Multi-channel frequency modulation signal real-time monitoring system

Abstract

The invention discloses a multi-channel frequency modulation signal real-time monitoring system which comprises at least one monitoring node and a remote cloud platform. The monitoring nodes simultaneously receive multiple paths of frequency modulation signals through the multi-channel radio frequency receiving unit, the signal processing unit demodulates and detects multiple quality parameters such as field intensity, signal-to-noise ratio, frequency offset and multipath interference, the main control unit generates alarm information, and finally the alarm information is uploaded to the cloud platform through the communication unit integrated with 4G / 5G and Wi-Fi. And the cloud platform is responsible for storing and analyzing data and pushing alarms and information display to the authorized user terminal. According to the invention, a multi-core DSP parallel processing architecture, dual-path power supply and battery redundancy power supply and multi-parameter association intelligent alarm logic are adopted, cloud networking management is realized, and the problems of few monitoring channels, low efficiency, insufficient intelligent degree and difficult remote operation and maintenance in the prior art are solved. Therefore, efficient, reliable and intelligent remote monitoring of multi-channel FM signals is realized.

Description

Technical Field

[0001] This invention relates to the field of broadcast signal monitoring technology, and in particular to a multi-channel FM signal real-time monitoring system. Background Technology

[0002] As an important means of information dissemination, FM broadcasting requires continuous monitoring of its broadcast quality. Currently, monitoring of FM signals largely relies on traditional monitoring or analysis instruments. These devices are typically deployed in equipment rooms or monitoring stations, and their functions are relatively limited, mostly capable of localized parameter measurement and display for a single or at most two or three signal channels, such as basic parameters like field strength and frequency offset. Existing technologies face the following pressing problems that need to be addressed:

[0003] Insufficient monitoring capacity and efficiency: With the increase in broadcast frequencies, existing single-channel or limited-channel equipment cannot simultaneously monitor multiple programs in real time. If multiple signals need to be monitored, multiple devices need to be stacked, resulting in a bloated system, high costs, and cumbersome operation.

[0004] Lack of intelligent analysis and fault diagnosis capabilities: Most existing equipment is limited to displaying the current value of various parameters or performing simple threshold over-limit alarms. It lacks the ability to perform correlation analysis on multiple parameters (such as frequency deviation, signal-to-noise ratio, multipath interference, etc.), and cannot intelligently identify and judge complex fault modes (such as external co-channel interference). It still relies on the experience of operation and maintenance personnel to make judgments, resulting in slow response speed and easy misjudgment.

[0005] Weak remote monitoring and centralized management capabilities: Traditional monitoring equipment often lacks efficient and reliable remote communication interfaces (such as 4G / 5G wireless transmission), or only provides simple local communication protocols, making it impossible to upload massive amounts of monitoring data to the central management platform in real time. This makes it difficult to achieve remote visualization of equipment status and unified network management of monitoring points across regions. Maintenance personnel must be on-site, making it impossible to achieve true unattended operation and intelligent maintenance.

[0006] The system's reliability design is inadequate: many monitoring points are located in remote areas with poor mains power stability, and most existing equipment uses a single power supply design. Once there is an unexpected power outage, the equipment will stop working immediately, not only failing to report the power outage status, but also creating monitoring blind spots and posing a significant safety hazard to broadcasting.

[0007] Therefore, there is an urgent need for a comprehensive monitoring system that can simultaneously monitor multiple signals, has intelligent analysis and diagnostic functions, supports centralized management on a remote cloud platform, and has high reliability. Summary of the Invention

[0008] To address the problems of limited functionality, limited monitoring channels, and inability to perform remote centralized real-time monitoring and intelligent analysis in existing frequency modulation signal monitoring equipment, this invention proposes a multi-channel frequency modulation signal real-time monitoring system.

