equal to the maximum storage value of the root mean square error value buffer, and the maximum storage value is 5-15.

[0016] Furthermore, the zero crossing rate threshold is 0.003-0.007.

[0017] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0018] The present invention adopts root mean square error as a method to measure signal strength, and determines whether an audio signal contains human voice through zero crossing rate analysis, thereby realizing real-time monitoring and analysis of broadcast signals.

[0019] The present invention can realize automatic detection of broadcast quality and coverage effect, and can also find harmful radio wave interference and unauthorized illegal radio wave radiation sources in the broadcast frequency band, and discover behaviors that seriously interfere with the order of air waves, such as unauthorized use of frequency, random setting of stations, and arbitrary increase of transmission power.

[0020] The present invention designs a reasonable buffer zone and threshold value and performs evaluation within a certain time window, which is suitable for the needs of real-time audio processing.

[0021] The present invention adopts a multi-threading method to simultaneously process the reception and monitoring of audio signals, thereby ensuring the response speed and stability of the system.

[0022] The present invention integrates detailed logging to facilitate debugging and problem tracking. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flowchart of the frequency component analysis unit of the present invention;

[0024] Figure 2 is a flowchart of the energy characteristic analysis unit of the present invention;

[0025] Figure 3 is a flowchart of the audibility analysis unit of the present invention;

[0026] Figure 4 It is a flowchart of the processing function of the present invention. DETAILED DESCRIPTION

[0027] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0028] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0029] Example 1

[0030] A broadcast signal monitoring and analysis system, such as Figure 1-4As shown, a broadcast signal monitoring and analysis system includes an acquisition layer, a data layer, a service layer and an application layer; the service layer includes an energy characteristic analysis unit, a frequency component analysis unit and an audibility analysis unit, the frequency component analysis unit reflects the frequency characteristics of the audio signal by calculating the zero crossing rate, the energy characteristic analysis unit obtains the intensity level of the audio signal by calculating the root mean square error value, and the audibility analysis module divides the audio signal into an audible human voice segment and a background noise segment by analyzing the frequency characteristics and intensity level of the audio signal; the data layer includes a storage module, the acquisition layer includes a multi-channel receiving and measuring terminal for receiving broadcast signals, the data layer is signal-connected to the acquisition layer, the service layer and the application layer, the service layer is signal-connected to the application layer, the service layer is controlled by the application layer, and the application layer can retrieve, play and process the audible human voice segment. Specifically, the multi-channel receiving terminal receives medium and short wave amplitude modulation broadcast signals through the radio frequency receiving module, and stores the received broadcast signals as audio signals in the data layer. The service layer can call the audio signals stored in the data layer and calculate their zero crossing rate and root mean square error value, because the strength of the audio signal is one of the key factors that determine whether it is easy to be heard by the human ear. High energy signals usually have higher audibility, and the root mean square error value not only reflects the average energy of the signal, but also takes into account the degree of change of the signal, and the calculation is relatively simple, which is suitable for real-time audio processing. Therefore, the root mean square error value is selected as an indicator of audibility judgment to help judge the audibility of the audio signal. By setting a reasonable threshold, high energy human voice signals and low energy background noise can be effectively distinguished. Because the frequency characteristics of human voice and background noise are significantly different. Human voice usually contains rich intermediate frequency components, while noise and music may have a wider frequency range. Therefore, the zero crossing rate that can characterize the frequency characteristics is selected as a fast and effective preprocessing step to help judge whether there may be human voice in the audio signal. The audibility analysis unit adjusts the root mean square error value according to the zero crossing rate, and performs audibility processing on the root mean square error value through the audibility analysis unit, obtains the audibility judgment value according to the audibility processing, judges the audibility of the audio signal according to the audibility judgment value, discards the audio signal less than the audibility threshold, and stores the audio signal greater than the audibility threshold in the data layer. The application layer can retrieve the audio signal stored in the data layer for playback and analysis, and can also control the service layer to process the audio signal according to specific needs.

