WO2023124843A1 - 多传感融合的高精度水位测量装置及方法 - Google Patents

多传感融合的高精度水位测量装置及方法 Download PDF

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WO2023124843A1
WO2023124843A1 PCT/CN2022/137044 CN2022137044W WO2023124843A1 WO 2023124843 A1 WO2023124843 A1 WO 2023124843A1 CN 2022137044 W CN2022137044 W CN 2022137044W WO 2023124843 A1 WO2023124843 A1 WO 2023124843A1
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water level
water
sensor
value
microprocessor
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PCT/CN2022/137044
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English (en)
French (fr)
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丁榕
彭进双
庄桂玉
石金双
谈书才
冯运
张海彬
谭志
徐恒兴
吴海权
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奥格科技股份有限公司
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Publication of WO2023124843A1 publication Critical patent/WO2023124843A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
    • G01F23/00—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm
    • G01F23/04—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm by dip members, e.g. dip-sticks
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
    • G01F23/00—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm
    • G01F23/14—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm by measurement of pressure
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
    • G01F23/00—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm
    • G01F23/22—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm by measuring physical variables, other than linear dimensions, pressure or weight, dependent on the level to be measured, e.g. by difference of heat transfer of steam or water
    • G01F23/28—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm by measuring physical variables, other than linear dimensions, pressure or weight, dependent on the level to be measured, e.g. by difference of heat transfer of steam or water by measuring the variations of parameters of electromagnetic or acoustic waves applied directly to the liquid or fluent solid material
    • G01F23/296—Acoustic waves

Definitions

  • the invention relates to the field of water level measurement, in particular to a multi-sensor fusion high-precision water level measurement device and method.
  • water level gauges there are many different water level gauges on the market, such as electronic water gauges, ultrasonic water level gauges, radar water level gauges and other water level measuring devices that integrate water level sensors and wireless data communication, which can realize continuous and automatic monitoring of water level data.
  • the above-mentioned equipment is bulky and needs to be installed by destroying the road surface or poles, which affects the city's municipal appearance and cannot be installed quickly.
  • the current mainstream water level measuring devices on the market generally use a single type of water level sensor, which cannot complement the advantages of different types of water level sensors to highlight the advantages of different types of water level sensors.
  • the electronic water gauge has high measurement accuracy and is not affected by environmental factors such as temperature, humidity, sediment, waves, and rainfall. The accuracy is generally 1cm, and the range can be customized freely.
  • the pressure sensor has ultra-compact size, high-precision resolution, large measuring range, and high waterproof level. It can be converted into the corresponding water level value by measuring the pressure.
  • the transmission medium of the water-mediated ultrasonic sensor (hereinafter referred to as "ultrasonic sensor”) is water.
  • the probe emits ultrasonic waves vertically to the horizontal plane of the earth and reflects at the junction of water and air.
  • the depth of water is measured by the time difference method. It has an ultra-compact volume, High precision resolution, large measuring range, high waterproof level. If the electronic water gauge, pressure sensor, and ultrasonic sensor can be calibrated and deeply fused with each other, they can learn from each other's strengths and make use of their advantages to realize the design conditions for the miniaturization of water level measurement devices.
  • the present invention provides a multi-sensor fusion high-precision water level measurement device and method, deep fusion of various types of sensors, high measurement accuracy, miniaturization of equipment volume, and easy installation , low maintenance cost, low equipment power consumption, etc., solves the problems of the existing water level measuring device, such as large volume, inconvenient installation, and difficulty in working for a long time.
  • the present invention provides a multi-sensor fusion high-precision water level measuring device, including a microprocessor, a power supply, a first water level sensor and a second water level sensor, the first water level sensor is an electronic water gauge provided with a water encounter monitoring module, The second water level sensor is a pressure sensor and/or an ultrasonic sensor, and the water-encountering monitoring module, the pressure sensor, and the ultrasonic sensor are respectively connected to the microprocessor, and the water-encountering monitoring module is used to send a signal for controlling the working mode of the measuring device;
  • the microprocessor collects the measured value of the electronic water gauge as the measurement result; when the water level value is greater than HA, the microprocessor collects the measured value of the second water level sensor, and compares the measured value Perform filter estimation processing to estimate the best measurement results;
  • the microprocessor is in a low power consumption mode and reports data periodically when there is no water, and when the water monitoring module encounters water, it reports to the microprocessor.
  • Send an interrupt signal the microprocessor switches from the low power consumption mode to the working mode and speeds up the data reporting, and turns on the measuring device to make it work normally;
  • the second is to turn off the power switch of the measuring device and not report the data when there is no water.
  • the microprocessor collects the measured value of the pressure sensor at the same time, and calibrates the atmospheric pressure value of the pressure sensor; when the water level value When it is greater than HA, the water level value adopts the measured value of the pressure sensor.
  • the second water level sensor is a pressure sensor and an ultrasonic sensor
  • the variance of the process noise W(n) of the fusion measurement of the pressure sensor and the ultrasonic sensor is Q, and the variance R of the measurement error, for the pressure
  • the parameters of sensors and ultrasonic sensors are averaged for processing;
  • the microprocessor When the water level value is not greater than HA, the microprocessor also collects the measured value of the pressure sensor, and calibrates the atmospheric pressure value of the pressure sensor;
  • the measured value of the pressure sensor is used as the water level value, and the measured values of the pressure sensor and the water-mediated ultrasonic sensor are fused to obtain an average value, and the average value is filtered and estimated.
  • the filter estimation process is based on the Kalman filter algorithm, and the state equation corresponding to the established Kalman filter state space model is:
  • n is the discrete time
  • X(n) is the state of the second water level sensor at time n
  • W(n) is the process noise
  • ⁇ is the state transition matrix
  • ⁇ is the noise driving matrix
  • V(n) is the measurement error of the second water level sensor
  • H is the observation matrix
  • Z(n) is the corresponding state observation signal.
  • the process of the filter estimation process is as follows:
  • the measurement deviation and its covariance P(n-1) at the n-1th moment are obtained;
  • the measurement deviation at the nth moment is calculated, and according to the water level value at the n-1th moment and the water level value at the nth moment, the state equation and the observation equation are used to obtain The estimate closest to the true value;
  • the state equation and the observation equation are continuously recursive through the Kalman filter algorithm, thereby estimating the optimal water level value.
  • the present invention provides a multi-sensor fusion high-precision water level measurement method.
  • the measurement method is based on the above-mentioned measuring device.
  • the water monitoring module in the ruler is equipped with detection electrodes, the detection electrodes are several stainless steel screws, and several stainless steel screws are arranged and installed in the vertical direction of the adapter plate; the measurement method includes the following steps:
  • the water monitoring module senses whether there is water through the detection electrode
  • the water-encounter monitoring module realizes the control of the working mode of the measuring device according to the sensing results, wherein the control methods include two types: one is that the microprocessor is in a low-power mode and reports data periodically when there is no water, and when the water-encounter monitoring module Send an interrupt signal to the microprocessor when encountering water, the microprocessor switches from low power consumption mode to working mode and speeds up the data reporting, and turns on the measuring device to make it work normally; the second is to turn off the power switch of the measuring device and not report when there is no water Data, when the water monitoring module encounters water, turn on the power switch of the measuring device to make the measuring device work normally and speed up the reporting of data;
  • the microprocessor collects the measured value of the electronic water gauge as the measurement result; when the water level value is greater than HA, the microprocessor collects the measured value of the second water level sensor, and performs filtering and estimation processing on the measured value, Estimate the best measurement results;
  • the filter estimation process is based on the Kalman filter algorithm, and the corresponding state equation of the established Kalman filter state-space model is:
  • n discrete time
  • X(n) is the state of the second water level sensor at time n
  • W(n) is the process noise
  • ⁇ is the state transition matrix
  • ⁇ is the noise driving matrix
  • V(n) is the measurement error of the second water level sensor
  • H is the observation matrix
  • Z(n) is the corresponding state observation signal
  • the microprocessor sends the optimal measurement result through the NB communication mode or the LORA communication mode.