[0009] The specific technical solution is as follows: A multi-channel frequency modulation signal real-time monitoring system, comprising:

[0010] At least one monitoring node and a remote cloud platform, each monitoring node comprising:

[0011] Multi-channel RF receiver unit: Simultaneously receives multiple FM signals;

[0012] Signal processing unit: Demodulates each signal and detects signal quality parameters;

[0013] Main control unit: controls and coordinates monitoring nodes and generates alarm information;

[0014] Communication unit: communicates data with the remote cloud platform;

[0015] The remote cloud platform is used to receive, store, and analyze data from monitoring nodes, and to provide data display and alarm information push services to authorized user terminals. By constructing a collaborative monitoring system composed of monitoring nodes and a remote cloud platform, centralized acquisition, remote transmission, and cloud management of multiple FM signals can be achieved, fundamentally solving the problem that traditional equipment cannot achieve multi-channel remote centralized monitoring.

[0016] Furthermore, the monitoring node also includes:

[0017] Power management unit: It adopts dual AC power input interfaces and has built-in priority switching circuit and lithium battery backup power.

[0018] The priority switching circuit is configured to prioritize the use of the main AC power supply and automatically and seamlessly switch to the backup AC power supply when the main power supply fails. When both AC power supplies fail, it automatically switches to the lithium battery backup power supply.

[0019] The main control unit monitors the status of the dual AC power supply in real time and generates a power outage alarm message, including device identification information, and uploads it to the remote cloud platform when switching to backup battery power. Employing a redundant design with dual AC power supply and lithium battery backup power, and configured with a priority switching circuit, it can automatically and seamlessly switch power supply when the main power supply fails, ensuring the monitoring node's continuous and stable operation in harsh power supply environments. Simultaneously, by actively uploading power outage alarms, it enables remote real-time detection of power supply faults.

[0020] Furthermore, the communication unit integrates a 4G / 5G cellular network module and a Wi-Fi module, and supports a dual network link backup strategy;

[0021] The main control unit is configured to prioritize communication via Ethernet wired connection. When the wired connection is interrupted, it automatically activates the 4G / 5G module to establish a communication link and reports the network switching event as status information to the cloud platform. By integrating 4G / 5G and Wi-Fi modules and adopting a dual network link backup strategy, the wireless link can be automatically activated for communication when the wired network is interrupted, effectively ensuring the continuity and reliability of the data upload channel and avoiding single points of failure in communication.

[0022] Furthermore, the signal processing unit employs a multi-core DSP processor parallel processing architecture: an independent processing core is allocated to each FM signal, enabling real-time synchronous measurement of field strength, signal-to-noise ratio, audio frequency offset, composite signal frequency offset, multipath interference intensity, pilot signal status, stereo indication status, and left and right channel audio levels for at least eight signals. By adopting a multi-core DSP parallel processing architecture and allocating an independent processing core to each signal, high-precision, real-time synchronous measurement of multiple parameters across multiple signals can be achieved, significantly improving the monitoring channel capacity and data accuracy.

[0023] Furthermore, the signal processing unit also includes a multi-parameter correlation analysis module, and the main control unit has pre-set correlation alarm logic;

[0024] When the multi-parameter correlation analysis module detects that the frequency offset of a certain signal exceeds the limit, and simultaneously detects that the signal-to-noise ratio of that signal drops beyond a first threshold, and the multipath interference intensity exceeds a second threshold, the correlation alarm logic triggers a composite alarm to indicate external interference from signals at the same frequency. By introducing the multi-parameter correlation analysis module and the preset correlation alarm logic, a composite alarm to indicate external interference from signals at the same frequency can be intelligently triggered when multiple conditions such as frequency offset exceeding the limit, signal-to-noise ratio drop, and multipath interference enhancement are simultaneously met, greatly improving the accuracy and intelligence of fault diagnosis.

[0025] Furthermore, the monitoring node is equipped with a front panel status indicator device, including LED indicator groups for indicating network and cloud connection status, lockout status of each radio frequency signal, dual power supply status, and backup battery charging status, providing localized one-stop visual monitoring of equipment operating status. By setting up an integrated status indicator device on the front panel, on-site maintenance personnel can be provided with one-stop visual monitoring of equipment status, greatly simplifying local maintenance work and improving maintenance efficiency.

