Intelligent electric meter anti-interference detection system and method based on multi-dimension signal analysis

Abstract

The application relates to the technical field of smart power grids and wireless communication security, and discloses a smart power meter anti-interference detection system and method based on multi-dimensional signal analysis, which comprises a main control chip, a wireless communication module and a power anomaly detection module; the main control chip comprises a communication quality analysis module and a data processing module; the method comprises the following steps: through synchronous analysis of radio frequency power and communication quality parameters, when communication quality degradation and abnormal power signal enhancement are identified, it is determined that malicious interference exists; subsequently, the wireless module is immediately controlled to be switched to a LoRa spread spectrum mode, and the occurrence time of the interference is recorded; the application realizes active and accurate identification of malicious interference, effectively overcomes the disadvantages of passive retransmission of the prior art, guarantees data reliability through communication mode switching, records attack time for tracing, and significantly improves the safety of the smart power meter.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of smart grid and wireless communication security, and particularly relates to a smart meter anti-interference detection system and method based on multi-dimensional signal analysis. BACKGROUND

[0002] With the popularity of smart grid, a new generation of smart meters widely uses wireless communication technologies such as LoRa and NB-IoT to realize remote automatic data collection, which greatly improves the efficiency of power management. To ensure data reliability, these wireless applications usually have error checking and retransmission protocols to deal with occasional signal fading problems in the network.

[0003] However, this mechanism relying on passive retransmission has inherent defects when facing targeted malicious radio interference. Since it is difficult to actively perceive the abnormality of the electromagnetic environment, it cannot fundamentally distinguish whether the communication failure is caused by normal network fluctuations or by the continuous suppression of illegal signal jammers.

[0004] Therefore, when encountering malicious attacks, the meter will only perform invalid cyclic retransmission and cannot switch to a more resistant communication strategy in time, which often leads to the delay or loss of critical metering data. At the same time, this mechanism is difficult to record the time of attack, leaving serious hidden dangers and blind areas for the security management of the power grid.

[0005] Therefore, the present application proposes a smart meter anti-interference detection system and method based on multi-dimensional signal analysis to solve the deficiencies of the prior art. SUMMARY

[0006] The purpose of the present application is to provide a smart meter anti-interference detection system and method based on multi-dimensional signal analysis, which solves the problem that existing smart meters lack active interference detection capability and are difficult to effectively respond to malicious attacks and record and trace.

[0007] To achieve the above purpose, the present application is implemented by the following technical scheme: a smart meter anti-interference detection system based on multi-dimensional signal analysis, comprising:

[0008] a master chip;

[0009] a wireless communication module, which is in communication connection with the master chip;

[0010] a power anomaly detection module, which is in signal connection with the master chip, for collecting radio frequency power in the working frequency band of the wireless communication module and outputting a power signal to the master chip;

[0011] The master chip comprises:

[0012] a communication quality analysis module configured to acquire a communication quality parameter generated or monitored by the wireless communication module when performing wireless communication;

[0013] a data processing module configured to receive the power signal and the communication quality parameter, and analyze the power signal and the communication quality parameter to determine whether there is malicious interference.

[0014] Preferably, the master chip is a microcontroller integrated with an analog-to-digital conversion (ADC) interface.

[0015] Preferably, the power anomaly detection module is provided with a miniature logarithmic detector chip ADL5513, a signal output end of the power anomaly detection module is connected to an analog-to-digital conversion (ADC) interface of the master chip, and the master chip collects output voltage data of the miniature logarithmic detector chip ADL5513 in real time.

[0016] The power anomaly detection module identifies abnormal energy peaks by performing periodic scanning on a communication frequency band, and generates the power signal based on the output voltage data.

[0017] Preferably, the communication quality parameter acquired by the communication quality analysis module includes at least one of a received signal strength indication, a bit error rate, a data packet loss rate, and a CRC failure rate.

[0018] Preferably, the step of acquiring the communication quality parameter by the communication quality analysis module includes:

[0019] The received signal strength indication and the bit error rate are acquired by sending an AT+CSQ standard instruction to the wireless communication module.