  • step S3 when the second water level sensor is a pressure sensor, when the water level value is not greater than HA, the microprocessor collects the measured value of the pressure sensor at the same time, and calibrates the atmospheric pressure value of the pressure sensor; when the water level value is greater than HA In HA, the water level value adopts the measured value of the pressure sensor;
  • step S4 when there is no water or the water level is low, the microprocessor sends the optimal measurement result through the NB communication mode; when the water level exceeds the penetration water level value of the measuring device, the microprocessor sends the most excellent measurement results.
  • the present invention has the following beneficial effects:
  • the working mode of the equipment is controlled by the detection electrode of the water detection module, and the detection electrode adopts the control mode based on the water detection.
  • the whole device When there is no water, the whole device is basically in the low power consumption mode of shutting down. When it encounters water, it will restart and enter the normal state.
  • Working mode so it has very low power consumption. It hardly consumes battery power when there is no water, which greatly prolongs the working time of the equipment and reduces the maintenance cost of the equipment. It is especially suitable for the water level monitoring environment without water for a long time.
  • the water ingress detection module is placed at the bottom of the equipment shell, which can effectively detect whether there is water in the equipment; the displacement sensor can monitor the illegal displacement of the equipment; if there is any abnormality in the internal and external environment, it will immediately report to the monitoring platform.
  • Fig. 1 is the modular block diagram of the high-precision water level gauge measuring device of multi-sensor fusion in the embodiment of the present invention
  • Fig. 2 is a partition measurement diagram of a high-precision water level gauge measuring device with multi-sensor fusion in an embodiment of the present invention
  • Fig. 3 is a schematic diagram of the electronic water gauge measurement of the multi-sensor fusion high-precision water level gauge measuring device in the embodiment of the present invention
  • Fig. 4 is the ultrasonic sensor measurement schematic diagram of the high-precision water level gauge measuring device of multi-sensor fusion in the embodiment of the present invention
  • Fig. 5 is a flow chart of switching transmission modes in an embodiment of the present invention.
  • Fig. 6 is a water level diagram corresponding to the segmented transmission mode in the embodiment of the present invention.
  • this embodiment provides a multi-sensor fusion high-precision water level gauge measurement device, including a plastic shell (upper cover and lower cover) 1, epoxy resin 3 for sealing and filling, a power module, and an FPC soft row Line 5, ultrasonic sensor 6, adapter plate 100, main board 200, power module includes battery 4; adapter plate 100 integrates electronic water gauge 102, stainless steel screw 2, pressure sensor 103 and display module 104, etc., electronic water gauge 102 is set There is a water monitoring module 101; the motherboard 200 integrates a microprocessor 201, a power conversion module 202, a NB communication module 203, a LORA communication module 204, a wired/wireless charging module 205, a Bluetooth module 206, a magnetic switch 207, a storage module 208, Electricity monitoring module 209, temperature and humidity module 210, water inflow detection module 211, displacement sensor 212, etc.
  • the main board and the adapter board are connected through the FPC flexible cable 5, and the microprocessor 201 is responsible for communicating
  • the electronic water gauge and pressure sensor are used to detect water level information, and the ranges are HA and HB respectively, and HA ⁇ HB.
  • the ultrasonic sensor is used to detect the water level information in the high range.
  • the ultrasonic sensor range is HC.
  • the ultrasonic sensor and the shell are coupled through a coupler.
  • the water level measurement range is HA ⁇ water level ⁇ HC.
  • the three sensors of electronic water gauge, pressure sensor and ultrasonic sensor constitute a full-range and no-blind zone measurement.
  • the water monitoring module in the adapter board is used to send a control signal to the main power supply or an interrupt signal to the microprocessor, so as to control the working mode of the measuring device of this embodiment.
  • the water-encounter monitoring module uses low-power components, and the detection electrode of the water-encounter monitoring module uses anti-corrosion stainless steel screws 2.
  • the detection electrode uses the conductivity of the water body to detect the water level, and the water can only touch the detection electrode; in this embodiment, multiple The stainless steel screws 2 are arranged and installed in the vertical direction of the adapter plate, as shown in Figure 3-4 shown.
  • the display module is used to display information such as charging and working status.
  • NB and LORA In terms of data transmission mode, two communication modules, NB and LORA, are used.
  • NB and LORA communication modules are respectively used for long and short distance communication with the monitoring platform.
  • the NB communication module is the main Internet of Things module, with ultra-low power consumption and ultra-wide operating temperature range, it is an ideal choice for the Internet of Things in various industries in smart cities to provide comprehensive SMS and data transmission services.
  • the LORA communication module uses spread spectrum technology to communicate. In the same urban and industrial application environment, its performance is better than that of radio frequency products that use traditional modulation methods. The advantages are particularly obvious in harsh noise environments.
  • the receiving sensitivity and sensitivity can be improved by reducing the transmission rate. communication distance.
  • LORA Compared with the NB communication module, LORA has higher receiving sensitivity (about 7dBm higher) and a longer effective communication distance (increasing the probability of successful communication) at low rates.
  • the NB module has a certain ability to penetrate stagnant water, and the LORA module has a stronger ability to penetrate stagnant water than the NB module under the same conditions.
  • the device uses the NB communication module to communicate with the monitoring platform through the base station relay.
  • the ability of the RF signal of the NB communication module to penetrate stagnant water is related to the distance from the device to the base station. The shorter the distance, the stronger the signal strength and the stronger the ability to penetrate stagnant water, and vice versa; therefore, the device can
  • the success rate of water communication is used to record the height value of the penetration water level (that is, the water depth h1).
  • water depth h1 Once the water level exceeds the penetrating water level of the device (water depth h1), switch from NB communication mode to LORA communication mode, and the microprocessor of the device performs point-to-point LORA communication with nearby relay devices. Since the distance between this device and the relay equipment is very short (several meters to tens of meters), use the LORA communication module of the two to communicate with the strong ability to penetrate the accumulated water, and finally use the NB communication module that comes with the relay equipment to communicate with the nearby base station . If the success rate of LORA communication is too low, you can set the LORA communication module to use the lowest communication rate to improve the probability of communication success. Its communication penetration depth is h2.
  • the transmission will be suspended, and the transmission mode will be selected by periodically detecting the water level and depth in turn. .
  • the water permeability of the device is greatly improved, which can meet the needs of many usage scenarios (such as passing through tunnels, under overpasses, urban roads, and low-lying places).
  • the magnetic switch is used for the non-contact switch of the equipment.
  • the microprocessor judges the power on and off of the equipment and the Bluetooth on and off according to the length of time for the magnet to control the magnetic switch, further reducing power consumption.
  • the power monitoring module is used to collect the voltage of the battery, convert it into power information and upload it to the monitoring platform, and prompt the management personnel in time when the battery capacity is insufficient.