[0026] Furthermore, the remote cloud platform features a standardized RESTful API interface and a public MQTT communication protocol, allowing third-party monitoring devices to connect after authorization and authentication, and receive real-time data streams and alarm information from designated monitoring nodes. By providing a standardized RESTful API and MQTT communication protocol through the cloud platform, authorized third-party monitoring devices can access and receive data, effectively improving the system's openness and integration capabilities, and avoiding information silos.

[0027] Furthermore, the system supports network management of multiple geographically dispersed monitoring nodes. The remote cloud platform aggregates and compares monitoring parameters from different nodes for the same transmission frequency, and performs preliminary fault location or interference source identification based on the spatial distribution differences of parameters from each node. By managing multiple geographically dispersed monitoring nodes in a network and performing aggregation, comparison, and spatial analysis of data at the same frequency based on the cloud platform, fault location and preliminary interference source identification can be achieved, thereby supporting network-level monitoring and macro-level decision-making.

[0028] Furthermore, the user terminal is a mobile smart terminal, which has a built-in monitoring application providing a visual human-machine interface. This application simultaneously displays multi-channel signal parameters from multiple monitoring nodes in the form of lists, graphs, and dashboards, and supports filtering and backtracking of historical alarm information by alarm level, time, and device location. By embedding a feature-rich monitoring application in the mobile smart terminal, maintenance personnel can be provided with intuitive and efficient multi-parameter visualization and historical data backtracking capabilities anytime, anywhere, significantly improving the flexibility and convenience of remote monitoring.

[0029] Furthermore, the charging and discharging management circuit of the lithium battery backup power supply is integrated into the power management unit, and the battery health status and charging cycle count are uploaded to the cloud platform as part of the device status information. By uploading the battery health status and charging cycle count as device status information to the cloud platform, remote predictive health management of the backup battery can be achieved, facilitating advance maintenance planning and further improving system reliability.

[0030] The above technical solution has the following advantages or technical effects:

[0031] 1. This invention achieves fully automated monitoring of multiple FM signals from acquisition, processing to transmission, management and analysis by constructing a systematic architecture of "monitoring nodes + cloud platform".

[0032] 2. This invention achieves a leap from "single-point single-parameter" monitoring capability to "multi-channel multi-parameter intelligent diagnosis" through multi-core DSP parallel processing and multi-parameter correlation analysis, significantly improving monitoring efficiency and accuracy.

[0033] 3. This invention ensures the system operates continuously and stably in complex environments and meets the high reliability requirements of unattended operation through multiple reliability designs such as dual power supply redundancy, dual network link backup, and battery health management.

[0034] 4. This invention achieves spatial correlation analysis and remote visual monitoring of monitoring data through cloud-based network management and mobile terminal applications, greatly improving the intelligence level and response speed of operation and maintenance management.

[0035] 5. By providing a standardized open interface, this invention has good scalability and integration, can be flexibly integrated into the existing monitoring system, protect user investment, and adapt to the future development needs of smart broadcasting. Attached Figure Description

[0036] Figure 1 This is a schematic diagram of the system structure of the present invention;

[0037] Figure 2 This is a schematic diagram of the monitoring node structure of the present invention. Detailed Implementation

[0038] To make the technical solution of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0039] like Figure 1 As shown, a multi-channel frequency modulation signal real-time monitoring system adopts a distributed architecture design and consists of several monitoring nodes, a remote cloud platform, and multiple user terminals.

[0040] Monitoring nodes are deployed at various monitoring points, responsible for collecting and initially processing FM signals. The remote cloud platform, serving as the system's central hub, is deployed on a cloud server cluster, providing equipment management, data storage, and analysis services. User terminals are mobile devices or PC workstations used by maintenance personnel. These terminals access the cloud platform via web browsers or mobile applications to achieve remote monitoring. The monitoring nodes, remote cloud platform, and user terminals are connected via the internet and mobile communication networks, forming a complete monitoring ecosystem.