[0020] The data packet loss rate is calculated by monitoring a message sequence number in a next HLS communication mode under a DLMS communication protocol.

[0021] The CRC failure rate is acquired by interacting with the wireless communication module to obtain the CRC failure rate counted by the wireless communication module based on a link layer CRC check.

[0022] Preferably, the condition for the data processing module to determine that there is malicious interference is that:

[0023] The communication quality parameter indicates that the communication quality is deteriorating, and the power signal indicates that the radio frequency power is higher than a preset power threshold.

[0024] Preferably, the communication quality deterioration includes:

[0025] The bit error rate in the communication quality parameters is consistently higher than a preset degradation threshold over multiple consecutive detection periods, while the fluctuation value of the received signal strength indicator is greater than a preset fluctuation threshold.

[0026] Preferably, after the data processing module determines that malicious interference exists, the main control chip executes a preset anti-interference response, the anti-interference response including:

[0027] Control the wireless communication module to switch to LoRa spread spectrum communication mode;

[0028] The time of the malicious interference is recorded in the meter's memory.

[0029] Preferably, the data processing module further includes:

[0030] The real-time voltage data of the power anomaly detection module is compared with the reference data in the pre-stored normal communication environment voltage database constructed based on historical data using a cosine similarity algorithm. The comparison results with a similarity lower than a preset similarity threshold are used as an auxiliary judgment basis for reducing the false alarm rate.

[0031] This invention also provides a method for anti-interference detection of smart meters based on multi-dimensional signal analysis, comprising the following steps:

[0032] The power anomaly detection module periodically scans the operating frequency band of the wireless communication module to collect radio frequency power and generate corresponding power signals. At the same time, it acquires the communication quality parameters generated or monitored by the wireless communication module during wireless communication.

[0033] The data processing module receives and analyzes the power signal and the communication quality parameters. When it is determined that the communication quality parameters indicate communication quality degradation and the power signal indicates that the radio frequency power is higher than a preset power threshold, it is determined that there is malicious interference.

[0034] Upon confirmation of malicious interference, the main control chip executes a preset anti-interference response, which includes:

[0035] Control the wireless communication module to switch to LoRa spread spectrum communication mode;

[0036] The time of the malicious interference is recorded in the meter's memory.

[0037] In summary, the present invention has at least one of the following beneficial technical effects:

[0038] 1. This invention achieves synchronous monitoring of the wireless environment and communication link by setting up an independent power anomaly detection module to collect physical layer radio frequency energy in the operating frequency band in real time, and combining it with multi-dimensional communication parameters obtained by the communication quality analysis module. This endows smart meters with the ability to actively detect interference, overcomes the passivity of existing technologies that rely solely on retransmission after communication failure, and solves the technical problem of difficulty in timely early warning of interference.

[0039] 2. This invention integrates and analyzes power signals and communication quality parameters through a data processing module, constructing an interference identification model based on the anomaly of "high power, low quality." Real-time power data is then compared with pre-stored normal environmental parameters to effectively distinguish malicious interference from normal strong signal sources, reducing the possibility of false alarms. This multi-dimensional, benchmark-based judgment logic achieves accurate identification of illegal signal jammers, making it more reliable than single-indicator judgment methods.

[0040] 3. This invention, upon accurately identifying malicious interference, can immediately trigger dynamic anti-interference measures and accurately record the time of the attack, solving the problems of delayed response and difficulty in tracing existing technologies. It can instantly control the wireless communication module to switch to a communication mode with stronger anti-interference capabilities, ensuring the continuity of critical data transmission; simultaneously, the timestamp recording of the attack event provides accurate evidence for subsequent operation and maintenance audits, improving the overall robustness and manageability of the smart meter. Attached Figure Description

[0041] Figure 1 This is a system architecture diagram of the present invention;

[0042] Figure 2 This is a flowchart of the method of the present invention. Detailed Implementation

[0043] The following is in conjunction with the appendix Figure 1 - Appendix Figure 2 The present invention will be further described in detail below.

