Secondary water supply pump room equipment safety monitoring system based on Internet of Things

Abstract

The invention relates to the technical field of digital information transmission, in particular to a secondary water supply pump room equipment safety monitoring system based on the Internet of Things, which comprises a data acquisition module for acquiring energy consumption data of pump room equipment, including current value, voltage value and operation time value, acquiring environmental parameters, including temperature value, humidity value and pressure value, and acquiring the energy consumption data of the pump room equipment, including current value, voltage value and operation time value; the method comprises the following steps: collecting user demand parameters including a water consumption value and a water consumption time value; according to the method, the optimal communication channel is selected, so that accurate transmission of the monitoring data is ensured, and data errors and transmission delay caused by poor channel quality are reduced. In addition, in combination with energy consumption real-time monitoring data and external factors such as power grid electricity price and weather forecast, the power demand and electricity price change can be dynamically predicted. The prediction enables the operation strategy of the pump room to be adjusted according to the prediction result, optimizes the energy use, reduces the meaningless energy consumption, and reduces the cost.

Description

Technical Field

[0001] The present invention relates to the technical field of digital information transmission, and in particular to a secondary water supply pump room equipment safety monitoring system based on the Internet of Things. Background Art

[0002] The secondary water supply pump room equipment safety monitoring system refers to a system used to monitor and manage the safety and operating status of various equipment in the water supply pump room. It mainly collects various parameter data such as water pressure, water temperature, pump operating status and energy consumption through sensors and monitoring equipment installed in the pump room, and then sends these data to the control center through digital information transmission technology. The control center will analyze the data to ensure that the equipment is operating in good condition and detect potential failures or safety risks in a timely manner.

[0003] The lack of monitoring and dynamic selection mechanisms for multiple channels in existing technologies results in insufficient response in the face of signal interference, making it difficult to ensure data continuity and integrity. In addition, existing technologies generally do not include external factors such as market electricity price changes and weather changes into the energy consumption management decision-making process, limiting the potential for energy consumption optimization. This lack of the ability to dynamically adapt to external changes may result in the inability to effectively adjust operating strategies during peak electricity demand periods, increasing energy waste and operating costs, and reducing efficiency and economy. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings existing in the prior art and to propose a secondary water supply pump room equipment safety monitoring system based on the Internet of Things.

[0005] In order to achieve the above purpose, the present invention adopts the following technical scheme: A secondary water supply pump room equipment safety monitoring system based on the Internet of Things includes: The data acquisition module collects energy consumption data of pump room equipment, including current value, voltage value, and operation time value, collects environmental parameters, including temperature value, humidity value, and pressure value, and collects user demand parameters, including water consumption value and water use time value, and integrates energy consumption data, environmental parameters, and user demand parameters to obtain comprehensive energy consumption data; monitors and records each parameter in the comprehensive energy consumption data in real time, stores it in the database, and generates real-time monitoring results of energy consumption; A multi-channel communication module monitors the signal strength value, interference level value and congestion value of the communication channel, calculates the performance index value of each channel, and obtains the performance index value; sorts the performance index values ​​and selects the channel to generate a communication channel selection result; The energy efficiency management module receives the data of the real-time monitoring results of energy consumption through the communication channel selection result, analyzes the energy consumption trend, calculates the current power load value and efficiency index value, and obtains the energy consumption analysis result; obtains the real-time power value of the power grid and weather forecast data, predicts the future power demand value and power price change value, and obtains the power demand and power price forecast results; compares the energy consumption value and cost value under each operation strategy according to the energy consumption analysis result and the power demand and power price forecast results, adjusts the start and stop time value of the pump group and the pump speed setting value, and generates the pump room operation optimization strategy; The fault recovery module monitors the working status of the current communication channel, detects the signal strength value, bit error rate value, and delay time value, and determines whether there is a fault in the current channel; when a channel fault is detected, the channel is selected for switching according to the performance indicator value.