[0041] Each monitoring node is assigned a unique device identifier (such as IMEI number or MAC address). This device identifier is bound to the monitoring node's geographical location information and registered with the remote cloud platform. The remote cloud platform uses the device identifier to distinguish and manage the data uploaded by each node.

[0042] like Figure 2 As shown, the monitoring nodes specifically include:

[0043] Multi-channel RF receiver unit: Implemented using an 8-channel FM receiver chip, such as TEF6686, equipped with a wideband receiving antenna, covering a frequency range of 87MHz to 108MHz. Each channel is equipped with an independent front-end bandpass filter and a low-noise amplifier (LNA), achieving a receiving sensitivity of 2μV.

[0044] Signal processing unit: Utilizing a multi-core DSP processor to implement a parallel processing architecture, such as the TMS320C6678, each processing core is responsible for demodulating and measuring parameters of one signal channel. Measured parameters include field strength (dBμV), signal-to-noise ratio (dB), audio frequency offset (kHz), composite signal frequency offset (kHz), multipath interference intensity (dB), pilot signal status, stereo indication status, and left / right channel audio levels (dBFS). Parameter measurements are implemented using specialized algorithms: field strength measurement employs an RMS detection algorithm, signal-to-noise ratio calculation uses frequency domain analysis methods, and frequency offset measurement uses phase demodulation technology. The system supports automatic identification and switching of multiple deemphasis modes, including 50μS and 75μS.

[0045] Main Control Unit: Employs an ARM Cortex-A series processor, such as the i.MX8, as the main controller, running an embedded Linux operating system. It coordinates the work of each unit, executes alarm logic judgments, and generates structured alarm information containing timestamps, device IDs, alarm types, and specific parameter values. The main control unit incorporates intelligent analysis algorithms capable of simultaneously performing correlation analysis on the changing trends of multiple parameters. When an abnormal combination of specific parameters is detected, the system triggers an intelligent alarm. For example, when a frequency offset value exceeding a preset range, a signal-to-noise ratio drop exceeding a threshold, and multipath interference intensity increase are simultaneously detected, the system determines it to be a co-channel interference event and generates corresponding diagnostic alarm information. This multi-parameter correlation analysis method significantly improves the accuracy of fault diagnosis.

[0046] Communication Unit: Integrates a 4G / 5G module (such as Quectel EC20), a Wi-Fi module (supporting 802.11ac), and a Gigabit Ethernet interface. It employs a link backup strategy, prioritizing wired network use and using the wireless network as a backup channel. It supports the MQTT protocol to establish persistent connections with the cloud platform, with a heartbeat interval of 30 seconds and a configurable data upload interval (default 1 second). The system prioritizes wired network connections by default; when a wired network interruption is detected, it automatically switches to the wireless network connection to ensure continuous data transmission. All communication data is encrypted using TLS for transmission, ensuring data security.

[0047] Power Management Unit: Employs dual AC220V inputs, equipped with overvoltage and overcurrent protection circuits. It features a built-in intelligent switching circuit and a lithium battery pack (12V / 10Ah). The switching logic is as follows: primary circuit priority; in case of primary circuit failure, switching to backup circuit within 10ms; in case of failure of both circuits, seamless switching to battery power. The battery supports three-stage intelligent charging: trickle charging (<13.5V), constant current charging (1A), and constant voltage charging (13.8V).

[0048] The main control unit has a built-in multi-parameter correlation analysis algorithm. When the following conditions are detected simultaneously, a "co-frequency interference alarm" is triggered: the audio frequency deviation exceeds ±75kHz (preset range), the signal-to-noise ratio drops by more than 15dB within 1 second (first threshold), and the multipath interference intensity is greater than -20dB (second threshold). The alarm information is encapsulated in JSON format.