  • the battery is a rechargeable lithium battery with a built-in protection board.
  • the power conversion module generates corresponding working voltage with high efficiency.
  • the charging module integrates wired and wireless charging methods; the Bluetooth module is used for device debugging, parameter query and setting; the magnetic switch is a non-contact switch, which improves the reliability of the device. Wireless charging, Bluetooth modules and non-contact magnetic switches do not need to be connected to the device with cables.
  • the potting epoxy resin can be soaked in water for a long time, which helps the device to reach the IP68 waterproof level, improves the waterproof ability of the device, and greatly improves the durability of the product. reliability.
  • the storage module is used to store key information such as historical water level information, related parameters, and IP addresses.
  • the temperature and humidity module is used to obtain the temperature and humidity inside the device, which is convenient for later maintenance; the water ingress detection module is placed at the bottom of the device shell to detect whether there is water in the device; the displacement sensor is used to monitor the illegal displacement of the device; Immediately report the abnormality to the monitoring platform.
  • the measuring device of this embodiment uses a plastic shell structurally, and injects epoxy resin to wrap the adapter board, and the product can be soaked in water for a long time after the product is glued, reaching the IP68 waterproof level, which greatly improves the reliability of the product.
  • the microprocessor When the water encounter monitoring module encounters water, it sends an interrupt signal to the microprocessor, and the measuring device works normally.
  • the microprocessor performs fusion calibration and segmental measurement through the multi-sensor fusion measurement technology, and uses Kalman filter for filtering, which improves the Multi-sensor fusion measurement accuracy; the microprocessor is in low power mode when there is no water.
  • the control of the working mode of the measuring device is realized through the detection electrode of the water monitoring module.
  • the control mode based on water monitoring has very low power consumption, which greatly prolongs the working time of the equipment. After the water level reaches a certain water level information, it intelligently adapts to the collection frequency, that is, the collection frequency is automatically controlled, and the higher the water level, the more frequent the collection.
  • the multi-sensor fusion measurement technology operated by the microprocessor has three combinations for the fusion of sensors:
  • the microprocessor collects the water level values of the electronic water gauge and the pressure sensor at the same time, and the measured value is expressed as the electronic water gauge.
  • the measured value is accurate, and the atmospheric pressure value of the pressure sensor is calibrated at the same time; because there is a certain correlation between the measured value of the electronic water gauge and the measured value of the pressure sensor, the actual average atmospheric pressure can be collected and calculated multiple times. From the measurement principle of the absolute pressure sensor, it can be known that the measured pressure P is the sum of the static water pressure P w and the atmospheric pressure P 0 , and the water body pressure is proportional to the water depth, as follows:
  • ⁇ is the density of water
  • g is the acceleration of gravity
  • both are constants
  • H(k) is The measured water level height of the electronic water gauge is averaged on P 0 (k) to reduce the measurement error:
  • the detection electrode uses a stainless steel screw with a diameter as small as possible. Take the average to minimize measurement error.
  • the water level value uses the measured value of the pressure sensor, and the measured value is filtered by the Kalman filter to obtain the final measurement result.
  • Kalman filtering is a time-domain filtering method, which is described by the state-space method.
  • the algorithm adopts a recursive form, and the data storage capacity is small. It can handle stationary random processes, multi-dimensional and non-stationary random processes, and is the most important optimal estimate.
  • the theory has been widely applied in various fields.
  • Formula (4) is the state equation
  • formula (5) is the observation equation
  • n is the discrete time
  • Z(n) ⁇ R m is the corresponding state observation signal
  • W (n) ⁇ R r is the process noise (white noise)
  • ⁇ is the state transition matrix
  • ⁇ is the noise driving matrix
  • H is the observation matrix.
  • the estimated value 22.87cm of the Kalman filter algorithm is closer to the real value 23.1cm.
  • update the deviation P(n) (1-K*H)*P(n
  • the Kalman filter algorithm greatly reduces the measurement error. Although the Kalman filter error has not completely disappeared, it is very likely that the state is close to the real value.
  • the transmission medium of the water-mediated ultrasonic sensor is water, so no matter the air pressure changes on the water surface, or the air contains a lot of steam, mist, and dust, it will not affect the normal operation of the water-mediated ultrasonic sensor and increase the measurement error.
  • the propagation speed of ultrasonic waves in water is related to the temperature and density of water, and requires a certain sound speed correction coefficient.
  • water-mediated ultrasonic sensors have higher measurement accuracy, and higher accuracy can be obtained if sound velocity and temperature compensation are used.
  • the water-mediated ultrasonic probe is generally installed in a coupled manner, which can realize non-contact water level measurement.
  • the Kalman filtering algorithm is also used for estimation processing, and the specific Kalman filtering process refers to the above-mentioned measurement technique (1).
  • the operation process is as follows: Assuming that the actual water level value at time n is to be estimated, the water level value at time n must be predicted based on the water level value at time n-1.
  • the water level value measured by the ultrasonic sensor is 23.5cm
  • the actual water level value is 23.1cm
  • the deviation of the measured value is 0.4cm.
  • the water level value measured at time n-1 can be 22.5cm, and at time n
  • the measured water level is 23.5cm, and the estimated value closest to the real value is obtained by using the state equation and observation equation.
  • the expected deviation is P(n
  • the variance of the process noise W(n) of the fusion measurement of the pressure sensor and the ultrasonic sensor is Q
  • the variance R of the measurement error is to process the average value of the parameters (such as Q, R) of the pressure sensor and the ultrasonic sensor.
  • the water level value of the electronic water gauge and the pressure sensor are collected at the same time, and the measured value is based on the water level value of the electronic water gauge. There is a certain correlation between the two. Multiple acquisitions can be used to calculate the actual average atmospheric pressure. For details, refer to Measurement Technology (1).
  • the fusion of the water level values measured by the pressure sensor and the water-mediated ultrasonic sensor is averaged (for example, weighted average), and related parameters are optimized, and Kalman filtering is used for the average value
  • the Kalman filtering process refers to the measurement technique (1) for the specific Kalman filtering process.
  • this embodiment also proposes a multi-sensor fusion high-precision water level measurement method, which is based on the above-mentioned measurement device; the measurement method includes the following steps:
  • the water monitoring module senses whether there is water through the detection electrode
  • the water-encounter monitoring module realizes the control of the working mode of the measuring device according to the sensing results, wherein the control methods include two types: one is that the microprocessor is in a low-power mode and reports data periodically when there is no water, and when the water-encounter monitoring module Send an interrupt signal to the microprocessor when encountering water, the microprocessor switches from low power consumption mode to working mode and speeds up the data reporting, and turns on the measuring device to make it work normally; the second is to turn off the power switch of the measuring device and not report when there is no water Data, when the water monitoring module encounters water, turn on the power switch of the measuring device to make the measuring device work normally and speed up the reporting of data;
  • the microprocessor collects the measured value of the electronic water gauge as the measurement result; when the water level value is greater than HA, the microprocessor collects the measured value of the second water level sensor, and performs filtering and estimation processing on the measured value, Estimate the best measurement results;
  • the filter estimation process is based on the Kalman filter algorithm, and the corresponding state equation of the established Kalman filter state-space model is:
  • n is the discrete time
  • X(n) is the state of the second water level sensor at time n
  • W(n) is the process noise
  • ⁇ is the state transition matrix
  • ⁇ is the noise driving matrix
  • V(n) is the measurement error of the second water level sensor
  • H is the observation matrix
  • Z(n) is the corresponding state observation signal
  • the microprocessor sends the optimal measurement result through the NB communication mode or the LORA communication mode.