[0006] Preferably, the steps for obtaining the real-time monitoring result of energy consumption are: Collect energy consumption data of pump room equipment, including current value, voltage value and running time value, and collect environmental parameters such as temperature value, humidity value and pressure value, as well as water consumption and water use time to obtain the initial data set; Based on the initial data set, calculate the comprehensive energy consumption index , the calculation formula is: in, represents the current value, Represents the voltage value, Represents the equipment running time, , , Represents temperature, humidity and pressure respectively. and Represents water consumption and water use time respectively. , , is the weight coefficient of each parameter combination; Based on the comprehensive energy consumption index, real-time monitoring and recording are performed, and the results are stored in a database to obtain real-time monitoring results of energy consumption.

[0007] Preferably, the steps for obtaining the performance indicator value are: Monitor the signal strength value, interference level value and congestion degree value of the communication channel to obtain a preliminary signal data set; Based on the preliminary signal data set, the performance index value of each channel is calculated , the calculation formula is: in, is the signal strength value, is the interference level value, is the congestion level value, , , and is the adjustment coefficient.

[0008] Preferably, the steps for obtaining the energy consumption analysis result are: Receive the data of the energy consumption real-time monitoring result through the communication channel selection result to obtain a preliminary energy consumption data set; Based on the preliminary energy consumption data set, calculate the current power load value and efficiency index value , the calculation formula is: and in, represents the total power consumption at each time point, is the number of time points, International electricity consumption; Based on the power load value and efficiency index value, the energy consumption trend is analyzed to obtain the energy consumption analysis results.

[0009] Preferably, the steps for obtaining the power demand and power price forecast results are: Obtain real-time power value and weather forecast data from the power grid to obtain preliminary market and environmental data sets; Forecast future electricity demand values ​​based on the preliminary market and environmental data sets and electricity price change , the calculation formula is: and in, is the current electricity value, is the predicted impact of weather factors on electricity demand, is the number of days in the forecast period, represents the standard deviation of electricity prices, is the weather change rate; Based on the power demand value and the electricity price change value, power demand and electricity price forecast results are synthesized.

[0010] Preferably, the steps for obtaining the pump room operation optimization strategy are: Collect and analyze energy consumption analysis results and power demand and the electricity price forecast results, integrate the data, and obtain a comprehensive energy and cost data set; Based on the comprehensive energy and cost data set, compare the energy consumption and operating cost under each pump room operation strategy, evaluate the economic benefits of each strategy, and obtain cost-effectiveness comparison results; Based on the cost-benefit comparison results, the start and stop times of the pump groups and the pump speed settings are adjusted to form a pump room operation optimization strategy.

[0011] Preferably, the working status of the current communication channel is monitored, the signal strength value, the bit error rate value, and the delay time value are detected, and it is determined whether the current channel has a fault; when a channel fault is detected, the steps of selecting a channel for switching according to the performance indicator value are as follows: Monitor the working status of the current communication channel, including signal strength value, bit error rate value and delay time value, and obtain a channel performance data set; Based on the channel performance data set, fault diagnosis is performed on signal strength, bit error rate and delay to determine whether there is a fault in the current channel and obtain a fault diagnosis result.

[0012] Preferably, when a channel failure is detected, a communication channel with a better performance index is selected for switching based on the fault diagnosis result and the performance index value.

[0013] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, selecting the optimal communication channel not only ensures the accurate transmission of monitoring data, but also reduces data errors and transmission delays caused by poor channel quality. In addition, by combining real-time monitoring data of energy consumption with external factors such as grid electricity prices and weather forecasts, it is possible to dynamically predict changes in electricity demand and electricity prices. This prediction enables the pump room operation strategy to be adjusted according to the prediction results, optimizes energy use, reduces unnecessary energy consumption and reduces costs. It enhances the economic operation efficiency of the pump room system and improves its adaptability to environmental changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0015] 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.

