Energy control method for vibration energy self-powered wireless sensor

Abstract

The invention discloses an energy control method for a vibration energy self-powered wireless sensor. The energy control method comprises the following steps: step 1, setting a working time slot of the sensor; step 2, predicting the average vibration frequency of the vibration source at the current time slot by using an exponential weighted moving average algorithm according to the vibration frequency of the previous vibration source collected by the sensor; 3, predicting the vibration energy collection power of the current time slot according to the vibration acceleration of the vibration source and the predicted average vibration frequency of the current time slot; step 4, adaptively calculating the working duty ratio of the sensor according to the vibration energy collection power predicted in the current time slot; and step 5, the sensor works at the current time slot by using the calculated duty ratio, and the method can enable the wireless sensing system to have higher energy utilization efficiency and longer life cycle through the energy management algorithm.

Description

Technical Field

[0001] The invention relates to the technical field of energy management of wireless sensor systems, and in particular to an energy control method for a vibration energy self-powered wireless sensor. Background Art

[0002] With the rapid development of information technology, wireless sensor systems have been widely used in many fields such as industrial monitoring, structural health assessment, and environmental monitoring. Wireless sensor systems sense the state of the external environment and transform it into effective data information. After local information processing, it is transmitted to the network through single-hop or multi-hop wireless communication to provide users with use. However, the energy available to traditional wireless sensor systems is limited and generally powered by batteries. If they are deployed in areas with complex terrain, the batteries are difficult to replace. When the battery energy is exhausted, the sensor node will not be able to continue to perform the task. Therefore, the introduction of energy harvesting (EH) technology is of great significance to the realization of sustainable unattended operation of wireless sensor systems.

[0003] Traditional environmental energy harvesting mainly includes solar energy, wind energy, etc. However, most industrial equipment is placed in indoor places such as manufacturing workshops and fan rooms, making it difficult to collect solar energy and wind energy. Vibration energy, as a new source of energy harvesting, is not affected by factors such as location and weather. At the same time, the electromagnetic vibration energy harvester in the vibration energy self-powered wireless sensor has a simple structure, low cost, and relatively high power density. The electromagnetic vibration energy harvester is designed based on Faraday's electromagnetic induction theorem, and its most basic structure consists only of a permanent magnet, a spring, and an induction coil. When external vibration exists, the action of the spring causes relative movement between the magnet and the induction coil, resulting in a change in the magnetic flux passing through the coil, which in turn generates an induced electromotive force in the induction coil, realizing the conversion of vibration energy into electrical energy.

[0004] Energy harvesting technology has significantly extended the operating life cycle of wireless sensor systems, but it has also brought new challenges. Wireless sensor systems need to achieve a balance between energy collection and consumption through energy management to avoid two extreme situations: on the one hand, if energy consumption is too low and energy collection is excessive, the energy storage device may be saturated and unable to fully utilize the energy that can be collected, resulting in waste; on the other hand, if energy consumption is too high and energy collection is insufficient, the sensor may be unable to operate normally due to energy exhaustion, ultimately affecting the long-term reliability of the system and the integrity of data collection.

[0005] Existing energy management methods for wireless sensor systems mainly include simple power management technologies such as fixed threshold control, rule-based scheduling strategies, and predictable energy arrival models. These methods have shown certain effects in scenarios where the energy supply is relatively stable and has periodic characteristics. However, because these methods usually rely on preset energy consumption models and static parameter configurations, they are difficult to adapt to vibration energy, an energy source with significant uncertainty, which may lead to energy exhaustion or decreased task performance in the system. Therefore, it is necessary to develop more adaptive energy management algorithms based on the characteristics of vibration energy collection. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention proposes an energy control method for a vibration energy self-powered wireless sensor. Through the energy management algorithm, the wireless sensor system can have higher energy utilization efficiency and a longer life cycle.