  • the microprocessor When there is no water or the water level is low, the microprocessor sends the optimal measurement result through the NB communication mode; when the water level exceeds the penetration water level value of the measuring device, the microprocessor sends the optimal measurement result through the LORA communication mode .

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  • Physics & Mathematics (AREA)
  • Fluid Mechanics (AREA)
  • General Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
  • Electromagnetism (AREA)
  • Thermal Sciences (AREA)
  • Measurement Of Levels Of Liquids Or Fluent Solid Materials (AREA)

Abstract

多传感融合的高精度水位测量装置及方法，水位测量装置包括微处理器(201)、电源模块、第一水位传感器和第二水位传感器，第一水位传感器为设有遇水监测模块(101)的电子水尺(102)，第二水位传感器为压力传感器(103)和/或超声波传感器(6)，遇水监测模块(101)用于发送控制测量装置工作模式的信号；水位值不大于HA时微处理器（201）采集电子水尺（102）的测量值作为测量结果；水位值大于HA时微处理器（201）采集第二水位传感器的测量值，并对测量值进行滤波估计处理，估算出最优的测量结果。水位测量装置将多传感器进行深度融合，测量精度高，实现了设备体积微型化，容易安装、维护成本低、功耗低、可长时间工作。

Description

多传感融合的高精度水位测量装置及方法 技术领域
本发明涉及水位测量领域，具体涉及多传感融合的高精度水位测量装置及方法。
背景技术
随着经济发展，城市日新月异，大中城市的建设在突飞猛进高速发展，城市圈也在不断扩大，各地正在进行智慧城市建设。近年来，由于强降雨引起的城市下穿隧道、立交桥下、城市道路、低洼处积水的现象常有发生，且有愈演愈烈的趋势。在多雨的城市，有些内涝积水高达1米，水位短时间内不能及时下降，给人们的出行带来不便，严重时引发行人失踪和死亡的事件。
目前市面上存在很多种不同的水位计，如电子水尺、超声波水位计、雷达水位计等集成了水位传感器、无线数据通讯于一体的水位测量装置，可以实现对水位数据的连续自动监测。上述设备体积大、需要破坏路面或者立杆安装，影响城市的市政市容，也无法实现快速安装。此外，目前市面上主流的水位测量装置一般采用单个类型的水位传感器，无法将不同类型水位传感器的优势互补，以突出不同类型水位传感器的优点。
电子水尺具有测量精度高，不受温度、湿度、泥沙、波浪、降雨等环境因素的影响，精度一般为1cm，量程可以自由定制。压力传感器具有超紧凑的体积、高精度分辨率、量程较大、防水等级高，可以通过测量压力的方式转换为对应水位值。水介式超声波传感器(以下简称“超声波传感器”)的传输介质为水，探头垂直大地水平面朝天发射超声波，在水和空气交界处发生反射，通过时差法测出水的深度，具有超紧凑的体积、高精度分辨率、量程较大、防水等级高。若能将电子水尺、压力传感器、超声波传感器三种传感器融之间进行相互校准、深度融合，则能取长补短、发挥优势，实现水位测量装置微型化的设计条件。
发明内容
有鉴于现有技术的上述缺陷，本发明提供多传感融合的高精度水位测量装置及方法，将多种类型传感器进行深度融合，测量精度高，实现了设备体积的微型化，还具有容易安装、维护成本低、设备功耗低等优点，解决了现有水位测量装置体积大、安装不便利、难以长时间工作的问题。
一方面，本发明提供多传感融合的高精度水位测量装置，包括微处理器、电源、第一水位传感器和第二水位传感器，第一水位传感器为设有遇水监测模块的电子水尺，第二水位传感器为压力传感器和/或超声波传感器，遇水监测模块、压力传感器、超声波传感器分别与微处理器连接，遇水监测模块用于发送控制所述测量装置工作模式的信号；
设电子水尺的量程为HA，水位值不大于HA时微处理器采集电子水尺的测量值作为测量结果；水位值大于HA时微处理器采集第二水位传感器的测量值，并对测量值进行滤波估计处理，估算出最优的测量结果；
通过遇水监测模块实现对所述测量装置工作模式的控制方式包括两种：一是无水时微处理器处于低功耗模式并周期上报数据，当遇水监测模块遇水时向微处理器发送中断信号，微处理器从低功耗模式切换到工作模式且加快上报数据，开启测量装置使其正常工作；二是无水时关闭测量装置的电源开关且不上报数据，当遇水监测模块遇水时开启测量装置的电源开关，使测量装置正常工作，且加快上报数据。
在一个优选的实施例中，当第二水位传感器为压力传感器时，在水位值不大于HA时，微处理器同时采集压力传感器的测量值，并对压力传感器的大气压值进行校准；当水位值大于HA时，水位值采用压力传感器的测量值。
在另一个优选的实施例中，当第二水位传感器为压力传感器和超声波传感器时，设压力传感器、超声波传感器融合测量的过程噪声W(n)的方差为Q、测量误差的方差R，对压力传感器、超声波传感器的参数取平均值进行处理；
在水位值不大于HA时，微处理器还采集压力传感器的测量值，并对压力传感器的大气压值进行校准；
当水位值大于HA时，水位值采用压力传感器的测量值，并对压力传感器和水介式超声波传感器的测量值融合取平均值，对所述平均值进行滤波估计处理。
优选地，所述滤波估计处理基于Kalman滤波算法，建立的Kalman滤波状态空间模型对应的状态方程为：
X(n+1)＝ΦX(n)+ΓW(n)＝X(n)+W(n)
其中n为离散时间，X(n)为时刻n的第二水位传感器状态，W(n)为过程噪声，Φ为状态转移矩阵，Γ为噪声驱动矩阵；
Kalman滤波状态空间模型对应的观测方程为：
Z(n)＝HX(n)+V(n)＝X(n)+V(n)
其中V(n)为第二水位传感器的测量误差，H为观测矩阵，Z(n)为对应状态观测信号。
进一步优先地，所述滤波估计处理的过程如下：
根据第n-1时刻的第二水位传感器测量的水位值和实际水位值，求取第n-1时刻的测量偏差及其协方差P(n-1)；
根据第n时刻的第二水位传感器测量的水位值和实际水位值，求取第n时刻的测量偏差，并根据第n-1时刻水位值、第n时刻水位值，运用状态方程和观测方程得到最逼近真实值的估计值；
通过Kalman滤波算法不断地递归状态方程和观测方程，从而估算出最优的水位值。