[0016] See also Figure 1 The present invention provides a technical solution: a secondary water supply pump room equipment safety monitoring system based on the Internet of Things includes: The data acquisition module collects energy consumption data of pump room equipment, including current value, voltage value, and operation time value, collects environmental parameters, including temperature value, humidity value, and pressure value, and collects user demand parameters, including water consumption value and water use time value, and integrates energy consumption data, environmental parameters, and user demand parameters to obtain comprehensive energy consumption data; monitors and records each parameter in the comprehensive energy consumption data in real time, stores it in the database, and generates real-time monitoring results of energy consumption; The multi-channel communication module monitors the signal strength value, interference level value and congestion value of the communication channel, calculates the performance index value of each channel, and obtains the performance index value; sorts the performance index values ​​and selects the channel to generate the communication channel selection result; here, the best channel in the sorting is selected; The energy efficiency management module receives the data of the real-time monitoring results of energy consumption through the communication channel selection results, analyzes the energy consumption trend, calculates the current power load value and efficiency index value, and obtains the energy consumption analysis results; obtains the real-time power value of the power grid and weather forecast data, predicts the future power demand value and power price change value, and obtains the power demand and power price forecast results; compares the energy consumption value and cost value under each operation strategy based on the energy consumption analysis results and the power demand and power price forecast results, adjusts the pump group start and stop time value and pump speed setting value, and generates the pump room operation optimization strategy; The fault recovery module monitors the working status of the current communication channel, detects the signal strength value, bit error rate value, and delay time value, and determines whether there is a fault in the current channel; when a channel fault is detected, the channel is selected for switching according to the performance indicator value.

[0017] The steps for obtaining real-time monitoring results of energy consumption are as follows: Collect energy consumption data of pump room equipment, including current value, voltage value and running time value, and collect environmental parameters such as temperature value, humidity value and pressure value, as well as water consumption and water use time to obtain the initial data set; Based on the initial data set, calculate the comprehensive energy consumption index , the calculation formula is: in, represents the current value, Represents the voltage value, Represents the equipment running time, , , Represents temperature, humidity and pressure respectively. and Represents water consumption and water use time respectively. , , is the weight coefficient of each parameter combination; Based on the comprehensive energy consumption indicators, real-time monitoring and recording are carried out, and the results are stored in the database to obtain real-time monitoring results of energy consumption.

[0018] Specifically, the energy consumption data of the pump room equipment is collected, involving real-time monitoring of current, voltage, and operating time. At the same time, environmental parameters such as temperature, humidity, pressure, and user demand for water consumption and water use time are collected. These data are captured in real time through multiple sensors. The sensors measure current and voltage accurately to milliamperes and millivolts to ensure data accuracy. The environmental parameter monitoring equipment has high sensitivity and can provide readings within the precise range of ±0.5°C and ±2%RH. The pressure sensor measurement range is usually set between 0 and 10 bars. User demand data is obtained through metering devices to track water consumption per minute. The sensor data undergoes preliminary processing, including peak filtering, baseline correction and signal smoothing, to ensure data reliability, thereby forming an initial data set.

[0019] The usefulness of the formula lies in that it combines three different dimensions: energy consumption, environmental factors, and user needs. , , Weight coefficients can flexibly optimize energy consumption for different operating environments or user behavior patterns; Calculation process: Set instance parameters: ampere, volt, Hour, Spend, , bar, Lift, Hours; Weight coefficient , , , according to the formula, the calculation process is as follows: The results show that the comprehensive energy consumption index is 6070, which represents the total energy consumption after considering equipment operation, environmental conditions and user needs. The higher the energy consumption index, the more energy is used, so further energy efficiency management and equipment optimization can be carried out based on this data.

[0020] Monitor comprehensive energy consumption data, track and record the operating status of pump room equipment in real time. During the monitoring process, the collected data include energy consumption index and environmental parameters. At the same time, through the threshold alarm mechanism, for example, the current abnormal threshold is set to ±10% of the standard operating current, and the temperature and pressure threshold settings are adjusted according to the equipment safety operation standards. Abnormal detection compares real-time data with the set safety range. If the temperature exceeds the safety range of 40°C to 45°C, the system automatically triggers an alarm. The recording function not only stores data, but also marks the time and duration of abnormal events for subsequent analysis. These monitored and recorded data are used by the system to optimize equipment performance and energy efficiency and generate real-time monitoring results of energy consumption.