[0049] The remote cloud platform adopts a microservice architecture, supporting multi-node network management. It can uniformly manage multiple geographically dispersed monitoring nodes and, by comparing and analyzing monitoring data from different nodes for the same frequency signal, pinpoint fault locations and identify interference sources. For example, when signal interference occurs in a certain area, the platform can analyze signal quality data from multiple nodes to preliminarily determine the approximate location of the interference source. The remote cloud platform includes the following service modules:

[0050] Device access service: Responsible for establishing secure connections (TLS 1.3 encryption) with monitoring nodes, and handling device registration, authentication, and status maintenance.

[0051] Data storage services: Monitoring data is stored using a time-series database (InfluxDB), and device metadata and alarm records are stored using a relational database (MySQL), supporting high-speed data read and write and long-term data retention.

[0052] Data analysis services: Implement multi-node data correlation analysis algorithms, including: field strength comparison analysis of the same frequency at different nodes, interference source localization algorithm (based on arrival field strength difference), trend prediction algorithm (based on historical data ARIMA model), and provide functions such as real-time data display, historical data query, trend analysis, and anomaly detection.

[0053] API Gateway Service: Provides RESTful API interfaces (HTTP / JSON) and an MQTT broker, supporting integration with third-party systems. API interfaces include: GET / devices / {id} / status to retrieve device status, POST / alarms / subscribe to subscribe to alarm information, and GET / history / data to query historical data.

[0054] The user terminal monitoring application is developed using the React Native framework and supports iOS and Android platforms. The main interface includes:

[0055] Dashboard View: Displays the field strength and signal-to-noise ratio of 8 signals in real time in the form of a signal strength dashboard. When the threshold is exceeded, it turns into a red warning.

[0056] Alarm list view: Displays all alarm events in chronological order, and supports filtering by alarm level (normal, important, urgent).

[0057] Historical data view: Provides a time selector (last 1 hour, 24 hours, 7 days), displays parameter change trends in the form of a line graph, and supports multi-point comparison display.

[0058] Map view: Based on GIS technology, the location of all monitoring nodes is displayed on the map, and the equipment status is represented by color coding (green for normal, yellow for warning, and red for fault).

[0059] The user terminal provides a web-based management interface and a mobile application. The management interface displays real-time signal parameters for each channel in a dashboard format, using color coding to identify device status. The system supports multi-node switching and provides a map mode to display node distribution. The alarm management interface displays alarm events in chronological order and supports filtering by type, level, and status. The historical data interface supports querying by time range, displays parameter change trends in a line graph format, and supports multi-parameter overlay display and data export functions.

[0060] The system configuration interface provides comprehensive management functions, including alarm threshold settings, notification method configuration, and user permission management. The system supports remote device upgrades and configuration synchronization, allowing maintenance personnel to perform batch configuration updates on monitoring nodes deployed in different locations via the network.

[0061] This system also provides a comprehensive alarm management mechanism. It supports multi-level alarm policies, triggering different levels of alarms based on the severity of parameter anomalies. Alarm information is notified to maintenance personnel through various methods, including SMS, email, and mobile application push notifications. The system records the complete alarm handling process, including the entire process of alarm generation, confirmation, processing, and deactivation.

[0062] The system provides comprehensive data backup and archiving capabilities. Monitoring data is automatically backed up to multiple storage nodes to ensure data security. The system supports data export, allowing historical data to be exported to formats such as CSV and Excel for further analysis and processing.

[0063] The system of this invention enables comprehensive monitoring and management of multiple FM signals, solving the problems of limited channel count, low intelligence level, and weak remote operation and maintenance capabilities of traditional monitoring equipment. Through highly integrated hardware design and intelligent software algorithms, it achieves high-efficiency and high-reliability signal monitoring, providing an effective technical means for ensuring the quality of broadcast signals.