另一方面，本发明提供多传感融合的高精度水位测量方法，该测量方法基于上述测量装置，上述测量装置还包括转接板，电子水尺、压力传感器设置在转接板上，电子水尺中遇水监测模块设有检测电极，检测电极为若干个不锈钢螺钉，若干个不锈钢螺钉在转接板的竖直方向排列安装；该测量方法包括以下步骤：
S1、遇水监测模块通过检测电极感应是否有水；
S2、遇水监测模块根据感应结果实现对所述测量装置工作模式的控制，其中控制方式包括两种：一是无水时微处理器处于低功耗模式并周期上报数据，当遇水监测模块遇水时向微处理器发送中断信号，微处理器从低功耗模式切换到工作模式且加快上报数据，开启测量装置使其正常工作；二是无水时关闭测量装置的电源开关且不上报数据，当遇水监测模块遇水时开启测量装置的电源开关，使测量装置正常工作，且加快上报数据；
S3、水位值不大于HA时，微处理器采集电子水尺的测量值作为测量结果；水位值大于HA时，微处理器采集第二水位传感器的测量值，并对测量值进行滤波估计处理，估算出最优的测量结果；
所述滤波估计处理基于Kalman滤波算法，建立的Kalman滤波状态空间模型对应的状态方程为：
X(n+1)＝ΦX(n)+ΓW(n)＝X(n)+W(n)
其中n为离散时间，X(n)为时刻n的第二水位传感器状态，W(n)为过程噪声，Φ 为状态转移矩阵，Γ为噪声驱动矩阵；
Kalman滤波状态空间模型对应的观测方程为：
Z(n)＝HX(n)+V(n)＝X(n)+V(n)
其中V(n)为第二水位传感器的测量误差，H为观测矩阵，Z(n)为对应状态观测信号；
S4、微处理器通过NB通信模式或LORA通信模式，发送最优的测量结果。
优选地，步骤S3中，当第二水位传感器为压力传感器时，在水位值不大于HA时，微处理器同时采集压力传感器的测量值，并对压力传感器的大气压值进行校准；当水位值大于HA时，水位值采用压力传感器的测量值；
步骤S4中，在无水或者水位低的时候，微处理器通过NB通信模式发送最优的测量结果；当水位高度超过测量装置的穿透水位高度值时，微处理器通过LORA通信模式发送最优的测量结果。
与现有技术相比，本发明具有如下有益效果：
1、采用多传感融合测量技术，并使用Kalman滤波器进行滤波，提高了测量精度；还实现了设备体积的微型化，具有安装简单、维护成本低、设备功耗低等优点。
2、通过遇水监测模块的检测电极控制设备的工作模式，而检测电极采用基于遇水监测的控制模式，无水时整个设备基本上处于关闭的低功耗模式，遇水时再启动进入正常工作模式，因而具有很低的功耗，无水时几乎不消耗电池电量，大大延长了设备的工作时间，降低了设备维护成本，特别适合于长时间无水的水位监测环境中。
3、使用以NB为主、LORA为辅的互为备份的水位分段传输方式，提升设备透水能力，提高设备的通信成功率。
4、进水检测模块置于设备壳体底部，可有效检测设备内部是否进水；位移传感器能监测设备非法位移；内外环境如有异常立即向监控平台报警。
附图说明
图1是本发明实施例中多传感融合的高精度水位计测量装置的模块框图；
图2是本发明实施例中多传感融合的高精度水位计测量装置的分区测量图；
图3是本发明实施例中多传感融合的高精度水位计测量装置的电子水尺测量示意图；
图4是本发明实施例中多传感融合的高精度水位计测量装置的超声波传感器测 量示意图；
图5是本发明实施例中传输方式的切换流程图；
图6是本发明实施例中分段传输方式对应的水位图。
具体实施方式
下面结合附图及实施例对本发明的实施方式进行详细说明，但是本发明可以由权利要求限定和覆盖的多种不同方式实现，即本发明的实施方式并不限于此。
实施例
如图1所示，本实施例提供多传感融合的高精度水位计测量装置，包括塑料外壳(上盖和下盖)1、用于密封填充的环氧树脂3、电源模块、FPC软排线5、超声波传感器6、转接板100、主板200，电源模块包括电池4；转接板100集成了电子水尺102、不锈钢螺钉2、压力传感器103及显示模块104等，电子水尺102设有遇水监测模块101；主板200集成了微处理器201、电源转换模块202、NB通信模块203、LORA通信模块204、有线/无线充电模块205、蓝牙模块206、磁开关207、存储模块208、电量监测模块209、温湿度模块210、进水检测模块211和位移传感器212等。主板和转接板通过FPC软排线5连接，微处理器201负责与各模块进行通信，协调控制各模块有序工作。其中：
如图2所示，电子水尺、压力传感器用于检测水位信息，量程分别为HA、HB，HA<HB。超声波传感器用于检测高段量程的水位信息，超声波传感器量程为HC，超声波传感器和外壳之间通过耦合器进行耦合，测量水位范围为HA<水位≤HC。本实施例中，电子水尺、压力传感器、超声波传感器三种传感器构成了全量程无盲区测量。
转接板中的遇水监测模块用于向总电源发送控制信号或向微处理器发送中断信号，实现对本实施例测量装置的工作模式的控制。遇水监测模块使用低功耗元器件，遇水监测模块的检测电极使用防腐型不锈钢螺钉2，检测电极利用水体导电特性检测水位，水接触到检测电极即可；在本实施例中，多个不锈钢螺钉2在转接板的竖直方向排列安装，如图3～图4中的
Figure PCTCN2022137044-appb-000001
所示。显示模块用于显示充电、工作状态等信息。
在数据传输方式上，使用NB、LORA两种通信模块，NB、LORA通信模块分别用于远近距离与监控平台通讯，通讯方式以NB为主、LORA为辅互为备份的水位分段传输方式，如图5～图6所示，提高了装置的透水能力和通信成功概率。NB通信模块是主推的物联网模块，具有超低功耗和超宽工作温度范围，是智慧城市各行业物联 网的理想选择，以提供完善的短信和数据传输服务。LORA通信模块使用扩频技术通讯，在同样的城市、工业应用环境，性能优于使用传统调制方式工作的射频产品，在恶劣的噪声环境下优势尤为明显，可以通过降低传输速率来提高接收灵敏度和通讯距离。相比NB通信模块，LORA在低速率时具有更高的接收灵敏度(高7dBm左右)和较远的有效通讯距离(提高通信成功概率)。NB模块有一定穿透积水能力，同等条件下LORA模块穿透积水能力比NB模块更强。
在无水或者水位(假设水位≤h0)很低的时候，设备使用NB通信模块通过基站中转与监控平台通讯。NB通信模块的射频信号穿透积水的能力与设备到基站的距离有关系，距离越短，信号强度越强，穿透积水能力越强，反之亦然；因此，设备可以根据穿透积水的通信成功率来记录穿透水位高度值(即水深h1)。一旦水位高度超过设备的穿透水位高度值(水深h1)，从NB通信模式切换到LORA通信模式，设备的微处理器与附近的中继设备进行点对点的LORA通信。由于本装置与中继设备距离很短(数米至几十米)，利用两者的LORA通信模块强穿透积水能力进行通信，最后使用中继设备自带的NB通信模块与附近基站通信。如LORA通信成功率过低，可以设置LORA通信模块使用最低的通信速率来提高通信成功概率，其通信透水深度为h2，一旦水深度超过h2，暂停传输，依次循环定时检测水位深度来选择传输方式。通过这种中继方式，装置的透水能力大大提高，能满足很多使用场景需要(如下穿隧道、立交桥下、城市道路、低洼处)。