[0021] The steps to obtain the performance indicator value are: Monitor the signal strength value, interference level value and congestion degree value of the communication channel to obtain a preliminary signal data set; Based on the preliminary signal data set, calculate the performance index value for each channel , the calculation formula is: in, is the signal strength value, is the interference level value, is the congestion level value, , ,and is the adjustment coefficient.

[0022] Specifically, in the process of monitoring communication channels, signal strength values, interference level values ​​and congestion degree values ​​are collected. Through sensors and high-frequency communication interfaces, the signal strength of each channel is captured in real time, and the noise and other possible interference in the channel are recorded immediately. At the same time, the channel utilization rate or traffic density is monitored to evaluate its congestion level. Then, the signal, interference and congestion data are preliminarily screened and analyzed to form a preliminary signal data set, which provides basic data for subsequent performance evaluation.

[0023] The formula is useful in that it can comprehensively consider the different impacts of the three dimensions of signal strength, interference level and congestion level, and adjust the weight of each factor in the total score through the adjustment coefficient to adapt to different communication environments; Represents the signal strength value, which is measured on a specific channel using a special signal strength detection instrument. Represents the interference level value, which is calculated by the total amount of interference elements in the channel. Represents the congestion level value, which is calculated by analyzing the traffic data of the communication channel. , ,and The acquisition is to collect historical communication data, including signal strength, interference level and congestion degree, and then perform statistical analysis on the collected data to calculate the influence of each parameter. This can be achieved through multiple regression analysis to determine the actual impact of each factor on communication efficiency; Calculation process: The signal strength of a communication channel is measured as 50 units, the interference level is 30 units, the congestion level is 20 units, and the adjustment coefficient is , , , put it into the formula and calculate: The result shows that the comprehensive performance score of the channel is 0.07609, which reflects the overall performance of the channel under current conditions. A lower score may indicate that the channel is not used efficiently and needs further optimization or adjustment.

[0024] The steps to obtain energy consumption analysis results are as follows: Receive data of real-time monitoring results of energy consumption through the communication channel selection result to obtain a preliminary energy consumption data set; Calculate the current power load value based on the preliminary energy consumption data set and efficiency index value , the calculation formula is: and in, represents the total power consumption at each time point, is the number of time points, International electricity consumption; Based on the power load value and efficiency index value, the energy consumption trend is analyzed to obtain the energy consumption analysis results.

[0025] Specifically, the data of the real-time monitoring result of energy consumption is received through the communication channel selection result to obtain a preliminary energy consumption data set, wherein the communication channel selection result is evaluated according to the previous performance indicator value to ensure the transmission quality and accuracy of the data. The preliminary data set includes information such as current, voltage and operating time collected from each device, which reflects the real-time operating status and energy consumption of the device. This data set provides necessary input information for subsequent calculation and analysis; The benefit of the formula is that by combining the ratio of actual power consumption to total power consumption, it can effectively evaluate the efficiency of energy use and provide a scientific basis for energy management; The parameter acquisition steps are to collect the power consumption data of each device at different time points. The parameter represents the total number of time points collected, which is calculated by the set sampling frequency and the total monitoring duration. The actual amount of electricity used is recorded and summarized in real time by the electric meter; Calculation process: There are 12 time points of data in one hour, and the power consumption at each time point is They are 10, 12, 11, 13, 10, 14, 10, 12, 11, 13, 10, 14 kWh respectively, and the total power consumption is Kilowatt-hour, actual electricity consumption kWh, number of time points ,but: The results show that the efficiency of energy use is about 92.3%, which means that most of the electricity is used effectively, and a small amount of electricity is lost in equipment standby or inefficient operation; Based on power load value and efficiency index value , analyze energy consumption trends and obtain energy consumption analysis results. In this process, real-time monitored energy consumption data and calculated efficiency indicators are used for trend analysis. By comparing the changes in power load and efficiency in different time periods, possible abnormal consumption or equipment efficiency decline can be identified, thereby providing decision support for equipment maintenance and energy efficiency improvement.