[0044] This invention provides an anti-interference detection system for smart meters based on multi-dimensional signal analysis, comprising:

[0045] A power anomaly detection module is connected to the main control chip for collecting radio frequency power within the operating frequency band of the wireless communication module and outputting a power signal to the main control chip.

[0046] In this embodiment, the core responsibility of the power anomaly detection module is to independently and objectively quantify the radio frequency power of the environment in which the smart meter is located at the physical layer, providing a crucial dimension for subsequent analysis and judgment. This aims to directly sense abnormal radio frequency energy generated by devices such as illegal signal jammers, overcoming the limitations of traditional solutions that rely solely on communication results for passive judgment.

[0047] In a preferred embodiment, the power anomaly detection module is integrated onto the circuit board (PCB) of the smart meter, and its core component is a miniature logarithmic detector chip, such as the ADL5513. The RF input of this chip is designed to couple RF signals within the operating frequency band of the wireless communication module, thereby ensuring that the frequency band it detects is consistent with the frequency band of normal communication of the meter.

[0048] This module establishes a direct signal connection with the main control chip. Specifically, the signal output terminal of the miniature logarithmic detector chip, i.e., a pin that provides analog voltage, is directly connected to an analog-to-digital converter (ADC) interface of the main control chip. This design enables the main control chip to perform high-precision real-time acquisition of the signal output by the power anomaly detection module.

[0049] The power anomaly detection module works by using a miniature logarithmic detector chip to precisely convert the power (typically in dBm) received at its RF input into a DC voltage signal that is logarithmically proportional to it. This logarithmic conversion characteristic allows the module to linearly characterize the input power over a very wide dynamic range, thus enabling it to sensitively capture energy changes ranging from weak ambient background noise to extremely strong interference signals.

[0050] During system operation, the main control chip schedules the power anomaly detection module to perform a scan of the operating frequency band at a preset period (e.g., every 5 minutes). During the scan, the main control chip continuously acquires the voltage data output by the logarithmic detector chip through its ADC interface. This digitized voltage data constitutes the power signal.

[0051] By analyzing this power signal, the system can effectively identify abnormal energy peaks in the environment, such as broadband noise covering the entire communication frequency band generated by jammers, or persistent strong signal suppression targeting a specific channel. This power signal is then transmitted to the data processing module, serving as one of the core bases for its multi-dimensional fusion analysis and final decision, providing indispensable physical layer evidence for identifying the typical interference scenario of "high power, low quality."

[0052] A wireless communication module, which is communicatively connected to the main control chip;

[0053] In this embodiment, the wireless communication module is a hardware entity that enables the smart meter to exchange wireless data with an external network (e.g., a data concentrator or a master station system). It establishes a close communication connection with the main control chip through a preset communication interface, such as a serial communication interface (UART). This connection is used not only to transmit the meter's business data but also to carry the interaction of control commands and status information.

[0054] In the technical solution of this invention, the wireless communication module serves a dual purpose. Its primary function is to act as a key data source for the communication quality analysis module. It is not merely a data channel, but rather a "sensor" capable of reflecting the channel state. Specifically, the wireless communication module is configured to respond to and execute specific query commands from the main control chip. For example, when the communication quality analysis module within the main control chip issues standard commands such as AT+CSQ, the wireless communication module can measure and report the current Received Signal Strength Indication (RSSI) and Bit Error Rate (BER) in real time, and transmit these parameters back to the main control chip via the communication interface for subsequent analysis.

[0055] Furthermore, the wireless communication module autonomously performs cyclic redundancy check (CRC) statistics on the data reception process within its internal link layer firmware. This means it can record the number of CRC check failures and cache this statistical data. The main control chip can actively acquire this CRC failure rate data through periodic network information interaction with the wireless communication module. In this way, the wireless communication module provides upper-layer analysis with multi-dimensional raw parameters that directly reflect the health status of the communication link.

[0056] Another key function of this wireless communication module is as the final "executor" of the anti-interference response strategy of this invention. In order to achieve effective dynamic anti-interference, an important technical feature of this module is that it has multi-mode communication capability and is subject to dynamic control by the main control chip.