[0007] In order to solve the above technical problems, the technical solution of the present invention is:

[0008] A method for energy control of a vibration energy self-powered wireless sensor, comprising the following steps:

[0009] Step 1, set the sensor working time slot;

[0010] Step 2: Based on the vibration frequencies of the previous vibration sources collected by the sensor, an exponentially weighted moving average algorithm is used to predict the average vibration frequency of the vibration source in the current time slot;

[0011] Step 3: predicting the vibration energy collection power of the current time slot according to the vibration acceleration of the vibration source and the average vibration frequency predicted in the current time slot;

[0012] Step 4: adaptively calculate the duty cycle of the sensor operation according to the vibration energy collection power predicted in the current time slot;

[0013] Step 5: The sensor operates using the calculated duty cycle in the current time slot.

[0014] Preferably, the working method of the sensor is: the sensor senses whether the vibration source is vibrating, and if the vibration source is in a non-vibrating state, the sensor maintains a low power consumption mode; if the sensor senses that the vibration source is in a vibrating state, the sensor switches to a working mode.

[0015] Preferably, the working time slot of the sensor is set to 10 minutes.

[0016] Preferably, the sensor includes a vibration pickup system and an energy conversion system, the vibration pickup system includes a moving mass block and a spring, the moving mass block and the spring cooperate to convert the mechanical vibration of the vibration source into the vibration of the moving mass block; the energy conversion system includes an induction coil and a permanent magnet, the induction coil and the permanent magnet convert the vibration energy of the moving mass block into electrical energy through Faraday's law of electromagnetic induction.

[0017] Preferably, in step 4, the method for predicting the vibration energy collection power in the current time slot is:

[0018] First, according to Laplace transform, when the vibration acceleration of the vibration source is a, the relative displacement of the moving mass block can be deduced to be z(t);

[0019] The magnetic flux and magnetic induction intensity are both related to the displacement of the moving mass block. According to the finite element method, the magnetic field is simulated using Ansoft Maxwell simulation software to obtain the magnetic flux of the moving mass block under different displacement conditions;

[0020] Secondly, based on Laplace transform, dynamics and Faraday's law of electromagnetic induction, a model was established using Simulink for simulation, and the output power P(a, ω) of the vibration generator when the load resistance is R was obtained. The output power P(a, ω) of the vibration generator corresponding to the vibration acceleration a and vibration frequency ω of different vibration sources was recorded, and combined with interpolation, the function F(a, ω) of the output power of the vibration generator with respect to the vibration acceleration a and vibration frequency ω was obtained.

[0021] Finally, at the beginning of each time slot, according to the vibration acceleration a of the vibration source and the predicted average vibration frequency ω of the vibration source in the current time slot, t , the predicted value of the vibration energy harvesting power in the current time slot is obtained through the function F(a,ω).

[0022] Preferably, in step 4, the calculation method of the duty cycle of the sensor is:

[0023] Step 4-1: Calculate the duty cycle d of the current time slot based on the predicted vibration energy collection power and the power of the sensor in working mode and sleep mode. predict ;

[0024] Step 4-2: Based on the difference between the remaining power percentage of the energy storage module in the sensor and the target power percentage, use the PID control algorithm to calculate the duty cycle d of the energy storage module. pid ;

[0025] Step 4-3: Use weight β to convert d predict and d pid Combined into the final duty cycle d final .

[0026] Preferably, in step 4-1, the duty cycle d of the current time slot is predict The calculation method is:

[0027]

[0028] Where P collect is the predicted vibration energy harvesting power, P sleep is the power of the sensor in sleep mode, P active is the power of the sensor in working mode;

[0029] When P collect >P active When predict The value of is limited to 1, that is, the sensor can maintain the working mode throughout the current time slot, and there is still excess harvested energy not used in the time slot; in this case, the PID control algorithm is used to dynamically increase d in subsequent time slots. predict value so that the overall energy consumed is still equal to the energy collected.

[0030] In addition, when there is a deviation between the predicted vibration energy harvesting power and the actual vibration energy harvesting power, or when the vibration source fails to maintain vibration in the entire time slot due to changes in the external environment, the PID control algorithm dynamically adjusts the d predict value so that the overall energy consumed is still equal to the energy collected.

[0031] Preferably, the weight β is the difference between the current remaining power percentage of the energy storage module and the target power percentage.