[0031] The frequency component analysis unit stores the calculated zero crossing rate in a zero crossing rate buffer. When the storage capacity of the zero crossing rate buffer reaches the maximum storage value, the average value of the zero crossing rate in the zero crossing rate buffer is calculated, and then the difference between each zero crossing rate and the average value is calculated, and the difference is stored in the zero crossing rate buffer. The energy characteristic analysis unit normalizes the calculated root mean square error value and rounds it off to obtain a normalized root mean square error value, and stores the normalized root mean square error value in the root mean square error value buffer. The audibility analysis unit determines whether the difference exceeds a preset zero crossing rate threshold. If the difference exceeds the preset zero crossing rate threshold, the normalized root mean square error value is increased to obtain a normalized root mean square error adjustment value, and the normalized root mean square error adjustment value is used to perform over-value audibility processing. If the difference does not exceed the preset zero crossing rate threshold, the normalized root mean square error value is directly used to perform normal value audibility processing.

[0032] The super-value audibility processing first performs a super-value comparison judgment to judge whether the normalized root mean square error adjustment value exceeds the preset super-value root mean square adjustment value. If so, the normalized root mean square error adjustment value is reset to zero, and then processed as a processing value through a processing function and the last processing time is updated. If not, it is judged whether the last processing time exceeds a preset time threshold. If so, the root mean square error value is added to form a new normalized root mean square error adjustment value, and then processed as a processing value through a processing function and the last processing time is updated. If not, it is processed as a processing value through a processing function and the last processing time is updated. The normal value audibility processing first performs a normal value comparison judgment to judge whether the normalized root mean square error value exceeds the preset normal value root mean square adjustment value. If so, the normalized root mean square error value is reset to zero, and then processed as a processing value through a processing function and the last processing time is updated. If not, it is judged whether the last processing time exceeds a preset time threshold. If so, the root mean square error value is added to form a new normalized root mean square error value, and then processed as a processing value through a processing function and the last processing time is updated. If not, it is processed as a processing value through a processing function and the last processing time is updated.

[0033] The processed values ​​fed into the processing function constitute a root mean square error value array. When the length of the root mean square error value array is greater than 2, the average value of the root mean square error value array is calculated and rounded to two decimal places, and the average value is stored in the log as the audibility judgment value; at the same time, the average value is stored in a specified Redis key and an expiration time is set.

[0034] The expiration time is 10s.

[0035] The preset time threshold is 1 second.

[0036] When the energy characteristic analysis unit normalizes the root mean square error value, the range is enlarged to 0-4; the over-value root mean square adjustment value is 3; and the normal value root mean square adjustment value is 1.

[0037] The maximum storage value of the zero-crossing rate buffer is equal to the maximum storage value of the root mean square error value buffer, and the maximum storage value is 10.

[0038] The zero crossing rate threshold is 0.005.

[0039] The principles and implementation methods of the present invention are described in this article using specific embodiments. The description of the above embodiments is only used to help understand the method and core ideas of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made to the present invention without departing from the principles of the present invention, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.

[0040] In the description of the present invention, it should be noted that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside", etc. indicate directions or positional relationships based on the directions or positional relationships shown in the accompanying drawings, or are the directions or positional relationships in which the inventive product is usually placed when in use. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore should not be understood as a limitation on the present invention.

[0041] In the description of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