[0026] The steps to obtain the power demand and electricity price forecast results are as follows: Obtain real-time power value and weather forecast data from the power grid to obtain preliminary market and environmental data sets; Forecast future electricity demand based on preliminary market and environmental data sets and electricity price change , the calculation formula is: and in, is the current electricity value, is the predicted impact of weather factors on electricity demand, is the number of days in the forecast period, represents the standard deviation of electricity prices, is the weather change rate; Based on the power demand value and the power price change value, the power demand and power price forecast results are synthesized.

[0027] Specifically, the formula is beneficial in that it can take into account the impact of weather factors on electricity demand and the historical volatility of electricity prices, making the forecast of electricity demand and electricity prices more accurate; The parameter acquisition step is to obtain the current electricity price through the real-time data interface of the power grid. The impact index of weather conditions on electricity demand obtained from the weather forecast service is updated daily. is the number of days in the forecast period, usually set to 30 days, To calculate the standard deviation of electricity price data over the past 30 days, is the rate of change obtained based on historical weather change data; Calculation process: Current electricity price / kWh, number of days in the forecast period , Weather Impact Index The average is 1.05, and the standard deviation of electricity prices , weather change rate ,but: The results show that the predicted future average electricity demand will remain at 0.13 / kWh based on current conditions, while the predicted fluctuation of electricity prices is very small, only 0.0005 / kWh, indicating that under current market and weather conditions, electricity demand and electricity prices are relatively stable; The process of obtaining real-time power grid electricity value and weather forecast data involves collecting information from multiple data sources. Electricity price data usually comes from publicly released information from local power grid companies or power markets, and weather forecast data is provided by the National Meteorological Administration, including temperature, humidity, wind speed and other parameters. The integration of these two types of data provides an important basis for the operation of the power market. Through real-time monitoring of electricity prices and weather data, electricity demand and price fluctuations can be effectively predicted, thereby providing a scientific basis for power dispatch and electricity price setting.

[0028] In the process of synthesizing the power demand and power price forecast results based on the power demand value and the power price change value, the power price and weather data obtained in the first step and the power demand and power price change forecast values ​​calculated in the second step are integrated, and multivariate regression analysis or time series analysis and other methods are used to estimate future power demand and power price trends, quantify the impact of different factors on the power market, and predict future changes, thereby providing decision support for power companies and policymakers.

[0029] The steps to obtain the pump room operation optimization strategy are as follows: Collect and analyze energy consumption analysis results and electricity demand and price forecast results, and integrate the data to obtain a comprehensive energy and cost data set; Based on the comprehensive energy and cost data set, the energy consumption and operating cost under each pump room operation strategy are compared, the economic benefits of each strategy are evaluated, and the cost-effectiveness comparison results are obtained; Based on the cost-benefit comparison results, the start and stop times of the pump groups and the pump speed settings are adjusted to form an optimization strategy for the pump room operation.

[0030] Specifically, the collected energy consumption analysis results and power demand and electricity price forecast results are checked and integrated. The validity and accuracy of various data are identified during the checking process to ensure that the data set contains comprehensive energy consumption records, electricity price history and weather forecast data. Not only the existing data needs to be integrated, but also the consistency and relevance of the data needs to be screened and verified through item-by-item comparison.

[0031] Inheriting the above comprehensive data set, the pump room operation strategies are compared and evaluated. The specific operations include setting multiple simulation scenarios, where each scenario simulates the impact on energy consumption and cost according to different pump speeds and operating times. In this process, the economic feasibility of each strategy is evaluated through cost-benefit analysis, with special attention paid to the strategy performance during high energy consumption and high cost periods. This method can objectively evaluate the performance of each operation strategy under different market conditions and power demand fluctuations, and determine the strategy.