[0032] Preferably, the working method of the sensor is: the sensor is in the front d of the current time slot final ×100% of the time is in working mode to collect vibration data of the vibration source; and it switches to sleep mode during the remaining time of the current time slot.

[0033] The present invention has the following characteristics and beneficial effects:

[0034] Using the above technical solution, the present invention uses the EWMA algorithm to predict the collected power of the current time slot based on the collected vibration signal, defines the duty cycle in combination with the power consumption of the sensor to achieve energy neutrality, and combines the PID control algorithm to further adjust the duty cycle to achieve precise and dynamic energy regulation, thereby achieving the effect of not needing to replace batteries regularly, supporting unattended operation, and reducing system maintenance costs. Compared with energy management algorithms that process solar energy, wind energy, and other energy sources with certain periodic characteristics, the algorithm proposed in the present invention shows more superior adaptability when dealing with vibration energy, an energy source with significant uncertainty: the algorithm can dynamically adjust the energy consumption strategy according to the real-time situation, thereby optimizing the energy utilization efficiency and improving the overall reliability of the system. In addition, the algorithm has low computing cost and data storage cost, and can be well applied to the problem of limited hardware resources of sensor equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0036] Figure 1 The present invention is a method flow chart of a method for energy control of a vibration energy self-powered wireless sensor according to an embodiment of the present invention.

[0037] Figure 2 The figure shows the trend of the remaining power of the energy storage module changing over time in the embodiment of the present invention. DETAILED DESCRIPTION

[0038] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0039] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and the like are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", and the like may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0040] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood by specific circumstances.

[0041] The present invention provides an energy control method for a vibration energy self-powered wireless sensor, comprising the following steps:

[0042] Step 1: Set the sensor working time slot.

[0043] It should be noted that the time slot can have different spans, such as 1 minute, 10 minutes, 30 minutes, 1 hour, etc. The smaller the span, the more accurate the energy prediction will be, but it will increase the computing cost and the switching frequency of the working mode, thereby increasing energy consumption. In this example, the time slot span selected is 10 minutes to balance energy prediction and energy consumption while facilitating data analysis and diagramming.

[0044] In addition, the working setting for the sensor operation is: the sensor senses whether the vibration source is vibrating. If the vibration source is in a non-vibrating state, the low power consumption mode is maintained; if the vibration source is sensed to be in a vibrating state, the sensor switches to the working mode.

[0045] Specifically, the sensor will reduce the sampling frequency in the low power mode to reduce power consumption, because the role of the low power mode is to detect the vibration of the vibration source when the vibration source is in a non-vibrating state, rather than collecting a specific vibration signal.

[0046] If the sensor senses that the vibration source is in a vibrating state, the sensor will collect the vibration signal, otherwise it will remain in low power consumption mode.

[0047] Step 2: Based on the vibration frequencies of the previous vibration sources collected by the sensor, an exponentially weighted moving average algorithm is used to predict the average vibration frequency of the vibration source in the current time slot.

[0048] Specifically, the Exponential Weighted Moving Average (EWMA) algorithm is used to predict the average vibration frequency ω of the vibration source at the current time slot t t ,Right now where ω t-1 is the EWMA value of the previous time slot, is the mean value of the vibration frequency of the previous time slot, and α is the smoothing coefficient.

[0049] The smoothing coefficient α plays a role in adjusting the weight distribution of the prediction value to the data of the historical time slot and the data of the previous time slot in the algorithm. When α is large, the EWMA prediction value is more biased towards the mean value of the vibration frequency of the previous time slot, so it can quickly respond to drastic changes in frequency; on the contrary, when α is small, the EWMA prediction value is more inclined to the past vibration frequency trend, thereby effectively smoothing short-term fluctuations and keeping track of long-term trends.

[0050] The selection of α needs to be reasonably adjusted according to the actual characteristics of the vibration source. If the frequency of the vibration source changes quickly and is unstable, in order to ensure that the system responds quickly to the latest vibration frequency, it is usually necessary to select a larger α value; for a vibration source that changes slowly and steadily, a smaller α value can be selected. The α value selected in this example is 0.6.

[0051] Step 3: predict the vibration energy collection power of the current time slot according to the vibration acceleration of the vibration source and the average vibration frequency predicted in the current time slot.