由于设备有防水要求，磁开关用于设备非接触式开关，微处理器根据磁铁控制磁开关时间的长短来判断设备开关机、蓝牙开启与关闭，进一步降低功耗。电量监测模块用于采集电池的电压，换算成电量信息并上传至监控平台，电池容量不足时及时提示管理人员。电池采用可充电式锂电池，内置保护板。电源转换模块高效率产生相应的工作电压。
充电模块集成了有线、无线两种充电方式；蓝牙模块用于设备的调试、参数查询和设置；磁开关为非接触式开关，提高了设备可靠性。无线充电、蓝牙模块和非接触式的磁开关不用有线连接设备，灌封环氧树脂可以长时间在水中浸泡，从而有助于设备达到IP68防水等级，提高设备的防水能力，大大提高了产品的可靠性。
存储模块用于存储水位历史信息、相关参数、IP地址等关键信息。温湿度模块用于获取设备内部的温度、湿度，便于后期维护；进水检测模块置于设备壳体底部，用 于检测设备内部是否进水；位移传感器用于监测设备非法位移；内外环境如有异常立即向监控平台报警。
本实施例的测量装置在结构上使用塑料外壳，以及注入环氧树脂包裹转接板、产品灌胶可以长时间在水中浸泡,达到IP68防水等级，大大提高了产品的可靠性。
遇水监测模块遇水时，向微处理器发出中断信号，测量装置正常工作，微处理器通过多传感融合测量技术，进行融合校准和分段测量，并使用Kalman滤波器进行滤波，提高了多传感融合测量精度；无水时微处理器处于低功耗模式。
具体来说，通过遇水监测模块的检测电极实现对测量装置工作模式的控制，其控制模式有两种：一种是无水时微处理器处于低功耗模式(且保持周期上报信息，其余时间模块处于关闭状态)，当检测电极遇水时向微处理器发送中断信号，微处理器从低功耗模式切换到工作模式，开启测量装置使其正常工作(加快上报)；另一种是无水时关闭测量装置的电源，微处理器也不工作(功耗最低，基本为零)，当检测电极遇水时立即开启测量装置的电源，使微处理器等测量装置的各模块单元正常工作(加快上报)。基于遇水监测的控制模式具有很低功耗，大大延长了设备的工作时间。水位到达某个水位信息后，智能地自适应采集频度，即采集频度自动控制，水位越高采集越频繁。
本实施例中，微处理器所运行的多传感融合测量技术，对传感器的融合有3种组合方式：
(1)电子水尺与压力传感器融合校准测量技术；
(2)电子水尺与超声波传感器融合分段测量技术；
(3)电子水尺、压力传感器与超声波传感器融合校准测量技术。
(一)电子水尺与压力传感器融合校准测量技术
如图3所示，正常工作，当水位值不大于电子水尺的量程时(低段量程水位≤HA)，微处理器同时采集电子水尺和压力传感器水位值，测量值以电子水尺的测量值为准，同时对压力传感器的大气压值进行校准；由于电子水尺的测量值与压力传感器的测量值存在某种相关性，可以多次采集并计算实际的大气压平均值。由绝压压力传感器测量原理可以知道，测量的压强P是静止水体压强P w和大气压强P 0之和，水体压强与水深成正比例关系，具体如下：
P(k)＝P 0(k)+P W(k)＝P 0(k)+ρgH(k)   (1)
P 0(k)＝P(k)-ρgH(k)    (2)
其中ρ为水的密度，g为重力加速度，两者均为常数，k为整数且1≦k≦m(如m＝15)，考虑到大气压在短时间内变化不大，H(k)为电子水尺的测量水位高度，对P 0(k)取平均值，以减小测量误差：
Figure PCTCN2022137044-appb-000002
为尽可能减小电子水尺的测量水位高度H(k)的测量误差，检测电极使用直径尺寸尽可能小的不锈钢螺钉，本实施例采用定制小尺寸螺钉，以及通过对P 0多次测量后取平均值尽可能减小测量误差。
当水位值大于电子水尺的量程时(水位>HA)，水位值采用压力传感器的测量值，并对测量值使用Kalman滤波器进行滤波，获得最终的测量结果。
由于压力传感器使用绝对压力传感器，受当地当时的温度、湿度、风速、空气成分(密度)、地形(如谷地)、大气环流、天气状况、测量误差等因素影响，因此需要对采集数据进行滤波估计处理。Kalman滤波是一种时域滤波方法，采用状态空间方法进行描述，算法采用递推形式，数据存储量小，可以处理平稳随机过程、多维和非平稳随机过程，是一种最重要的最优估计理论，被广泛应用到各领域。
Kalman滤波状态空间模型描述的动态系统，如式(4)、式(5)所示：
X(n+1)＝ΦX(n)+ΓW(n)   (4)
Z(n)＝HX(n)+V(n)    (5)
式(4)为状态方程，式(5)为观测方程，n为离散时间，系统在时刻n的压力状态X(n)∈R n，Z(n)∈R m为对应状态观测信号，W(n)∈R r为过程噪声(白噪声)，V(n)∈R m观测(测量)噪声，Φ为状态转移矩阵，Γ为噪声驱动矩阵，H为观测矩阵。
假设：W(n)和V(n)是均值为0、方差分别为Q和R的不相关白噪声；初始状态X(0)不相关于W(n)和V(n)，E[X(0)]＝μ 0，E[(X(0)-μ 0)(X(0)-μ 0) T]＝P 0。
根据式(4)、式(5)及上述假设，得到递推Kalman滤波器如下：
状态一步预测：X(n+1|n)＝ΦX(n|n)    (6)
一步预测协方差：P(n+1|n)＝ΦP(n|n)Φ T+ΓQΓ T    (7)
滤波器增益矩阵：K(n+1)＝P(n+1|n)H T[HP(n+1|n)H T+R] -1    (8)
状态更新：ε(n+1)＝Z(n+1)-HX(n+1|n)     (9)
X(n+1|n+1)＝X(n+1|n)+K(n+1)ε(n+1)     (10)
协方差矩阵更新：P(n+1|n+1)＝[I n-K(n+1)H]P(n+1|n)    (11)
其中X(0|0)＝μ 0，P(0|0)＝P 0。
本实施例中，假设压力传感器工作时，受到外部诸多因素影响，引入的过程噪声W(n)方差为Q，大小为Q＝0.04；压力传感器第n次测量的噪声V(n)，其方差为R。压力状态X(n)是n时刻的压力值(对应水位值)，由于X(n)是一维变量压力值，即状态转移矩阵Φ＝1，噪声驱动矩阵Γ＝1，观测矩阵H＝1，那么建立的Kalman滤波状态空间模型对应的状态方程如式(12)所示：
X(n+1)＝ΦX(n)+ΓW(n)＝X(n)+W(n)   (12)
假设压力传感器出厂测量误差为±0.6cm(对应水位值)，可以得知压力传感器的方差R为0.36，即测量数据不是完全正确的，存在测量误差V(n)。那么Kalman滤波状态空间模型对应的观测方程如式(13)所示：
Z(n)＝HX(n)+V(n)＝X(n)+V(n)   (13)
假设要估算n时刻的实际水位值，首先要根据第n-1时刻的水位值来预测n时刻的水位值。水位测量的滤波运算(即滤波估计处理)过程如下：
(1)假设第n-1时刻，压力传感器测量的水位值为22.8cm，实际的水位值为23cm，测量值的偏差为0.2cm，即协方差P(n-1)＝0.2*0.2＝0.04。
(2)在第n时刻，压力计传感器测量的水位值为23.5cm，实际的水位值为23.1cm，测量值的偏差为0.4cm，可以根据n-1时刻水位值22.8cm、n时刻水位值23.5cm，运用状态方程和观测方程得到最逼近真实的估计值。