[0057] In a preferred embodiment, the wireless communication module supports at least one conventional communication mode (e.g., NB-IoT or other narrowband IoT technologies) and one communication mode with high anti-interference characteristics. According to the core objective of this invention, when the data processing module ultimately determines that malicious interference exists, the main control chip immediately issues a control command through the communication interface, ordering the wireless communication module to dynamically switch from its current operating mode to a preset, more robust LoRa spread spectrum communication mode. After switching to LoRa mode, the module utilizes its spread spectrum gain and excellent multipath fading resistance to complete communication in environments with extremely low signal-to-noise ratios, thereby ensuring that critical metering data can still be successfully transmitted during periods of malicious interference.

[0058] The main control chip includes:

[0059] A communication quality analysis module is used to obtain communication quality parameters generated or monitored by the wireless communication module during wireless communication.

[0060] The data processing module is used to receive the power signal and the communication quality parameters, and to analyze the power signal and the communication quality parameters to determine whether there is malicious interference.

[0061] In this embodiment, the main control chip constitutes the control and decision-making core of the entire anti-interference detection system. Preferably, the main control chip is a high-performance microcontroller (MCU) with multiple analog-to-digital converter (ADC) interfaces. It not only handles the basic metering and management functions of the smart meter itself, but more importantly, its hardware capabilities and internally embedded software logic jointly realize the active interference detection function described in this invention. The main control chip directly receives analog voltage signals from the power anomaly detection module through its ADC interface and runs two key functional modules through its internal processing unit: a communication quality analysis module and a data processing module.

[0062] The communication quality analysis module, as one of the system's data input terminals, has the core responsibility of comprehensively and in real-time acquiring communication quality parameters reflecting the current communication link status from the wireless communication module connected to the main control chip. This aims to capture abnormal behavior caused by external interference from the perspective of the "result" of communication behavior. In a preferred embodiment, the parameters acquired by this module are multi-dimensional, including at least one or more of the following: Received Signal Strength Indicator (RSSI), Bit Error Rate (BER), Packet Loss Rate, and Cyclic Redundancy Check (CRC) failure rate, to construct a complete profile of communication quality.

[0063] To acquire the aforementioned parameters, the communication quality analysis module is configured to perform specific operations. For example, it can actively query and obtain the current received signal strength indication and bit error rate by sending the industry-standard AT+CSQ command to the wireless communication module. This method offers good compatibility and reliability. Furthermore, regarding the key indicator of packet loss rate, the module can utilize the characteristics of upper-layer communication protocols. For instance, by monitoring the message sequence number field in the header of each data packet in the HLS (High Security Level) communication mode under the DLMS communication protocol, since this field is an incrementing sequence number, the module can accurately calculate packet loss by analyzing its continuity. Additionally, for the CRC failure rate, the module can obtain failure rate data calculated by the wireless communication module based on CRC check results within its hardware or link layer through periodic internal network information exchange with the wireless communication module.

[0064] The data processing module, acting as the "brain" of the system, is the functional entity that executes the core analysis and decision-making logic. It receives power signals from the power anomaly detection module and multi-dimensional communication quality parameters from the communication quality analysis module, and performs fusion analysis on these two types of heterogeneous data to ultimately determine whether malicious interference exists.

[0065] The core of the data processing module's judgment logic lies in identifying an "abnormal" physical phenomenon: strong ambient radio frequency energy but extremely poor communication quality. Therefore, the primary condition for determining the presence of malicious interference is set as follows: the communication quality parameters indicate degraded communication quality, while the power signal indicates that the radio frequency power is higher than a preset power threshold.

[0066] Based on this, the present invention provides a specific and operable definition of "communication quality degradation" to avoid ambiguous judgments and improve robustness. Specifically, communication quality degradation is defined as a composite condition involving time and volatility: the bit error rate (BER) of the communication quality parameter is consistently higher than a preset degradation threshold (e.g., 15%) for multiple consecutive detection periods (e.g., three consecutive periods), while the fluctuation value of the Received Signal Strength Indication (RSSI) is greater than a preset fluctuation threshold (e.g., 20 dBm). The design concept is that genuine malicious interference usually manifests as persistent communication quality suppression, which may be accompanied by drastic and irregular jumps in signal strength. Combining these two characteristics can effectively distinguish malicious interference from occasional and transient channel fading.