[0052] It should be noted that the energy supply of the sensor is based on the built-in vibration generator, and its basic components can be divided into the following according to their functions:

[0053] A vibration pickup system consisting of a moving mass block and a spring that converts the mechanical vibration of the vibration source into the vibration of the moving mass block;

[0054] An energy conversion system consisting of an induction coil and a permanent magnet that converts the vibration energy of a moving mass block into electrical energy through Faraday's electromagnetic induction theorem.

[0055] Specifically, first, according to Laplace transform, when the vibration acceleration of the vibration source is a, the relative displacement of the moving mass block can be derived as z(t);

[0056] The magnetic flux and magnetic induction intensity are both related to the displacement of the moving mass block. According to the finite element method, the magnetic field is simulated using Ansoft Maxwell simulation software to obtain the magnetic flux of the moving mass block under different displacement conditions;

[0057] Secondly, based on Laplace transform, dynamics and Faraday's law of electromagnetic induction, a model was established using Simulink for simulation, and the output power P(a,ω) of the vibration generator when the load resistance was R was obtained. The output power P(a,ω) of the vibration generator corresponding to the vibration acceleration a and vibration frequency ω of different vibration sources was recorded, and combined with interpolation, the function F(a,ω) of the vibration generator output power with respect to the vibration acceleration a and vibration frequency ω was obtained.

[0058] It should be noted that the function F(a, ω) is obtained by combining the data obtained by the previous simulation with interpolation. Different types of vibration generators obtain different functions. The general steps are given here. Therefore, in this embodiment, no specific explanation is given.

[0059] Finally, at the beginning of each time slot, according to the vibration acceleration a of the vibration source and the predicted average vibration frequency ω of the vibration source in the current time slot, t , the predicted value of the vibration energy harvesting power in the current time slot is obtained through the function F(a,ω).

[0060] Step 4: Adaptively calculate the duty cycle of the sensor based on the vibration energy harvesting power predicted in the current time slot:

[0061] Step 4-1: Calculate the duty cycle d of the current time slot based on the predicted vibration energy collection power and the power of the sensor in working mode and sleep mode. predict ;

[0062] Specifically, after obtaining the predicted vibration energy collection power, the duty cycle d can be calculated in combination with the predicted vibration energy collection power. predict ,The calculation rule is to make the energy consumed in the current time slot equal to the collected energy, so as to avoid the occurrence of two extreme situations: on the one hand, if the energy consumption is too low and the energy collection is excessive, the energy storage device may not be able to fully utilize the energy that can be collected due to saturation, resulting in waste; on the other hand, if the energy consumption is too high and the energy collection is insufficient, the sensor may not be able to operate normally due to energy exhaustion, ultimately affecting the long-term reliability of the system and the integrity of data collection.

[0063] The duty cycle of the current time slot d predict The calculation method is:

[0064]

[0065] Where P collectis the predicted vibration energy harvesting power, P sleep is the power of the sensor in sleep mode, P active is the power of the sensor in working mode;

[0066] When P collect >P active When predict The value of is limited to 1, that is, the sensor can maintain the working mode throughout the current time slot, and there is still excess harvested energy not used in the time slot; in this case, the PID control algorithm is used to dynamically increase d in subsequent time slots. predict value so that the overall energy consumed is still equal to the energy collected.

[0067] In addition, when there is a deviation between the predicted vibration energy harvesting power and the actual vibration energy harvesting power, or when the vibration source fails to maintain vibration in the entire time slot due to changes in the external environment, the PID control algorithm dynamically adjusts the d predict value so that the overall energy consumed is still equal to the energy collected.

[0068] Step 4-2: Based on the difference between the remaining power percentage of the energy storage module in the sensor and the target power percentage, use the PID control algorithm to calculate the duty cycle d of the energy storage module. pid .

[0069] Specifically, based on the difference between the remaining power percentage of the current energy storage module (e.g., rechargeable battery, capacitor, etc.) and the target power percentage, a PID control algorithm is used to calculate d pid The target power percentage refers to the power level that the energy storage module is expected to maintain, and its specific value can be set during the system initialization phase. The target power percentage value selected in this example is 80%.