首先；使用n-1时刻的水位值预测第n时刻的水位值，预计偏差为P(n|n-1)＝P(n-1)+Q＝0.04+0.04＝0.08，计算Kalman滤波算法的增益K＝P(n|n-1)/(P(n|n-1)+R)＝0.04/(0.04+0.36)＝0.1，可以利用n时刻的测量值，运用状态方程得到的估算值为X(n)＝ΦX(n-1)+KW(n-1)＝22.8+0.1*(23.5-22.8)＝22.87cm。可知与n-1时刻的测量值22.8cm和n时刻的测量值23.5cm相比较，Kalman滤波算法的估计值22.87cm更接近于真实值23.1cm。与此同时，更新n时刻的偏差P(n)＝(1-K*H)*P(n|n-1)＝(1-0.1*1)*0.04＝0.036，最后根据估算值X(n)＝22.87cm和n时刻偏差P(n)＝0.036，继续对观测方程的下一时刻观测数据Z(n+1)进行更新和处理。Kalman滤波算法与压力传感器直接测量的水位相比，大大降低了测量误差，虽然Kalman滤波误差没有完 全消失，但它是状态极可能地逼近真实值。
(3)通过Kalman滤波算法不断地递归状态方程和观测方程，从而估算出最优的压力值。
(二)电子水尺与超声波传感器融合分段测量技术
正常工作，当水位值小于电子水尺的量程(低段量程水位≤HA)时，使用电子水尺的测量值；当水位值大于电子水尺的量程(水位>HA)时，采用超声波传感器测量值，用于检测高段量程(HA<水位≤HC)的水位信息，如图4所示，并使用Kalman滤波器进行滤波，提高了超声波传感器测量精度；两种传感器构成了全量程无盲区测量。
水介式超声波传感器传输介质是水，因此无论水面上空气气压变化，或者是空气含有大量蒸汽、雾滴、尘埃，都不会影响水介式超声波传感器的正常工作和加大测量误差。超声波在水中的传播速度与水的温度、密度等相关，需要一定的声速修正系数。水介式超声波传感器与气介式、固介式的传感器相比有较高的测量梢度，如采用声速温度补偿方式还可以得到更高的精度。根据测量对象的不同，水介式超声探头一般采用耦合式安装，可以实现非接触式的水位测量。
由于超声波在水中的传播速度受水体的温度、杂物、气泡、测量误差等因素影响，因此需要对采集数据进行滤波估计处理。同样采用Kalman滤波算法进行估值处理，具体Kalman滤波过程参考上述测量技术(一)。
假设超声波传感器工作时，受到外部诸多因素影响，引入过程噪声W(n)，其方差为Q，大小为Q＝0.09；超声波传感器第n次测量的噪声V(n)，其方差为R。超声波传感器状态X(n)是n时刻的超声波传感器水位值(对应水位值)，由于X(n)是一维变量超声波传感器水位值，即状态转移矩阵Φ＝1，噪声驱动矩阵Γ＝1，观测矩阵H＝1，那么Kalman滤波状态空间模型对应的状态方程如式(14)所示：
X(n+1)＝ΦX(n)+ΓW(n)＝X(n)+W(n)     (14)
假设超声波传感器出厂测量误差为±1cm(对应水位值)，可以得知超声波传感器的方差R为1，即测量数据不是完全正确的，存在测量误差V(n)。那么对应的观测方程如式(15)所示：
Z(n)＝HX(n)+V(n)＝X(n)+V(n)     (15)
运算过程如下：假设要估算n时刻的实际水位值，首先要根据第n-1时刻的水位 值来预测n时刻的水位值。
(1)假设第n-1时刻，超声波传感器测量的水位值来为22.5cm，实际的水位值为23cm，测量值的偏差为0.5cm，即协方差P(n-1)＝0.5*0.5＝0.25。
(2)在第n时刻，超声波传感器测量的水位值为23.5cm，实际的水位值为23.1cm，测量值的偏差为0.4cm，可以根据n-1时刻测量的水位值为22.5cm、n时刻测量的水位值为23.5cm，运用状态方程和观测方程得到最逼近真实的估计值。
首先使用n-1时刻的水位值预测第n时刻的水位值，预计偏差为P(n|n-1)＝P(n-1)+Q＝0.25+0.09＝0.34，计算Kalman滤波算法的增益K＝P(n|n-1)/(P(n|n-1)+R)＝0.34/(0.34+1)＝0.2537，可以利用n时刻的测量值，运用状态方程得到的估算值为
Figure PCTCN2022137044-appb-000003
可知与n-1时刻的测量值22.5cm和n时刻的测量值23.5cm相比较，Kalman滤波算法的估计值22.7537cm更接近于真实值23.1cm。与此同时，更新n时刻的偏差P(n)＝(1-K*H)*P(n|n-1)＝(1-0.2537*1)*0.34＝0.2537，最后根据估算值X(n)＝22.7532cm和n时刻偏差P(n)＝0.2537,继续对观测方程的下一刻观测数据Z(n+1)进行更新和处理。Kalman滤波算法与超声波传感器直接测量的水位相比，大大降低了偏差，虽然Kalman滤波误差没有完全消失，但它是状态尽可能地逼近真实值。
(3)Kalman滤波算法不断地递归状态方程和观测方程，从而估算最优的超声波传感器水位值。
(三)电子水尺、压力传感器和超声波传感器融合校准测量技术
需要确认压力传感器、超声波传感器融合测量的过程噪声W(n)的方差为Q、测量误差的方差R，对压力传感器、超声波传感器的参数(如Q、R)取平均值进行处理，具体算法参考上述测量技术(一)和测量技术(二)。
正常工作，水位值不大于电子水尺的量程时(低段量程水位≤HA)，同时采集电子水尺和压力传感器的水位值，测量值以电子水尺的水位值为准，同时对压力传感器的大气压值进行校准，两者存在某种相关性，可以采用多次采集并计算实际的大气压平均值，具体参考测量技术(一)。
当水位值大于电子水尺的量程时(水位>HA)，对压力传感器和水介式超声波传感器测量的水位值融合取平均值(例如加权平均)，并优化相关参数，对平均值使用Kalman滤波器进行滤波估计处理，具体Kalman滤波过程参考测量技术(一)。
基于相同的发明构思，本实施例还提出多传感融合的高精度水位测量方法，该测量方法基于上述测量装置；测量方法包括以下步骤：
S1、遇水监测模块通过检测电极感应是否有水；
S2、遇水监测模块根据感应结果实现对所述测量装置工作模式的控制，其中控制方式包括两种：一是无水时微处理器处于低功耗模式并周期上报数据，当遇水监测模块遇水时向微处理器发送中断信号，微处理器从低功耗模式切换到工作模式且加快上报数据，开启测量装置使其正常工作；二是无水时关闭测量装置的电源开关且不上报数据，当遇水监测模块遇水时开启测量装置的电源开关，使测量装置正常工作，且加快上报数据；
S3、水位值不大于HA时，微处理器采集电子水尺的测量值作为测量结果；水位值大于HA时，微处理器采集第二水位传感器的测量值，并对测量值进行滤波估计处理，估算出最优的测量结果；
所述滤波估计处理基于Kalman滤波算法，建立的Kalman滤波状态空间模型对应的状态方程为：
X(n+1)＝ΦX(n)+ΓW(n)＝X(n)+W(n)
其中n为离散时间，X(n)为时刻n的第二水位传感器状态，W(n)为过程噪声，Φ为状态转移矩阵，Γ为噪声驱动矩阵；