[0032] Based on the results of the cost-benefit analysis, the start and stop time of the pump group and the pump speed setting are adjusted. By analyzing the operating parameters, the pump speed and operating time are manually set in the control system. These parameter adjustments are aimed at achieving dual optimization of energy and cost. During the adjustment process, real-time energy consumption data and electricity price changes are continuously monitored to ensure that all settings closely follow market dynamics and the actual needs of the grid load. Through these real-time adjustments, the pump room's operating strategy can minimize energy costs while ensuring efficiency.

[0033] Monitor the working status of the current communication channel, detect the signal strength value, bit error rate value, delay time value, and determine whether the current channel has a fault; when a channel fault is detected, the steps of selecting a channel for switching according to the performance indicator value are as follows: Monitor the working status of the current communication channel, including signal strength value, bit error rate value and delay time value, and obtain a channel performance data set; Based on the channel performance data set, perform fault diagnosis on signal strength, bit error rate and delay, determine whether there is a fault in the current channel, and obtain the fault diagnosis result; When a channel failure is detected, a communication channel with a better performance index is selected for switching based on the fault diagnosis result and the performance index value.

[0034] Specifically, after initializing the monitoring, the equipment is adjusted to regularly capture signal strength, bit error rate and delay time parameters. The signal strength is directly measured and converted into a numerical value. The bit error rate is automatically recorded in the form of error bits per second. The delay time records the time difference between the sending and receiving of the data packet. These parameters are summarized to form a comprehensive channel performance data set, which provides a real-time view of the signal quality and sets a safety threshold for the signal strength. For example, a signal less than -85dBm is considered weak and the signal source or environmental interference needs to be checked. A bit error rate exceeding 5 error bits per kilobit is considered high and may indicate physical or frequency interference. A delay time exceeding 100 milliseconds is considered to be non-compliant with real-time communication standards and indicates network congestion or configuration problems.

[0035] Based on the channel performance data set, abnormal fluctuations in signal strength, bit error rate and delay are identified, and fault diagnosis is performed by comparing with the set threshold. Signal strength lower than the threshold or abnormal bit error rate and delay directly trigger the fault state, and identify which parameters exceed the normal operating range of communication. These parameter points exceeding the threshold are marked as potential fault signals. If the continuous measurement results of any parameter show abnormality, a specific fault diagnosis result is generated.

[0036] When a channel failure is discovered, the fault response is activated immediately. An evaluation is performed based on the previous fault diagnosis results and the performance indicator values ​​of each channel. The channel with the best performance indicator is selected for switching. The selected channel undergoes a short load test before switching to ensure that the new channel can meet the current communication needs. The continuity of communication and data integrity are maintained during the switching process to ensure stable operation of communication that is not affected by the failure.

Claims

1. A secondary water supply pump room equipment safety monitoring system based on the Internet of Things, characterized in that: The system comprises: The data acquisition module collects energy consumption data of pump room equipment, including current value, voltage value, and operation time value, collects environmental parameters, including temperature value, humidity value, and pressure value, and collects user demand parameters, including water consumption value and water use time value, and integrates energy consumption data, environmental parameters, and user demand parameters to obtain comprehensive energy consumption data; monitors and records each parameter in the comprehensive energy consumption data in real time, stores it in the database, and generates real-time monitoring results of energy consumption; A multi-channel communication module monitors the signal strength value, interference level value and congestion value of the communication channel, calculates the performance index value of each channel, and obtains the performance index value; sorts the performance index values ​​and selects the channel to generate a communication channel selection result; The energy efficiency management module receives the data of the real-time monitoring results of energy consumption through the communication channel selection result, analyzes the energy consumption trend, calculates the current power load value and efficiency index value, and obtains the energy consumption analysis result; obtains the real-time power value of the power grid and weather forecast data, predicts the future power demand value and power price change value, and obtains the power demand and power price forecast results; compares the energy consumption value and cost value under each operation strategy according to the energy consumption analysis result and the power demand and power price forecast results, adjusts the start and stop time value of the pump group and the pump speed setting value, and generates the pump room operation optimization strategy; The fault recovery module monitors the working status of the current communication channel, detects the signal strength value, bit error rate value, and delay time value, and determines whether there is a fault in the current channel; when a channel fault is detected, the channel is selected for switching according to the performance indicator value.