[0070] It should be noted that the PID control algorithm has significant advantages in this scenario. Its proportional (P) control can directly adjust the duty cycle according to the current deviation, thereby quickly responding to changes in the power level; the integral (I) control corrects the long-term steady-state error by accumulating historical deviations to ensure that the system eventually converges to the target power level; the differential (D) control predicts the trend in advance by monitoring the rate of change of the deviation, thereby improving the system's response speed to sudden changes. The parameters of the PID control algorithm (proportional coefficient, integral coefficient, differential coefficient) can be determined by the Ziegler-Nichols method or empirical trial and error method. The parameters selected in this example are K p =72,K i =5,K d =3.

[0071] Step 4-3: Use weight β to convert d predictand d pid Combined into the final duty cycle d final .

[0072] Specifically, in order to calculate the final duty cycle d final , by introducing the weight parameter β, the predicted duty cycle d predict The duty cycle d calculated by the PID control algorithm pid Combine them in a weighted summation manner, that is, d final =(1-β)·d predict +β·d pid The value of the weight parameter β depends on the difference between the current remaining power percentage of the energy storage module and the target power percentage. When the remaining power of the energy storage module is close to the target power, it means that the prediction algorithm works well, d final It is more inclined to increase the proportion of predicted value; when the remaining power of the energy storage module is significantly different from the target power, d final It is more inclined to increase the proportion of PID control algorithm output to enhance the dynamic response capability of the system.

[0073] Step 5: The sensor operates using the calculated duty cycle in the current time slot.

[0074] Specifically, the sensor uses a duty cycle d in the current time slot. final To work, the sensor is in the first d of the current time slot final ×100% of the time is in non-mode, collecting data such as the vibration frequency and vibration amplitude of the vibration source; switching to sleep mode during the remaining time of the current time slot. And returning to step 1 in the next time slot.

[0075] The following results were obtained based on the technical solution provided in the above example.

[0076] In this example, the maximum capacity of the energy storage module is 1000mWh. Figure 1 The figure shows the trend of the remaining power of the energy storage module over time in this energy management method. By analyzing the data in the figure, it can be clearly observed that the remaining power can always be relatively stably maintained near the target power value, showing good energy balance. From the quantitative results, the absolute error of the remaining power is always controlled within 10mWh, and the relative error is less than 1%, indicating that the system can maintain relatively accurate energy management for a long time.

[0077] This result shows that the proposed energy management method can achieve efficient and stable energy control in the application of vibration energy self-powered wireless sensors, fully meeting the needs of wireless sensors for low power consumption and long-term operation. More importantly, in the face of complex factors such as environmental changes and fluctuations in vibration energy sources, this method demonstrates excellent dynamic adjustment capabilities, can flexibly respond to the uncertainty of energy supply, and ensure that the system can still maintain stable operation in a dynamic environment.

[0078] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited to the described embodiments. For those skilled in the art, various changes, modifications, substitutions and variations of these embodiments including components are made without departing from the principles and spirit of the present invention, and still fall within the scope of protection of the present invention.

Claims

1. A method for energy control of a vibration energy self-powered wireless sensor, characterized in that: The steps include: Step 1, set the sensor working time slot; Step 2: Based on the vibration frequencies of the previous vibration sources collected by the sensor, an exponentially weighted moving average algorithm is used to predict the average vibration frequency of the vibration source in the current time slot; Step 3: predicting the vibration energy collection power of the current time slot according to the vibration acceleration of the vibration source and the average vibration frequency predicted in the current time slot; Step 4: adaptively calculate the duty cycle of the sensor operation according to the vibration energy collection power predicted in the current time slot; Step 5: The sensor operates using the calculated duty cycle in the current time slot.

2. The energy control method for vibration energy self-powered wireless sensor according to claim 1, characterized in that: The working method of the sensor is: the sensor senses whether the vibration source is vibrating, and if the vibration source is in a non-vibrating state, the sensor maintains a low power consumption mode; if the sensor senses that the vibration source is in a vibrating state, the sensor switches to a working mode.