[0067] To further improve the accuracy of system decision-making and effectively reduce false alarms caused by the presence of other legitimate high-power signal sources in the environment (such as nearby base stations, Wi-Fi hotspots, etc.), the data processing module is also configured to execute an auxiliary judgment process based on historical data. Specifically, the data processing module calls a normal communication environment voltage database pre-stored in the meter's memory. This database is collected and constructed under typical environments confirmed to be interference-free (e.g., low-traffic periods at night). During the judgment process, the module uses the voltage data (i.e., the original form of the power signal) output by the power anomaly detection module in real time as a vector and compares it with the reference data vector stored in the database using cosine similarity.

[0068] The mathematical principle behind this comparison can be expressed as:

[0069] ;

[0070] In the formula, This represents a vector composed of voltage data collected in real time by the power anomaly detection module. This represents a reference data vector extracted from the normal communication environment voltage database; and They are vectors sum vector In the Dimensional components; The dimension of the vector is the number of data sampling points.

[0071] The closer the calculated similarity value is to 1, the more similar the two signals are in waveform and distribution. The data processing module compares the calculated similarity with a preset similarity threshold (e.g., 0.7). When the similarity is below this threshold, the comparison result is used as a strong auxiliary criterion, significantly increasing the confidence level for ultimately determining it as malicious interference. This is equivalent to adding a "whitelist" filtering mechanism to the system, enabling it to identify signals that are "strong in energy but have a normal pattern," thus focusing on the real threats.

[0072] Finally, when the data processing module integrates all the above main and auxiliary judgment conditions and finally determines that malicious interference exists, the main control chip will immediately trigger the preset anti-interference response. For example, it will control the wireless communication module to switch to the LoRa spread spectrum communication mode with stronger anti-interference capability and issue a recording instruction: record the time of the malicious interference, accurately record the time of the malicious interference in the non-volatile memory of the meter, thereby realizing a complete closed loop from active detection to effective response and post-event traceability.

[0073] This invention also provides a method for anti-interference detection of smart meters based on multi-dimensional signal analysis, comprising the following steps:

[0074] The power anomaly detection module periodically scans the operating frequency band of the wireless communication module to collect radio frequency power and generate corresponding power signals. At the same time, it acquires the communication quality parameters generated or monitored by the wireless communication module during wireless communication.

[0075] The data processing module receives and analyzes the power signal and the communication quality parameters. When it is determined that the communication quality parameters indicate communication quality degradation and the power signal indicates that the radio frequency power is higher than a preset power threshold, it is determined that there is malicious interference.

[0076] Upon confirmation of malicious interference, the main control chip executes a preset anti-interference response, which includes:

[0077] Control the wireless communication module to switch to LoRa spread spectrum communication mode;

[0078] The time of the malicious interference is recorded in the meter's memory.

[0079] The method in this embodiment can be used to execute the above system embodiment, and its principle and technical effect are similar, so it will not be described again here.

[0080] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A smart meter anti-interference detection system based on multi-dimensional signal analysis, characterized in that, include: Main control chip; A wireless communication module, which is communicatively connected to the main control chip; A power anomaly detection module is connected to the main control chip for collecting radio frequency power within the operating frequency band of the wireless communication module and outputting a power signal to the main control chip. The main control chip includes: A communication quality analysis module is used to obtain communication quality parameters generated or monitored by the wireless communication module during wireless communication. The data processing module is used to receive the power signal and the communication quality parameters, and analyze the power signal and the communication quality parameters to determine whether there is malicious interference; it also includes comparing the real-time voltage data of the power anomaly detection module with the reference data in the pre-stored normal communication environment voltage database constructed based on historical data using a cosine similarity algorithm, and using the comparison results with a similarity lower than a preset similarity threshold as an auxiliary judgment basis for reducing the false alarm rate; Specifically, the data processing module calls a normal communication environment voltage database pre-stored in the meter's memory. This database is collected and constructed under typical conditions confirmed to be free of interference. When making a judgment, the data processing module takes the voltage data output in real time by the power anomaly detection module as a vector and compares it with the reference data vector stored in the database using cosine similarity. The mathematical principle behind this comparison is expressed as follows: In the formula, This represents a vector composed of voltage data collected in real time by the power anomaly detection module. This represents a reference data vector extracted from the normal communication environment voltage database; and They are vectors sum vector In the Dimensional components; The dimension of the vector is the number of data sampling points; the closer the calculated similarity value is to 1, the more similar the two are in waveform and distribution.