Claims

1. A broadcast signal monitoring and analysis system, characterized in that: It includes an acquisition layer, a data layer, a service layer and an application layer; the service layer includes an energy characteristic analysis unit, a frequency component analysis unit and an audibility analysis unit, the frequency component analysis unit reflects the frequency characteristics of the audio signal by calculating the zero crossing rate, the energy characteristic analysis unit obtains the intensity level of the audio signal by calculating the root mean square error value, and the audibility analysis module divides the audio signal into a human voice audible segment and a background noise segment by analyzing the frequency characteristics and intensity level of the audio signal; the data layer includes a storage module, the acquisition layer includes a multi-channel receiving and measuring terminal for receiving broadcast signals, the data layer is signal-connected to the acquisition layer, the service layer and the application layer, the service layer is signal-connected to the application layer, the service layer is controlled by the application layer, and the application layer can retrieve, play and process the human voice audible segment; the audibility analysis unit is based on The zero-crossing rate adjusts the root mean square error value, and performs audibility processing on the root mean square error value through the audibility analysis unit, obtains the audibility judgment value according to the audibility processing, judges the audibility of the audio signal according to the audibility judgment value, discards the audio signal less than the audibility threshold, and stores the audio signal greater than the audibility threshold in the data layer; the frequency component analysis unit stores the calculated zero-crossing rate in the zero-crossing rate buffer, and when the storage capacity of the zero-crossing rate buffer reaches the maximum storage value, calculates the average value of the zero-crossing rate in the zero-crossing rate buffer, and then calculates the difference between each zero-crossing rate and the average value, and stores the difference in the zero-crossing rate buffer; the energy characteristic analysis unit performs normalization processing on the calculated root mean square error value to obtain a normalized root mean square error value, and stores the normalized root mean square error value in the root mean square error value buffer; The audibility analysis unit determines whether the difference exceeds a preset zero-crossing rate threshold. If the difference exceeds the preset zero-crossing rate threshold, the normalized root mean square error value is increased to obtain a normalized root mean square error adjustment value, and the normalized root mean square error adjustment value is used to perform over-value audibility processing. If the difference does not exceed the preset zero-crossing rate threshold, the normalized root mean square error value is directly used to perform normal value audibility processing. The over-value audibility processing first performs an over-value comparison judgment to determine whether the normalized root mean square error adjustment value exceeds the preset over-value root mean square adjustment value. If so, the normalized root mean square error adjustment value is reset to zero, and then used as a processing value for processing through a processing function and the last processing time is updated. If not, it is determined whether the last processing time exceeds the preset time threshold. If so, the root mean square error value is added to form a new The normalized root mean square error adjustment value is then processed as a processing value through a processing function and the last processing time is updated. If not, it is processed as a processing value through a processing function and the last processing time is updated. The normal value audibility processing first performs a normal value comparison judgment to determine whether the normalized root mean square error value exceeds a preset normal value root mean square adjustment value. If so, the normalized root mean square error value is reset to zero, and then processed as a processing value through a processing function and the last processing time is updated. If not, it is determined whether the last processing time exceeds a preset time threshold. If so, the root mean square error value is added to form a new normalized root mean square error value, and then processed as a processing value through a processing function and the last processing time is updated. If not, it is processed as a processing value through a processing function and the last processing time is updated.

2. The broadcast signal monitoring and analysis system according to claim 1, characterized in that: The processed values ​​fed into the processing function constitute a root mean square error value array. When the length of the root mean square error value array is greater than 2, the average value of the root mean square error value array is calculated, and the average value is stored in the log as the audibility judgment value; at the same time, the average value is stored in a specified Redis key and an expiration time is set.

3. The broadcast signal monitoring and analysis system according to claim 2, characterized in that: The expiration time is 5-15s.

4. The broadcast signal monitoring and analysis system according to claim 1, characterized in that: The preset time threshold is 1 second.

5. The broadcast signal monitoring and analysis system according to claim 1, characterized in that: When the energy characteristic analysis unit normalizes the root mean square error value, the range is enlarged to 0-4; the over-value root mean square adjustment value is 3; and the normal value root mean square adjustment value is 1.

6. The broadcast signal monitoring and analysis system according to claim 1, characterized in that: The maximum storage value of the zero-crossing rate buffer is equal to the maximum storage value of the root mean square error value buffer, and the maximum storage value is 5-15.

7. The broadcast signal monitoring and analysis system according to claim 1, characterized in that: The zero crossing rate threshold is 0.003-0.007.

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