3. The energy control method for vibration energy self-powered wireless sensor according to claim 1, characterized in that: The working time slot of the sensor is set to 10 minutes.

4. The energy control method for vibration energy self-powered wireless sensor according to claim 1, characterized in that: The sensor includes a vibration pickup system and an energy conversion system. The vibration pickup system includes a moving mass block and a spring. The moving mass block and the spring cooperate to convert the mechanical vibration of the vibration source into the vibration of the moving mass block. The energy conversion system includes an induction coil and a permanent magnet. The induction coil and the permanent magnet convert the vibration energy of the moving mass block into electrical energy through Faraday's electromagnetic induction theorem.

5. The energy control method for vibration energy self-powered wireless sensor according to claim 4, characterized in that: In step 4, the method for predicting the vibration energy collection power in the current time slot is: First, according to Laplace transform, when the vibration acceleration of the vibration source is a, the relative displacement of the moving mass block can be deduced to be z(t); The magnetic flux and magnetic induction intensity are both related to the displacement of the moving mass block. According to the finite element method, the magnetic field is simulated using Ansoft Maxwell simulation software to obtain the magnetic flux of the moving mass block under different displacement conditions; Secondly, based on Laplace transform, dynamics and Faraday's law of electromagnetic induction, a model was established using Simulink for simulation, and the output power P(a, ω) of the vibration generator when the load resistance is R was obtained. The output power P(a, ω) of the vibration generator corresponding to the vibration acceleration a and vibration frequency ω of different vibration sources was recorded, and combined with interpolation, the function F(a, ω) of the output power of the vibration generator with respect to the vibration acceleration a and vibration frequency ω was obtained. Finally, at the beginning of each time slot, according to the vibration acceleration a of the vibration source and the predicted average vibration frequency ω of the vibration source in the current time slot, t , the predicted value of the vibration energy harvesting power in the current time slot is obtained through the function F(a,ω).

6. The energy control method for vibration energy self-powered wireless sensor according to claim 2, characterized in that: In step 4, the calculation method of the duty cycle of the sensor is: Step 4-1: Calculate the duty cycle d of the current time slot based on the predicted vibration energy collection power and the power of the sensor in working mode and sleep mode. predict ; Step 4-2: Based on the difference between the remaining power percentage of the energy storage module in the sensor and the target power percentage, use the PID control algorithm to calculate the duty cycle d of the energy storage module. pid ; Step 4-3: Use weight β to convert d predict and d pid Combined into the final duty cycle d final .

7. The energy control method for vibration energy self-powered wireless sensor according to claim 6, characterized in that: In step 4-1, the duty cycle d of the current time slot predict The calculation method is: Where P collect is the predicted vibration energy harvesting power, P sleep is the power of the sensor in sleep mode, P active is the power of the sensor in working mode; By adjusting the duty cycle d of the current time slot predict Dynamic adjustments are made so that the overall energy consumed still equals the energy collected.

8. The energy control method for vibration energy self-powered wireless sensor according to claim 7, characterized in that: The duty cycle d of the current time slot predict The dynamic adjustment method is: when P collect >P active When predict The value of is limited to 1, that is, the sensor can maintain the working mode throughout the current time slot, and there is still excess harvested energy not used in the time slot; in this case, the PID control algorithm is used to dynamically increase d in subsequent time slots. predict value so that the overall energy consumed is still equal to the energy collected; In addition, when there is a deviation between the predicted vibration energy harvesting power and the actual vibration energy harvesting power, or when the vibration source fails to maintain vibration in the entire time slot due to changes in the external environment, the PID control algorithm dynamically adjusts the d predict value so that the overall energy consumed is still equal to the energy collected.

9. The energy control method for vibration energy self-powered wireless sensor according to claim 6, characterized in that: The weight β is the difference between the current remaining power percentage of the energy storage module and the target power percentage.

10. The energy control method for vibration energy self-powered wireless sensor according to claim 6, characterized in that: The working method of the sensor is: the sensor is in the front d of the current time slot final ×100% of the time is in working mode to collect vibration data of the vibration source; and it switches to sleep mode during the remaining time of the current time slot.

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