[0064] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A real-time monitoring system for multi-channel frequency modulation signals, characterized in that, include: At least one monitoring node and a remote cloud platform, each monitoring node comprising: Multi-channel RF receiver unit: Simultaneously receives multiple FM signals; Signal processing unit: Demodulates each signal and detects signal quality parameters; Main control unit: controls and coordinates monitoring nodes and generates alarm information; Communication unit: communicates data with the remote cloud platform; The remote cloud platform is used to receive, store, and analyze data from monitoring nodes, and to provide data display and alarm information push services to authorized user terminals.

2. The multi-channel frequency modulation signal real-time monitoring system according to claim 1, characterized in that, The monitoring nodes also include: Power management unit: It adopts dual AC power input interfaces and has built-in priority switching circuit and lithium battery backup power. The priority switching circuit is configured to prioritize the use of the main AC power supply and automatically and seamlessly switch to the backup AC power supply when the main power supply fails. When both AC power supplies fail, it automatically switches to the lithium battery backup power supply. The main control unit monitors the status of the dual AC power supply in real time, and when switching to backup battery power, it generates a power outage alarm message including device identification information and uploads it to the remote cloud platform.

3. A multi-channel frequency modulation signal real-time monitoring system according to claim 1 or 2, characterized in that, The communication unit integrates a 4G / 5G cellular network module and a Wi-Fi module, and supports a dual network link backup strategy; The main control unit is configured to prioritize communication via Ethernet wired connection. When the wired connection is interrupted, the 4G / 5G module is automatically activated to establish a communication link, and the network switching event is reported to the cloud platform as status information.

4. The multi-channel frequency modulation signal real-time monitoring system according to claim 1, characterized in that, The signal processing unit adopts a multi-core DSP processor parallel processing architecture: an independent processing core is allocated to each FM signal to realize real-time synchronous measurement of field strength, signal-to-noise ratio, audio frequency offset, composite signal frequency offset, multipath interference intensity, pilot signal status, stereo indication status, and left and right channel audio levels of at least 8 signals.

5. The multi-channel frequency modulation signal real-time monitoring system according to claim 4, characterized in that, The signal processing unit also includes a multi-parameter correlation analysis module, and the main control unit has pre-set correlation alarm logic. When the multi-parameter correlation analysis module detects that the frequency offset of a certain signal exceeds the limit, and simultaneously detects that the signal-to-noise ratio of that signal drops beyond the first threshold and the multipath interference intensity exceeds the second threshold, the correlation alarm logic triggers a composite alarm to indicate external interference from co-frequency signals.

6. The multi-channel frequency modulation signal real-time monitoring system according to claim 1, characterized in that, The monitoring node is equipped with a front panel status indicator device, including an LED indicator group for indicating network and cloud connection status, lock status of each radio frequency signal, dual power supply status and backup battery charging status, providing localized one-stop visual monitoring of the device's operating status.

7. The multi-channel frequency modulation signal real-time monitoring system according to claim 1, characterized in that, The remote cloud platform has a standardized RESTful API interface and an open MQTT communication protocol, allowing third-party monitoring devices to access the platform after authorization and authentication, and receive real-time data streams and alarm information from designated monitoring nodes.

8. The multi-channel frequency modulation signal real-time monitoring system according to claim 1, characterized in that, The system supports network management of multiple geographically dispersed monitoring nodes. The remote cloud platform aggregates and compares monitoring parameters from different nodes for the same transmission frequency, and performs preliminary judgment on fault location or interference source location based on the spatial distribution differences of parameters of each node.

9. The multi-channel frequency modulation signal real-time monitoring system according to claim 1, characterized in that, The user terminal is a mobile smart terminal with a built-in monitoring application that provides a visual human-machine interface. The monitoring application displays multiple signal parameters of multiple monitoring nodes simultaneously in the form of lists, graphs, and dashboards, and supports filtering and tracing historical alarm information by alarm level, time, and device location.

10. A multi-channel frequency modulation signal real-time monitoring system according to claim 2, characterized in that, The charging and discharging management circuit of the lithium battery backup power supply is integrated into the power management unit, and uploads the battery health status and charging cycle count as part of the device status information to the cloud platform.

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