2. The smart meter anti-interference detection system based on multi-dimensional signal analysis according to claim 1, characterized in that, The main control chip is a microcontroller with an integrated analog-to-digital converter (ADC) interface.

3. The smart meter anti-interference detection system based on multi-dimensional signal analysis according to claim 1, characterized in that, The power anomaly detection module is equipped with a miniature logarithmic detector chip ADL5513. The signal output terminal of the power anomaly detection module is connected to the analog-to-digital converter (ADC) interface of the main control chip. The main control chip collects the output voltage data of the miniature logarithmic detector chip ADL5513 in real time. The power anomaly detection module identifies abnormal energy peaks by performing periodic scans of the communication frequency band and generates the power signal based on the output voltage data.

4. The smart meter anti-interference detection system based on multi-dimensional signal analysis according to claim 1, characterized in that, The communication quality parameters obtained by the communication quality analysis module include at least one of the following: received signal strength indication, bit error rate, data packet loss rate, and CRC failure rate.

5. The smart meter anti-interference detection system based on multi-dimensional signal analysis according to claim 4, characterized in that, The steps for the communication quality analysis module to obtain the communication quality parameters include: The received signal strength indication and the bit error rate are obtained by sending AT+CSQ standard commands to the wireless communication module. The packet loss rate is calculated by monitoring the message sequence number in the next HLS communication mode of the DLMS communication protocol; By periodically exchanging network information with the wireless communication module, the CRC failure rate, calculated by the wireless communication module based on link-layer CRC check within its internal system, is obtained.

6. The anti-interference detection system for smart meters based on multi-dimensional signal analysis according to claim 4, characterized in that, The data processing module determines that malicious interference exists under the following conditions: The communication quality parameter indicates communication quality degradation, while the power signal indicates that the radio frequency power is higher than a preset power threshold.

7. The anti-interference detection system for smart meters based on multi-dimensional signal analysis according to claim 6, characterized in that, The communication quality degradation includes: The bit error rate in the communication quality parameters is consistently higher than a preset degradation threshold over multiple consecutive detection periods, while the fluctuation value of the received signal strength indicator is greater than a preset fluctuation threshold.

8. The anti-interference detection system for smart meters based on multi-dimensional signal analysis according to claim 6, characterized in that, After the data processing module determines that malicious interference exists, the main control chip executes a preset anti-interference response, which includes: Control the wireless communication module to switch to LoRa spread spectrum communication mode; The time of the malicious interference is recorded in the meter's memory.

9. A smart meter anti-interference detection method based on multi-dimensional signal analysis, applied to the smart meter anti-interference detection system based on multi-dimensional signal analysis as described in any one of claims 1-8, characterized in that, Includes the following steps: The power anomaly detection module periodically scans the operating frequency band of the wireless communication module to collect radio frequency power and generate corresponding power signals. At the same time, it acquires the communication quality parameters generated or monitored by the wireless communication module during wireless communication. The data processing module receives and analyzes the power signal and the communication quality parameters. When it is determined that the communication quality parameters indicate communication quality degradation and the power signal indicates that the radio frequency power is higher than a preset power threshold, it is determined that there is malicious interference. Upon confirmation of malicious interference, the main control chip executes a preset anti-interference response, which includes: Control the wireless communication module to switch to LoRa spread spectrum communication mode; The time of the malicious interference is recorded in the meter's memory.

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