Kalman滤波状态空间模型对应的观测方程为：
Z(n)＝HX(n)+V(n)＝X(n)+V(n)
其中V(n)为第二水位传感器的测量误差，H为观测矩阵，Z(n)为对应状态观测信号；
S4、微处理器通过NB通信模式或LORA通信模式，发送最优的测量结果。
在无水或者水位低的时候，微处理器通过NB通信模式发送最优的测量结果；当水位高度超过测量装置的穿透水位高度值时，微处理器通过LORA通信模式发送最优的测量结果。
上述实施例为本发明较佳的实施方式，但本发明的实施方式并不受上述实施例的限制，其他的任何未背离本发明的精神实质与原理下所作的改变、修饰、替代、组合、简化，均应为等效的置换方式，都包含在本发明的保护范围之内。

Claims (10)

  1. 多传感融合的高精度水位测量装置，其特征在于，所述测量装置包括微处理器、电源、第一水位传感器和第二水位传感器，第一水位传感器为设有遇水监测模块的电子水尺，第二水位传感器为压力传感器和/或超声波传感器，遇水监测模块、压力传感器、超声波传感器分别与微处理器连接，遇水监测模块用于发送控制所述测量装置工作模式的信号；
    设电子水尺的量程为HA，水位值不大于HA时微处理器采集电子水尺的测量值作为测量结果；水位值大于HA时微处理器采集第二水位传感器的测量值，并对测量值进行滤波估计处理，估算出最优的测量结果；
    通过遇水监测模块实现对所述测量装置工作模式的控制方式包括两种：一是无水时微处理器处于低功耗模式并周期上报数据，当遇水监测模块遇水时向微处理器发送中断信号，微处理器从低功耗模式切换到工作模式且加快上报数据，开启测量装置使其正常工作；二是无水时关闭测量装置的电源开关且不上报数据，当遇水监测模块遇水时开启测量装置的电源开关，使测量装置正常工作，且加快上报数据。
  2. 根据权利要求1所述的高精度水位测量装置，其特征在于，当第二水位传感器为压力传感器时，在水位值不大于HA时，微处理器同时采集压力传感器的测量值，并对压力传感器的大气压值进行校准；当水位值大于HA时，水位值采用压力传感器的测量值。
  3. 根据权利要求1所述的高精度水位测量装置，其特征在于，当第二水位传感器为压力传感器和超声波传感器时，设压力传感器、超声波传感器融合测量的过程噪声W(n)的方差为Q、测量误差的方差R，对压力传感器、超声波传感器的参数取平均值进行处理；
    在水位值不大于HA时，微处理器还采集压力传感器的测量值，并对压力传感器的大气压值进行校准；
    当水位值大于HA时，水位值采用压力传感器的测量值，并对压力传感器和水介式超声波传感器的测量值融合取平均值，对所述平均值进行滤波估计处理。
  4. 根据权利要求1所述的高精度水位测量装置，其特征在于，所述滤波估计处理基于Kalman滤波算法，建立的Kalman滤波状态空间模型对应的状态方程为：
    X(n+1)＝ΦX(n)+ΓW(n)＝X(n)+W(n)
    其中n为离散时间，X(n)为时刻n的第二水位传感器状态，W(n)为过程噪声，Φ为 状态转移矩阵，Γ为噪声驱动矩阵；
    Kalman滤波状态空间模型对应的观测方程为：
    Z(n)＝HX(n)+V(n)＝X(n)+V(n)
    其中V(n)为第二水位传感器的测量误差，H为观测矩阵，Z(n)为对应状态观测信号。
  5. 根据权利要求4所述的高精度水位测量装置，其特征在于，所述滤波估计处理的过程如下：
    根据第n-1时刻的第二水位传感器测量的水位值和实际水位值，求取第n-1时刻的测量偏差及其协方差P(n-1)；
    根据第n时刻的第二水位传感器测量的水位值和实际水位值，求取第n时刻的测量偏差，并根据第n-1时刻水位值、第n时刻水位值，运用状态方程和观测方程得到最逼近真实值的估计值；
    通过Kalman滤波算法不断地递归状态方程和观测方程，从而估算出最优的水位值。
  6. 根据权利要求1所述的高精度水位测量装置，其特征在于，所述测量装置还包括转接板和主板，电子水尺、压力传感器设置在转接板上，微处理器集成在主板上，转接板和主板通过FPC软排线连接。
  7. 根据权利要求6所述的高精度水位测量装置，其特征在于，所述主板上还设有分别与微处理器连接的NB通信模块和LORA通信模块；在无水或者水位低的时候，微处理器通过NB通信模块经基站中转与监控平台通讯；当水位高度超过测量装置的穿透水位高度值时，从NB通信模式切换到LORA通信模式，微处理器与中继设备进行点对点的LORA通信。
  8. 根据权利要求6所述的高精度水位测量装置，其特征在于，电子水尺中遇水监测模块设有检测电极，检测电极为若干个不锈钢螺钉，若干个不锈钢螺钉在转接板的竖直方向排列安装。
  9. 基于权利要求1所述多传感融合的高精度水位测量装置的测量方法，其特征在于，所述测量装置还包括转接板，电子水尺、压力传感器设置在转接板上，电子水尺中遇水监测模块设有检测电极，检测电极为若干个不锈钢螺钉，若干个不锈钢螺钉在转接板的竖直方向排列安装；所述测量方法包括以下步骤：
    S1、遇水监测模块通过检测电极感应是否有水；
    S2、遇水监测模块根据感应结果实现对所述测量装置工作模式的控制，其中控制方 式包括两种：一是无水时微处理器处于低功耗模式并周期上报数据，当遇水监测模块遇水时向微处理器发送中断信号，微处理器从低功耗模式切换到工作模式且加快上报数据，开启测量装置使其正常工作；二是无水时关闭测量装置的电源开关且不上报数据，当遇水监测模块遇水时开启测量装置的电源开关，使测量装置正常工作，且加快上报数据；
    S3、水位值不大于HA时，微处理器采集电子水尺的测量值作为测量结果；水位值大于HA时，微处理器采集第二水位传感器的测量值，并对测量值进行滤波估计处理，估算出最优的测量结果；
    所述滤波估计处理基于Kalman滤波算法，建立的Kalman滤波状态空间模型对应的状态方程为：
    X(n+1)＝ΦX(n)+ΓW(n)＝X(n)+W(n)
    其中n为离散时间，X(n)为时刻n的第二水位传感器状态，W(n)为过程噪声，Φ为状态转移矩阵，Γ为噪声驱动矩阵；
    Kalman滤波状态空间模型对应的观测方程为：
    Z(n)＝HX(n)+V(n)＝X(n)+V(n)
    其中V(n)为第二水位传感器的测量误差，H为观测矩阵，Z(n)为对应状态观测信号；
    S4、微处理器通过NB通信模式或LORA通信模式，发送最优的测量结果。
  10. 根据权利要求9所述的测量方法，其特征在于，步骤S3中，当第二水位传感器为压力传感器时，在水位值不大于HA时，微处理器同时采集压力传感器的测量值，并对压力传感器的大气压值进行校准；当水位值大于HA时，水位值采用压力传感器的测量值；
    步骤S4中，在无水或者水位低的时候，微处理器通过NB通信模式发送最优的测量结果；当水位高度超过测量装置的穿透水位高度值时，微处理器通过LORA通信模式发送最优的测量结果。
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