2. The secondary water supply pump room equipment safety monitoring system based on the Internet of Things according to claim 1 is characterized in that: The steps for obtaining the real-time monitoring result of energy consumption are as follows: Collect energy consumption data of pump room equipment, including current value, voltage value and running time value, and collect environmental parameters such as temperature value, humidity value and pressure value, as well as water consumption and water use time to obtain the initial data set; Based on the initial data set, calculate the comprehensive energy consumption index , the calculation formula is: in, represents the current value, Represents the voltage value, Represents the equipment running time, , , Represents temperature, humidity and pressure respectively. and Represents water consumption and water use time respectively. , , is the weight coefficient of each parameter combination; Based on the comprehensive energy consumption index, real-time monitoring and recording are performed, and the results are stored in a database to obtain real-time monitoring results of energy consumption.

3. The secondary water supply pump room equipment safety monitoring system based on the Internet of Things according to claim 1 is characterized in that: The steps for obtaining the performance indicator value are as follows: Monitor the signal strength value, interference level value and congestion degree value of the communication channel to obtain a preliminary signal data set; Based on the preliminary signal data set, the performance index value of each channel is calculated , the calculation formula is: in, is the signal strength value, is the interference level value, is the congestion level value, , ,and is the adjustment coefficient.

4. The secondary water supply pump room equipment safety monitoring system based on the Internet of Things according to claim 1 is characterized in that: The steps for obtaining the energy consumption analysis result are: Receive the data of the energy consumption real-time monitoring result through the communication channel selection result to obtain a preliminary energy consumption data set; Based on the preliminary energy consumption data set, calculate the current power load value and efficiency index value , the calculation formula is: and in, represents the total power consumption at each time point, is the number of time points, International electricity consumption; Based on the power load value and efficiency index value, the energy consumption trend is analyzed to obtain the energy consumption analysis results.

5. The secondary water supply pump room equipment safety monitoring system based on the Internet of Things according to claim 1 is characterized in that: The steps for obtaining the power demand and power price forecast results are as follows: Obtain real-time power value and weather forecast data from the power grid to obtain preliminary market and environmental data sets; Forecast future electricity demand values ​​based on the preliminary market and environmental data sets and electricity price changes , the calculation formula is: and in, is the current electricity value, is the predicted impact of weather factors on electricity demand, is the number of days in the forecast period, represents the standard deviation of electricity prices, is the weather change rate; Based on the power demand value and the electricity price change value, power demand and electricity price forecast results are synthesized.

6. The secondary water supply pump room equipment safety monitoring system based on the Internet of Things according to claim 1 is characterized in that: The steps for obtaining the pump room operation optimization strategy are as follows: Collect and analyze energy consumption analysis results and power demand and the electricity price forecast results, integrate the data, and obtain a comprehensive energy and cost data set; Based on the comprehensive energy and cost data set, compare the energy consumption and operating cost under each pump room operation strategy, evaluate the economic benefits of each strategy, and obtain cost-effectiveness comparison results; Based on the cost-benefit comparison results, the start and stop times of the pump groups and the pump speed settings are adjusted to form a pump room operation optimization strategy.

7. The secondary water supply pump room equipment safety monitoring system based on the Internet of Things according to claim 1 is characterized in that: Monitor the working status of the current communication channel, detect the signal strength value, bit error rate value, delay time value, and determine whether the current channel has a fault; when a channel fault is detected, the steps of selecting a channel for switching according to the performance indicator value are as follows: Monitor the working status of the current communication channel, including signal strength value, bit error rate value and delay time value, and obtain a channel performance data set; Based on the channel performance data set, fault diagnosis is performed on the signal strength, bit error rate and delay to determine whether there is a fault in the current channel and obtain a fault diagnosis result.

8. The secondary water supply pump room equipment safety monitoring system based on the Internet of Things according to claim 7 is characterized in that: Also includes: When a channel failure is detected, a communication channel with a better performance index is selected for switching based on the fault diagnosis result and the performance index value.

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